From d8b895000d0816bca50aa573073d8b55087deb5b Mon Sep 17 00:00:00 2001 From: Haotian Zhang Date: Fri, 23 Feb 2024 00:00:16 -0500 Subject: [PATCH 01/30] add colbert import (#11309) cr --- docs/examples/node_postprocessor/ColbertRerank.ipynb | 2 ++ 1 file changed, 2 insertions(+) diff --git a/docs/examples/node_postprocessor/ColbertRerank.ipynb b/docs/examples/node_postprocessor/ColbertRerank.ipynb index ef067ae7f151a..11c346a42c2e7 100644 --- a/docs/examples/node_postprocessor/ColbertRerank.ipynb +++ b/docs/examples/node_postprocessor/ColbertRerank.ipynb @@ -109,6 +109,8 @@ "metadata": {}, "outputs": [], "source": [ + "from llama_index.postprocessor.colbert_rerank import ColbertRerank\n", + "\n", "colbert_reranker = ColbertRerank(\n", " top_n=5,\n", " model=\"colbert-ir/colbertv2.0\",\n", From caf56ac50e1727913d9df8d94e159c03e1f3105d Mon Sep 17 00:00:00 2001 From: Rudolf Olah <89982117+rudolfolah@users.noreply.github.com> Date: Fri, 23 Feb 2024 00:46:04 -0500 Subject: [PATCH 02/30] Documentation Update for customization.rst: fixed link and package name (#11307) Update customization.rst * fixed link to LlamaHub * updated package name to reflect what's in PyPi --- docs/getting_started/customization.rst | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/getting_started/customization.rst b/docs/getting_started/customization.rst index c2638073e94ab..2bd8362a150fd 100644 --- a/docs/getting_started/customization.rst +++ b/docs/getting_started/customization.rst @@ -37,14 +37,14 @@ In this tutorial, we start with the code you wrote for the `starter example `_. Then, you can use it in your code: From d34e5a8b36fb696fb4f07a4b264a83b1c1f32f27 Mon Sep 17 00:00:00 2001 From: Julien Bouquillon Date: Fri, 23 Feb 2024 16:50:20 +0100 Subject: [PATCH 03/30] chore: fix doc comments (#11322) * chore: fix doc comments * Update base.py * Update base.py --- .../llama_index/readers/file/markdown/base.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/markdown/base.py b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/markdown/base.py index 228e749a4257f..e0e39e53de5cb 100644 --- a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/markdown/base.py +++ b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/markdown/base.py @@ -71,12 +71,12 @@ def markdown_to_tups(self, markdown_text: str) -> List[Tuple[Optional[str], str] return markdown_tups def remove_images(self, content: str) -> str: - """Get a dictionary of a markdown file from its path.""" + """Remove images in markdown content.""" pattern = r"!{1}\[\[(.*)\]\]" return re.sub(pattern, "", content) def remove_hyperlinks(self, content: str) -> str: - """Get a dictionary of a markdown file from its path.""" + """Remove hyperlinks in markdown content.""" pattern = r"\[(.*?)\]\((.*?)\)" return re.sub(pattern, r"\1", content) From 7e959cc888d03ef0b7089491beab5ecfc3976f5a Mon Sep 17 00:00:00 2001 From: Rodrigo Nogueira <121117945+rodrigo-f-nogueira@users.noreply.github.com> Date: Fri, 23 Feb 2024 13:19:28 -0300 Subject: [PATCH 04/30] Add system prompt (#11325) * add system prompt workaround * remove workaround flag * fix lint --- .../llama_index/llms/maritalk/base.py | 27 ++++++++++--------- 1 file changed, 15 insertions(+), 12 deletions(-) diff --git a/llama-index-integrations/llms/llama-index-llms-maritalk/llama_index/llms/maritalk/base.py b/llama-index-integrations/llms/llama-index-llms-maritalk/llama_index/llms/maritalk/base.py index 5c48794561c6b..b544d9f5d267e 100644 --- a/llama-index-integrations/llms/llama-index-llms-maritalk/llama_index/llms/maritalk/base.py +++ b/llama-index-integrations/llms/llama-index-llms-maritalk/llama_index/llms/maritalk/base.py @@ -45,11 +45,6 @@ class Maritalk(LLM): description="Nucleus sampling parameter controlling the size of" " the probability mass considered for sampling.", ) - system_message_workaround: bool = Field( - default=True, - description="Whether to include a workaround for system" - " message by adding it as a user message.", - ) _endpoint: str = PrivateAttr("https://chat.maritaca.ai/api/chat/inference") @@ -79,13 +74,21 @@ def metadata(self) -> LLMMetadata: @llm_chat_callback() def chat(self, messages: Sequence[ChatMessage], **kwargs: Any) -> ChatResponse: # Prepare the data payload for the Maritalk API - formatted_messages = [ - { - "role": "user" if msg.role == MessageRole.USER else "assistant", - "content": msg.content, - } - for msg in messages - ] + formatted_messages = [] + for msg in messages: + if msg.role == MessageRole.SYSTEM: + # Add system message as a user message + formatted_messages.append({"role": "user", "content": msg.content}) + # Follow it by an assistant message acknowledging it, to maintain conversation flow + formatted_messages.append({"role": "assistant", "content": "ok"}) + else: + # Format user and assistant messages as before + formatted_messages.append( + { + "role": "user" if msg.role == MessageRole.USER else "assistant", + "content": msg.content, + } + ) data = { "messages": formatted_messages, From cf289420110f067a5ea300e8bb85fecb9d935fa8 Mon Sep 17 00:00:00 2001 From: Will Deaderick Date: Fri, 23 Feb 2024 10:33:13 -0600 Subject: [PATCH 05/30] Implement OpensearchVectorStore document deletion (#11292) --- .../llama_index/vector_stores/opensearch/base.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/llama_index/vector_stores/opensearch/base.py b/llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/llama_index/vector_stores/opensearch/base.py index ed34f3a313fb4..7644617b3d71e 100644 --- a/llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/llama_index/vector_stores/opensearch/base.py +++ b/llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/llama_index/vector_stores/opensearch/base.py @@ -350,7 +350,8 @@ def delete_doc_id(self, doc_id: str) -> None: Args: doc_id (str): document id """ - self._os_client.delete(index=self._index, id=doc_id) + body = {"query": {"match": {"metadata.ref_doc_id": doc_id}}} + self._os_client.delete_by_query(index=self._index, body=body) def query( self, From 7d93b49ff98f4bdd8c6a4a61d49c40618a36e0a1 Mon Sep 17 00:00:00 2001 From: Samuel MICHEL <74212431+mchlsam@users.noreply.github.com> Date: Fri, 23 Feb 2024 18:47:42 +0100 Subject: [PATCH 06/30] Fix base.py (#11327) --- .../llama_index/embeddings/instructor/base.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-instructor/llama_index/embeddings/instructor/base.py b/llama-index-integrations/embeddings/llama-index-embeddings-instructor/llama_index/embeddings/instructor/base.py index ed58e7aa08f2e..e2b351e1ed248 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-instructor/llama_index/embeddings/instructor/base.py +++ b/llama-index-integrations/embeddings/llama-index-embeddings-instructor/llama_index/embeddings/instructor/base.py @@ -54,7 +54,7 @@ def class_name(cls) -> str: def _format_query_text(self, query_text: str) -> List[str]: """Format query text.""" - instruction = self.text_instruction + instruction = self.query_instruction if instruction is None: instruction = get_query_instruct_for_model_name(self.model_name) From 50806ba526dde4a054842394fe32e3880646fe6d Mon Sep 17 00:00:00 2001 From: Anush Date: Fri, 23 Feb 2024 23:47:21 +0530 Subject: [PATCH 07/30] chore(deps): bump Fastembed to latest (#11329) --- .../llama_index/embeddings/fastembed/base.py | 10 ++++------ .../llama-index-embeddings-fastembed/pyproject.toml | 2 +- 2 files changed, 5 insertions(+), 7 deletions(-) diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-fastembed/llama_index/embeddings/fastembed/base.py b/llama-index-integrations/embeddings/llama-index-embeddings-fastembed/llama_index/embeddings/fastembed/base.py index f0785ba06c6e3..9db6a8c304786 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-fastembed/llama_index/embeddings/fastembed/base.py +++ b/llama-index-integrations/embeddings/llama-index-embeddings-fastembed/llama_index/embeddings/fastembed/base.py @@ -4,7 +4,7 @@ from llama_index.core.base.embeddings.base import BaseEmbedding from llama_index.core.bridge.pydantic import Field, PrivateAttr -from fastembed.embedding import FlagEmbedding +from fastembed import TextEmbedding class FastEmbedEmbedding(BaseEmbedding): @@ -51,10 +51,8 @@ class FastEmbedEmbedding(BaseEmbedding): doc_embed_type: Literal["default", "passage"] = Field( "default", - description="Type of embedding to use for documents.\n" - "'default': Uses FastEmbed's default embedding method.\n" - "'passage': Prefixes the text with 'passage' before embedding.\n" - "Defaults to 'default'.", + description="Type of embedding method to use for documents.\n" + "Available options are 'default' and 'passage'.", ) _model: Any = PrivateAttr() @@ -78,7 +76,7 @@ def __init__( doc_embed_type=doc_embed_type, ) - self._model = FlagEmbedding( + self._model = TextEmbedding( model_name=model_name, max_length=max_length, cache_dir=cache_dir, diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-fastembed/pyproject.toml b/llama-index-integrations/embeddings/llama-index-embeddings-fastembed/pyproject.toml index a962096f48c8f..e43bf035ece9e 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-fastembed/pyproject.toml +++ b/llama-index-integrations/embeddings/llama-index-embeddings-fastembed/pyproject.toml @@ -32,7 +32,7 @@ version = "0.1.3" [tool.poetry.dependencies] python = ">=3.8.1,<3.12" llama-index-core = "^0.10.11.post1" -fastembed = "^0.1.3" +fastembed = "^0.2.2" [tool.poetry.group.dev.dependencies] ipython = "8.10.0" From 8f8d46353c9f0140d50a398a629f05d85a037c9c Mon Sep 17 00:00:00 2001 From: Graden Rea Date: Fri, 23 Feb 2024 11:17:53 -0800 Subject: [PATCH 08/30] Add Groq LLM integration (#11317) * Generate skeleton for Groq LLM integration. * Use OpenAI-like to implement Groq LLM integraton. Co-authored-by: gavinsherry --------- Co-authored-by: gavinsherry --- docs/examples/llm/groq.ipynb | 318 ++++++++++++++++++ docs/module_guides/models/llms/modules.md | 9 + .../llms/llama-index-llms-groq/.gitignore | 153 +++++++++ .../llms/llama-index-llms-groq/BUILD | 3 + .../llms/llama-index-llms-groq/Makefile | 17 + .../llms/llama-index-llms-groq/README.md | 52 +++ .../llama_index/llms/groq/BUILD | 1 + .../llama_index/llms/groq/__init__.py | 3 + .../llama_index/llms/groq/base.py | 28 ++ .../llms/llama-index-llms-groq/pyproject.toml | 63 ++++ .../llms/llama-index-llms-groq/tests/BUILD | 1 + .../llama-index-llms-groq/tests/__init__.py | 0 .../tests/test_integration_groq.py | 22 ++ .../tests/test_llms_groq.py | 7 + 14 files changed, 677 insertions(+) create mode 100644 docs/examples/llm/groq.ipynb create mode 100644 llama-index-integrations/llms/llama-index-llms-groq/.gitignore create mode 100644 llama-index-integrations/llms/llama-index-llms-groq/BUILD create mode 100644 llama-index-integrations/llms/llama-index-llms-groq/Makefile create mode 100644 llama-index-integrations/llms/llama-index-llms-groq/README.md create mode 100644 llama-index-integrations/llms/llama-index-llms-groq/llama_index/llms/groq/BUILD create mode 100644 llama-index-integrations/llms/llama-index-llms-groq/llama_index/llms/groq/__init__.py create mode 100644 llama-index-integrations/llms/llama-index-llms-groq/llama_index/llms/groq/base.py create mode 100644 llama-index-integrations/llms/llama-index-llms-groq/pyproject.toml create mode 100644 llama-index-integrations/llms/llama-index-llms-groq/tests/BUILD create mode 100644 llama-index-integrations/llms/llama-index-llms-groq/tests/__init__.py create mode 100644 llama-index-integrations/llms/llama-index-llms-groq/tests/test_integration_groq.py create mode 100644 llama-index-integrations/llms/llama-index-llms-groq/tests/test_llms_groq.py diff --git a/docs/examples/llm/groq.ipynb b/docs/examples/llm/groq.ipynb new file mode 100644 index 0000000000000..530c4f05deefe --- /dev/null +++ b/docs/examples/llm/groq.ipynb @@ -0,0 +1,318 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "4d1b897a", + "metadata": {}, + "source": [ + "\"Open" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "2e33dced-e587-4397-81b3-d6606aa1738a", + "metadata": {}, + "source": [ + "# Groq\n", + "\n", + "Welcome to Groq! 🚀 At Groq, we've developed the world's first Language Processing Unit™, or LPU. The Groq LPU has a deterministic, single core streaming architecture that sets the standard for GenAI inference speed with predictable and repeatable performance for any given workload.\n", + "\n", + "Beyond the architecture, our software is designed to empower developers like you with the tools you need to create innovative, powerful AI applications. With Groq as your engine, you can:\n", + "\n", + "* Achieve uncompromised low latency and performance for real-time AI and HPC inferences 🔥\n", + "* Know the exact performance and compute time for any given workload 🔮\n", + "* Take advantage of our cutting-edge technology to stay ahead of the competition 💪\n", + "\n", + "Want more Groq? Check out our [website](https://groq.com) for more resources and join our [Discord community](https://discord.gg/JvNsBDKeCG) to connect with our developers!" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "5863dde9-84a0-4c33-ad52-cc767442f63f", + "metadata": {}, + "source": [ + "## Setup" + ] + }, + { + "cell_type": "markdown", + "id": "833bdb2b", + "metadata": {}, + "source": [ + "If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4aff387e", + "metadata": {}, + "outputs": [], + "source": [ + "% pip install llama-index-llms-groq" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9bbbc106", + "metadata": {}, + "outputs": [], + "source": [ + "!pip install llama-index" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ad297f19-998f-4485-aa2f-d67020058b7d", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "None of PyTorch, TensorFlow >= 2.0, or Flax have been found. Models won't be available and only tokenizers, configuration and file/data utilities can be used.\n" + ] + } + ], + "source": [ + "from llama_index.llms.groq import Groq" + ] + }, + { + "cell_type": "markdown", + "id": "4eefec25", + "metadata": {}, + "source": [ + "Create an API key at the [Groq console](https://console.groq.com/keys), then set it to the environment variable `GROQ_API_KEY`.\n", + "\n", + "```bash\n", + "export GROQ_API_KEY=\n", + "```\n", + "\n", + "Alternatively, you can pass your API key to the LLM when you init it:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "152ced37-9a42-47be-9a39-4218521f5e72", + "metadata": {}, + "outputs": [], + "source": [ + "llm = Groq(model=\"mixtral-8x7b-32768\", api_key=\"your_api_key\")" + ] + }, + { + "cell_type": "markdown", + "id": "562455fe", + "metadata": {}, + "source": [ + "A list of available LLM models can be found [here](https://console.groq.com/docs/models)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d61b10bb-e911-47fb-8e84-19828cf224be", + "metadata": {}, + "outputs": [], + "source": [ + "response = llm.complete(\"Explain the importance of low latency LLMs\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3bd14f4e-c245-4384-a471-97e4ddfcb40e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Low latency Large Language Models (LLMs) are important in certain applications due to their ability to process and respond to inputs quickly. Latency refers to the time delay between a user's request and the system's response. In some real-time or time-sensitive applications, low latency is critical to ensure a smooth user experience and prevent delays or lag.\n", + "\n", + "For example, in conversational agents or chatbots, users expect quick and responsive interactions. If the system takes too long to process and respond to user inputs, it can negatively impact the user experience and lead to frustration. Similarly, in applications such as real-time language translation or speech recognition, low latency is essential to provide accurate and timely feedback to the user.\n", + "\n", + "Furthermore, low latency LLMs can enable new use cases and applications that require real-time or near real-time processing of language inputs. For instance, in the field of autonomous vehicles, low latency LLMs can be used for real-time speech recognition and natural language understanding, enabling voice-controlled interfaces that allow drivers to keep their hands on the wheel and eyes on the road.\n", + "\n", + "In summary, low latency LLMs are important for providing a smooth and responsive user experience, enabling real-time or near real-time processing of language inputs, and unlocking new use cases and applications that require real-time or near real-time processing of language inputs.\n" + ] + } + ], + "source": [ + "print(response)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "3ba9503c-b440-43c6-a50c-676c79993813", + "metadata": {}, + "source": [ + "#### Call `chat` with a list of messages" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ee8a4a55-5680-4dc6-a44c-fc8ad7892f80", + "metadata": {}, + "outputs": [], + "source": [ + "from llama_index.core.llms import ChatMessage\n", + "\n", + "messages = [\n", + " ChatMessage(\n", + " role=\"system\", content=\"You are a pirate with a colorful personality\"\n", + " ),\n", + " ChatMessage(role=\"user\", content=\"What is your name\"),\n", + "]\n", + "resp = llm.chat(messages)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2a9bfe53-d15b-4e75-9d91-8c5d024f4eda", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "assistant: Arr, I be known as Captain Redbeard, the fiercest pirate on the seven seas! But ye can call me Cap'n Redbeard for short. I'm a fearsome pirate with a love for treasure and adventure, and I'm always ready for a good time! Whether I'm swabbin' the deck or swiggin' grog, I'm always up for a bit of fun. So hoist the Jolly Roger and let's set sail for adventure, me hearties!\n" + ] + } + ], + "source": [ + "print(resp)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "25ad1b00-28fc-4bcd-96c4-d5b35605721a", + "metadata": {}, + "source": [ + "### Streaming" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "13c641fa-345a-4dce-87c5-ab1f6dcf4757", + "metadata": {}, + "source": [ + "Using `stream_complete` endpoint " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "06da1ef1-2f6b-497c-847b-62dd2df11491", + "metadata": {}, + "outputs": [], + "source": [ + "response = llm.stream_complete(\"Explain the importance of low latency LLMs\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1b851def-5160-46e5-a30c-5a3ef2356b79", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Low latency Large Language Models (LLMs) are important in the field of artificial intelligence and natural language processing (NLP) due to several reasons:\n", + "\n", + "1. Real-time applications: Low latency LLMs are essential for real-time applications such as chatbots, voice assistants, and real-time translation services. These applications require immediate responses, and high latency can result in a poor user experience.\n", + "2. Improved user experience: Low latency LLMs can provide a more seamless and responsive user experience. Users are more likely to continue using a service that provides quick and accurate responses, leading to higher user engagement and satisfaction.\n", + "3. Better decision-making: In some applications, such as financial trading or autonomous vehicles, low latency LLMs can provide critical information in real-time, enabling better decision-making and reducing the risk of accidents.\n", + "4. Scalability: Low latency LLMs can handle a higher volume of requests, making them more scalable and suitable for large-scale applications.\n", + "5. Competitive advantage: Low latency LLMs can provide a competitive advantage in industries where real-time decision-making and responsiveness are critical. For example, in online gaming or e-commerce, low latency LLMs can provide a more immersive and engaging user experience, leading to higher customer loyalty and revenue.\n", + "\n", + "In summary, low latency LLMs are essential for real-time applications, providing a better user experience, enabling better decision-making, improving scalability, and providing a competitive advantage. As LLMs continue to play an increasingly important role in various industries, low latency will become even more critical for their success." + ] + } + ], + "source": [ + "for r in response:\n", + " print(r.delta, end=\"\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "ca52051d-6b28-49d7-98f5-82e266a1c7a6", + "metadata": {}, + "source": [ + "Using `stream_chat` endpoint" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fe553190-52a9-436d-84ae-4dd99a1808f4", + "metadata": {}, + "outputs": [], + "source": [ + "from llama_index.core.llms import ChatMessage\n", + "\n", + "messages = [\n", + " ChatMessage(\n", + " role=\"system\", content=\"You are a pirate with a colorful personality\"\n", + " ),\n", + " ChatMessage(role=\"user\", content=\"What is your name\"),\n", + "]\n", + "resp = llm.stream_chat(messages)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "154c503c-f893-4b6b-8a65-a9a27b636046", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Arr, I be known as Captain Candybeard! A more colorful and swashbuckling pirate, ye will never find!" + ] + } + ], + "source": [ + "for r in resp:\n", + " print(r.delta, end=\"\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/module_guides/models/llms/modules.md b/docs/module_guides/models/llms/modules.md index 66e93f0f3e30b..a94cc66010b4e 100644 --- a/docs/module_guides/models/llms/modules.md +++ b/docs/module_guides/models/llms/modules.md @@ -94,6 +94,15 @@ maxdepth: 1 /examples/llm/gradient_model_adapter.ipynb ``` +## Groq + +```{toctree} +--- +maxdepth: 1 +--- +/examples/llm/groq.ipynb +``` + ## Hugging Face ```{toctree} diff --git a/llama-index-integrations/llms/llama-index-llms-groq/.gitignore b/llama-index-integrations/llms/llama-index-llms-groq/.gitignore new file mode 100644 index 0000000000000..990c18de22908 --- /dev/null +++ b/llama-index-integrations/llms/llama-index-llms-groq/.gitignore @@ -0,0 +1,153 @@ +llama_index/_static +.DS_Store +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +bin/ +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +etc/ +include/ +lib/ +lib64/ +parts/ +sdist/ +share/ +var/ +wheels/ +pip-wheel-metadata/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +.ruff_cache + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +target/ + +# Jupyter Notebook +.ipynb_checkpoints +notebooks/ + +# IPython +profile_default/ +ipython_config.py + +# pyenv +.python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ +pyvenv.cfg + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# Jetbrains +.idea +modules/ +*.swp + +# VsCode +.vscode + +# pipenv +Pipfile +Pipfile.lock + +# pyright +pyrightconfig.json diff --git a/llama-index-integrations/llms/llama-index-llms-groq/BUILD b/llama-index-integrations/llms/llama-index-llms-groq/BUILD new file mode 100644 index 0000000000000..0896ca890d8bf --- /dev/null +++ b/llama-index-integrations/llms/llama-index-llms-groq/BUILD @@ -0,0 +1,3 @@ +poetry_requirements( + name="poetry", +) diff --git a/llama-index-integrations/llms/llama-index-llms-groq/Makefile b/llama-index-integrations/llms/llama-index-llms-groq/Makefile new file mode 100644 index 0000000000000..b9eab05aa3706 --- /dev/null +++ b/llama-index-integrations/llms/llama-index-llms-groq/Makefile @@ -0,0 +1,17 @@ +GIT_ROOT ?= $(shell git rev-parse --show-toplevel) + +help: ## Show all Makefile targets. + @grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[33m%-30s\033[0m %s\n", $$1, $$2}' + +format: ## Run code autoformatters (black). + pre-commit install + git ls-files | xargs pre-commit run black --files + +lint: ## Run linters: pre-commit (black, ruff, codespell) and mypy + pre-commit install && git ls-files | xargs pre-commit run --show-diff-on-failure --files + +test: ## Run tests via pytest. + pytest tests + +watch-docs: ## Build and watch documentation. + sphinx-autobuild docs/ docs/_build/html --open-browser --watch $(GIT_ROOT)/llama_index/ diff --git a/llama-index-integrations/llms/llama-index-llms-groq/README.md b/llama-index-integrations/llms/llama-index-llms-groq/README.md new file mode 100644 index 0000000000000..99ea8b26666b4 --- /dev/null +++ b/llama-index-integrations/llms/llama-index-llms-groq/README.md @@ -0,0 +1,52 @@ +# LlamaIndex Llms Integration: Groq + +Welcome to Groq! 🚀 At Groq, we've developed the world's first Language Processing Unit™, or LPU. The Groq LPU has a deterministic, single core streaming architecture that sets the standard for GenAI inference speed with predictable and repeatable performance for any given workload. + +Beyond the architecture, our software is designed to empower developers like you with the tools you need to create innovative, powerful AI applications. With Groq as your engine, you can: + +- Achieve uncompromised low latency and performance for real-time AI and HPC inferences 🔥 +- Know the exact performance and compute time for any given workload 🔮 +- Take advantage of our cutting-edge technology to stay ahead of the competition 💪 + +Want more Groq? Check out our [website](https://groq.com) for more resources and join our [Discord community](https://discord.gg/JvNsBDKeCG) to connect with our developers! + +## Develop + +To create a development environment, install poetry then run: + +```bash +poetry install --with dev +``` + +## Testing + +To test the integration, first enter the poetry venv: + +```bash +poetry shell +``` + +Then tests can be run with make + +```bash +make test +``` + +### Integration tests + +Integration tests will be skipped unless an API key is provided. API keys can be created ath the [groq console](https://console.groq.com/keys). +Once created, store the API key in an environment variable and run tests + +```bash +export GROQ_API_KEY= +make test +``` + +## Linting and Formatting + +Linting and code formatting can be executed with make. + +```bash +make format +make lint +``` diff --git a/llama-index-integrations/llms/llama-index-llms-groq/llama_index/llms/groq/BUILD b/llama-index-integrations/llms/llama-index-llms-groq/llama_index/llms/groq/BUILD new file mode 100644 index 0000000000000..db46e8d6c978c --- /dev/null +++ b/llama-index-integrations/llms/llama-index-llms-groq/llama_index/llms/groq/BUILD @@ -0,0 +1 @@ +python_sources() diff --git a/llama-index-integrations/llms/llama-index-llms-groq/llama_index/llms/groq/__init__.py b/llama-index-integrations/llms/llama-index-llms-groq/llama_index/llms/groq/__init__.py new file mode 100644 index 0000000000000..45fedbbff3446 --- /dev/null +++ b/llama-index-integrations/llms/llama-index-llms-groq/llama_index/llms/groq/__init__.py @@ -0,0 +1,3 @@ +from llama_index.llms.groq.base import Groq + +__all__ = ["Groq"] diff --git a/llama-index-integrations/llms/llama-index-llms-groq/llama_index/llms/groq/base.py b/llama-index-integrations/llms/llama-index-llms-groq/llama_index/llms/groq/base.py new file mode 100644 index 0000000000000..fed294f6c8b52 --- /dev/null +++ b/llama-index-integrations/llms/llama-index-llms-groq/llama_index/llms/groq/base.py @@ -0,0 +1,28 @@ +import os +from typing import Any, Optional + +from llama_index.llms.openai_like import OpenAILike + + +class Groq(OpenAILike): + def __init__( + self, + model: str, + api_key: Optional[str] = None, + api_base: str = "https://api.groq.com/openai/v1", + is_chat_model: bool = True, + **kwargs: Any, + ) -> None: + api_key = api_key or os.environ.get("GROQ_API_KEY", None) + super().__init__( + model=model, + api_key=api_key, + api_base=api_base, + is_chat_model=is_chat_model, + **kwargs, + ) + + @classmethod + def class_name(cls) -> str: + """Get class name.""" + return "Groq" diff --git a/llama-index-integrations/llms/llama-index-llms-groq/pyproject.toml b/llama-index-integrations/llms/llama-index-llms-groq/pyproject.toml new file mode 100644 index 0000000000000..0a90d93ead5e5 --- /dev/null +++ b/llama-index-integrations/llms/llama-index-llms-groq/pyproject.toml @@ -0,0 +1,63 @@ +[build-system] +build-backend = "poetry.core.masonry.api" +requires = ["poetry-core"] + +[tool.codespell] +check-filenames = true +check-hidden = true +skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb" + +[tool.llamahub] +contains_example = false +import_path = "llama_index.llms.groq" + +[tool.llamahub.class_authors] +Groq = "gradenr" + +[tool.mypy] +disallow_untyped_defs = true +exclude = ["_static", "build", "examples", "notebooks", "venv"] +ignore_missing_imports = true +python_version = "3.8" + +[tool.poetry] +authors = ["Your Name "] +description = "llama-index llms groq integration" +exclude = ["**/BUILD"] +license = "MIT" +name = "llama-index-llms-groq" +readme = "README.md" +version = "0.1.3" + +[tool.poetry.dependencies] +python = ">=3.8.1,<4.0" +llama-index-core = "^0.10.1" +llama-index-llms-openai-like = "^0.1.3" + +[tool.poetry.group.dev.dependencies] +ipython = "8.10.0" +jupyter = "^1.0.0" +mypy = "0.991" +pre-commit = "3.2.0" +pylint = "2.15.10" +pytest = "7.2.1" +pytest-mock = "3.11.1" +ruff = "0.0.292" +tree-sitter-languages = "^1.8.0" +types-Deprecated = ">=0.1.0" +types-PyYAML = "^6.0.12.12" +types-protobuf = "^4.24.0.4" +types-redis = "4.5.5.0" +types-requests = "2.28.11.8" +types-setuptools = "67.1.0.0" + +[tool.poetry.group.dev.dependencies.black] +extras = ["jupyter"] +version = "<=23.9.1,>=23.7.0" + +[tool.poetry.group.dev.dependencies.codespell] +extras = ["toml"] +version = ">=v2.2.6" + +[[tool.poetry.packages]] +include = "llama_index/" diff --git a/llama-index-integrations/llms/llama-index-llms-groq/tests/BUILD b/llama-index-integrations/llms/llama-index-llms-groq/tests/BUILD new file mode 100644 index 0000000000000..dabf212d7e716 --- /dev/null +++ b/llama-index-integrations/llms/llama-index-llms-groq/tests/BUILD @@ -0,0 +1 @@ +python_tests() diff --git a/llama-index-integrations/llms/llama-index-llms-groq/tests/__init__.py b/llama-index-integrations/llms/llama-index-llms-groq/tests/__init__.py new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/llama-index-integrations/llms/llama-index-llms-groq/tests/test_integration_groq.py b/llama-index-integrations/llms/llama-index-llms-groq/tests/test_integration_groq.py new file mode 100644 index 0000000000000..4f1ca90960c54 --- /dev/null +++ b/llama-index-integrations/llms/llama-index-llms-groq/tests/test_integration_groq.py @@ -0,0 +1,22 @@ +import os + +import pytest + +from llama_index.llms.groq import Groq + + +@pytest.mark.skipif("GROQ_API_KEY" not in os.environ, reason="No Groq API key") +def test_completion(): + groq = Groq(model="mixtral-8x7b-32768", temperature=0, max_tokens=2) + resp = groq.complete("hello") + assert resp.text == "Hello" + + +@pytest.mark.skipif("GROQ_API_KEY" not in os.environ, reason="No Groq API key") +def test_stream_completion(): + groq = Groq(model="mixtral-8x7b-32768", temperature=0, max_tokens=2) + stream = groq.stream_complete("hello") + text = None + for chunk in stream: + text = chunk.text + assert text == "Hello" diff --git a/llama-index-integrations/llms/llama-index-llms-groq/tests/test_llms_groq.py b/llama-index-integrations/llms/llama-index-llms-groq/tests/test_llms_groq.py new file mode 100644 index 0000000000000..bfcef34eb0216 --- /dev/null +++ b/llama-index-integrations/llms/llama-index-llms-groq/tests/test_llms_groq.py @@ -0,0 +1,7 @@ +from llama_index.core.base.llms.base import BaseLLM +from llama_index.llms.groq import Groq + + +def test_embedding_class(): + names_of_base_classes = [b.__name__ for b in Groq.__mro__] + assert BaseLLM.__name__ in names_of_base_classes From f6ad23eb6613cfc57ebd8883c3815ce4dc0fb1bf Mon Sep 17 00:00:00 2001 From: Rana Banerjee Date: Sat, 24 Feb 2024 00:56:22 +0530 Subject: [PATCH 09/30] Return the object along with the subject when extracting the keywords (#11326) --- .../llama_index/core/indices/knowledge_graph/retrievers.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/llama-index-core/llama_index/core/indices/knowledge_graph/retrievers.py b/llama-index-core/llama_index/core/indices/knowledge_graph/retrievers.py index 91bd96719272b..4256eeb3d3832 100644 --- a/llama-index-core/llama_index/core/indices/knowledge_graph/retrievers.py +++ b/llama-index-core/llama_index/core/indices/knowledge_graph/retrievers.py @@ -173,6 +173,10 @@ def _extract_rel_text_keywords(self, rel_texts: List[str]) -> List[str]: keyword = rel_text.split(",")[0] if keyword: keywords.append(keyword.strip("(\"'")) + # Return the Object as well + keyword = rel_text.split(",")[2] + if keyword: + keywords.append(keyword.strip(" ()\"'")) return keywords def _retrieve( From ab367af700b50d115d3d58e3bfe228955bfed029 Mon Sep 17 00:00:00 2001 From: Michael David Date: Fri, 23 Feb 2024 11:37:22 -0800 Subject: [PATCH 10/30] Fix milvus delete with ref_doc_ids when they don't exist (#11315) --- .../llama_index/vector_stores/milvus/base.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/llama-index-integrations/vector_stores/llama-index-vector-stores-milvus/llama_index/vector_stores/milvus/base.py b/llama-index-integrations/vector_stores/llama-index-vector-stores-milvus/llama_index/vector_stores/milvus/base.py index 65d8fafb002e7..570ed49fc0927 100644 --- a/llama-index-integrations/vector_stores/llama-index-vector-stores-milvus/llama_index/vector_stores/milvus/base.py +++ b/llama-index-integrations/vector_stores/llama-index-vector-stores-milvus/llama_index/vector_stores/milvus/base.py @@ -221,9 +221,10 @@ def delete(self, ref_doc_id: str, **delete_kwargs: Any) -> None: collection_name=self.collection_name, filter=f"{self.doc_id_field} in [{','.join(doc_ids)}]", ) - ids = [entry["id"] for entry in entries] - self.milvusclient.delete(collection_name=self.collection_name, pks=ids) - logger.debug(f"Successfully deleted embedding with doc_id: {doc_ids}") + if len(entries) > 0: + ids = [entry["id"] for entry in entries] + self.milvusclient.delete(collection_name=self.collection_name, pks=ids) + logger.debug(f"Successfully deleted embedding with doc_id: {doc_ids}") def query(self, query: VectorStoreQuery, **kwargs: Any) -> VectorStoreQueryResult: """Query index for top k most similar nodes. From b285c6f8bf640266357befcc3654f394738376f7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Benjamin=20Clavi=C3=A9?= Date: Fri, 23 Feb 2024 22:42:29 +0100 Subject: [PATCH 11/30] fix(ColbertRerank): calculate ColBERT similarity per token rather than vs pooled query embeds (#11335) fix: calculate ColBERT similarity per token rather than vs pooled query embedding --- .../llama_index/postprocessor/colbert_rerank/base.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/llama-index-integrations/postprocessor/llama-index-postprocessor-colbert-rerank/llama_index/postprocessor/colbert_rerank/base.py b/llama-index-integrations/postprocessor/llama-index-postprocessor-colbert-rerank/llama_index/postprocessor/colbert_rerank/base.py index dbf08fefbc216..c934ec2dc28c0 100644 --- a/llama-index-integrations/postprocessor/llama-index-postprocessor-colbert-rerank/llama_index/postprocessor/colbert_rerank/base.py +++ b/llama-index-integrations/postprocessor/llama-index-postprocessor-colbert-rerank/llama_index/postprocessor/colbert_rerank/base.py @@ -53,9 +53,7 @@ def _calculate_sim(self, query: str, documents_text_list: List[str]) -> List[flo # Query: [batch_size, query_length, embedding_size] -> [batch_size, query_length, 1, embedding_size] # Document: [batch_size, doc_length, embedding_size] -> [batch_size, 1, doc_length, embedding_size] query_encoding = self._tokenizer(query, return_tensors="pt") - query_embedding = ( - self._model(**query_encoding).last_hidden_state.mean(dim=1).unsqueeze(0) - ) + query_embedding = self._model(**query_encoding).last_hidden_state rerank_score_list = [] for document_text in documents_text_list: From a0123bb18d930e9e5e5e8a5e9a908f8be47ff3bc Mon Sep 17 00:00:00 2001 From: Naveen Tatikonda Date: Fri, 23 Feb 2024 16:49:16 -0600 Subject: [PATCH 12/30] Update OpenSearch Documentation (#11334) --- docs/module_guides/storing/vector_stores.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/module_guides/storing/vector_stores.md b/docs/module_guides/storing/vector_stores.md index e09e63318e9db..c55268e35c4d8 100644 --- a/docs/module_guides/storing/vector_stores.md +++ b/docs/module_guides/storing/vector_stores.md @@ -36,7 +36,7 @@ We are actively adding more integrations and improving feature coverage for each | MyScale | cloud | ✓ | ✓ | ✓ | ✓ | | | Milvus / Zilliz | self-hosted / cloud | ✓ | | ✓ | ✓ | | | Neo4jVector | self-hosted / cloud | | | ✓ | ✓ | | -| OpenSearch | self-hosted / cloud | ✓ | | ✓ | ✓ | | +| OpenSearch | self-hosted / cloud | ✓ | | ✓ | ✓ | ✓ | | Pinecone | cloud | ✓ | ✓ | ✓ | ✓ | | | Postgres | self-hosted / cloud | ✓ | ✓ | ✓ | ✓ | ✓ | | pgvecto.rs | self-hosted / cloud | ✓ | ✓ | ✓ | ✓ | | From ebf757b7a24d7c9a555bb6dabc39d12a04765bbe Mon Sep 17 00:00:00 2001 From: Haotian Zhang Date: Fri, 23 Feb 2024 19:42:12 -0500 Subject: [PATCH 13/30] fix pkg for Fireworks (#11339) --- .../llama-index-embeddings-fireworks/pyproject.toml | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-fireworks/pyproject.toml b/llama-index-integrations/embeddings/llama-index-embeddings-fireworks/pyproject.toml index b70613264a68b..4eb400aa05e7b 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-fireworks/pyproject.toml +++ b/llama-index-integrations/embeddings/llama-index-embeddings-fireworks/pyproject.toml @@ -8,19 +8,20 @@ check-hidden = true skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb" [tool.llamahub] -classes = ["FireworksEmbedding"] contains_example = false import_path = "llama_index.embeddings.fireworks" +[tool.llamahub.class_authors] +FireworksEmbedding = "benjibc" + [tool.mypy] disallow_untyped_defs = true exclude = ["_static", "build", "examples", "notebooks", "venv"] -explicit_package_bases = true ignore_missing_imports = true python_version = "3.8" [tool.poetry] -authors = ["Your Name "] +authors = ["benjibc"] description = "llama-index embeddings fireworks integration" license = "MIT" name = "llama-index-embeddings-fireworks" @@ -29,7 +30,7 @@ version = "0.1.1" [tool.poetry.dependencies] python = ">=3.8.1,<3.12" -llama-index-core = "^0.10.1" +llama-index-core = "^0.10.12" llama-index-llms-openai = "^0.1.1" [tool.poetry.group.dev.dependencies] From 44faac91742ef688d66f16cfd1adb811f43b53c2 Mon Sep 17 00:00:00 2001 From: Vitali Avagyan Date: Sat, 24 Feb 2024 01:00:25 +0000 Subject: [PATCH 14/30] fix: support other regions for aws s3 storage (#11340) --- docs/examples/llm/mymagic.ipynb | 2 ++ .../llama_index/llms/mymagic/base.py | 7 ++++++- 2 files changed, 8 insertions(+), 1 deletion(-) diff --git a/docs/examples/llm/mymagic.ipynb b/docs/examples/llm/mymagic.ipynb index d1ee8a10a3251..823dffe442058 100644 --- a/docs/examples/llm/mymagic.ipynb +++ b/docs/examples/llm/mymagic.ipynb @@ -66,6 +66,7 @@ " session=\"your-session-name\", # files should be located in this folder on which batch inference will be run\n", " role_arn=\"your-role-arn\",\n", " system_prompt=\"your-system-prompt\",\n", + " region=\"your-bucket-region\",\n", ")" ] }, @@ -123,6 +124,7 @@ " session=\"your-session-name\", # files should be located in this folder on which batch inference will be run\n", " role_arn=\"your-role-arn\",\n", " system_prompt=\"your-system-prompt\",\n", + " region=\"your-bucket-region\",\n", " )\n", " response = await allm.acomplete(\n", " question=\"your-question\",\n", diff --git a/llama-index-integrations/llms/llama-index-llms-mymagic/llama_index/llms/mymagic/base.py b/llama-index-integrations/llms/llama-index-llms-mymagic/llama_index/llms/mymagic/base.py index 9c3f6f3ea3ae3..5d7e49d15be0b 100644 --- a/llama-index-integrations/llms/llama-index-llms-mymagic/llama_index/llms/mymagic/base.py +++ b/llama-index-integrations/llms/llama-index-llms-mymagic/llama_index/llms/mymagic/base.py @@ -36,7 +36,7 @@ class MyMagicAI(LLM): description="The session to use. This is a subfolder in the bucket where your data is located.", ) role_arn: Optional[str] = Field( - None, description="ARN for role assumption in AWS S3" + None, description="ARN for role assumption in AWS S3." ) system_prompt: str = Field( default="Answer the question based only on the given content. Do not give explanations or examples. Do not continue generating more text after the answer.", @@ -45,6 +45,9 @@ class MyMagicAI(LLM): question_data: Dict[str, Any] = Field( default_factory=dict, description="The data to send to the MyMagicAI API." ) + region: Optional[str] = Field( + "eu-west-2", description="The region the bucket is in. Only used for AWS S3." + ) def __init__( self, @@ -54,6 +57,7 @@ def __init__( session: str, system_prompt: Optional[str], role_arn: Optional[str] = None, + region: Optional[str] = None, **kwargs: Any, ) -> None: super().__init__(**kwargs) @@ -66,6 +70,7 @@ def __init__( "max_tokens": self.max_tokens, "role_arn": role_arn, "system_prompt": system_prompt, + "region": region, } @classmethod From c127baca5422e50af0962a9a94f32436d8f7845b Mon Sep 17 00:00:00 2001 From: "Yufei (Benny) Chen" <1585539+benjibc@users.noreply.github.com> Date: Fri, 23 Feb 2024 20:33:04 -0800 Subject: [PATCH 15/30] two more notebooks for Fireworks (#11343) --- .../vector_stores/ChromaFireworksNomic.ipynb | 382 +++++++ ...MongoDBAtlasVectorSearchRAGFireworks.ipynb | 956 ++++++++++++++++++ 2 files changed, 1338 insertions(+) create mode 100644 docs/examples/vector_stores/ChromaFireworksNomic.ipynb create mode 100644 docs/examples/vector_stores/MongoDBAtlasVectorSearchRAGFireworks.ipynb diff --git a/docs/examples/vector_stores/ChromaFireworksNomic.ipynb b/docs/examples/vector_stores/ChromaFireworksNomic.ipynb new file mode 100644 index 0000000000000..6193a1d41e749 --- /dev/null +++ b/docs/examples/vector_stores/ChromaFireworksNomic.ipynb @@ -0,0 +1,382 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "id": "0af3ec93", + "metadata": {}, + "source": [ + "\"Open" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "307804a3-c02b-4a57-ac0d-172c30ddc851", + "metadata": {}, + "source": [ + "# Chroma + Fireworks + Nomic with Matryoshka embedding\n", + "\n", + "This example is adapted from the ChromaIndex example, + how to use Matryoshka embedding from Nomic on top of Fireworks.ai.\n", + "\n", + "## Chroma\n", + "\n", + ">[Chroma](https://docs.trychroma.com/getting-started) is a AI-native open-source vector database focused on developer productivity and happiness. Chroma is licensed under Apache 2.0.\n", + "\n", + "\n", + " \"Discord\"\n", + "   \n", + " \n", + " \"License\"\n", + "   \n", + " \"Integration\n", + "\n", + "- [Website](https://www.trychroma.com/)\n", + "- [Documentation](https://docs.trychroma.com/)\n", + "- [Twitter](https://twitter.com/trychroma)\n", + "- [Discord](https://discord.gg/MMeYNTmh3x)\n", + "\n", + "Chroma is fully-typed, fully-tested and fully-documented.\n", + "\n", + "Install Chroma with:\n", + "\n", + "```sh\n", + "pip install chromadb\n", + "```\n", + "\n", + "Chroma runs in various modes. See below for examples of each integrated with LangChain.\n", + "- `in-memory` - in a python script or jupyter notebook\n", + "- `in-memory with persistance` - in a script or notebook and save/load to disk\n", + "- `in a docker container` - as a server running your local machine or in the cloud\n", + "\n", + "Like any other database, you can: \n", + "- `.add` \n", + "- `.get` \n", + "- `.update`\n", + "- `.upsert`\n", + "- `.delete`\n", + "- `.peek`\n", + "- and `.query` runs the similarity search.\n", + "\n", + "View full docs at [docs](https://docs.trychroma.com/reference/Collection). \n", + "\n", + "## Nomic\n", + "\n", + "Nomic published a new embedding model nomic-ai/nomic-embed-text-v1.5 that is capable of returning variable embedding size depending on how cost sensitive you are. For more information please check out their model [here](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5) and their website [here](https://home.nomic.ai/)\n", + "\n", + "## Fireworks.ai\n", + "\n", + "Fireworks is the leading OSS model inference provider. In this example we will use Fireworks to run the nomic model as well as mixtral-8x7b-instruct model as the query engine. For more information about fireworks, please check out their website [here](https://fireworks.ai)\n" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "b5331b6b", + "metadata": {}, + "source": [ + "## Basic Example\n", + "\n", + "In this basic example, we take the Paul Graham essay, split it into chunks, embed it using an open-source embedding model, load it into Chroma, and then query it." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "54361467", + "metadata": {}, + "source": [ + "If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e46f9e63", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "%pip install -q llama-index-vector-stores-chroma llama-index-llms-fireworks llama-index-embeddings-fireworks==0.1.2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0ffe7d98", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "%pip install -q llama-index" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "f7010b1d-d1bb-4f08-9309-a328bb4ea396", + "metadata": {}, + "source": [ + "#### Creating a Chroma Index" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b3df0b97", + "metadata": {}, + "outputs": [], + "source": [ + "!pip install llama-index chromadb --quiet\n", + "!pip install -q chromadb\n", + "!pip install -q pydantic==1.10.11" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d48af8e1", + "metadata": {}, + "outputs": [], + "source": [ + "# import\n", + "from llama_index.core import VectorStoreIndex, SimpleDirectoryReader\n", + "from llama_index.vector_stores.chroma import ChromaVectorStore\n", + "from llama_index.core import StorageContext\n", + "from llama_index.embeddings.fireworks import FireworksEmbedding\n", + "from llama_index.llms.fireworks import Fireworks\n", + "from IPython.display import Markdown, display\n", + "import chromadb" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "374a148b", + "metadata": {}, + "outputs": [], + "source": [ + "# set up Fireworks.ai Key\n", + "import getpass\n", + "\n", + "fw_api_key = getpass.getpass(\"Fireworks API Key:\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "7b9a55de", + "metadata": {}, + "source": [ + "Download Data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "01f19bc6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--2024-02-24 01:44:58-- https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt\n", + "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.111.133, 185.199.110.133, 185.199.109.133, ...\n", + "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.111.133|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 75042 (73K) [text/plain]\n", + "Saving to: ‘data/paul_graham/paul_graham_essay.txt’\n", + "\n", + "data/paul_graham/pa 100%[===================>] 73.28K --.-KB/s in 0.01s \n", + "\n", + "2024-02-24 01:44:58 (5.15 MB/s) - ‘data/paul_graham/paul_graham_essay.txt’ saved [75042/75042]\n", + "\n" + ] + } + ], + "source": [ + "!mkdir -p 'data/paul_graham/'\n", + "!wget 'https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt' -O 'data/paul_graham/paul_graham_essay.txt'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "667f3cb3-ce18-48d5-b9aa-bfc1a1f0f0f6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "show list of text ['file_path: data/paul_graham/paul_graham_essay.txt What I Worked On February 2021 Before college the two main things I worked on, outside of school, were writing and programming. I didn\\'t write essays. I wrote what beginning writers were supposed to write then, and probably still are: short stories. My stories were awful. They had hardly any plot, just characters with strong feelings, which I imagined made them deep. The first programs I tried writing were on the IBM 1401 that our school district used for what was then called \"data processing.\" This was in 9th grade, so I was 13 or 14. The school district\\'s 1401 happened to be in the basement of our junior high school, and my friend Rich Draves and I got permission to use it. It was like a mini Bond villain\\'s lair down there, with all these alien-looking machines — CPU, disk drives, printer, card reader — sitting up on a raised floor under bright fluorescent lights. The language we used was an early version of Fortran. You had to type programs on punch cards, then stack them in the card reader and press a button to load the program into memory and run it. The result would ordinarily be to print something on the spectacularly loud printer. I was puzzled by the 1401. I couldn\\'t figure out what to do with it. And in retrospect there\\'s not much I could have done with it. The only form of input to programs was data stored on punched cards, and I didn\\'t have any data stored on punched cards. The only other option was to do things that didn\\'t rely on any input, like calculate approximations of pi, but I didn\\'t know enough math to do anything interesting of that type. So I\\'m not surprised I can\\'t remember any programs I wrote, because they can\\'t have done much. My clearest memory is of the moment I learned it was possible for programs not to terminate, when one of mine didn\\'t. On a machine without time-sharing, this was a social as well as a technical error, as the data center manager\\'s expression made clear. With microcomputers, everything changed. Now you could have a computer sitting right in front of you, on a desk, that could respond to your keystrokes as it was running instead of just churning through a stack of punch cards and then stopping. [1] The first of my friends to get a microcomputer built it himself. It was sold as a kit by Heathkit. I remember vividly how impressed and envious I felt watching him sitting in front of it, typing programs right into the computer. Computers were expensive in those days and it took me years of nagging before I convinced my father to buy one, a TRS-80, in about 1980. The gold standard then was the Apple II, but a TRS-80 was good enough. This was when I really started programming. I wrote simple games, a program to predict how high my model rockets would fly, and a word processor that my father used to write at least one book. There was only room in memory for about 2 pages of text, so he\\'d write 2 pages at a time and then print them out, but it was a lot better than a typewriter. Though I liked programming, I didn\\'t plan to study it in college. In college I was going to study philosophy, which sounded much more powerful. It seemed, to my naive high school self, to be the study of the ultimate truths, compared to which the things studied in other fields would be mere domain knowledge. What I discovered when I got to college was that the other fields took up so much of the space of ideas that there wasn\\'t much left for these supposed ultimate truths. All that seemed left for philosophy were edge cases that people in other fields felt could safely be ignored. I couldn\\'t have put this into words when I was 18. All I knew at the time was that I kept taking philosophy courses and they kept being boring. So I decided to switch to AI. AI was in the air in the mid 1980s, but there were two things especially that made me want to work on it: a novel by Heinlein called The Moon is a Harsh Mistress, which featured an intelligent computer called Mike, and a PBS documentary that showed Terry Winograd using SHRDLU. I haven\\'t tried rereading The Moon is a Harsh Mistress, so I don\\'t know how well it has aged, but when I read it I was drawn entirely into its world. It seemed only a matter of time before we\\'d have Mike, and when I saw Winograd using SHRDLU, it seemed like that time would be a few years at most.', 'file_path: data/paul_graham/paul_graham_essay.txt I couldn\\'t have put this into words when I was 18. All I knew at the time was that I kept taking philosophy courses and they kept being boring. So I decided to switch to AI. AI was in the air in the mid 1980s, but there were two things especially that made me want to work on it: a novel by Heinlein called The Moon is a Harsh Mistress, which featured an intelligent computer called Mike, and a PBS documentary that showed Terry Winograd using SHRDLU. I haven\\'t tried rereading The Moon is a Harsh Mistress, so I don\\'t know how well it has aged, but when I read it I was drawn entirely into its world. It seemed only a matter of time before we\\'d have Mike, and when I saw Winograd using SHRDLU, it seemed like that time would be a few years at most. All you had to do was teach SHRDLU more words. There weren\\'t any classes in AI at Cornell then, not even graduate classes, so I started trying to teach myself. Which meant learning Lisp, since in those days Lisp was regarded as the language of AI. The commonly used programming languages then were pretty primitive, and programmers\\' ideas correspondingly so. The default language at Cornell was a Pascal-like language called PL/I, and the situation was similar elsewhere. Learning Lisp expanded my concept of a program so fast that it was years before I started to have a sense of where the new limits were. This was more like it; this was what I had expected college to do. It wasn\\'t happening in a class, like it was supposed to, but that was ok. For the next couple years I was on a roll. I knew what I was going to do. For my undergraduate thesis, I reverse-engineered SHRDLU. My God did I love working on that program. It was a pleasing bit of code, but what made it even more exciting was my belief — hard to imagine now, but not unique in 1985 — that it was already climbing the lower slopes of intelligence. I had gotten into a program at Cornell that didn\\'t make you choose a major. You could take whatever classes you liked, and choose whatever you liked to put on your degree. I of course chose \"Artificial Intelligence.\" When I got the actual physical diploma, I was dismayed to find that the quotes had been included, which made them read as scare-quotes. At the time this bothered me, but now it seems amusingly accurate, for reasons I was about to discover. I applied to 3 grad schools: MIT and Yale, which were renowned for AI at the time, and Harvard, which I\\'d visited because Rich Draves went there, and was also home to Bill Woods, who\\'d invented the type of parser I used in my SHRDLU clone. Only Harvard accepted me, so that was where I went. I don\\'t remember the moment it happened, or if there even was a specific moment, but during the first year of grad school I realized that AI, as practiced at the time, was a hoax. By which I mean the sort of AI in which a program that\\'s told \"the dog is sitting on the chair\" translates this into some formal representation and adds it to the list of things it knows. What these programs really showed was that there\\'s a subset of natural language that\\'s a formal language. But a very proper subset. It was clear that there was an unbridgeable gap between what they could do and actually understanding natural language. It was not, in fact, simply a matter of teaching SHRDLU more words. That whole way of doing AI, with explicit data structures representing concepts, was not going to work. Its brokenness did, as so often happens, generate a lot of opportunities to write papers about various band-aids that could be applied to it, but it was never going to get us Mike. So I looked around to see what I could salvage from the wreckage of my plans, and there was Lisp. I knew from experience that Lisp was interesting for its own sake and not just for its association with AI, even though that was the main reason people cared about it at the time. So I decided to focus on Lisp. In fact, I decided to write a book about Lisp hacking. It\\'s scary to think how little I knew about Lisp hacking when I started writing that book. But there\\'s nothing like writing a book about something to help you learn it. The book, On Lisp, wasn\\'t published till 1993, but I wrote much of it in grad school. Computer Science is an uneasy alliance between two halves, theory and systems. The theory people prove things, and the systems people build things. I wanted to build things.', 'file_path: data/paul_graham/paul_graham_essay.txt So I looked around to see what I could salvage from the wreckage of my plans, and there was Lisp. I knew from experience that Lisp was interesting for its own sake and not just for its association with AI, even though that was the main reason people cared about it at the time. So I decided to focus on Lisp. In fact, I decided to write a book about Lisp hacking. It\\'s scary to think how little I knew about Lisp hacking when I started writing that book. But there\\'s nothing like writing a book about something to help you learn it. The book, On Lisp, wasn\\'t published till 1993, but I wrote much of it in grad school. Computer Science is an uneasy alliance between two halves, theory and systems. The theory people prove things, and the systems people build things. I wanted to build things. I had plenty of respect for theory — indeed, a sneaking suspicion that it was the more admirable of the two halves — but building things seemed so much more exciting. The problem with systems work, though, was that it didn\\'t last. Any program you wrote today, no matter how good, would be obsolete in a couple decades at best. People might mention your software in footnotes, but no one would actually use it. And indeed, it would seem very feeble work. Only people with a sense of the history of the field would even realize that, in its time, it had been good. There were some surplus Xerox Dandelions floating around the computer lab at one point. Anyone who wanted one to play around with could have one. I was briefly tempted, but they were so slow by present standards; what was the point? No one else wanted one either, so off they went. That was what happened to systems work. I wanted not just to build things, but to build things that would last. In this dissatisfied state I went in 1988 to visit Rich Draves at CMU, where he was in grad school. One day I went to visit the Carnegie Institute, where I\\'d spent a lot of time as a kid. While looking at a painting there I realized something that might seem obvious, but was a big surprise to me. There, right on the wall, was something you could make that would last. Paintings didn\\'t become obsolete. Some of the best ones were hundreds of years old. And moreover this was something you could make a living doing. Not as easily as you could by writing software, of course, but I thought if you were really industrious and lived really cheaply, it had to be possible to make enough to survive. And as an artist you could be truly independent. You wouldn\\'t have a boss, or even need to get research funding. I had always liked looking at paintings. Could I make them? I had no idea. I\\'d never imagined it was even possible. I knew intellectually that people made art — that it didn\\'t just appear spontaneously — but it was as if the people who made it were a different species. They either lived long ago or were mysterious geniuses doing strange things in profiles in Life magazine. The idea of actually being able to make art, to put that verb before that noun, seemed almost miraculous. That fall I started taking art classes at Harvard. Grad students could take classes in any department, and my advisor, Tom Cheatham, was very easy going. If he even knew about the strange classes I was taking, he never said anything. So now I was in a PhD program in computer science, yet planning to be an artist, yet also genuinely in love with Lisp hacking and working away at On Lisp. In other words, like many a grad student, I was working energetically on multiple projects that were not my thesis. I didn\\'t see a way out of this situation. I didn\\'t want to drop out of grad school, but how else was I going to get out? I remember when my friend Robert Morris got kicked out of Cornell for writing the internet worm of 1988, I was envious that he\\'d found such a spectacular way to get out of grad school. Then one day in April 1990 a crack appeared in the wall. I ran into professor Cheatham and he asked if I was far enough along to graduate that June. I didn\\'t have a word of my dissertation written, but in what must have been the quickest bit of thinking in my life, I decided to take a shot at writing one in the 5 weeks or so that remained before the deadline, reusing parts of On Lisp where I could, and I was able to respond, with no perceptible delay \"Yes, I think so. I\\'ll give you something to read in a few days.\"', 'file_path: data/paul_graham/paul_graham_essay.txt I didn\\'t want to drop out of grad school, but how else was I going to get out? I remember when my friend Robert Morris got kicked out of Cornell for writing the internet worm of 1988, I was envious that he\\'d found such a spectacular way to get out of grad school. Then one day in April 1990 a crack appeared in the wall. I ran into professor Cheatham and he asked if I was far enough along to graduate that June. I didn\\'t have a word of my dissertation written, but in what must have been the quickest bit of thinking in my life, I decided to take a shot at writing one in the 5 weeks or so that remained before the deadline, reusing parts of On Lisp where I could, and I was able to respond, with no perceptible delay \"Yes, I think so. I\\'ll give you something to read in a few days.\" I picked applications of continuations as the topic. In retrospect I should have written about macros and embedded languages. There\\'s a whole world there that\\'s barely been explored. But all I wanted was to get out of grad school, and my rapidly written dissertation sufficed, just barely. Meanwhile I was applying to art schools. I applied to two: RISD in the US, and the Accademia di Belli Arti in Florence, which, because it was the oldest art school, I imagined would be good. RISD accepted me, and I never heard back from the Accademia, so off to Providence I went. I\\'d applied for the BFA program at RISD, which meant in effect that I had to go to college again. This was not as strange as it sounds, because I was only 25, and art schools are full of people of different ages. RISD counted me as a transfer sophomore and said I had to do the foundation that summer. The foundation means the classes that everyone has to take in fundamental subjects like drawing, color, and design. Toward the end of the summer I got a big surprise: a letter from the Accademia, which had been delayed because they\\'d sent it to Cambridge England instead of Cambridge Massachusetts, inviting me to take the entrance exam in Florence that fall. This was now only weeks away. My nice landlady let me leave my stuff in her attic. I had some money saved from consulting work I\\'d done in grad school; there was probably enough to last a year if I lived cheaply. Now all I had to do was learn Italian. Only stranieri (foreigners) had to take this entrance exam. In retrospect it may well have been a way of excluding them, because there were so many stranieri attracted by the idea of studying art in Florence that the Italian students would otherwise have been outnumbered. I was in decent shape at painting and drawing from the RISD foundation that summer, but I still don\\'t know how I managed to pass the written exam. I remember that I answered the essay question by writing about Cezanne, and that I cranked up the intellectual level as high as I could to make the most of my limited vocabulary. [2] I\\'m only up to age 25 and already there are such conspicuous patterns. Here I was, yet again about to attend some august institution in the hopes of learning about some prestigious subject, and yet again about to be disappointed. The students and faculty in the painting department at the Accademia were the nicest people you could imagine, but they had long since arrived at an arrangement whereby the students wouldn\\'t require the faculty to teach anything, and in return the faculty wouldn\\'t require the students to learn anything. And at the same time all involved would adhere outwardly to the conventions of a 19th century atelier. We actually had one of those little stoves, fed with kindling, that you see in 19th century studio paintings, and a nude model sitting as close to it as possible without getting burned. Except hardly anyone else painted her besides me. The rest of the students spent their time chatting or occasionally trying to imitate things they\\'d seen in American art magazines. Our model turned out to live just down the street from me. She made a living from a combination of modelling and making fakes for a local antique dealer. She\\'d copy an obscure old painting out of a book, and then he\\'d take the copy and maltreat it to make it look old. [3] While I was a student at the Accademia I started painting still lives in my bedroom at night. These paintings were tiny, because the room was, and because I painted them on leftover scraps of canvas, which was all I could afford at the time.', 'file_path: data/paul_graham/paul_graham_essay.txt We actually had one of those little stoves, fed with kindling, that you see in 19th century studio paintings, and a nude model sitting as close to it as possible without getting burned. Except hardly anyone else painted her besides me. The rest of the students spent their time chatting or occasionally trying to imitate things they\\'d seen in American art magazines. Our model turned out to live just down the street from me. She made a living from a combination of modelling and making fakes for a local antique dealer. She\\'d copy an obscure old painting out of a book, and then he\\'d take the copy and maltreat it to make it look old. [3] While I was a student at the Accademia I started painting still lives in my bedroom at night. These paintings were tiny, because the room was, and because I painted them on leftover scraps of canvas, which was all I could afford at the time. Painting still lives is different from painting people, because the subject, as its name suggests, can\\'t move. People can\\'t sit for more than about 15 minutes at a time, and when they do they don\\'t sit very still. So the traditional m.o. for painting people is to know how to paint a generic person, which you then modify to match the specific person you\\'re painting. Whereas a still life you can, if you want, copy pixel by pixel from what you\\'re seeing. You don\\'t want to stop there, of course, or you get merely photographic accuracy, and what makes a still life interesting is that it\\'s been through a head. You want to emphasize the visual cues that tell you, for example, that the reason the color changes suddenly at a certain point is that it\\'s the edge of an object. By subtly emphasizing such things you can make paintings that are more realistic than photographs not just in some metaphorical sense, but in the strict information-theoretic sense. [4] I liked painting still lives because I was curious about what I was seeing. In everyday life, we aren\\'t consciously aware of much we\\'re seeing. Most visual perception is handled by low-level processes that merely tell your brain \"that\\'s a water droplet\" without telling you details like where the lightest and darkest points are, or \"that\\'s a bush\" without telling you the shape and position of every leaf. This is a feature of brains, not a bug. In everyday life it would be distracting to notice every leaf on every bush. But when you have to paint something, you have to look more closely, and when you do there\\'s a lot to see. You can still be noticing new things after days of trying to paint something people usually take for granted, just as you can after days of trying to write an essay about something people usually take for granted. This is not the only way to paint. I\\'m not 100% sure it\\'s even a good way to paint. But it seemed a good enough bet to be worth trying. Our teacher, professor Ulivi, was a nice guy. He could see I worked hard, and gave me a good grade, which he wrote down in a sort of passport each student had. But the Accademia wasn\\'t teaching me anything except Italian, and my money was running out, so at the end of the first year I went back to the US. I wanted to go back to RISD, but I was now broke and RISD was very expensive, so I decided to get a job for a year and then return to RISD the next fall. I got one at a company called Interleaf, which made software for creating documents. You mean like Microsoft Word? Exactly. That was how I learned that low end software tends to eat high end software. But Interleaf still had a few years to live yet. [5] Interleaf had done something pretty bold. Inspired by Emacs, they\\'d added a scripting language, and even made the scripting language a dialect of Lisp. Now they wanted a Lisp hacker to write things in it. This was the closest thing I\\'ve had to a normal job, and I hereby apologize to my boss and coworkers, because I was a bad employee. Their Lisp was the thinnest icing on a giant C cake, and since I didn\\'t know C and didn\\'t want to learn it, I never understood most of the software. Plus I was terribly irresponsible. This was back when a programming job meant showing up every day during certain working hours. That seemed unnatural to me, and on this point the rest of the world is coming around to my way of thinking, but at the time it caused a lot of friction.', 'file_path: data/paul_graham/paul_graham_essay.txt But Interleaf still had a few years to live yet. [5] Interleaf had done something pretty bold. Inspired by Emacs, they\\'d added a scripting language, and even made the scripting language a dialect of Lisp. Now they wanted a Lisp hacker to write things in it. This was the closest thing I\\'ve had to a normal job, and I hereby apologize to my boss and coworkers, because I was a bad employee. Their Lisp was the thinnest icing on a giant C cake, and since I didn\\'t know C and didn\\'t want to learn it, I never understood most of the software. Plus I was terribly irresponsible. This was back when a programming job meant showing up every day during certain working hours. That seemed unnatural to me, and on this point the rest of the world is coming around to my way of thinking, but at the time it caused a lot of friction. Toward the end of the year I spent much of my time surreptitiously working on On Lisp, which I had by this time gotten a contract to publish. The good part was that I got paid huge amounts of money, especially by art student standards. In Florence, after paying my part of the rent, my budget for everything else had been $7 a day. Now I was getting paid more than 4 times that every hour, even when I was just sitting in a meeting. By living cheaply I not only managed to save enough to go back to RISD, but also paid off my college loans. I learned some useful things at Interleaf, though they were mostly about what not to do. I learned that it\\'s better for technology companies to be run by product people than sales people (though sales is a real skill and people who are good at it are really good at it), that it leads to bugs when code is edited by too many people, that cheap office space is no bargain if it\\'s depressing, that planned meetings are inferior to corridor conversations, that big, bureaucratic customers are a dangerous source of money, and that there\\'s not much overlap between conventional office hours and the optimal time for hacking, or conventional offices and the optimal place for it. But the most important thing I learned, and which I used in both Viaweb and Y Combinator, is that the low end eats the high end: that it\\'s good to be the \"entry level\" option, even though that will be less prestigious, because if you\\'re not, someone else will be, and will squash you against the ceiling. Which in turn means that prestige is a danger sign. When I left to go back to RISD the next fall, I arranged to do freelance work for the group that did projects for customers, and this was how I survived for the next several years. When I came back to visit for a project later on, someone told me about a new thing called HTML, which was, as he described it, a derivative of SGML. Markup language enthusiasts were an occupational hazard at Interleaf and I ignored him, but this HTML thing later became a big part of my life. In the fall of 1992 I moved back to Providence to continue at RISD. The foundation had merely been intro stuff, and the Accademia had been a (very civilized) joke. Now I was going to see what real art school was like. But alas it was more like the Accademia than not. Better organized, certainly, and a lot more expensive, but it was now becoming clear that art school did not bear the same relationship to art that medical school bore to medicine. At least not the painting department. The textile department, which my next door neighbor belonged to, seemed to be pretty rigorous. No doubt illustration and architecture were too. But painting was post-rigorous. Painting students were supposed to express themselves, which to the more worldly ones meant to try to cook up some sort of distinctive signature style. A signature style is the visual equivalent of what in show business is known as a \"schtick\": something that immediately identifies the work as yours and no one else\\'s. For example, when you see a painting that looks like a certain kind of cartoon, you know it\\'s by Roy Lichtenstein. So if you see a big painting of this type hanging in the apartment of a hedge fund manager, you know he paid millions of dollars for it. That\\'s not always why artists have a signature style, but it\\'s usually why buyers pay a lot for such work. [6] There were plenty of earnest students too: kids who \"could draw\" in high school, and now had come to what was supposed to be the best art school in the country, to learn to draw even better.', 'file_path: data/paul_graham/paul_graham_essay.txt Painting students were supposed to express themselves, which to the more worldly ones meant to try to cook up some sort of distinctive signature style. A signature style is the visual equivalent of what in show business is known as a \"schtick\": something that immediately identifies the work as yours and no one else\\'s. For example, when you see a painting that looks like a certain kind of cartoon, you know it\\'s by Roy Lichtenstein. So if you see a big painting of this type hanging in the apartment of a hedge fund manager, you know he paid millions of dollars for it. That\\'s not always why artists have a signature style, but it\\'s usually why buyers pay a lot for such work. [6] There were plenty of earnest students too: kids who \"could draw\" in high school, and now had come to what was supposed to be the best art school in the country, to learn to draw even better. They tended to be confused and demoralized by what they found at RISD, but they kept going, because painting was what they did. I was not one of the kids who could draw in high school, but at RISD I was definitely closer to their tribe than the tribe of signature style seekers. I learned a lot in the color class I took at RISD, but otherwise I was basically teaching myself to paint, and I could do that for free. So in 1993 I dropped out. I hung around Providence for a bit, and then my college friend Nancy Parmet did me a big favor. A rent-controlled apartment in a building her mother owned in New York was becoming vacant. Did I want it? It wasn\\'t much more than my current place, and New York was supposed to be where the artists were. So yes, I wanted it! [7] Asterix comics begin by zooming in on a tiny corner of Roman Gaul that turns out not to be controlled by the Romans. You can do something similar on a map of New York City: if you zoom in on the Upper East Side, there\\'s a tiny corner that\\'s not rich, or at least wasn\\'t in 1993. It\\'s called Yorkville, and that was my new home. Now I was a New York artist — in the strictly technical sense of making paintings and living in New York. I was nervous about money, because I could sense that Interleaf was on the way down. Freelance Lisp hacking work was very rare, and I didn\\'t want to have to program in another language, which in those days would have meant C++ if I was lucky. So with my unerring nose for financial opportunity, I decided to write another book on Lisp. This would be a popular book, the sort of book that could be used as a textbook. I imagined myself living frugally off the royalties and spending all my time painting. (The painting on the cover of this book, ANSI Common Lisp, is one that I painted around this time.) The best thing about New York for me was the presence of Idelle and Julian Weber. Idelle Weber was a painter, one of the early photorealists, and I\\'d taken her painting class at Harvard. I\\'ve never known a teacher more beloved by her students. Large numbers of former students kept in touch with her, including me. After I moved to New York I became her de facto studio assistant. She liked to paint on big, square canvases, 4 to 5 feet on a side. One day in late 1994 as I was stretching one of these monsters there was something on the radio about a famous fund manager. He wasn\\'t that much older than me, and was super rich. The thought suddenly occurred to me: why don\\'t I become rich? Then I\\'ll be able to work on whatever I want. Meanwhile I\\'d been hearing more and more about this new thing called the World Wide Web. Robert Morris showed it to me when I visited him in Cambridge, where he was now in grad school at Harvard. It seemed to me that the web would be a big deal. I\\'d seen what graphical user interfaces had done for the popularity of microcomputers. It seemed like the web would do the same for the internet. If I wanted to get rich, here was the next train leaving the station. I was right about that part. What I got wrong was the idea. I decided we should start a company to put art galleries online. I can\\'t honestly say, after reading so many Y Combinator applications, that this was the worst startup idea ever, but it was up there. Art galleries didn\\'t want to be online, and still don\\'t, not the fancy ones. That\\'s not how they sell.', 'file_path: data/paul_graham/paul_graham_essay.txt Meanwhile I\\'d been hearing more and more about this new thing called the World Wide Web. Robert Morris showed it to me when I visited him in Cambridge, where he was now in grad school at Harvard. It seemed to me that the web would be a big deal. I\\'d seen what graphical user interfaces had done for the popularity of microcomputers. It seemed like the web would do the same for the internet. If I wanted to get rich, here was the next train leaving the station. I was right about that part. What I got wrong was the idea. I decided we should start a company to put art galleries online. I can\\'t honestly say, after reading so many Y Combinator applications, that this was the worst startup idea ever, but it was up there. Art galleries didn\\'t want to be online, and still don\\'t, not the fancy ones. That\\'s not how they sell. I wrote some software to generate web sites for galleries, and Robert wrote some to resize images and set up an http server to serve the pages. Then we tried to sign up galleries. To call this a difficult sale would be an understatement. It was difficult to give away. A few galleries let us make sites for them for free, but none paid us. Then some online stores started to appear, and I realized that except for the order buttons they were identical to the sites we\\'d been generating for galleries. This impressive-sounding thing called an \"internet storefront\" was something we already knew how to build. So in the summer of 1995, after I submitted the camera-ready copy of ANSI Common Lisp to the publishers, we started trying to write software to build online stores. At first this was going to be normal desktop software, which in those days meant Windows software. That was an alarming prospect, because neither of us knew how to write Windows software or wanted to learn. We lived in the Unix world. But we decided we\\'d at least try writing a prototype store builder on Unix. Robert wrote a shopping cart, and I wrote a new site generator for stores — in Lisp, of course. We were working out of Robert\\'s apartment in Cambridge. His roommate was away for big chunks of time, during which I got to sleep in his room. For some reason there was no bed frame or sheets, just a mattress on the floor. One morning as I was lying on this mattress I had an idea that made me sit up like a capital L. What if we ran the software on the server, and let users control it by clicking on links? Then we\\'d never have to write anything to run on users\\' computers. We could generate the sites on the same server we\\'d serve them from. Users wouldn\\'t need anything more than a browser. This kind of software, known as a web app, is common now, but at the time it wasn\\'t clear that it was even possible. To find out, we decided to try making a version of our store builder that you could control through the browser. A couple days later, on August 12, we had one that worked. The UI was horrible, but it proved you could build a whole store through the browser, without any client software or typing anything into the command line on the server. Now we felt like we were really onto something. I had visions of a whole new generation of software working this way. You wouldn\\'t need versions, or ports, or any of that crap. At Interleaf there had been a whole group called Release Engineering that seemed to be at least as big as the group that actually wrote the software. Now you could just update the software right on the server. We started a new company we called Viaweb, after the fact that our software worked via the web, and we got $10,000 in seed funding from Idelle\\'s husband Julian. In return for that and doing the initial legal work and giving us business advice, we gave him 10% of the company. Ten years later this deal became the model for Y Combinator\\'s. We knew founders needed something like this, because we\\'d needed it ourselves. At this stage I had a negative net worth, because the thousand dollars or so I had in the bank was more than counterbalanced by what I owed the government in taxes. (Had I diligently set aside the proper proportion of the money I\\'d made consulting for Interleaf? No, I had not.) So although Robert had his graduate student stipend, I needed that seed funding to live on. We originally hoped to launch in September, but we got more ambitious about the software as we worked on it.', 'file_path: data/paul_graham/paul_graham_essay.txt In return for that and doing the initial legal work and giving us business advice, we gave him 10% of the company. Ten years later this deal became the model for Y Combinator\\'s. We knew founders needed something like this, because we\\'d needed it ourselves. At this stage I had a negative net worth, because the thousand dollars or so I had in the bank was more than counterbalanced by what I owed the government in taxes. (Had I diligently set aside the proper proportion of the money I\\'d made consulting for Interleaf? No, I had not.) So although Robert had his graduate student stipend, I needed that seed funding to live on. We originally hoped to launch in September, but we got more ambitious about the software as we worked on it. Eventually we managed to build a WYSIWYG site builder, in the sense that as you were creating pages, they looked exactly like the static ones that would be generated later, except that instead of leading to static pages, the links all referred to closures stored in a hash table on the server. It helped to have studied art, because the main goal of an online store builder is to make users look legit, and the key to looking legit is high production values. If you get page layouts and fonts and colors right, you can make a guy running a store out of his bedroom look more legit than a big company. (If you\\'re curious why my site looks so old-fashioned, it\\'s because it\\'s still made with this software. It may look clunky today, but in 1996 it was the last word in slick.) In September, Robert rebelled. \"We\\'ve been working on this for a month,\" he said, \"and it\\'s still not done.\" This is funny in retrospect, because he would still be working on it almost 3 years later. But I decided it might be prudent to recruit more programmers, and I asked Robert who else in grad school with him was really good. He recommended Trevor Blackwell, which surprised me at first, because at that point I knew Trevor mainly for his plan to reduce everything in his life to a stack of notecards, which he carried around with him. But Rtm was right, as usual. Trevor turned out to be a frighteningly effective hacker. It was a lot of fun working with Robert and Trevor. They\\'re the two most independent-minded people I know, and in completely different ways. If you could see inside Rtm\\'s brain it would look like a colonial New England church, and if you could see inside Trevor\\'s it would look like the worst excesses of Austrian Rococo. We opened for business, with 6 stores, in January 1996. It was just as well we waited a few months, because although we worried we were late, we were actually almost fatally early. There was a lot of talk in the press then about ecommerce, but not many people actually wanted online stores. [8] There were three main parts to the software: the editor, which people used to build sites and which I wrote, the shopping cart, which Robert wrote, and the manager, which kept track of orders and statistics, and which Trevor wrote. In its time, the editor was one of the best general-purpose site builders. I kept the code tight and didn\\'t have to integrate with any other software except Robert\\'s and Trevor\\'s, so it was quite fun to work on. If all I\\'d had to do was work on this software, the next 3 years would have been the easiest of my life. Unfortunately I had to do a lot more, all of it stuff I was worse at than programming, and the next 3 years were instead the most stressful. There were a lot of startups making ecommerce software in the second half of the 90s. We were determined to be the Microsoft Word, not the Interleaf. Which meant being easy to use and inexpensive. It was lucky for us that we were poor, because that caused us to make Viaweb even more inexpensive than we realized. We charged $100 a month for a small store and $300 a month for a big one. This low price was a big attraction, and a constant thorn in the sides of competitors, but it wasn\\'t because of some clever insight that we set the price low. We had no idea what businesses paid for things. $300 a month seemed like a lot of money to us. We did a lot of things right by accident like that. For example, we did what\\'s now called \"doing things that don\\'t scale,\" although at the time we would have described it as \"being so lame that we\\'re driven to the most desperate measures to get users.\" The most common of which was building stores for them.', 'file_path: data/paul_graham/paul_graham_essay.txt Which meant being easy to use and inexpensive. It was lucky for us that we were poor, because that caused us to make Viaweb even more inexpensive than we realized. We charged $100 a month for a small store and $300 a month for a big one. This low price was a big attraction, and a constant thorn in the sides of competitors, but it wasn\\'t because of some clever insight that we set the price low. We had no idea what businesses paid for things. $300 a month seemed like a lot of money to us. We did a lot of things right by accident like that. For example, we did what\\'s now called \"doing things that don\\'t scale,\" although at the time we would have described it as \"being so lame that we\\'re driven to the most desperate measures to get users.\" The most common of which was building stores for them. This seemed particularly humiliating, since the whole raison d\\'etre of our software was that people could use it to make their own stores. But anything to get users. We learned a lot more about retail than we wanted to know. For example, that if you could only have a small image of a man\\'s shirt (and all images were small then by present standards), it was better to have a closeup of the collar than a picture of the whole shirt. The reason I remember learning this was that it meant I had to rescan about 30 images of men\\'s shirts. My first set of scans were so beautiful too. Though this felt wrong, it was exactly the right thing to be doing. Building stores for users taught us about retail, and about how it felt to use our software. I was initially both mystified and repelled by \"business\" and thought we needed a \"business person\" to be in charge of it, but once we started to get users, I was converted, in much the same way I was converted to fatherhood once I had kids. Whatever users wanted, I was all theirs. Maybe one day we\\'d have so many users that I couldn\\'t scan their images for them, but in the meantime there was nothing more important to do. Another thing I didn\\'t get at the time is that growth rate is the ultimate test of a startup. Our growth rate was fine. We had about 70 stores at the end of 1996 and about 500 at the end of 1997. I mistakenly thought the thing that mattered was the absolute number of users. And that is the thing that matters in the sense that that\\'s how much money you\\'re making, and if you\\'re not making enough, you might go out of business. But in the long term the growth rate takes care of the absolute number. If we\\'d been a startup I was advising at Y Combinator, I would have said: Stop being so stressed out, because you\\'re doing fine. You\\'re growing 7x a year. Just don\\'t hire too many more people and you\\'ll soon be profitable, and then you\\'ll control your own destiny. Alas I hired lots more people, partly because our investors wanted me to, and partly because that\\'s what startups did during the Internet Bubble. A company with just a handful of employees would have seemed amateurish. So we didn\\'t reach breakeven until about when Yahoo bought us in the summer of 1998. Which in turn meant we were at the mercy of investors for the entire life of the company. And since both we and our investors were noobs at startups, the result was a mess even by startup standards. It was a huge relief when Yahoo bought us. In principle our Viaweb stock was valuable. It was a share in a business that was profitable and growing rapidly. But it didn\\'t feel very valuable to me; I had no idea how to value a business, but I was all too keenly aware of the near-death experiences we seemed to have every few months. Nor had I changed my grad student lifestyle significantly since we started. So when Yahoo bought us it felt like going from rags to riches. Since we were going to California, I bought a car, a yellow 1998 VW GTI. I remember thinking that its leather seats alone were by far the most luxurious thing I owned. The next year, from the summer of 1998 to the summer of 1999, must have been the least productive of my life. I didn\\'t realize it at the time, but I was worn out from the effort and stress of running Viaweb. For a while after I got to California I tried to continue my usual m.o.'] nomic-ai/nomic-embed-text-v1.5 {}\n", + "show list of text [\"file_path: data/paul_graham/paul_graham_essay.txt But it didn't feel very valuable to me; I had no idea how to value a business, but I was all too keenly aware of the near-death experiences we seemed to have every few months. Nor had I changed my grad student lifestyle significantly since we started. So when Yahoo bought us it felt like going from rags to riches. Since we were going to California, I bought a car, a yellow 1998 VW GTI. I remember thinking that its leather seats alone were by far the most luxurious thing I owned. The next year, from the summer of 1998 to the summer of 1999, must have been the least productive of my life. I didn't realize it at the time, but I was worn out from the effort and stress of running Viaweb. For a while after I got to California I tried to continue my usual m.o. of programming till 3 in the morning, but fatigue combined with Yahoo's prematurely aged culture and grim cube farm in Santa Clara gradually dragged me down. After a few months it felt disconcertingly like working at Interleaf. Yahoo had given us a lot of options when they bought us. At the time I thought Yahoo was so overvalued that they'd never be worth anything, but to my astonishment the stock went up 5x in the next year. I hung on till the first chunk of options vested, then in the summer of 1999 I left. It had been so long since I'd painted anything that I'd half forgotten why I was doing this. My brain had been entirely full of software and men's shirts for 4 years. But I had done this to get rich so I could paint, I reminded myself, and now I was rich, so I should go paint. When I said I was leaving, my boss at Yahoo had a long conversation with me about my plans. I told him all about the kinds of pictures I wanted to paint. At the time I was touched that he took such an interest in me. Now I realize it was because he thought I was lying. My options at that point were worth about $2 million a month. If I was leaving that kind of money on the table, it could only be to go and start some new startup, and if I did, I might take people with me. This was the height of the Internet Bubble, and Yahoo was ground zero of it. My boss was at that moment a billionaire. Leaving then to start a new startup must have seemed to him an insanely, and yet also plausibly, ambitious plan. But I really was quitting to paint, and I started immediately. There was no time to lose. I'd already burned 4 years getting rich. Now when I talk to founders who are leaving after selling their companies, my advice is always the same: take a vacation. That's what I should have done, just gone off somewhere and done nothing for a month or two, but the idea never occurred to me. So I tried to paint, but I just didn't seem to have any energy or ambition. Part of the problem was that I didn't know many people in California. I'd compounded this problem by buying a house up in the Santa Cruz Mountains, with a beautiful view but miles from anywhere. I stuck it out for a few more months, then in desperation I went back to New York, where unless you understand about rent control you'll be surprised to hear I still had my apartment, sealed up like a tomb of my old life. Idelle was in New York at least, and there were other people trying to paint there, even though I didn't know any of them. When I got back to New York I resumed my old life, except now I was rich. It was as weird as it sounds. I resumed all my old patterns, except now there were doors where there hadn't been. Now when I was tired of walking, all I had to do was raise my hand, and (unless it was raining) a taxi would stop to pick me up. Now when I walked past charming little restaurants I could go in and order lunch. It was exciting for a while. Painting started to go better. I experimented with a new kind of still life where I'd paint one painting in the old way, then photograph it and print it, blown up, on canvas, and then use that as the underpainting for a second still life, painted from the same objects (which hopefully hadn't rotted yet). Meanwhile I looked for an apartment to buy. Now I could actually choose what neighborhood to live in. Where, I asked myself and various real estate agents, is the Cambridge of New York?\", 'file_path: data/paul_graham/paul_graham_essay.txt It was as weird as it sounds. I resumed all my old patterns, except now there were doors where there hadn\\'t been. Now when I was tired of walking, all I had to do was raise my hand, and (unless it was raining) a taxi would stop to pick me up. Now when I walked past charming little restaurants I could go in and order lunch. It was exciting for a while. Painting started to go better. I experimented with a new kind of still life where I\\'d paint one painting in the old way, then photograph it and print it, blown up, on canvas, and then use that as the underpainting for a second still life, painted from the same objects (which hopefully hadn\\'t rotted yet). Meanwhile I looked for an apartment to buy. Now I could actually choose what neighborhood to live in. Where, I asked myself and various real estate agents, is the Cambridge of New York? Aided by occasional visits to actual Cambridge, I gradually realized there wasn\\'t one. Huh. Around this time, in the spring of 2000, I had an idea. It was clear from our experience with Viaweb that web apps were the future. Why not build a web app for making web apps? Why not let people edit code on our server through the browser, and then host the resulting applications for them? [9] You could run all sorts of services on the servers that these applications could use just by making an API call: making and receiving phone calls, manipulating images, taking credit card payments, etc. I got so excited about this idea that I couldn\\'t think about anything else. It seemed obvious that this was the future. I didn\\'t particularly want to start another company, but it was clear that this idea would have to be embodied as one, so I decided to move to Cambridge and start it. I hoped to lure Robert into working on it with me, but there I ran into a hitch. Robert was now a postdoc at MIT, and though he\\'d made a lot of money the last time I\\'d lured him into working on one of my schemes, it had also been a huge time sink. So while he agreed that it sounded like a plausible idea, he firmly refused to work on it. Hmph. Well, I\\'d do it myself then. I recruited Dan Giffin, who had worked for Viaweb, and two undergrads who wanted summer jobs, and we got to work trying to build what it\\'s now clear is about twenty companies and several open source projects worth of software. The language for defining applications would of course be a dialect of Lisp. But I wasn\\'t so naive as to assume I could spring an overt Lisp on a general audience; we\\'d hide the parentheses, like Dylan did. By then there was a name for the kind of company Viaweb was, an \"application service provider,\" or ASP. This name didn\\'t last long before it was replaced by \"software as a service,\" but it was current for long enough that I named this new company after it: it was going to be called Aspra. I started working on the application builder, Dan worked on network infrastructure, and the two undergrads worked on the first two services (images and phone calls). But about halfway through the summer I realized I really didn\\'t want to run a company — especially not a big one, which it was looking like this would have to be. I\\'d only started Viaweb because I needed the money. Now that I didn\\'t need money anymore, why was I doing this? If this vision had to be realized as a company, then screw the vision. I\\'d build a subset that could be done as an open source project. Much to my surprise, the time I spent working on this stuff was not wasted after all. After we started Y Combinator, I would often encounter startups working on parts of this new architecture, and it was very useful to have spent so much time thinking about it and even trying to write some of it. The subset I would build as an open source project was the new Lisp, whose parentheses I now wouldn\\'t even have to hide. A lot of Lisp hackers dream of building a new Lisp, partly because one of the distinctive features of the language is that it has dialects, and partly, I think, because we have in our minds a Platonic form of Lisp that all existing dialects fall short of. I certainly did. So at the end of the summer Dan and I switched to working on this new dialect of Lisp, which I called Arc, in a house I bought in Cambridge. The following spring, lightning struck.', \"file_path: data/paul_graham/paul_graham_essay.txt Much to my surprise, the time I spent working on this stuff was not wasted after all. After we started Y Combinator, I would often encounter startups working on parts of this new architecture, and it was very useful to have spent so much time thinking about it and even trying to write some of it. The subset I would build as an open source project was the new Lisp, whose parentheses I now wouldn't even have to hide. A lot of Lisp hackers dream of building a new Lisp, partly because one of the distinctive features of the language is that it has dialects, and partly, I think, because we have in our minds a Platonic form of Lisp that all existing dialects fall short of. I certainly did. So at the end of the summer Dan and I switched to working on this new dialect of Lisp, which I called Arc, in a house I bought in Cambridge. The following spring, lightning struck. I was invited to give a talk at a Lisp conference, so I gave one about how we'd used Lisp at Viaweb. Afterward I put a postscript file of this talk online, on paulgraham.com, which I'd created years before using Viaweb but had never used for anything. In one day it got 30,000 page views. What on earth had happened? The referring urls showed that someone had posted it on Slashdot. [10] Wow, I thought, there's an audience. If I write something and put it on the web, anyone can read it. That may seem obvious now, but it was surprising then. In the print era there was a narrow channel to readers, guarded by fierce monsters known as editors. The only way to get an audience for anything you wrote was to get it published as a book, or in a newspaper or magazine. Now anyone could publish anything. This had been possible in principle since 1993, but not many people had realized it yet. I had been intimately involved with building the infrastructure of the web for most of that time, and a writer as well, and it had taken me 8 years to realize it. Even then it took me several years to understand the implications. It meant there would be a whole new generation of essays. [11] In the print era, the channel for publishing essays had been vanishingly small. Except for a few officially anointed thinkers who went to the right parties in New York, the only people allowed to publish essays were specialists writing about their specialties. There were so many essays that had never been written, because there had been no way to publish them. Now they could be, and I was going to write them. [12] I've worked on several different things, but to the extent there was a turning point where I figured out what to work on, it was when I started publishing essays online. From then on I knew that whatever else I did, I'd always write essays too. I knew that online essays would be a marginal medium at first. Socially they'd seem more like rants posted by nutjobs on their GeoCities sites than the genteel and beautifully typeset compositions published in The New Yorker. But by this point I knew enough to find that encouraging instead of discouraging. One of the most conspicuous patterns I've noticed in my life is how well it has worked, for me at least, to work on things that weren't prestigious. Still life has always been the least prestigious form of painting. Viaweb and Y Combinator both seemed lame when we started them. I still get the glassy eye from strangers when they ask what I'm writing, and I explain that it's an essay I'm going to publish on my web site. Even Lisp, though prestigious intellectually in something like the way Latin is, also seems about as hip. It's not that unprestigious types of work are good per se. But when you find yourself drawn to some kind of work despite its current lack of prestige, it's a sign both that there's something real to be discovered there, and that you have the right kind of motives. Impure motives are a big danger for the ambitious. If anything is going to lead you astray, it will be the desire to impress people. So while working on things that aren't prestigious doesn't guarantee you're on the right track, it at least guarantees you're not on the most common type of wrong one. Over the next several years I wrote lots of essays about all kinds of different topics. O'Reilly reprinted a collection of them as a book, called Hackers & Painters after one of the essays in it. I also worked on spam filters, and did some more painting.\", 'file_path: data/paul_graham/paul_graham_essay.txt It\\'s not that unprestigious types of work are good per se. But when you find yourself drawn to some kind of work despite its current lack of prestige, it\\'s a sign both that there\\'s something real to be discovered there, and that you have the right kind of motives. Impure motives are a big danger for the ambitious. If anything is going to lead you astray, it will be the desire to impress people. So while working on things that aren\\'t prestigious doesn\\'t guarantee you\\'re on the right track, it at least guarantees you\\'re not on the most common type of wrong one. Over the next several years I wrote lots of essays about all kinds of different topics. O\\'Reilly reprinted a collection of them as a book, called Hackers & Painters after one of the essays in it. I also worked on spam filters, and did some more painting. I used to have dinners for a group of friends every thursday night, which taught me how to cook for groups. And I bought another building in Cambridge, a former candy factory (and later, twas said, porn studio), to use as an office. One night in October 2003 there was a big party at my house. It was a clever idea of my friend Maria Daniels, who was one of the thursday diners. Three separate hosts would all invite their friends to one party. So for every guest, two thirds of the other guests would be people they didn\\'t know but would probably like. One of the guests was someone I didn\\'t know but would turn out to like a lot: a woman called Jessica Livingston. A couple days later I asked her out. Jessica was in charge of marketing at a Boston investment bank. This bank thought it understood startups, but over the next year, as she met friends of mine from the startup world, she was surprised how different reality was. And how colorful their stories were. So she decided to compile a book of interviews with startup founders. When the bank had financial problems and she had to fire half her staff, she started looking for a new job. In early 2005 she interviewed for a marketing job at a Boston VC firm. It took them weeks to make up their minds, and during this time I started telling her about all the things that needed to be fixed about venture capital. They should make a larger number of smaller investments instead of a handful of giant ones, they should be funding younger, more technical founders instead of MBAs, they should let the founders remain as CEO, and so on. One of my tricks for writing essays had always been to give talks. The prospect of having to stand up in front of a group of people and tell them something that won\\'t waste their time is a great spur to the imagination. When the Harvard Computer Society, the undergrad computer club, asked me to give a talk, I decided I would tell them how to start a startup. Maybe they\\'d be able to avoid the worst of the mistakes we\\'d made. So I gave this talk, in the course of which I told them that the best sources of seed funding were successful startup founders, because then they\\'d be sources of advice too. Whereupon it seemed they were all looking expectantly at me. Horrified at the prospect of having my inbox flooded by business plans (if I\\'d only known), I blurted out \"But not me!\" and went on with the talk. But afterward it occurred to me that I should really stop procrastinating about angel investing. I\\'d been meaning to since Yahoo bought us, and now it was 7 years later and I still hadn\\'t done one angel investment. Meanwhile I had been scheming with Robert and Trevor about projects we could work on together. I missed working with them, and it seemed like there had to be something we could collaborate on. As Jessica and I were walking home from dinner on March 11, at the corner of Garden and Walker streets, these three threads converged. Screw the VCs who were taking so long to make up their minds. We\\'d start our own investment firm and actually implement the ideas we\\'d been talking about. I\\'d fund it, and Jessica could quit her job and work for it, and we\\'d get Robert and Trevor as partners too. [13] Once again, ignorance worked in our favor. We had no idea how to be angel investors, and in Boston in 2005 there were no Ron Conways to learn from. So we just made what seemed like the obvious choices, and some of the things we did turned out to be novel. There are multiple components to Y Combinator, and we didn\\'t figure them all out at once. The part we got first was to be an angel firm.', 'file_path: data/paul_graham/paul_graham_essay.txt As Jessica and I were walking home from dinner on March 11, at the corner of Garden and Walker streets, these three threads converged. Screw the VCs who were taking so long to make up their minds. We\\'d start our own investment firm and actually implement the ideas we\\'d been talking about. I\\'d fund it, and Jessica could quit her job and work for it, and we\\'d get Robert and Trevor as partners too. [13] Once again, ignorance worked in our favor. We had no idea how to be angel investors, and in Boston in 2005 there were no Ron Conways to learn from. So we just made what seemed like the obvious choices, and some of the things we did turned out to be novel. There are multiple components to Y Combinator, and we didn\\'t figure them all out at once. The part we got first was to be an angel firm. In those days, those two words didn\\'t go together. There were VC firms, which were organized companies with people whose job it was to make investments, but they only did big, million dollar investments. And there were angels, who did smaller investments, but these were individuals who were usually focused on other things and made investments on the side. And neither of them helped founders enough in the beginning. We knew how helpless founders were in some respects, because we remembered how helpless we\\'d been. For example, one thing Julian had done for us that seemed to us like magic was to get us set up as a company. We were fine writing fairly difficult software, but actually getting incorporated, with bylaws and stock and all that stuff, how on earth did you do that? Our plan was not only to make seed investments, but to do for startups everything Julian had done for us. YC was not organized as a fund. It was cheap enough to run that we funded it with our own money. That went right by 99% of readers, but professional investors are thinking \"Wow, that means they got all the returns.\" But once again, this was not due to any particular insight on our part. We didn\\'t know how VC firms were organized. It never occurred to us to try to raise a fund, and if it had, we wouldn\\'t have known where to start. [14] The most distinctive thing about YC is the batch model: to fund a bunch of startups all at once, twice a year, and then to spend three months focusing intensively on trying to help them. That part we discovered by accident, not merely implicitly but explicitly due to our ignorance about investing. We needed to get experience as investors. What better way, we thought, than to fund a whole bunch of startups at once? We knew undergrads got temporary jobs at tech companies during the summer. Why not organize a summer program where they\\'d start startups instead? We wouldn\\'t feel guilty for being in a sense fake investors, because they would in a similar sense be fake founders. So while we probably wouldn\\'t make much money out of it, we\\'d at least get to practice being investors on them, and they for their part would probably have a more interesting summer than they would working at Microsoft. We\\'d use the building I owned in Cambridge as our headquarters. We\\'d all have dinner there once a week — on tuesdays, since I was already cooking for the thursday diners on thursdays — and after dinner we\\'d bring in experts on startups to give talks. We knew undergrads were deciding then about summer jobs, so in a matter of days we cooked up something we called the Summer Founders Program, and I posted an announcement on my site, inviting undergrads to apply. I had never imagined that writing essays would be a way to get \"deal flow,\" as investors call it, but it turned out to be the perfect source. [15] We got 225 applications for the Summer Founders Program, and we were surprised to find that a lot of them were from people who\\'d already graduated, or were about to that spring. Already this SFP thing was starting to feel more serious than we\\'d intended. We invited about 20 of the 225 groups to interview in person, and from those we picked 8 to fund. They were an impressive group. That first batch included reddit, Justin Kan and Emmett Shear, who went on to found Twitch, Aaron Swartz, who had already helped write the RSS spec and would a few years later become a martyr for open access, and Sam Altman, who would later become the second president of YC. I don\\'t think it was entirely luck that the first batch was so good.', 'file_path: data/paul_graham/paul_graham_essay.txt [15] We got 225 applications for the Summer Founders Program, and we were surprised to find that a lot of them were from people who\\'d already graduated, or were about to that spring. Already this SFP thing was starting to feel more serious than we\\'d intended. We invited about 20 of the 225 groups to interview in person, and from those we picked 8 to fund. They were an impressive group. That first batch included reddit, Justin Kan and Emmett Shear, who went on to found Twitch, Aaron Swartz, who had already helped write the RSS spec and would a few years later become a martyr for open access, and Sam Altman, who would later become the second president of YC. I don\\'t think it was entirely luck that the first batch was so good. You had to be pretty bold to sign up for a weird thing like the Summer Founders Program instead of a summer job at a legit place like Microsoft or Goldman Sachs. The deal for startups was based on a combination of the deal we did with Julian ($10k for 10%) and what Robert said MIT grad students got for the summer ($6k). We invested $6k per founder, which in the typical two-founder case was $12k, in return for 6%. That had to be fair, because it was twice as good as the deal we ourselves had taken. Plus that first summer, which was really hot, Jessica brought the founders free air conditioners. [16] Fairly quickly I realized that we had stumbled upon the way to scale startup funding. Funding startups in batches was more convenient for us, because it meant we could do things for a lot of startups at once, but being part of a batch was better for the startups too. It solved one of the biggest problems faced by founders: the isolation. Now you not only had colleagues, but colleagues who understood the problems you were facing and could tell you how they were solving them. As YC grew, we started to notice other advantages of scale. The alumni became a tight community, dedicated to helping one another, and especially the current batch, whose shoes they remembered being in. We also noticed that the startups were becoming one another\\'s customers. We used to refer jokingly to the \"YC GDP,\" but as YC grows this becomes less and less of a joke. Now lots of startups get their initial set of customers almost entirely from among their batchmates. I had not originally intended YC to be a full-time job. I was going to do three things: hack, write essays, and work on YC. As YC grew, and I grew more excited about it, it started to take up a lot more than a third of my attention. But for the first few years I was still able to work on other things. In the summer of 2006, Robert and I started working on a new version of Arc. This one was reasonably fast, because it was compiled into Scheme. To test this new Arc, I wrote Hacker News in it. It was originally meant to be a news aggregator for startup founders and was called Startup News, but after a few months I got tired of reading about nothing but startups. Plus it wasn\\'t startup founders we wanted to reach. It was future startup founders. So I changed the name to Hacker News and the topic to whatever engaged one\\'s intellectual curiosity. HN was no doubt good for YC, but it was also by far the biggest source of stress for me. If all I\\'d had to do was select and help founders, life would have been so easy. And that implies that HN was a mistake. Surely the biggest source of stress in one\\'s work should at least be something close to the core of the work. Whereas I was like someone who was in pain while running a marathon not from the exertion of running, but because I had a blister from an ill-fitting shoe. When I was dealing with some urgent problem during YC, there was about a 60% chance it had to do with HN, and a 40% chance it had do with everything else combined. [17] As well as HN, I wrote all of YC\\'s internal software in Arc. But while I continued to work a good deal in Arc, I gradually stopped working on Arc, partly because I didn\\'t have time to, and partly because it was a lot less attractive to mess around with the language now that we had all this infrastructure depending on it. So now my three projects were reduced to two: writing essays and working on YC. YC was different from other kinds of work I\\'ve done. Instead of deciding for myself what to work on, the problems came to me.', 'file_path: data/paul_graham/paul_graham_essay.txt When I was dealing with some urgent problem during YC, there was about a 60% chance it had to do with HN, and a 40% chance it had do with everything else combined. [17] As well as HN, I wrote all of YC\\'s internal software in Arc. But while I continued to work a good deal in Arc, I gradually stopped working on Arc, partly because I didn\\'t have time to, and partly because it was a lot less attractive to mess around with the language now that we had all this infrastructure depending on it. So now my three projects were reduced to two: writing essays and working on YC. YC was different from other kinds of work I\\'ve done. Instead of deciding for myself what to work on, the problems came to me. Every 6 months there was a new batch of startups, and their problems, whatever they were, became our problems. It was very engaging work, because their problems were quite varied, and the good founders were very effective. If you were trying to learn the most you could about startups in the shortest possible time, you couldn\\'t have picked a better way to do it. There were parts of the job I didn\\'t like. Disputes between cofounders, figuring out when people were lying to us, fighting with people who maltreated the startups, and so on. But I worked hard even at the parts I didn\\'t like. I was haunted by something Kevin Hale once said about companies: \"No one works harder than the boss.\" He meant it both descriptively and prescriptively, and it was the second part that scared me. I wanted YC to be good, so if how hard I worked set the upper bound on how hard everyone else worked, I\\'d better work very hard. One day in 2010, when he was visiting California for interviews, Robert Morris did something astonishing: he offered me unsolicited advice. I can only remember him doing that once before. One day at Viaweb, when I was bent over double from a kidney stone, he suggested that it would be a good idea for him to take me to the hospital. That was what it took for Rtm to offer unsolicited advice. So I remember his exact words very clearly. \"You know,\" he said, \"you should make sure Y Combinator isn\\'t the last cool thing you do.\" At the time I didn\\'t understand what he meant, but gradually it dawned on me that he was saying I should quit. This seemed strange advice, because YC was doing great. But if there was one thing rarer than Rtm offering advice, it was Rtm being wrong. So this set me thinking. It was true that on my current trajectory, YC would be the last thing I did, because it was only taking up more of my attention. It had already eaten Arc, and was in the process of eating essays too. Either YC was my life\\'s work or I\\'d have to leave eventually. And it wasn\\'t, so I would. In the summer of 2012 my mother had a stroke, and the cause turned out to be a blood clot caused by colon cancer. The stroke destroyed her balance, and she was put in a nursing home, but she really wanted to get out of it and back to her house, and my sister and I were determined to help her do it. I used to fly up to Oregon to visit her regularly, and I had a lot of time to think on those flights. On one of them I realized I was ready to hand YC over to someone else. I asked Jessica if she wanted to be president, but she didn\\'t, so we decided we\\'d try to recruit Sam Altman. We talked to Robert and Trevor and we agreed to make it a complete changing of the guard. Up till that point YC had been controlled by the original LLC we four had started. But we wanted YC to last for a long time, and to do that it couldn\\'t be controlled by the founders. So if Sam said yes, we\\'d let him reorganize YC. Robert and I would retire, and Jessica and Trevor would become ordinary partners. When we asked Sam if he wanted to be president of YC, initially he said no. He wanted to start a startup to make nuclear reactors. But I kept at it, and in October 2013 he finally agreed. We decided he\\'d take over starting with the winter 2014 batch. For the rest of 2013 I left running YC more and more to Sam, partly so he could learn the job, and partly because I was focused on my mother, whose cancer had returned.', \"file_path: data/paul_graham/paul_graham_essay.txt Up till that point YC had been controlled by the original LLC we four had started. But we wanted YC to last for a long time, and to do that it couldn't be controlled by the founders. So if Sam said yes, we'd let him reorganize YC. Robert and I would retire, and Jessica and Trevor would become ordinary partners. When we asked Sam if he wanted to be president of YC, initially he said no. He wanted to start a startup to make nuclear reactors. But I kept at it, and in October 2013 he finally agreed. We decided he'd take over starting with the winter 2014 batch. For the rest of 2013 I left running YC more and more to Sam, partly so he could learn the job, and partly because I was focused on my mother, whose cancer had returned. She died on January 15, 2014. We knew this was coming, but it was still hard when it did. I kept working on YC till March, to help get that batch of startups through Demo Day, then I checked out pretty completely. (I still talk to alumni and to new startups working on things I'm interested in, but that only takes a few hours a week.) What should I do next? Rtm's advice hadn't included anything about that. I wanted to do something completely different, so I decided I'd paint. I wanted to see how good I could get if I really focused on it. So the day after I stopped working on YC, I started painting. I was rusty and it took a while to get back into shape, but it was at least completely engaging. [18] I spent most of the rest of 2014 painting. I'd never been able to work so uninterruptedly before, and I got to be better than I had been. Not good enough, but better. Then in November, right in the middle of a painting, I ran out of steam. Up till that point I'd always been curious to see how the painting I was working on would turn out, but suddenly finishing this one seemed like a chore. So I stopped working on it and cleaned my brushes and haven't painted since. So far anyway. I realize that sounds rather wimpy. But attention is a zero sum game. If you can choose what to work on, and you choose a project that's not the best one (or at least a good one) for you, then it's getting in the way of another project that is. And at 50 there was some opportunity cost to screwing around. I started writing essays again, and wrote a bunch of new ones over the next few months. I even wrote a couple that weren't about startups. Then in March 2015 I started working on Lisp again. The distinctive thing about Lisp is that its core is a language defined by writing an interpreter in itself. It wasn't originally intended as a programming language in the ordinary sense. It was meant to be a formal model of computation, an alternative to the Turing machine. If you want to write an interpreter for a language in itself, what's the minimum set of predefined operators you need? The Lisp that John McCarthy invented, or more accurately discovered, is an answer to that question. [19] McCarthy didn't realize this Lisp could even be used to program computers till his grad student Steve Russell suggested it. Russell translated McCarthy's interpreter into IBM 704 machine language, and from that point Lisp started also to be a programming language in the ordinary sense. But its origins as a model of computation gave it a power and elegance that other languages couldn't match. It was this that attracted me in college, though I didn't understand why at the time. McCarthy's 1960 Lisp did nothing more than interpret Lisp expressions. It was missing a lot of things you'd want in a programming language. So these had to be added, and when they were, they weren't defined using McCarthy's original axiomatic approach. That wouldn't have been feasible at the time. McCarthy tested his interpreter by hand-simulating the execution of programs. But it was already getting close to the limit of interpreters you could test that way — indeed, there was a bug in it that McCarthy had overlooked. To test a more complicated interpreter, you'd have had to run it, and computers then weren't powerful enough. Now they are, though. Now you could continue using McCarthy's axiomatic approach till you'd defined a complete programming language. And as long as every change you made to McCarthy's Lisp was a discoveredness-preserving transformation, you could, in principle, end up with a complete language that had this quality.\", 'file_path: data/paul_graham/paul_graham_essay.txt It was missing a lot of things you\\'d want in a programming language. So these had to be added, and when they were, they weren\\'t defined using McCarthy\\'s original axiomatic approach. That wouldn\\'t have been feasible at the time. McCarthy tested his interpreter by hand-simulating the execution of programs. But it was already getting close to the limit of interpreters you could test that way — indeed, there was a bug in it that McCarthy had overlooked. To test a more complicated interpreter, you\\'d have had to run it, and computers then weren\\'t powerful enough. Now they are, though. Now you could continue using McCarthy\\'s axiomatic approach till you\\'d defined a complete programming language. And as long as every change you made to McCarthy\\'s Lisp was a discoveredness-preserving transformation, you could, in principle, end up with a complete language that had this quality. Harder to do than to talk about, of course, but if it was possible in principle, why not try? So I decided to take a shot at it. It took 4 years, from March 26, 2015 to October 12, 2019. It was fortunate that I had a precisely defined goal, or it would have been hard to keep at it for so long. I wrote this new Lisp, called Bel, in itself in Arc. That may sound like a contradiction, but it\\'s an indication of the sort of trickery I had to engage in to make this work. By means of an egregious collection of hacks I managed to make something close enough to an interpreter written in itself that could actually run. Not fast, but fast enough to test. I had to ban myself from writing essays during most of this time, or I\\'d never have finished. In late 2015 I spent 3 months writing essays, and when I went back to working on Bel I could barely understand the code. Not so much because it was badly written as because the problem is so convoluted. When you\\'re working on an interpreter written in itself, it\\'s hard to keep track of what\\'s happening at what level, and errors can be practically encrypted by the time you get them. So I said no more essays till Bel was done. But I told few people about Bel while I was working on it. So for years it must have seemed that I was doing nothing, when in fact I was working harder than I\\'d ever worked on anything. Occasionally after wrestling for hours with some gruesome bug I\\'d check Twitter or HN and see someone asking \"Does Paul Graham still code?\" Working on Bel was hard but satisfying. I worked on it so intensively that at any given time I had a decent chunk of the code in my head and could write more there. I remember taking the boys to the coast on a sunny day in 2015 and figuring out how to deal with some problem involving continuations while I watched them play in the tide pools. It felt like I was doing life right. I remember that because I was slightly dismayed at how novel it felt. The good news is that I had more moments like this over the next few years. In the summer of 2016 we moved to England. We wanted our kids to see what it was like living in another country, and since I was a British citizen by birth, that seemed the obvious choice. We only meant to stay for a year, but we liked it so much that we still live there. So most of Bel was written in England. In the fall of 2019, Bel was finally finished. Like McCarthy\\'s original Lisp, it\\'s a spec rather than an implementation, although like McCarthy\\'s Lisp it\\'s a spec expressed as code. Now that I could write essays again, I wrote a bunch about topics I\\'d had stacked up. I kept writing essays through 2020, but I also started to think about other things I could work on. How should I choose what to do? Well, how had I chosen what to work on in the past? I wrote an essay for myself to answer that question, and I was surprised how long and messy the answer turned out to be. If this surprised me, who\\'d lived it, then I thought perhaps it would be interesting to other people, and encouraging to those with similarly messy lives. So I wrote a more detailed version for others to read, and this is the last sentence of it. Notes [1] My experience skipped a step in the evolution of computers: time-sharing machines with interactive OSes. I went straight from batch processing to microcomputers, which made microcomputers seem all the more exciting.', \"file_path: data/paul_graham/paul_graham_essay.txt Now that I could write essays again, I wrote a bunch about topics I'd had stacked up. I kept writing essays through 2020, but I also started to think about other things I could work on. How should I choose what to do? Well, how had I chosen what to work on in the past? I wrote an essay for myself to answer that question, and I was surprised how long and messy the answer turned out to be. If this surprised me, who'd lived it, then I thought perhaps it would be interesting to other people, and encouraging to those with similarly messy lives. So I wrote a more detailed version for others to read, and this is the last sentence of it. Notes [1] My experience skipped a step in the evolution of computers: time-sharing machines with interactive OSes. I went straight from batch processing to microcomputers, which made microcomputers seem all the more exciting. [2] Italian words for abstract concepts can nearly always be predicted from their English cognates (except for occasional traps like polluzione). It's the everyday words that differ. So if you string together a lot of abstract concepts with a few simple verbs, you can make a little Italian go a long way. [3] I lived at Piazza San Felice 4, so my walk to the Accademia went straight down the spine of old Florence: past the Pitti, across the bridge, past Orsanmichele, between the Duomo and the Baptistery, and then up Via Ricasoli to Piazza San Marco. I saw Florence at street level in every possible condition, from empty dark winter evenings to sweltering summer days when the streets were packed with tourists. [4] You can of course paint people like still lives if you want to, and they're willing. That sort of portrait is arguably the apex of still life painting, though the long sitting does tend to produce pained expressions in the sitters. [5] Interleaf was one of many companies that had smart people and built impressive technology, and yet got crushed by Moore's Law. In the 1990s the exponential growth in the power of commodity (i.e. Intel) processors rolled up high-end, special-purpose hardware and software companies like a bulldozer. [6] The signature style seekers at RISD weren't specifically mercenary. In the art world, money and coolness are tightly coupled. Anything expensive comes to be seen as cool, and anything seen as cool will soon become equally expensive. [7] Technically the apartment wasn't rent-controlled but rent-stabilized, but this is a refinement only New Yorkers would know or care about. The point is that it was really cheap, less than half market price. [8] Most software you can launch as soon as it's done. But when the software is an online store builder and you're hosting the stores, if you don't have any users yet, that fact will be painfully obvious. So before we could launch publicly we had to launch privately, in the sense of recruiting an initial set of users and making sure they had decent-looking stores. [9] We'd had a code editor in Viaweb for users to define their own page styles. They didn't know it, but they were editing Lisp expressions underneath. But this wasn't an app editor, because the code ran when the merchants' sites were generated, not when shoppers visited them. [10] This was the first instance of what is now a familiar experience, and so was what happened next, when I read the comments and found they were full of angry people. How could I claim that Lisp was better than other languages? Weren't they all Turing complete? People who see the responses to essays I write sometimes tell me how sorry they feel for me, but I'm not exaggerating when I reply that it has always been like this, since the very beginning. It comes with the territory. An essay must tell readers things they don't already know, and some people dislike being told such things. [11] People put plenty of stuff on the internet in the 90s of course, but putting something online is not the same as publishing it online. Publishing online means you treat the online version as the (or at least a) primary version. [12] There is a general lesson here that our experience with Y Combinator also teaches: Customs continue to constrain you long after the restrictions that caused them have disappeared. Customary VC practice had once, like the customs about publishing essays, been based on real constraints. Startups had once been much more expensive to start, and proportionally rare.\"] nomic-ai/nomic-embed-text-v1.5 {}\n", + "show list of text ['file_path: data/paul_graham/paul_graham_essay.txt People who see the responses to essays I write sometimes tell me how sorry they feel for me, but I\\'m not exaggerating when I reply that it has always been like this, since the very beginning. It comes with the territory. An essay must tell readers things they don\\'t already know, and some people dislike being told such things. [11] People put plenty of stuff on the internet in the 90s of course, but putting something online is not the same as publishing it online. Publishing online means you treat the online version as the (or at least a) primary version. [12] There is a general lesson here that our experience with Y Combinator also teaches: Customs continue to constrain you long after the restrictions that caused them have disappeared. Customary VC practice had once, like the customs about publishing essays, been based on real constraints. Startups had once been much more expensive to start, and proportionally rare. Now they could be cheap and common, but the VCs\\' customs still reflected the old world, just as customs about writing essays still reflected the constraints of the print era. Which in turn implies that people who are independent-minded (i.e. less influenced by custom) will have an advantage in fields affected by rapid change (where customs are more likely to be obsolete). Here\\'s an interesting point, though: you can\\'t always predict which fields will be affected by rapid change. Obviously software and venture capital will be, but who would have predicted that essay writing would be? [13] Y Combinator was not the original name. At first we were called Cambridge Seed. But we didn\\'t want a regional name, in case someone copied us in Silicon Valley, so we renamed ourselves after one of the coolest tricks in the lambda calculus, the Y combinator. I picked orange as our color partly because it\\'s the warmest, and partly because no VC used it. In 2005 all the VCs used staid colors like maroon, navy blue, and forest green, because they were trying to appeal to LPs, not founders. The YC logo itself is an inside joke: the Viaweb logo had been a white V on a red circle, so I made the YC logo a white Y on an orange square. [14] YC did become a fund for a couple years starting in 2009, because it was getting so big I could no longer afford to fund it personally. But after Heroku got bought we had enough money to go back to being self-funded. [15] I\\'ve never liked the term \"deal flow,\" because it implies that the number of new startups at any given time is fixed. This is not only false, but it\\'s the purpose of YC to falsify it, by causing startups to be founded that would not otherwise have existed. [16] She reports that they were all different shapes and sizes, because there was a run on air conditioners and she had to get whatever she could, but that they were all heavier than she could carry now. [17] Another problem with HN was a bizarre edge case that occurs when you both write essays and run a forum. When you run a forum, you\\'re assumed to see if not every conversation, at least every conversation involving you. And when you write essays, people post highly imaginative misinterpretations of them on forums. Individually these two phenomena are tedious but bearable, but the combination is disastrous. You actually have to respond to the misinterpretations, because the assumption that you\\'re present in the conversation means that not responding to any sufficiently upvoted misinterpretation reads as a tacit admission that it\\'s correct. But that in turn encourages more; anyone who wants to pick a fight with you senses that now is their chance. [18] The worst thing about leaving YC was not working with Jessica anymore. We\\'d been working on YC almost the whole time we\\'d known each other, and we\\'d neither tried nor wanted to separate it from our personal lives, so leaving was like pulling up a deeply rooted tree. [19] One way to get more precise about the concept of invented vs discovered is to talk about space aliens. Any sufficiently advanced alien civilization would certainly know about the Pythagorean theorem, for example. I believe, though with less certainty, that they would also know about the Lisp in McCarthy\\'s 1960 paper. But if so there\\'s no reason to suppose that this is the limit of the language that might be known to them. Presumably aliens need numbers and errors and I/O too. So it seems likely there exists at least one path out of McCarthy\\'s Lisp along which discoveredness is preserved.', \"file_path: data/paul_graham/paul_graham_essay.txt [18] The worst thing about leaving YC was not working with Jessica anymore. We'd been working on YC almost the whole time we'd known each other, and we'd neither tried nor wanted to separate it from our personal lives, so leaving was like pulling up a deeply rooted tree. [19] One way to get more precise about the concept of invented vs discovered is to talk about space aliens. Any sufficiently advanced alien civilization would certainly know about the Pythagorean theorem, for example. I believe, though with less certainty, that they would also know about the Lisp in McCarthy's 1960 paper. But if so there's no reason to suppose that this is the limit of the language that might be known to them. Presumably aliens need numbers and errors and I/O too. So it seems likely there exists at least one path out of McCarthy's Lisp along which discoveredness is preserved. Thanks to Trevor Blackwell, John Collison, Patrick Collison, Daniel Gackle, Ralph Hazell, Jessica Livingston, Robert Morris, and Harj Taggar for reading drafts of this.\"] nomic-ai/nomic-embed-text-v1.5 {}\n" + ] + }, + { + "data": { + "text/markdown": [ + "The author, growing up, primarily worked on writing and programming. He started by writing short stories, which he admits were not very good, and tried programming on an IBM 1401 in ninth grade. However, he found it puzzling as he couldn't figure out what to do with it due to the lack of input data. His first significant experience with programming came with the advent of microcomputers, which he could use right at his desk and receive immediate responses. He built his own microcomputer and later convinced his father to buy a TRS-80. He wrote simple games, a program to predict rocket flights, and a word processor. Despite his interest in programming, he initially planned to study philosophy in college, but eventually switched to AI." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from llama_index.llms.fireworks import Fireworks\n", + "from llama_index.embeddings.fireworks import FireworksEmbedding\n", + "\n", + "llm = Fireworks(\n", + " temperature=0, model=\"accounts/fireworks/models/mixtral-8x7b-instruct\"\n", + ")\n", + "\n", + "# create client and a new collection\n", + "chroma_client = chromadb.EphemeralClient()\n", + "chroma_collection = chroma_client.create_collection(\"quickstart\")\n", + "\n", + "# define embedding function\n", + "embed_model = FireworksEmbedding(\n", + " model_name=\"nomic-ai/nomic-embed-text-v1.5\",\n", + ")\n", + "\n", + "# load documents\n", + "documents = SimpleDirectoryReader(\"./data/paul_graham/\").load_data()\n", + "\n", + "# set up ChromaVectorStore and load in data\n", + "vector_store = ChromaVectorStore(chroma_collection=chroma_collection)\n", + "storage_context = StorageContext.from_defaults(vector_store=vector_store)\n", + "index = VectorStoreIndex.from_documents(\n", + " documents, storage_context=storage_context, embed_model=embed_model\n", + ")\n", + "\n", + "# Query Data\n", + "query_engine = index.as_query_engine(llm=llm)\n", + "response = query_engine.query(\"What did the author do growing up?\")\n", + "display(Markdown(f\"{response}\"))" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "349de571", + "metadata": {}, + "source": [ + "## Basic Example (including saving to disk) and resizable embeddings\n", + "\n", + "Extending the previous example, if you want to save to disk, simply initialize the Chroma client and pass the directory where you want the data to be saved to. \n", + "\n", + "`Caution`: Chroma makes a best-effort to automatically save data to disk, however multiple in-memory clients can stomp each other's work. As a best practice, only have one client per path running at any given time.\n", + "\n", + "Also we are going to resize the embeddings down to 128 dimensions. This is helpful for cases where you are cost conscious on the database side." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9c3a56a5", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "show list of text ['file_path: data/paul_graham/paul_graham_essay.txt What I Worked On February 2021 Before college the two main things I worked on, outside of school, were writing and programming. I didn\\'t write essays. I wrote what beginning writers were supposed to write then, and probably still are: short stories. My stories were awful. They had hardly any plot, just characters with strong feelings, which I imagined made them deep. The first programs I tried writing were on the IBM 1401 that our school district used for what was then called \"data processing.\" This was in 9th grade, so I was 13 or 14. The school district\\'s 1401 happened to be in the basement of our junior high school, and my friend Rich Draves and I got permission to use it. It was like a mini Bond villain\\'s lair down there, with all these alien-looking machines — CPU, disk drives, printer, card reader — sitting up on a raised floor under bright fluorescent lights. The language we used was an early version of Fortran. You had to type programs on punch cards, then stack them in the card reader and press a button to load the program into memory and run it. The result would ordinarily be to print something on the spectacularly loud printer. I was puzzled by the 1401. I couldn\\'t figure out what to do with it. And in retrospect there\\'s not much I could have done with it. The only form of input to programs was data stored on punched cards, and I didn\\'t have any data stored on punched cards. The only other option was to do things that didn\\'t rely on any input, like calculate approximations of pi, but I didn\\'t know enough math to do anything interesting of that type. So I\\'m not surprised I can\\'t remember any programs I wrote, because they can\\'t have done much. My clearest memory is of the moment I learned it was possible for programs not to terminate, when one of mine didn\\'t. On a machine without time-sharing, this was a social as well as a technical error, as the data center manager\\'s expression made clear. With microcomputers, everything changed. Now you could have a computer sitting right in front of you, on a desk, that could respond to your keystrokes as it was running instead of just churning through a stack of punch cards and then stopping. [1] The first of my friends to get a microcomputer built it himself. It was sold as a kit by Heathkit. I remember vividly how impressed and envious I felt watching him sitting in front of it, typing programs right into the computer. Computers were expensive in those days and it took me years of nagging before I convinced my father to buy one, a TRS-80, in about 1980. The gold standard then was the Apple II, but a TRS-80 was good enough. This was when I really started programming. I wrote simple games, a program to predict how high my model rockets would fly, and a word processor that my father used to write at least one book. There was only room in memory for about 2 pages of text, so he\\'d write 2 pages at a time and then print them out, but it was a lot better than a typewriter. Though I liked programming, I didn\\'t plan to study it in college. In college I was going to study philosophy, which sounded much more powerful. It seemed, to my naive high school self, to be the study of the ultimate truths, compared to which the things studied in other fields would be mere domain knowledge. What I discovered when I got to college was that the other fields took up so much of the space of ideas that there wasn\\'t much left for these supposed ultimate truths. All that seemed left for philosophy were edge cases that people in other fields felt could safely be ignored. I couldn\\'t have put this into words when I was 18. All I knew at the time was that I kept taking philosophy courses and they kept being boring. So I decided to switch to AI. AI was in the air in the mid 1980s, but there were two things especially that made me want to work on it: a novel by Heinlein called The Moon is a Harsh Mistress, which featured an intelligent computer called Mike, and a PBS documentary that showed Terry Winograd using SHRDLU. I haven\\'t tried rereading The Moon is a Harsh Mistress, so I don\\'t know how well it has aged, but when I read it I was drawn entirely into its world. It seemed only a matter of time before we\\'d have Mike, and when I saw Winograd using SHRDLU, it seemed like that time would be a few years at most.', 'file_path: data/paul_graham/paul_graham_essay.txt I couldn\\'t have put this into words when I was 18. All I knew at the time was that I kept taking philosophy courses and they kept being boring. So I decided to switch to AI. AI was in the air in the mid 1980s, but there were two things especially that made me want to work on it: a novel by Heinlein called The Moon is a Harsh Mistress, which featured an intelligent computer called Mike, and a PBS documentary that showed Terry Winograd using SHRDLU. I haven\\'t tried rereading The Moon is a Harsh Mistress, so I don\\'t know how well it has aged, but when I read it I was drawn entirely into its world. It seemed only a matter of time before we\\'d have Mike, and when I saw Winograd using SHRDLU, it seemed like that time would be a few years at most. All you had to do was teach SHRDLU more words. There weren\\'t any classes in AI at Cornell then, not even graduate classes, so I started trying to teach myself. Which meant learning Lisp, since in those days Lisp was regarded as the language of AI. The commonly used programming languages then were pretty primitive, and programmers\\' ideas correspondingly so. The default language at Cornell was a Pascal-like language called PL/I, and the situation was similar elsewhere. Learning Lisp expanded my concept of a program so fast that it was years before I started to have a sense of where the new limits were. This was more like it; this was what I had expected college to do. It wasn\\'t happening in a class, like it was supposed to, but that was ok. For the next couple years I was on a roll. I knew what I was going to do. For my undergraduate thesis, I reverse-engineered SHRDLU. My God did I love working on that program. It was a pleasing bit of code, but what made it even more exciting was my belief — hard to imagine now, but not unique in 1985 — that it was already climbing the lower slopes of intelligence. I had gotten into a program at Cornell that didn\\'t make you choose a major. You could take whatever classes you liked, and choose whatever you liked to put on your degree. I of course chose \"Artificial Intelligence.\" When I got the actual physical diploma, I was dismayed to find that the quotes had been included, which made them read as scare-quotes. At the time this bothered me, but now it seems amusingly accurate, for reasons I was about to discover. I applied to 3 grad schools: MIT and Yale, which were renowned for AI at the time, and Harvard, which I\\'d visited because Rich Draves went there, and was also home to Bill Woods, who\\'d invented the type of parser I used in my SHRDLU clone. Only Harvard accepted me, so that was where I went. I don\\'t remember the moment it happened, or if there even was a specific moment, but during the first year of grad school I realized that AI, as practiced at the time, was a hoax. By which I mean the sort of AI in which a program that\\'s told \"the dog is sitting on the chair\" translates this into some formal representation and adds it to the list of things it knows. What these programs really showed was that there\\'s a subset of natural language that\\'s a formal language. But a very proper subset. It was clear that there was an unbridgeable gap between what they could do and actually understanding natural language. It was not, in fact, simply a matter of teaching SHRDLU more words. That whole way of doing AI, with explicit data structures representing concepts, was not going to work. Its brokenness did, as so often happens, generate a lot of opportunities to write papers about various band-aids that could be applied to it, but it was never going to get us Mike. So I looked around to see what I could salvage from the wreckage of my plans, and there was Lisp. I knew from experience that Lisp was interesting for its own sake and not just for its association with AI, even though that was the main reason people cared about it at the time. So I decided to focus on Lisp. In fact, I decided to write a book about Lisp hacking. It\\'s scary to think how little I knew about Lisp hacking when I started writing that book. But there\\'s nothing like writing a book about something to help you learn it. The book, On Lisp, wasn\\'t published till 1993, but I wrote much of it in grad school. Computer Science is an uneasy alliance between two halves, theory and systems. The theory people prove things, and the systems people build things. I wanted to build things.', 'file_path: data/paul_graham/paul_graham_essay.txt So I looked around to see what I could salvage from the wreckage of my plans, and there was Lisp. I knew from experience that Lisp was interesting for its own sake and not just for its association with AI, even though that was the main reason people cared about it at the time. So I decided to focus on Lisp. In fact, I decided to write a book about Lisp hacking. It\\'s scary to think how little I knew about Lisp hacking when I started writing that book. But there\\'s nothing like writing a book about something to help you learn it. The book, On Lisp, wasn\\'t published till 1993, but I wrote much of it in grad school. Computer Science is an uneasy alliance between two halves, theory and systems. The theory people prove things, and the systems people build things. I wanted to build things. I had plenty of respect for theory — indeed, a sneaking suspicion that it was the more admirable of the two halves — but building things seemed so much more exciting. The problem with systems work, though, was that it didn\\'t last. Any program you wrote today, no matter how good, would be obsolete in a couple decades at best. People might mention your software in footnotes, but no one would actually use it. And indeed, it would seem very feeble work. Only people with a sense of the history of the field would even realize that, in its time, it had been good. There were some surplus Xerox Dandelions floating around the computer lab at one point. Anyone who wanted one to play around with could have one. I was briefly tempted, but they were so slow by present standards; what was the point? No one else wanted one either, so off they went. That was what happened to systems work. I wanted not just to build things, but to build things that would last. In this dissatisfied state I went in 1988 to visit Rich Draves at CMU, where he was in grad school. One day I went to visit the Carnegie Institute, where I\\'d spent a lot of time as a kid. While looking at a painting there I realized something that might seem obvious, but was a big surprise to me. There, right on the wall, was something you could make that would last. Paintings didn\\'t become obsolete. Some of the best ones were hundreds of years old. And moreover this was something you could make a living doing. Not as easily as you could by writing software, of course, but I thought if you were really industrious and lived really cheaply, it had to be possible to make enough to survive. And as an artist you could be truly independent. You wouldn\\'t have a boss, or even need to get research funding. I had always liked looking at paintings. Could I make them? I had no idea. I\\'d never imagined it was even possible. I knew intellectually that people made art — that it didn\\'t just appear spontaneously — but it was as if the people who made it were a different species. They either lived long ago or were mysterious geniuses doing strange things in profiles in Life magazine. The idea of actually being able to make art, to put that verb before that noun, seemed almost miraculous. That fall I started taking art classes at Harvard. Grad students could take classes in any department, and my advisor, Tom Cheatham, was very easy going. If he even knew about the strange classes I was taking, he never said anything. So now I was in a PhD program in computer science, yet planning to be an artist, yet also genuinely in love with Lisp hacking and working away at On Lisp. In other words, like many a grad student, I was working energetically on multiple projects that were not my thesis. I didn\\'t see a way out of this situation. I didn\\'t want to drop out of grad school, but how else was I going to get out? I remember when my friend Robert Morris got kicked out of Cornell for writing the internet worm of 1988, I was envious that he\\'d found such a spectacular way to get out of grad school. Then one day in April 1990 a crack appeared in the wall. I ran into professor Cheatham and he asked if I was far enough along to graduate that June. I didn\\'t have a word of my dissertation written, but in what must have been the quickest bit of thinking in my life, I decided to take a shot at writing one in the 5 weeks or so that remained before the deadline, reusing parts of On Lisp where I could, and I was able to respond, with no perceptible delay \"Yes, I think so. I\\'ll give you something to read in a few days.\"', 'file_path: data/paul_graham/paul_graham_essay.txt I didn\\'t want to drop out of grad school, but how else was I going to get out? I remember when my friend Robert Morris got kicked out of Cornell for writing the internet worm of 1988, I was envious that he\\'d found such a spectacular way to get out of grad school. Then one day in April 1990 a crack appeared in the wall. I ran into professor Cheatham and he asked if I was far enough along to graduate that June. I didn\\'t have a word of my dissertation written, but in what must have been the quickest bit of thinking in my life, I decided to take a shot at writing one in the 5 weeks or so that remained before the deadline, reusing parts of On Lisp where I could, and I was able to respond, with no perceptible delay \"Yes, I think so. I\\'ll give you something to read in a few days.\" I picked applications of continuations as the topic. In retrospect I should have written about macros and embedded languages. There\\'s a whole world there that\\'s barely been explored. But all I wanted was to get out of grad school, and my rapidly written dissertation sufficed, just barely. Meanwhile I was applying to art schools. I applied to two: RISD in the US, and the Accademia di Belli Arti in Florence, which, because it was the oldest art school, I imagined would be good. RISD accepted me, and I never heard back from the Accademia, so off to Providence I went. I\\'d applied for the BFA program at RISD, which meant in effect that I had to go to college again. This was not as strange as it sounds, because I was only 25, and art schools are full of people of different ages. RISD counted me as a transfer sophomore and said I had to do the foundation that summer. The foundation means the classes that everyone has to take in fundamental subjects like drawing, color, and design. Toward the end of the summer I got a big surprise: a letter from the Accademia, which had been delayed because they\\'d sent it to Cambridge England instead of Cambridge Massachusetts, inviting me to take the entrance exam in Florence that fall. This was now only weeks away. My nice landlady let me leave my stuff in her attic. I had some money saved from consulting work I\\'d done in grad school; there was probably enough to last a year if I lived cheaply. Now all I had to do was learn Italian. Only stranieri (foreigners) had to take this entrance exam. In retrospect it may well have been a way of excluding them, because there were so many stranieri attracted by the idea of studying art in Florence that the Italian students would otherwise have been outnumbered. I was in decent shape at painting and drawing from the RISD foundation that summer, but I still don\\'t know how I managed to pass the written exam. I remember that I answered the essay question by writing about Cezanne, and that I cranked up the intellectual level as high as I could to make the most of my limited vocabulary. [2] I\\'m only up to age 25 and already there are such conspicuous patterns. Here I was, yet again about to attend some august institution in the hopes of learning about some prestigious subject, and yet again about to be disappointed. The students and faculty in the painting department at the Accademia were the nicest people you could imagine, but they had long since arrived at an arrangement whereby the students wouldn\\'t require the faculty to teach anything, and in return the faculty wouldn\\'t require the students to learn anything. And at the same time all involved would adhere outwardly to the conventions of a 19th century atelier. We actually had one of those little stoves, fed with kindling, that you see in 19th century studio paintings, and a nude model sitting as close to it as possible without getting burned. Except hardly anyone else painted her besides me. The rest of the students spent their time chatting or occasionally trying to imitate things they\\'d seen in American art magazines. Our model turned out to live just down the street from me. She made a living from a combination of modelling and making fakes for a local antique dealer. She\\'d copy an obscure old painting out of a book, and then he\\'d take the copy and maltreat it to make it look old. [3] While I was a student at the Accademia I started painting still lives in my bedroom at night. These paintings were tiny, because the room was, and because I painted them on leftover scraps of canvas, which was all I could afford at the time.', 'file_path: data/paul_graham/paul_graham_essay.txt We actually had one of those little stoves, fed with kindling, that you see in 19th century studio paintings, and a nude model sitting as close to it as possible without getting burned. Except hardly anyone else painted her besides me. The rest of the students spent their time chatting or occasionally trying to imitate things they\\'d seen in American art magazines. Our model turned out to live just down the street from me. She made a living from a combination of modelling and making fakes for a local antique dealer. She\\'d copy an obscure old painting out of a book, and then he\\'d take the copy and maltreat it to make it look old. [3] While I was a student at the Accademia I started painting still lives in my bedroom at night. These paintings were tiny, because the room was, and because I painted them on leftover scraps of canvas, which was all I could afford at the time. Painting still lives is different from painting people, because the subject, as its name suggests, can\\'t move. People can\\'t sit for more than about 15 minutes at a time, and when they do they don\\'t sit very still. So the traditional m.o. for painting people is to know how to paint a generic person, which you then modify to match the specific person you\\'re painting. Whereas a still life you can, if you want, copy pixel by pixel from what you\\'re seeing. You don\\'t want to stop there, of course, or you get merely photographic accuracy, and what makes a still life interesting is that it\\'s been through a head. You want to emphasize the visual cues that tell you, for example, that the reason the color changes suddenly at a certain point is that it\\'s the edge of an object. By subtly emphasizing such things you can make paintings that are more realistic than photographs not just in some metaphorical sense, but in the strict information-theoretic sense. [4] I liked painting still lives because I was curious about what I was seeing. In everyday life, we aren\\'t consciously aware of much we\\'re seeing. Most visual perception is handled by low-level processes that merely tell your brain \"that\\'s a water droplet\" without telling you details like where the lightest and darkest points are, or \"that\\'s a bush\" without telling you the shape and position of every leaf. This is a feature of brains, not a bug. In everyday life it would be distracting to notice every leaf on every bush. But when you have to paint something, you have to look more closely, and when you do there\\'s a lot to see. You can still be noticing new things after days of trying to paint something people usually take for granted, just as you can after days of trying to write an essay about something people usually take for granted. This is not the only way to paint. I\\'m not 100% sure it\\'s even a good way to paint. But it seemed a good enough bet to be worth trying. Our teacher, professor Ulivi, was a nice guy. He could see I worked hard, and gave me a good grade, which he wrote down in a sort of passport each student had. But the Accademia wasn\\'t teaching me anything except Italian, and my money was running out, so at the end of the first year I went back to the US. I wanted to go back to RISD, but I was now broke and RISD was very expensive, so I decided to get a job for a year and then return to RISD the next fall. I got one at a company called Interleaf, which made software for creating documents. You mean like Microsoft Word? Exactly. That was how I learned that low end software tends to eat high end software. But Interleaf still had a few years to live yet. [5] Interleaf had done something pretty bold. Inspired by Emacs, they\\'d added a scripting language, and even made the scripting language a dialect of Lisp. Now they wanted a Lisp hacker to write things in it. This was the closest thing I\\'ve had to a normal job, and I hereby apologize to my boss and coworkers, because I was a bad employee. Their Lisp was the thinnest icing on a giant C cake, and since I didn\\'t know C and didn\\'t want to learn it, I never understood most of the software. Plus I was terribly irresponsible. This was back when a programming job meant showing up every day during certain working hours. That seemed unnatural to me, and on this point the rest of the world is coming around to my way of thinking, but at the time it caused a lot of friction.', 'file_path: data/paul_graham/paul_graham_essay.txt But Interleaf still had a few years to live yet. [5] Interleaf had done something pretty bold. Inspired by Emacs, they\\'d added a scripting language, and even made the scripting language a dialect of Lisp. Now they wanted a Lisp hacker to write things in it. This was the closest thing I\\'ve had to a normal job, and I hereby apologize to my boss and coworkers, because I was a bad employee. Their Lisp was the thinnest icing on a giant C cake, and since I didn\\'t know C and didn\\'t want to learn it, I never understood most of the software. Plus I was terribly irresponsible. This was back when a programming job meant showing up every day during certain working hours. That seemed unnatural to me, and on this point the rest of the world is coming around to my way of thinking, but at the time it caused a lot of friction. Toward the end of the year I spent much of my time surreptitiously working on On Lisp, which I had by this time gotten a contract to publish. The good part was that I got paid huge amounts of money, especially by art student standards. In Florence, after paying my part of the rent, my budget for everything else had been $7 a day. Now I was getting paid more than 4 times that every hour, even when I was just sitting in a meeting. By living cheaply I not only managed to save enough to go back to RISD, but also paid off my college loans. I learned some useful things at Interleaf, though they were mostly about what not to do. I learned that it\\'s better for technology companies to be run by product people than sales people (though sales is a real skill and people who are good at it are really good at it), that it leads to bugs when code is edited by too many people, that cheap office space is no bargain if it\\'s depressing, that planned meetings are inferior to corridor conversations, that big, bureaucratic customers are a dangerous source of money, and that there\\'s not much overlap between conventional office hours and the optimal time for hacking, or conventional offices and the optimal place for it. But the most important thing I learned, and which I used in both Viaweb and Y Combinator, is that the low end eats the high end: that it\\'s good to be the \"entry level\" option, even though that will be less prestigious, because if you\\'re not, someone else will be, and will squash you against the ceiling. Which in turn means that prestige is a danger sign. When I left to go back to RISD the next fall, I arranged to do freelance work for the group that did projects for customers, and this was how I survived for the next several years. When I came back to visit for a project later on, someone told me about a new thing called HTML, which was, as he described it, a derivative of SGML. Markup language enthusiasts were an occupational hazard at Interleaf and I ignored him, but this HTML thing later became a big part of my life. In the fall of 1992 I moved back to Providence to continue at RISD. The foundation had merely been intro stuff, and the Accademia had been a (very civilized) joke. Now I was going to see what real art school was like. But alas it was more like the Accademia than not. Better organized, certainly, and a lot more expensive, but it was now becoming clear that art school did not bear the same relationship to art that medical school bore to medicine. At least not the painting department. The textile department, which my next door neighbor belonged to, seemed to be pretty rigorous. No doubt illustration and architecture were too. But painting was post-rigorous. Painting students were supposed to express themselves, which to the more worldly ones meant to try to cook up some sort of distinctive signature style. A signature style is the visual equivalent of what in show business is known as a \"schtick\": something that immediately identifies the work as yours and no one else\\'s. For example, when you see a painting that looks like a certain kind of cartoon, you know it\\'s by Roy Lichtenstein. So if you see a big painting of this type hanging in the apartment of a hedge fund manager, you know he paid millions of dollars for it. That\\'s not always why artists have a signature style, but it\\'s usually why buyers pay a lot for such work. [6] There were plenty of earnest students too: kids who \"could draw\" in high school, and now had come to what was supposed to be the best art school in the country, to learn to draw even better.', 'file_path: data/paul_graham/paul_graham_essay.txt Painting students were supposed to express themselves, which to the more worldly ones meant to try to cook up some sort of distinctive signature style. A signature style is the visual equivalent of what in show business is known as a \"schtick\": something that immediately identifies the work as yours and no one else\\'s. For example, when you see a painting that looks like a certain kind of cartoon, you know it\\'s by Roy Lichtenstein. So if you see a big painting of this type hanging in the apartment of a hedge fund manager, you know he paid millions of dollars for it. That\\'s not always why artists have a signature style, but it\\'s usually why buyers pay a lot for such work. [6] There were plenty of earnest students too: kids who \"could draw\" in high school, and now had come to what was supposed to be the best art school in the country, to learn to draw even better. They tended to be confused and demoralized by what they found at RISD, but they kept going, because painting was what they did. I was not one of the kids who could draw in high school, but at RISD I was definitely closer to their tribe than the tribe of signature style seekers. I learned a lot in the color class I took at RISD, but otherwise I was basically teaching myself to paint, and I could do that for free. So in 1993 I dropped out. I hung around Providence for a bit, and then my college friend Nancy Parmet did me a big favor. A rent-controlled apartment in a building her mother owned in New York was becoming vacant. Did I want it? It wasn\\'t much more than my current place, and New York was supposed to be where the artists were. So yes, I wanted it! [7] Asterix comics begin by zooming in on a tiny corner of Roman Gaul that turns out not to be controlled by the Romans. You can do something similar on a map of New York City: if you zoom in on the Upper East Side, there\\'s a tiny corner that\\'s not rich, or at least wasn\\'t in 1993. It\\'s called Yorkville, and that was my new home. Now I was a New York artist — in the strictly technical sense of making paintings and living in New York. I was nervous about money, because I could sense that Interleaf was on the way down. Freelance Lisp hacking work was very rare, and I didn\\'t want to have to program in another language, which in those days would have meant C++ if I was lucky. So with my unerring nose for financial opportunity, I decided to write another book on Lisp. This would be a popular book, the sort of book that could be used as a textbook. I imagined myself living frugally off the royalties and spending all my time painting. (The painting on the cover of this book, ANSI Common Lisp, is one that I painted around this time.) The best thing about New York for me was the presence of Idelle and Julian Weber. Idelle Weber was a painter, one of the early photorealists, and I\\'d taken her painting class at Harvard. I\\'ve never known a teacher more beloved by her students. Large numbers of former students kept in touch with her, including me. After I moved to New York I became her de facto studio assistant. She liked to paint on big, square canvases, 4 to 5 feet on a side. One day in late 1994 as I was stretching one of these monsters there was something on the radio about a famous fund manager. He wasn\\'t that much older than me, and was super rich. The thought suddenly occurred to me: why don\\'t I become rich? Then I\\'ll be able to work on whatever I want. Meanwhile I\\'d been hearing more and more about this new thing called the World Wide Web. Robert Morris showed it to me when I visited him in Cambridge, where he was now in grad school at Harvard. It seemed to me that the web would be a big deal. I\\'d seen what graphical user interfaces had done for the popularity of microcomputers. It seemed like the web would do the same for the internet. If I wanted to get rich, here was the next train leaving the station. I was right about that part. What I got wrong was the idea. I decided we should start a company to put art galleries online. I can\\'t honestly say, after reading so many Y Combinator applications, that this was the worst startup idea ever, but it was up there. Art galleries didn\\'t want to be online, and still don\\'t, not the fancy ones. That\\'s not how they sell.', 'file_path: data/paul_graham/paul_graham_essay.txt Meanwhile I\\'d been hearing more and more about this new thing called the World Wide Web. Robert Morris showed it to me when I visited him in Cambridge, where he was now in grad school at Harvard. It seemed to me that the web would be a big deal. I\\'d seen what graphical user interfaces had done for the popularity of microcomputers. It seemed like the web would do the same for the internet. If I wanted to get rich, here was the next train leaving the station. I was right about that part. What I got wrong was the idea. I decided we should start a company to put art galleries online. I can\\'t honestly say, after reading so many Y Combinator applications, that this was the worst startup idea ever, but it was up there. Art galleries didn\\'t want to be online, and still don\\'t, not the fancy ones. That\\'s not how they sell. I wrote some software to generate web sites for galleries, and Robert wrote some to resize images and set up an http server to serve the pages. Then we tried to sign up galleries. To call this a difficult sale would be an understatement. It was difficult to give away. A few galleries let us make sites for them for free, but none paid us. Then some online stores started to appear, and I realized that except for the order buttons they were identical to the sites we\\'d been generating for galleries. This impressive-sounding thing called an \"internet storefront\" was something we already knew how to build. So in the summer of 1995, after I submitted the camera-ready copy of ANSI Common Lisp to the publishers, we started trying to write software to build online stores. At first this was going to be normal desktop software, which in those days meant Windows software. That was an alarming prospect, because neither of us knew how to write Windows software or wanted to learn. We lived in the Unix world. But we decided we\\'d at least try writing a prototype store builder on Unix. Robert wrote a shopping cart, and I wrote a new site generator for stores — in Lisp, of course. We were working out of Robert\\'s apartment in Cambridge. His roommate was away for big chunks of time, during which I got to sleep in his room. For some reason there was no bed frame or sheets, just a mattress on the floor. One morning as I was lying on this mattress I had an idea that made me sit up like a capital L. What if we ran the software on the server, and let users control it by clicking on links? Then we\\'d never have to write anything to run on users\\' computers. We could generate the sites on the same server we\\'d serve them from. Users wouldn\\'t need anything more than a browser. This kind of software, known as a web app, is common now, but at the time it wasn\\'t clear that it was even possible. To find out, we decided to try making a version of our store builder that you could control through the browser. A couple days later, on August 12, we had one that worked. The UI was horrible, but it proved you could build a whole store through the browser, without any client software or typing anything into the command line on the server. Now we felt like we were really onto something. I had visions of a whole new generation of software working this way. You wouldn\\'t need versions, or ports, or any of that crap. At Interleaf there had been a whole group called Release Engineering that seemed to be at least as big as the group that actually wrote the software. Now you could just update the software right on the server. We started a new company we called Viaweb, after the fact that our software worked via the web, and we got $10,000 in seed funding from Idelle\\'s husband Julian. In return for that and doing the initial legal work and giving us business advice, we gave him 10% of the company. Ten years later this deal became the model for Y Combinator\\'s. We knew founders needed something like this, because we\\'d needed it ourselves. At this stage I had a negative net worth, because the thousand dollars or so I had in the bank was more than counterbalanced by what I owed the government in taxes. (Had I diligently set aside the proper proportion of the money I\\'d made consulting for Interleaf? No, I had not.) So although Robert had his graduate student stipend, I needed that seed funding to live on. We originally hoped to launch in September, but we got more ambitious about the software as we worked on it.', 'file_path: data/paul_graham/paul_graham_essay.txt In return for that and doing the initial legal work and giving us business advice, we gave him 10% of the company. Ten years later this deal became the model for Y Combinator\\'s. We knew founders needed something like this, because we\\'d needed it ourselves. At this stage I had a negative net worth, because the thousand dollars or so I had in the bank was more than counterbalanced by what I owed the government in taxes. (Had I diligently set aside the proper proportion of the money I\\'d made consulting for Interleaf? No, I had not.) So although Robert had his graduate student stipend, I needed that seed funding to live on. We originally hoped to launch in September, but we got more ambitious about the software as we worked on it. Eventually we managed to build a WYSIWYG site builder, in the sense that as you were creating pages, they looked exactly like the static ones that would be generated later, except that instead of leading to static pages, the links all referred to closures stored in a hash table on the server. It helped to have studied art, because the main goal of an online store builder is to make users look legit, and the key to looking legit is high production values. If you get page layouts and fonts and colors right, you can make a guy running a store out of his bedroom look more legit than a big company. (If you\\'re curious why my site looks so old-fashioned, it\\'s because it\\'s still made with this software. It may look clunky today, but in 1996 it was the last word in slick.) In September, Robert rebelled. \"We\\'ve been working on this for a month,\" he said, \"and it\\'s still not done.\" This is funny in retrospect, because he would still be working on it almost 3 years later. But I decided it might be prudent to recruit more programmers, and I asked Robert who else in grad school with him was really good. He recommended Trevor Blackwell, which surprised me at first, because at that point I knew Trevor mainly for his plan to reduce everything in his life to a stack of notecards, which he carried around with him. But Rtm was right, as usual. Trevor turned out to be a frighteningly effective hacker. It was a lot of fun working with Robert and Trevor. They\\'re the two most independent-minded people I know, and in completely different ways. If you could see inside Rtm\\'s brain it would look like a colonial New England church, and if you could see inside Trevor\\'s it would look like the worst excesses of Austrian Rococo. We opened for business, with 6 stores, in January 1996. It was just as well we waited a few months, because although we worried we were late, we were actually almost fatally early. There was a lot of talk in the press then about ecommerce, but not many people actually wanted online stores. [8] There were three main parts to the software: the editor, which people used to build sites and which I wrote, the shopping cart, which Robert wrote, and the manager, which kept track of orders and statistics, and which Trevor wrote. In its time, the editor was one of the best general-purpose site builders. I kept the code tight and didn\\'t have to integrate with any other software except Robert\\'s and Trevor\\'s, so it was quite fun to work on. If all I\\'d had to do was work on this software, the next 3 years would have been the easiest of my life. Unfortunately I had to do a lot more, all of it stuff I was worse at than programming, and the next 3 years were instead the most stressful. There were a lot of startups making ecommerce software in the second half of the 90s. We were determined to be the Microsoft Word, not the Interleaf. Which meant being easy to use and inexpensive. It was lucky for us that we were poor, because that caused us to make Viaweb even more inexpensive than we realized. We charged $100 a month for a small store and $300 a month for a big one. This low price was a big attraction, and a constant thorn in the sides of competitors, but it wasn\\'t because of some clever insight that we set the price low. We had no idea what businesses paid for things. $300 a month seemed like a lot of money to us. We did a lot of things right by accident like that. For example, we did what\\'s now called \"doing things that don\\'t scale,\" although at the time we would have described it as \"being so lame that we\\'re driven to the most desperate measures to get users.\" The most common of which was building stores for them.', 'file_path: data/paul_graham/paul_graham_essay.txt Which meant being easy to use and inexpensive. It was lucky for us that we were poor, because that caused us to make Viaweb even more inexpensive than we realized. We charged $100 a month for a small store and $300 a month for a big one. This low price was a big attraction, and a constant thorn in the sides of competitors, but it wasn\\'t because of some clever insight that we set the price low. We had no idea what businesses paid for things. $300 a month seemed like a lot of money to us. We did a lot of things right by accident like that. For example, we did what\\'s now called \"doing things that don\\'t scale,\" although at the time we would have described it as \"being so lame that we\\'re driven to the most desperate measures to get users.\" The most common of which was building stores for them. This seemed particularly humiliating, since the whole raison d\\'etre of our software was that people could use it to make their own stores. But anything to get users. We learned a lot more about retail than we wanted to know. For example, that if you could only have a small image of a man\\'s shirt (and all images were small then by present standards), it was better to have a closeup of the collar than a picture of the whole shirt. The reason I remember learning this was that it meant I had to rescan about 30 images of men\\'s shirts. My first set of scans were so beautiful too. Though this felt wrong, it was exactly the right thing to be doing. Building stores for users taught us about retail, and about how it felt to use our software. I was initially both mystified and repelled by \"business\" and thought we needed a \"business person\" to be in charge of it, but once we started to get users, I was converted, in much the same way I was converted to fatherhood once I had kids. Whatever users wanted, I was all theirs. Maybe one day we\\'d have so many users that I couldn\\'t scan their images for them, but in the meantime there was nothing more important to do. Another thing I didn\\'t get at the time is that growth rate is the ultimate test of a startup. Our growth rate was fine. We had about 70 stores at the end of 1996 and about 500 at the end of 1997. I mistakenly thought the thing that mattered was the absolute number of users. And that is the thing that matters in the sense that that\\'s how much money you\\'re making, and if you\\'re not making enough, you might go out of business. But in the long term the growth rate takes care of the absolute number. If we\\'d been a startup I was advising at Y Combinator, I would have said: Stop being so stressed out, because you\\'re doing fine. You\\'re growing 7x a year. Just don\\'t hire too many more people and you\\'ll soon be profitable, and then you\\'ll control your own destiny. Alas I hired lots more people, partly because our investors wanted me to, and partly because that\\'s what startups did during the Internet Bubble. A company with just a handful of employees would have seemed amateurish. So we didn\\'t reach breakeven until about when Yahoo bought us in the summer of 1998. Which in turn meant we were at the mercy of investors for the entire life of the company. And since both we and our investors were noobs at startups, the result was a mess even by startup standards. It was a huge relief when Yahoo bought us. In principle our Viaweb stock was valuable. It was a share in a business that was profitable and growing rapidly. But it didn\\'t feel very valuable to me; I had no idea how to value a business, but I was all too keenly aware of the near-death experiences we seemed to have every few months. Nor had I changed my grad student lifestyle significantly since we started. So when Yahoo bought us it felt like going from rags to riches. Since we were going to California, I bought a car, a yellow 1998 VW GTI. I remember thinking that its leather seats alone were by far the most luxurious thing I owned. The next year, from the summer of 1998 to the summer of 1999, must have been the least productive of my life. I didn\\'t realize it at the time, but I was worn out from the effort and stress of running Viaweb. For a while after I got to California I tried to continue my usual m.o.'] nomic-ai/nomic-embed-text-v1.5 {'dimensions': 128}\n", + "show list of text [\"file_path: data/paul_graham/paul_graham_essay.txt But it didn't feel very valuable to me; I had no idea how to value a business, but I was all too keenly aware of the near-death experiences we seemed to have every few months. Nor had I changed my grad student lifestyle significantly since we started. So when Yahoo bought us it felt like going from rags to riches. Since we were going to California, I bought a car, a yellow 1998 VW GTI. I remember thinking that its leather seats alone were by far the most luxurious thing I owned. The next year, from the summer of 1998 to the summer of 1999, must have been the least productive of my life. I didn't realize it at the time, but I was worn out from the effort and stress of running Viaweb. For a while after I got to California I tried to continue my usual m.o. of programming till 3 in the morning, but fatigue combined with Yahoo's prematurely aged culture and grim cube farm in Santa Clara gradually dragged me down. After a few months it felt disconcertingly like working at Interleaf. Yahoo had given us a lot of options when they bought us. At the time I thought Yahoo was so overvalued that they'd never be worth anything, but to my astonishment the stock went up 5x in the next year. I hung on till the first chunk of options vested, then in the summer of 1999 I left. It had been so long since I'd painted anything that I'd half forgotten why I was doing this. My brain had been entirely full of software and men's shirts for 4 years. But I had done this to get rich so I could paint, I reminded myself, and now I was rich, so I should go paint. When I said I was leaving, my boss at Yahoo had a long conversation with me about my plans. I told him all about the kinds of pictures I wanted to paint. At the time I was touched that he took such an interest in me. Now I realize it was because he thought I was lying. My options at that point were worth about $2 million a month. If I was leaving that kind of money on the table, it could only be to go and start some new startup, and if I did, I might take people with me. This was the height of the Internet Bubble, and Yahoo was ground zero of it. My boss was at that moment a billionaire. Leaving then to start a new startup must have seemed to him an insanely, and yet also plausibly, ambitious plan. But I really was quitting to paint, and I started immediately. There was no time to lose. I'd already burned 4 years getting rich. Now when I talk to founders who are leaving after selling their companies, my advice is always the same: take a vacation. That's what I should have done, just gone off somewhere and done nothing for a month or two, but the idea never occurred to me. So I tried to paint, but I just didn't seem to have any energy or ambition. Part of the problem was that I didn't know many people in California. I'd compounded this problem by buying a house up in the Santa Cruz Mountains, with a beautiful view but miles from anywhere. I stuck it out for a few more months, then in desperation I went back to New York, where unless you understand about rent control you'll be surprised to hear I still had my apartment, sealed up like a tomb of my old life. Idelle was in New York at least, and there were other people trying to paint there, even though I didn't know any of them. When I got back to New York I resumed my old life, except now I was rich. It was as weird as it sounds. I resumed all my old patterns, except now there were doors where there hadn't been. Now when I was tired of walking, all I had to do was raise my hand, and (unless it was raining) a taxi would stop to pick me up. Now when I walked past charming little restaurants I could go in and order lunch. It was exciting for a while. Painting started to go better. I experimented with a new kind of still life where I'd paint one painting in the old way, then photograph it and print it, blown up, on canvas, and then use that as the underpainting for a second still life, painted from the same objects (which hopefully hadn't rotted yet). Meanwhile I looked for an apartment to buy. Now I could actually choose what neighborhood to live in. Where, I asked myself and various real estate agents, is the Cambridge of New York?\", 'file_path: data/paul_graham/paul_graham_essay.txt It was as weird as it sounds. I resumed all my old patterns, except now there were doors where there hadn\\'t been. Now when I was tired of walking, all I had to do was raise my hand, and (unless it was raining) a taxi would stop to pick me up. Now when I walked past charming little restaurants I could go in and order lunch. It was exciting for a while. Painting started to go better. I experimented with a new kind of still life where I\\'d paint one painting in the old way, then photograph it and print it, blown up, on canvas, and then use that as the underpainting for a second still life, painted from the same objects (which hopefully hadn\\'t rotted yet). Meanwhile I looked for an apartment to buy. Now I could actually choose what neighborhood to live in. Where, I asked myself and various real estate agents, is the Cambridge of New York? Aided by occasional visits to actual Cambridge, I gradually realized there wasn\\'t one. Huh. Around this time, in the spring of 2000, I had an idea. It was clear from our experience with Viaweb that web apps were the future. Why not build a web app for making web apps? Why not let people edit code on our server through the browser, and then host the resulting applications for them? [9] You could run all sorts of services on the servers that these applications could use just by making an API call: making and receiving phone calls, manipulating images, taking credit card payments, etc. I got so excited about this idea that I couldn\\'t think about anything else. It seemed obvious that this was the future. I didn\\'t particularly want to start another company, but it was clear that this idea would have to be embodied as one, so I decided to move to Cambridge and start it. I hoped to lure Robert into working on it with me, but there I ran into a hitch. Robert was now a postdoc at MIT, and though he\\'d made a lot of money the last time I\\'d lured him into working on one of my schemes, it had also been a huge time sink. So while he agreed that it sounded like a plausible idea, he firmly refused to work on it. Hmph. Well, I\\'d do it myself then. I recruited Dan Giffin, who had worked for Viaweb, and two undergrads who wanted summer jobs, and we got to work trying to build what it\\'s now clear is about twenty companies and several open source projects worth of software. The language for defining applications would of course be a dialect of Lisp. But I wasn\\'t so naive as to assume I could spring an overt Lisp on a general audience; we\\'d hide the parentheses, like Dylan did. By then there was a name for the kind of company Viaweb was, an \"application service provider,\" or ASP. This name didn\\'t last long before it was replaced by \"software as a service,\" but it was current for long enough that I named this new company after it: it was going to be called Aspra. I started working on the application builder, Dan worked on network infrastructure, and the two undergrads worked on the first two services (images and phone calls). But about halfway through the summer I realized I really didn\\'t want to run a company — especially not a big one, which it was looking like this would have to be. I\\'d only started Viaweb because I needed the money. Now that I didn\\'t need money anymore, why was I doing this? If this vision had to be realized as a company, then screw the vision. I\\'d build a subset that could be done as an open source project. Much to my surprise, the time I spent working on this stuff was not wasted after all. After we started Y Combinator, I would often encounter startups working on parts of this new architecture, and it was very useful to have spent so much time thinking about it and even trying to write some of it. The subset I would build as an open source project was the new Lisp, whose parentheses I now wouldn\\'t even have to hide. A lot of Lisp hackers dream of building a new Lisp, partly because one of the distinctive features of the language is that it has dialects, and partly, I think, because we have in our minds a Platonic form of Lisp that all existing dialects fall short of. I certainly did. So at the end of the summer Dan and I switched to working on this new dialect of Lisp, which I called Arc, in a house I bought in Cambridge. The following spring, lightning struck.', \"file_path: data/paul_graham/paul_graham_essay.txt Much to my surprise, the time I spent working on this stuff was not wasted after all. After we started Y Combinator, I would often encounter startups working on parts of this new architecture, and it was very useful to have spent so much time thinking about it and even trying to write some of it. The subset I would build as an open source project was the new Lisp, whose parentheses I now wouldn't even have to hide. A lot of Lisp hackers dream of building a new Lisp, partly because one of the distinctive features of the language is that it has dialects, and partly, I think, because we have in our minds a Platonic form of Lisp that all existing dialects fall short of. I certainly did. So at the end of the summer Dan and I switched to working on this new dialect of Lisp, which I called Arc, in a house I bought in Cambridge. The following spring, lightning struck. I was invited to give a talk at a Lisp conference, so I gave one about how we'd used Lisp at Viaweb. Afterward I put a postscript file of this talk online, on paulgraham.com, which I'd created years before using Viaweb but had never used for anything. In one day it got 30,000 page views. What on earth had happened? The referring urls showed that someone had posted it on Slashdot. [10] Wow, I thought, there's an audience. If I write something and put it on the web, anyone can read it. That may seem obvious now, but it was surprising then. In the print era there was a narrow channel to readers, guarded by fierce monsters known as editors. The only way to get an audience for anything you wrote was to get it published as a book, or in a newspaper or magazine. Now anyone could publish anything. This had been possible in principle since 1993, but not many people had realized it yet. I had been intimately involved with building the infrastructure of the web for most of that time, and a writer as well, and it had taken me 8 years to realize it. Even then it took me several years to understand the implications. It meant there would be a whole new generation of essays. [11] In the print era, the channel for publishing essays had been vanishingly small. Except for a few officially anointed thinkers who went to the right parties in New York, the only people allowed to publish essays were specialists writing about their specialties. There were so many essays that had never been written, because there had been no way to publish them. Now they could be, and I was going to write them. [12] I've worked on several different things, but to the extent there was a turning point where I figured out what to work on, it was when I started publishing essays online. From then on I knew that whatever else I did, I'd always write essays too. I knew that online essays would be a marginal medium at first. Socially they'd seem more like rants posted by nutjobs on their GeoCities sites than the genteel and beautifully typeset compositions published in The New Yorker. But by this point I knew enough to find that encouraging instead of discouraging. One of the most conspicuous patterns I've noticed in my life is how well it has worked, for me at least, to work on things that weren't prestigious. Still life has always been the least prestigious form of painting. Viaweb and Y Combinator both seemed lame when we started them. I still get the glassy eye from strangers when they ask what I'm writing, and I explain that it's an essay I'm going to publish on my web site. Even Lisp, though prestigious intellectually in something like the way Latin is, also seems about as hip. It's not that unprestigious types of work are good per se. But when you find yourself drawn to some kind of work despite its current lack of prestige, it's a sign both that there's something real to be discovered there, and that you have the right kind of motives. Impure motives are a big danger for the ambitious. If anything is going to lead you astray, it will be the desire to impress people. So while working on things that aren't prestigious doesn't guarantee you're on the right track, it at least guarantees you're not on the most common type of wrong one. Over the next several years I wrote lots of essays about all kinds of different topics. O'Reilly reprinted a collection of them as a book, called Hackers & Painters after one of the essays in it. I also worked on spam filters, and did some more painting.\", 'file_path: data/paul_graham/paul_graham_essay.txt It\\'s not that unprestigious types of work are good per se. But when you find yourself drawn to some kind of work despite its current lack of prestige, it\\'s a sign both that there\\'s something real to be discovered there, and that you have the right kind of motives. Impure motives are a big danger for the ambitious. If anything is going to lead you astray, it will be the desire to impress people. So while working on things that aren\\'t prestigious doesn\\'t guarantee you\\'re on the right track, it at least guarantees you\\'re not on the most common type of wrong one. Over the next several years I wrote lots of essays about all kinds of different topics. O\\'Reilly reprinted a collection of them as a book, called Hackers & Painters after one of the essays in it. I also worked on spam filters, and did some more painting. I used to have dinners for a group of friends every thursday night, which taught me how to cook for groups. And I bought another building in Cambridge, a former candy factory (and later, twas said, porn studio), to use as an office. One night in October 2003 there was a big party at my house. It was a clever idea of my friend Maria Daniels, who was one of the thursday diners. Three separate hosts would all invite their friends to one party. So for every guest, two thirds of the other guests would be people they didn\\'t know but would probably like. One of the guests was someone I didn\\'t know but would turn out to like a lot: a woman called Jessica Livingston. A couple days later I asked her out. Jessica was in charge of marketing at a Boston investment bank. This bank thought it understood startups, but over the next year, as she met friends of mine from the startup world, she was surprised how different reality was. And how colorful their stories were. So she decided to compile a book of interviews with startup founders. When the bank had financial problems and she had to fire half her staff, she started looking for a new job. In early 2005 she interviewed for a marketing job at a Boston VC firm. It took them weeks to make up their minds, and during this time I started telling her about all the things that needed to be fixed about venture capital. They should make a larger number of smaller investments instead of a handful of giant ones, they should be funding younger, more technical founders instead of MBAs, they should let the founders remain as CEO, and so on. One of my tricks for writing essays had always been to give talks. The prospect of having to stand up in front of a group of people and tell them something that won\\'t waste their time is a great spur to the imagination. When the Harvard Computer Society, the undergrad computer club, asked me to give a talk, I decided I would tell them how to start a startup. Maybe they\\'d be able to avoid the worst of the mistakes we\\'d made. So I gave this talk, in the course of which I told them that the best sources of seed funding were successful startup founders, because then they\\'d be sources of advice too. Whereupon it seemed they were all looking expectantly at me. Horrified at the prospect of having my inbox flooded by business plans (if I\\'d only known), I blurted out \"But not me!\" and went on with the talk. But afterward it occurred to me that I should really stop procrastinating about angel investing. I\\'d been meaning to since Yahoo bought us, and now it was 7 years later and I still hadn\\'t done one angel investment. Meanwhile I had been scheming with Robert and Trevor about projects we could work on together. I missed working with them, and it seemed like there had to be something we could collaborate on. As Jessica and I were walking home from dinner on March 11, at the corner of Garden and Walker streets, these three threads converged. Screw the VCs who were taking so long to make up their minds. We\\'d start our own investment firm and actually implement the ideas we\\'d been talking about. I\\'d fund it, and Jessica could quit her job and work for it, and we\\'d get Robert and Trevor as partners too. [13] Once again, ignorance worked in our favor. We had no idea how to be angel investors, and in Boston in 2005 there were no Ron Conways to learn from. So we just made what seemed like the obvious choices, and some of the things we did turned out to be novel. There are multiple components to Y Combinator, and we didn\\'t figure them all out at once. The part we got first was to be an angel firm.', 'file_path: data/paul_graham/paul_graham_essay.txt As Jessica and I were walking home from dinner on March 11, at the corner of Garden and Walker streets, these three threads converged. Screw the VCs who were taking so long to make up their minds. We\\'d start our own investment firm and actually implement the ideas we\\'d been talking about. I\\'d fund it, and Jessica could quit her job and work for it, and we\\'d get Robert and Trevor as partners too. [13] Once again, ignorance worked in our favor. We had no idea how to be angel investors, and in Boston in 2005 there were no Ron Conways to learn from. So we just made what seemed like the obvious choices, and some of the things we did turned out to be novel. There are multiple components to Y Combinator, and we didn\\'t figure them all out at once. The part we got first was to be an angel firm. In those days, those two words didn\\'t go together. There were VC firms, which were organized companies with people whose job it was to make investments, but they only did big, million dollar investments. And there were angels, who did smaller investments, but these were individuals who were usually focused on other things and made investments on the side. And neither of them helped founders enough in the beginning. We knew how helpless founders were in some respects, because we remembered how helpless we\\'d been. For example, one thing Julian had done for us that seemed to us like magic was to get us set up as a company. We were fine writing fairly difficult software, but actually getting incorporated, with bylaws and stock and all that stuff, how on earth did you do that? Our plan was not only to make seed investments, but to do for startups everything Julian had done for us. YC was not organized as a fund. It was cheap enough to run that we funded it with our own money. That went right by 99% of readers, but professional investors are thinking \"Wow, that means they got all the returns.\" But once again, this was not due to any particular insight on our part. We didn\\'t know how VC firms were organized. It never occurred to us to try to raise a fund, and if it had, we wouldn\\'t have known where to start. [14] The most distinctive thing about YC is the batch model: to fund a bunch of startups all at once, twice a year, and then to spend three months focusing intensively on trying to help them. That part we discovered by accident, not merely implicitly but explicitly due to our ignorance about investing. We needed to get experience as investors. What better way, we thought, than to fund a whole bunch of startups at once? We knew undergrads got temporary jobs at tech companies during the summer. Why not organize a summer program where they\\'d start startups instead? We wouldn\\'t feel guilty for being in a sense fake investors, because they would in a similar sense be fake founders. So while we probably wouldn\\'t make much money out of it, we\\'d at least get to practice being investors on them, and they for their part would probably have a more interesting summer than they would working at Microsoft. We\\'d use the building I owned in Cambridge as our headquarters. We\\'d all have dinner there once a week — on tuesdays, since I was already cooking for the thursday diners on thursdays — and after dinner we\\'d bring in experts on startups to give talks. We knew undergrads were deciding then about summer jobs, so in a matter of days we cooked up something we called the Summer Founders Program, and I posted an announcement on my site, inviting undergrads to apply. I had never imagined that writing essays would be a way to get \"deal flow,\" as investors call it, but it turned out to be the perfect source. [15] We got 225 applications for the Summer Founders Program, and we were surprised to find that a lot of them were from people who\\'d already graduated, or were about to that spring. Already this SFP thing was starting to feel more serious than we\\'d intended. We invited about 20 of the 225 groups to interview in person, and from those we picked 8 to fund. They were an impressive group. That first batch included reddit, Justin Kan and Emmett Shear, who went on to found Twitch, Aaron Swartz, who had already helped write the RSS spec and would a few years later become a martyr for open access, and Sam Altman, who would later become the second president of YC. I don\\'t think it was entirely luck that the first batch was so good.', 'file_path: data/paul_graham/paul_graham_essay.txt [15] We got 225 applications for the Summer Founders Program, and we were surprised to find that a lot of them were from people who\\'d already graduated, or were about to that spring. Already this SFP thing was starting to feel more serious than we\\'d intended. We invited about 20 of the 225 groups to interview in person, and from those we picked 8 to fund. They were an impressive group. That first batch included reddit, Justin Kan and Emmett Shear, who went on to found Twitch, Aaron Swartz, who had already helped write the RSS spec and would a few years later become a martyr for open access, and Sam Altman, who would later become the second president of YC. I don\\'t think it was entirely luck that the first batch was so good. You had to be pretty bold to sign up for a weird thing like the Summer Founders Program instead of a summer job at a legit place like Microsoft or Goldman Sachs. The deal for startups was based on a combination of the deal we did with Julian ($10k for 10%) and what Robert said MIT grad students got for the summer ($6k). We invested $6k per founder, which in the typical two-founder case was $12k, in return for 6%. That had to be fair, because it was twice as good as the deal we ourselves had taken. Plus that first summer, which was really hot, Jessica brought the founders free air conditioners. [16] Fairly quickly I realized that we had stumbled upon the way to scale startup funding. Funding startups in batches was more convenient for us, because it meant we could do things for a lot of startups at once, but being part of a batch was better for the startups too. It solved one of the biggest problems faced by founders: the isolation. Now you not only had colleagues, but colleagues who understood the problems you were facing and could tell you how they were solving them. As YC grew, we started to notice other advantages of scale. The alumni became a tight community, dedicated to helping one another, and especially the current batch, whose shoes they remembered being in. We also noticed that the startups were becoming one another\\'s customers. We used to refer jokingly to the \"YC GDP,\" but as YC grows this becomes less and less of a joke. Now lots of startups get their initial set of customers almost entirely from among their batchmates. I had not originally intended YC to be a full-time job. I was going to do three things: hack, write essays, and work on YC. As YC grew, and I grew more excited about it, it started to take up a lot more than a third of my attention. But for the first few years I was still able to work on other things. In the summer of 2006, Robert and I started working on a new version of Arc. This one was reasonably fast, because it was compiled into Scheme. To test this new Arc, I wrote Hacker News in it. It was originally meant to be a news aggregator for startup founders and was called Startup News, but after a few months I got tired of reading about nothing but startups. Plus it wasn\\'t startup founders we wanted to reach. It was future startup founders. So I changed the name to Hacker News and the topic to whatever engaged one\\'s intellectual curiosity. HN was no doubt good for YC, but it was also by far the biggest source of stress for me. If all I\\'d had to do was select and help founders, life would have been so easy. And that implies that HN was a mistake. Surely the biggest source of stress in one\\'s work should at least be something close to the core of the work. Whereas I was like someone who was in pain while running a marathon not from the exertion of running, but because I had a blister from an ill-fitting shoe. When I was dealing with some urgent problem during YC, there was about a 60% chance it had to do with HN, and a 40% chance it had do with everything else combined. [17] As well as HN, I wrote all of YC\\'s internal software in Arc. But while I continued to work a good deal in Arc, I gradually stopped working on Arc, partly because I didn\\'t have time to, and partly because it was a lot less attractive to mess around with the language now that we had all this infrastructure depending on it. So now my three projects were reduced to two: writing essays and working on YC. YC was different from other kinds of work I\\'ve done. Instead of deciding for myself what to work on, the problems came to me.', 'file_path: data/paul_graham/paul_graham_essay.txt When I was dealing with some urgent problem during YC, there was about a 60% chance it had to do with HN, and a 40% chance it had do with everything else combined. [17] As well as HN, I wrote all of YC\\'s internal software in Arc. But while I continued to work a good deal in Arc, I gradually stopped working on Arc, partly because I didn\\'t have time to, and partly because it was a lot less attractive to mess around with the language now that we had all this infrastructure depending on it. So now my three projects were reduced to two: writing essays and working on YC. YC was different from other kinds of work I\\'ve done. Instead of deciding for myself what to work on, the problems came to me. Every 6 months there was a new batch of startups, and their problems, whatever they were, became our problems. It was very engaging work, because their problems were quite varied, and the good founders were very effective. If you were trying to learn the most you could about startups in the shortest possible time, you couldn\\'t have picked a better way to do it. There were parts of the job I didn\\'t like. Disputes between cofounders, figuring out when people were lying to us, fighting with people who maltreated the startups, and so on. But I worked hard even at the parts I didn\\'t like. I was haunted by something Kevin Hale once said about companies: \"No one works harder than the boss.\" He meant it both descriptively and prescriptively, and it was the second part that scared me. I wanted YC to be good, so if how hard I worked set the upper bound on how hard everyone else worked, I\\'d better work very hard. One day in 2010, when he was visiting California for interviews, Robert Morris did something astonishing: he offered me unsolicited advice. I can only remember him doing that once before. One day at Viaweb, when I was bent over double from a kidney stone, he suggested that it would be a good idea for him to take me to the hospital. That was what it took for Rtm to offer unsolicited advice. So I remember his exact words very clearly. \"You know,\" he said, \"you should make sure Y Combinator isn\\'t the last cool thing you do.\" At the time I didn\\'t understand what he meant, but gradually it dawned on me that he was saying I should quit. This seemed strange advice, because YC was doing great. But if there was one thing rarer than Rtm offering advice, it was Rtm being wrong. So this set me thinking. It was true that on my current trajectory, YC would be the last thing I did, because it was only taking up more of my attention. It had already eaten Arc, and was in the process of eating essays too. Either YC was my life\\'s work or I\\'d have to leave eventually. And it wasn\\'t, so I would. In the summer of 2012 my mother had a stroke, and the cause turned out to be a blood clot caused by colon cancer. The stroke destroyed her balance, and she was put in a nursing home, but she really wanted to get out of it and back to her house, and my sister and I were determined to help her do it. I used to fly up to Oregon to visit her regularly, and I had a lot of time to think on those flights. On one of them I realized I was ready to hand YC over to someone else. I asked Jessica if she wanted to be president, but she didn\\'t, so we decided we\\'d try to recruit Sam Altman. We talked to Robert and Trevor and we agreed to make it a complete changing of the guard. Up till that point YC had been controlled by the original LLC we four had started. But we wanted YC to last for a long time, and to do that it couldn\\'t be controlled by the founders. So if Sam said yes, we\\'d let him reorganize YC. Robert and I would retire, and Jessica and Trevor would become ordinary partners. When we asked Sam if he wanted to be president of YC, initially he said no. He wanted to start a startup to make nuclear reactors. But I kept at it, and in October 2013 he finally agreed. We decided he\\'d take over starting with the winter 2014 batch. For the rest of 2013 I left running YC more and more to Sam, partly so he could learn the job, and partly because I was focused on my mother, whose cancer had returned.', \"file_path: data/paul_graham/paul_graham_essay.txt Up till that point YC had been controlled by the original LLC we four had started. But we wanted YC to last for a long time, and to do that it couldn't be controlled by the founders. So if Sam said yes, we'd let him reorganize YC. Robert and I would retire, and Jessica and Trevor would become ordinary partners. When we asked Sam if he wanted to be president of YC, initially he said no. He wanted to start a startup to make nuclear reactors. But I kept at it, and in October 2013 he finally agreed. We decided he'd take over starting with the winter 2014 batch. For the rest of 2013 I left running YC more and more to Sam, partly so he could learn the job, and partly because I was focused on my mother, whose cancer had returned. She died on January 15, 2014. We knew this was coming, but it was still hard when it did. I kept working on YC till March, to help get that batch of startups through Demo Day, then I checked out pretty completely. (I still talk to alumni and to new startups working on things I'm interested in, but that only takes a few hours a week.) What should I do next? Rtm's advice hadn't included anything about that. I wanted to do something completely different, so I decided I'd paint. I wanted to see how good I could get if I really focused on it. So the day after I stopped working on YC, I started painting. I was rusty and it took a while to get back into shape, but it was at least completely engaging. [18] I spent most of the rest of 2014 painting. I'd never been able to work so uninterruptedly before, and I got to be better than I had been. Not good enough, but better. Then in November, right in the middle of a painting, I ran out of steam. Up till that point I'd always been curious to see how the painting I was working on would turn out, but suddenly finishing this one seemed like a chore. So I stopped working on it and cleaned my brushes and haven't painted since. So far anyway. I realize that sounds rather wimpy. But attention is a zero sum game. If you can choose what to work on, and you choose a project that's not the best one (or at least a good one) for you, then it's getting in the way of another project that is. And at 50 there was some opportunity cost to screwing around. I started writing essays again, and wrote a bunch of new ones over the next few months. I even wrote a couple that weren't about startups. Then in March 2015 I started working on Lisp again. The distinctive thing about Lisp is that its core is a language defined by writing an interpreter in itself. It wasn't originally intended as a programming language in the ordinary sense. It was meant to be a formal model of computation, an alternative to the Turing machine. If you want to write an interpreter for a language in itself, what's the minimum set of predefined operators you need? The Lisp that John McCarthy invented, or more accurately discovered, is an answer to that question. [19] McCarthy didn't realize this Lisp could even be used to program computers till his grad student Steve Russell suggested it. Russell translated McCarthy's interpreter into IBM 704 machine language, and from that point Lisp started also to be a programming language in the ordinary sense. But its origins as a model of computation gave it a power and elegance that other languages couldn't match. It was this that attracted me in college, though I didn't understand why at the time. McCarthy's 1960 Lisp did nothing more than interpret Lisp expressions. It was missing a lot of things you'd want in a programming language. So these had to be added, and when they were, they weren't defined using McCarthy's original axiomatic approach. That wouldn't have been feasible at the time. McCarthy tested his interpreter by hand-simulating the execution of programs. But it was already getting close to the limit of interpreters you could test that way — indeed, there was a bug in it that McCarthy had overlooked. To test a more complicated interpreter, you'd have had to run it, and computers then weren't powerful enough. Now they are, though. Now you could continue using McCarthy's axiomatic approach till you'd defined a complete programming language. And as long as every change you made to McCarthy's Lisp was a discoveredness-preserving transformation, you could, in principle, end up with a complete language that had this quality.\", 'file_path: data/paul_graham/paul_graham_essay.txt It was missing a lot of things you\\'d want in a programming language. So these had to be added, and when they were, they weren\\'t defined using McCarthy\\'s original axiomatic approach. That wouldn\\'t have been feasible at the time. McCarthy tested his interpreter by hand-simulating the execution of programs. But it was already getting close to the limit of interpreters you could test that way — indeed, there was a bug in it that McCarthy had overlooked. To test a more complicated interpreter, you\\'d have had to run it, and computers then weren\\'t powerful enough. Now they are, though. Now you could continue using McCarthy\\'s axiomatic approach till you\\'d defined a complete programming language. And as long as every change you made to McCarthy\\'s Lisp was a discoveredness-preserving transformation, you could, in principle, end up with a complete language that had this quality. Harder to do than to talk about, of course, but if it was possible in principle, why not try? So I decided to take a shot at it. It took 4 years, from March 26, 2015 to October 12, 2019. It was fortunate that I had a precisely defined goal, or it would have been hard to keep at it for so long. I wrote this new Lisp, called Bel, in itself in Arc. That may sound like a contradiction, but it\\'s an indication of the sort of trickery I had to engage in to make this work. By means of an egregious collection of hacks I managed to make something close enough to an interpreter written in itself that could actually run. Not fast, but fast enough to test. I had to ban myself from writing essays during most of this time, or I\\'d never have finished. In late 2015 I spent 3 months writing essays, and when I went back to working on Bel I could barely understand the code. Not so much because it was badly written as because the problem is so convoluted. When you\\'re working on an interpreter written in itself, it\\'s hard to keep track of what\\'s happening at what level, and errors can be practically encrypted by the time you get them. So I said no more essays till Bel was done. But I told few people about Bel while I was working on it. So for years it must have seemed that I was doing nothing, when in fact I was working harder than I\\'d ever worked on anything. Occasionally after wrestling for hours with some gruesome bug I\\'d check Twitter or HN and see someone asking \"Does Paul Graham still code?\" Working on Bel was hard but satisfying. I worked on it so intensively that at any given time I had a decent chunk of the code in my head and could write more there. I remember taking the boys to the coast on a sunny day in 2015 and figuring out how to deal with some problem involving continuations while I watched them play in the tide pools. It felt like I was doing life right. I remember that because I was slightly dismayed at how novel it felt. The good news is that I had more moments like this over the next few years. In the summer of 2016 we moved to England. We wanted our kids to see what it was like living in another country, and since I was a British citizen by birth, that seemed the obvious choice. We only meant to stay for a year, but we liked it so much that we still live there. So most of Bel was written in England. In the fall of 2019, Bel was finally finished. Like McCarthy\\'s original Lisp, it\\'s a spec rather than an implementation, although like McCarthy\\'s Lisp it\\'s a spec expressed as code. Now that I could write essays again, I wrote a bunch about topics I\\'d had stacked up. I kept writing essays through 2020, but I also started to think about other things I could work on. How should I choose what to do? Well, how had I chosen what to work on in the past? I wrote an essay for myself to answer that question, and I was surprised how long and messy the answer turned out to be. If this surprised me, who\\'d lived it, then I thought perhaps it would be interesting to other people, and encouraging to those with similarly messy lives. So I wrote a more detailed version for others to read, and this is the last sentence of it. Notes [1] My experience skipped a step in the evolution of computers: time-sharing machines with interactive OSes. I went straight from batch processing to microcomputers, which made microcomputers seem all the more exciting.', \"file_path: data/paul_graham/paul_graham_essay.txt Now that I could write essays again, I wrote a bunch about topics I'd had stacked up. I kept writing essays through 2020, but I also started to think about other things I could work on. How should I choose what to do? Well, how had I chosen what to work on in the past? I wrote an essay for myself to answer that question, and I was surprised how long and messy the answer turned out to be. If this surprised me, who'd lived it, then I thought perhaps it would be interesting to other people, and encouraging to those with similarly messy lives. So I wrote a more detailed version for others to read, and this is the last sentence of it. Notes [1] My experience skipped a step in the evolution of computers: time-sharing machines with interactive OSes. I went straight from batch processing to microcomputers, which made microcomputers seem all the more exciting. [2] Italian words for abstract concepts can nearly always be predicted from their English cognates (except for occasional traps like polluzione). It's the everyday words that differ. So if you string together a lot of abstract concepts with a few simple verbs, you can make a little Italian go a long way. [3] I lived at Piazza San Felice 4, so my walk to the Accademia went straight down the spine of old Florence: past the Pitti, across the bridge, past Orsanmichele, between the Duomo and the Baptistery, and then up Via Ricasoli to Piazza San Marco. I saw Florence at street level in every possible condition, from empty dark winter evenings to sweltering summer days when the streets were packed with tourists. [4] You can of course paint people like still lives if you want to, and they're willing. That sort of portrait is arguably the apex of still life painting, though the long sitting does tend to produce pained expressions in the sitters. [5] Interleaf was one of many companies that had smart people and built impressive technology, and yet got crushed by Moore's Law. In the 1990s the exponential growth in the power of commodity (i.e. Intel) processors rolled up high-end, special-purpose hardware and software companies like a bulldozer. [6] The signature style seekers at RISD weren't specifically mercenary. In the art world, money and coolness are tightly coupled. Anything expensive comes to be seen as cool, and anything seen as cool will soon become equally expensive. [7] Technically the apartment wasn't rent-controlled but rent-stabilized, but this is a refinement only New Yorkers would know or care about. The point is that it was really cheap, less than half market price. [8] Most software you can launch as soon as it's done. But when the software is an online store builder and you're hosting the stores, if you don't have any users yet, that fact will be painfully obvious. So before we could launch publicly we had to launch privately, in the sense of recruiting an initial set of users and making sure they had decent-looking stores. [9] We'd had a code editor in Viaweb for users to define their own page styles. They didn't know it, but they were editing Lisp expressions underneath. But this wasn't an app editor, because the code ran when the merchants' sites were generated, not when shoppers visited them. [10] This was the first instance of what is now a familiar experience, and so was what happened next, when I read the comments and found they were full of angry people. How could I claim that Lisp was better than other languages? Weren't they all Turing complete? People who see the responses to essays I write sometimes tell me how sorry they feel for me, but I'm not exaggerating when I reply that it has always been like this, since the very beginning. It comes with the territory. An essay must tell readers things they don't already know, and some people dislike being told such things. [11] People put plenty of stuff on the internet in the 90s of course, but putting something online is not the same as publishing it online. Publishing online means you treat the online version as the (or at least a) primary version. [12] There is a general lesson here that our experience with Y Combinator also teaches: Customs continue to constrain you long after the restrictions that caused them have disappeared. Customary VC practice had once, like the customs about publishing essays, been based on real constraints. Startups had once been much more expensive to start, and proportionally rare.\"] nomic-ai/nomic-embed-text-v1.5 {'dimensions': 128}\n", + "show list of text ['file_path: data/paul_graham/paul_graham_essay.txt People who see the responses to essays I write sometimes tell me how sorry they feel for me, but I\\'m not exaggerating when I reply that it has always been like this, since the very beginning. It comes with the territory. An essay must tell readers things they don\\'t already know, and some people dislike being told such things. [11] People put plenty of stuff on the internet in the 90s of course, but putting something online is not the same as publishing it online. Publishing online means you treat the online version as the (or at least a) primary version. [12] There is a general lesson here that our experience with Y Combinator also teaches: Customs continue to constrain you long after the restrictions that caused them have disappeared. Customary VC practice had once, like the customs about publishing essays, been based on real constraints. Startups had once been much more expensive to start, and proportionally rare. Now they could be cheap and common, but the VCs\\' customs still reflected the old world, just as customs about writing essays still reflected the constraints of the print era. Which in turn implies that people who are independent-minded (i.e. less influenced by custom) will have an advantage in fields affected by rapid change (where customs are more likely to be obsolete). Here\\'s an interesting point, though: you can\\'t always predict which fields will be affected by rapid change. Obviously software and venture capital will be, but who would have predicted that essay writing would be? [13] Y Combinator was not the original name. At first we were called Cambridge Seed. But we didn\\'t want a regional name, in case someone copied us in Silicon Valley, so we renamed ourselves after one of the coolest tricks in the lambda calculus, the Y combinator. I picked orange as our color partly because it\\'s the warmest, and partly because no VC used it. In 2005 all the VCs used staid colors like maroon, navy blue, and forest green, because they were trying to appeal to LPs, not founders. The YC logo itself is an inside joke: the Viaweb logo had been a white V on a red circle, so I made the YC logo a white Y on an orange square. [14] YC did become a fund for a couple years starting in 2009, because it was getting so big I could no longer afford to fund it personally. But after Heroku got bought we had enough money to go back to being self-funded. [15] I\\'ve never liked the term \"deal flow,\" because it implies that the number of new startups at any given time is fixed. This is not only false, but it\\'s the purpose of YC to falsify it, by causing startups to be founded that would not otherwise have existed. [16] She reports that they were all different shapes and sizes, because there was a run on air conditioners and she had to get whatever she could, but that they were all heavier than she could carry now. [17] Another problem with HN was a bizarre edge case that occurs when you both write essays and run a forum. When you run a forum, you\\'re assumed to see if not every conversation, at least every conversation involving you. And when you write essays, people post highly imaginative misinterpretations of them on forums. Individually these two phenomena are tedious but bearable, but the combination is disastrous. You actually have to respond to the misinterpretations, because the assumption that you\\'re present in the conversation means that not responding to any sufficiently upvoted misinterpretation reads as a tacit admission that it\\'s correct. But that in turn encourages more; anyone who wants to pick a fight with you senses that now is their chance. [18] The worst thing about leaving YC was not working with Jessica anymore. We\\'d been working on YC almost the whole time we\\'d known each other, and we\\'d neither tried nor wanted to separate it from our personal lives, so leaving was like pulling up a deeply rooted tree. [19] One way to get more precise about the concept of invented vs discovered is to talk about space aliens. Any sufficiently advanced alien civilization would certainly know about the Pythagorean theorem, for example. I believe, though with less certainty, that they would also know about the Lisp in McCarthy\\'s 1960 paper. But if so there\\'s no reason to suppose that this is the limit of the language that might be known to them. Presumably aliens need numbers and errors and I/O too. So it seems likely there exists at least one path out of McCarthy\\'s Lisp along which discoveredness is preserved.', \"file_path: data/paul_graham/paul_graham_essay.txt [18] The worst thing about leaving YC was not working with Jessica anymore. We'd been working on YC almost the whole time we'd known each other, and we'd neither tried nor wanted to separate it from our personal lives, so leaving was like pulling up a deeply rooted tree. [19] One way to get more precise about the concept of invented vs discovered is to talk about space aliens. Any sufficiently advanced alien civilization would certainly know about the Pythagorean theorem, for example. I believe, though with less certainty, that they would also know about the Lisp in McCarthy's 1960 paper. But if so there's no reason to suppose that this is the limit of the language that might be known to them. Presumably aliens need numbers and errors and I/O too. So it seems likely there exists at least one path out of McCarthy's Lisp along which discoveredness is preserved. Thanks to Trevor Blackwell, John Collison, Patrick Collison, Daniel Gackle, Ralph Hazell, Jessica Livingston, Robert Morris, and Harj Taggar for reading drafts of this.\"] nomic-ai/nomic-embed-text-v1.5 {'dimensions': 128}\n" + ] + }, + { + "data": { + "text/markdown": [ + "The author, during their childhood and teenage years, worked on two main things outside of school: writing and programming. They started by writing short stories, which they describe as having hardly any plot, focusing more on characters with strong feelings. They began programming using an IBM 1401 computer in their junior high school's basement, where they wrote programs in an early version of Fortran, which were run using punch cards. However, they found it challenging due to the lack of input data and their limited mathematical knowledge. The advent of microcomputers significantly changed their experience with programming, making it more interactive and engaging. They received a TRS-80 microcomputer and wrote simple games, a program to predict model rocket flights, and a word processor. Despite their interest in programming, they initially planned to study philosophy in college, before switching to AI." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# save to disk\n", + "\n", + "db = chromadb.PersistentClient(path=\"./chroma_db\")\n", + "chroma_collection = db.get_or_create_collection(\"quickstart\")\n", + "vector_store = ChromaVectorStore(chroma_collection=chroma_collection)\n", + "storage_context = StorageContext.from_defaults(vector_store=vector_store)\n", + "\n", + "embed_model = FireworksEmbedding(\n", + " model_name=\"nomic-ai/nomic-embed-text-v1.5\",\n", + " api_base=\"https://api.fireworks.ai/inference/v1\",\n", + " dimensions=128,\n", + ")\n", + "index = VectorStoreIndex.from_documents(\n", + " documents, storage_context=storage_context, embed_model=embed_model\n", + ")\n", + "\n", + "# load from disk\n", + "db2 = chromadb.PersistentClient(path=\"./chroma_db\")\n", + "chroma_collection = db2.get_or_create_collection(\"quickstart\")\n", + "vector_store = ChromaVectorStore(chroma_collection=chroma_collection)\n", + "index = VectorStoreIndex.from_vector_store(\n", + " vector_store,\n", + " embed_model=embed_model,\n", + ")\n", + "\n", + "# Query Data from the persisted index\n", + "query_engine = index.as_query_engine(llm=llm)\n", + "response = query_engine.query(\"What did the author do growing up?\")\n", + "display(Markdown(f\"{response}\"))" + ] + }, + { + "cell_type": "markdown", + "id": "2f27a0a7", + "metadata": {}, + "source": [ + "You can see that the results are the same across the two, so you can experiment with the dimension sizes and then experiment with the cost and quality trade-off yourself." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "base", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/examples/vector_stores/MongoDBAtlasVectorSearchRAGFireworks.ipynb b/docs/examples/vector_stores/MongoDBAtlasVectorSearchRAGFireworks.ipynb new file mode 100644 index 0000000000000..f1c0db04e7472 --- /dev/null +++ b/docs/examples/vector_stores/MongoDBAtlasVectorSearchRAGFireworks.ipynb @@ -0,0 +1,956 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: llama-index in /mnt/disks/data/llama_index/.venv/lib/python3.10/site-packages (0.10.12)\n", + "Requirement already satisfied: llama-index-agent-openai<0.2.0,>=0.1.4 in /mnt/disks/data/llama_index/.venv/lib/python3.10/site-packages (from llama-index) (0.1.5)\n", + "Requirement already satisfied: llama-index-cli<0.2.0,>=0.1.2 in 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restaurant_idattributescuisineDogsAllowedembeddingOutdoorSeatingboroughaddress_idnamemenuTakeOutlocationPriceRangeHappyHourreview_countsponsoredstars
040366661{'Alcohol': ''none'', 'Ambience': '{'romantic'...Tex-MexNone[-0.14520384, 0.018315623, -0.018330636, -0.10...TrueManhattan{'building': '627', 'coord': [-73.975980999999...{'$oid': '6095a34a7c34416a90d3206b'}Baby Bo'S BurritosNoneTrue{'coordinates': [-73.97598099999999, 40.745132...1.0None10NaN2.5
140367442{'Alcohol': ''beer_and_wine'', 'Ambience': '{'...AmericanTrue[-0.11977468, -0.02157107, 0.0038846824, -0.09...TrueStaten Island{'building': '17', 'coord': [-74.1350211, 40.6...{'$oid': '6095a34a7c34416a90d3209e'}Buddy'S Wonder Bar[Grilled cheese sandwich, Baked potato, Lasagn...True{'coordinates': [-74.1350211, 40.6369042], 'ty...2.0None62NaN3.5
240364610{'Alcohol': ''none'', 'Ambience': '{'touristy'...AmericanNone[-0.1004329, -0.014882699, -0.033005167, -0.09...TrueStaten Island{'building': '37', 'coord': [-74.138263, 40.54...{'$oid': '6095a34a7c34416a90d31ff6'}Great Kills Yacht Club[Mozzarella sticks, Mushroom swiss burger, Spi...True{'coordinates': [-74.138263, 40.546681], 'type...1.0None72NaN4.0
340365288{'Alcohol': None, 'Ambience': '{'touristy': Fa...AmericanNone[-0.11735515, -0.0397448, -0.0072645755, -0.09...TrueManhattan{'building': '842', 'coord': [-73.970637000000...{'$oid': '6095a34a7c34416a90d32017'}Keats Restaurant[French fries, Chicken pot pie, Mac & cheese, ...True{'coordinates': [-73.97063700000001, 40.751495...2.0True149NaN4.0
440363151{'Alcohol': None, 'Ambience': None, 'BYOB': No...BakeryNone[-0.096541286, -0.009661355, 0.04402167, -0.12...TrueManhattan{'building': '120', 'coord': [-73.9998042, 40....{'$oid': '6095a34a7c34416a90d31fbd'}Olive'S[doughnuts, chocolate chip cookies, chocolate ...True{'coordinates': [-73.9998042, 40.7251256], 'ty...1.0None7NaN5.0
\n", + "
" + ], + "text/plain": [ + " restaurant_id attributes cuisine \\\n", + "0 40366661 {'Alcohol': ''none'', 'Ambience': '{'romantic'... Tex-Mex \n", + "1 40367442 {'Alcohol': ''beer_and_wine'', 'Ambience': '{'... American \n", + "2 40364610 {'Alcohol': ''none'', 'Ambience': '{'touristy'... American \n", + "3 40365288 {'Alcohol': None, 'Ambience': '{'touristy': Fa... American \n", + "4 40363151 {'Alcohol': None, 'Ambience': None, 'BYOB': No... Bakery \n", + "\n", + " DogsAllowed embedding \\\n", + "0 None [-0.14520384, 0.018315623, -0.018330636, -0.10... \n", + "1 True [-0.11977468, -0.02157107, 0.0038846824, -0.09... \n", + "2 None [-0.1004329, -0.014882699, -0.033005167, -0.09... \n", + "3 None [-0.11735515, -0.0397448, -0.0072645755, -0.09... \n", + "4 None [-0.096541286, -0.009661355, 0.04402167, -0.12... \n", + "\n", + " OutdoorSeating borough \\\n", + "0 True Manhattan \n", + "1 True Staten Island \n", + "2 True Staten Island \n", + "3 True Manhattan \n", + "4 True Manhattan \n", + "\n", + " address \\\n", + "0 {'building': '627', 'coord': [-73.975980999999... \n", + "1 {'building': '17', 'coord': [-74.1350211, 40.6... \n", + "2 {'building': '37', 'coord': [-74.138263, 40.54... \n", + "3 {'building': '842', 'coord': [-73.970637000000... \n", + "4 {'building': '120', 'coord': [-73.9998042, 40.... \n", + "\n", + " _id name \\\n", + "0 {'$oid': '6095a34a7c34416a90d3206b'} Baby Bo'S Burritos \n", + "1 {'$oid': '6095a34a7c34416a90d3209e'} Buddy'S Wonder Bar \n", + "2 {'$oid': '6095a34a7c34416a90d31ff6'} Great Kills Yacht Club \n", + "3 {'$oid': '6095a34a7c34416a90d32017'} Keats Restaurant \n", + "4 {'$oid': '6095a34a7c34416a90d31fbd'} Olive'S \n", + "\n", + " menu TakeOut \\\n", + "0 None True \n", + "1 [Grilled cheese sandwich, Baked potato, Lasagn... True \n", + "2 [Mozzarella sticks, Mushroom swiss burger, Spi... True \n", + "3 [French fries, Chicken pot pie, Mac & cheese, ... True \n", + "4 [doughnuts, chocolate chip cookies, chocolate ... True \n", + "\n", + " location PriceRange HappyHour \\\n", + "0 {'coordinates': [-73.97598099999999, 40.745132... 1.0 None \n", + "1 {'coordinates': [-74.1350211, 40.6369042], 'ty... 2.0 None \n", + "2 {'coordinates': [-74.138263, 40.546681], 'type... 1.0 None \n", + "3 {'coordinates': [-73.97063700000001, 40.751495... 2.0 True \n", + "4 {'coordinates': [-73.9998042, 40.7251256], 'ty... 1.0 None \n", + "\n", + " review_count sponsored stars \n", + "0 10 NaN 2.5 \n", + "1 62 NaN 3.5 \n", + "2 72 NaN 4.0 \n", + "3 149 NaN 4.0 \n", + "4 7 NaN 5.0 " + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from datasets import load_dataset\n", + "import pandas as pd\n", + "\n", + "# https://huggingface.co/datasets/AIatMongoDB/whatscooking.restaurants\n", + "dataset = load_dataset(\"AIatMongoDB/whatscooking.restaurants\")\n", + "\n", + "# Convert the dataset to a pandas dataframe\n", + "dataset_df = pd.DataFrame(dataset[\"train\"])\n", + "\n", + "dataset_df.head(5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Remove data point where fullplot coloumn is missing\n", + "# dataset_df = dataset_df.dropna(subset=[\"fullplot\"])\n", + "# print(\"\\nNumber of missing values in each column after removal:\")\n", + "# print(dataset_df.isnull().sum())\n", + "\n", + "# # Remove the plot_embedding from each data point in the dataset as we are going to create new embeddings with the new OpenAI emebedding Model \"text-embedding-3-small\"\n", + "# dataset_df = dataset_df.drop(columns=[\"plot_embedding\"])\n", + "\n", + "# dataset_df.head(5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from llama_index.core.settings import Settings\n", + "from llama_index.llms.fireworks import Fireworks\n", + "from llama_index.embeddings.fireworks import FireworksEmbedding\n", + "\n", + "embed_model = FireworksEmbedding(\n", + " embed_batch_size=1024,\n", + " model_name=\"nomic-ai/nomic-embed-text-v1.5\",\n", + " api_key=fw_api_key,\n", + ")\n", + "llm = Fireworks(\n", + " temperature=0,\n", + " model=\"accounts/fireworks/models/mixtral-8x7b-instruct\",\n", + " api_key=fw_api_key,\n", + ")\n", + "\n", + "Settings.llm = llm\n", + "Settings.embed_model = embed_model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "The LLM sees this: \n", + " Metadata: restaurant_id=>40366661\n", + "attributes=>{\"Alcohol\": \"'none'\", \"Ambience\": \"{'romantic': False, 'intimate': False, 'classy': False, 'hipster': False, 'divey': False, 'touristy': False, 'trendy': False, 'upscale': False, 'casual': False}\", \"BYOB\": null, \"BestNights\": null, \"BikeParking\": null, \"BusinessAcceptsBitcoin\": null, \"BusinessAcceptsCreditCards\": null, \"BusinessParking\": \"None\", \"Caters\": \"True\", \"DriveThru\": null, \"GoodForDancing\": null, \"GoodForKids\": \"True\", \"GoodForMeal\": null, \"HasTV\": \"True\", \"Music\": null, \"NoiseLevel\": \"'average'\", \"RestaurantsAttire\": \"'casual'\", \"RestaurantsDelivery\": \"True\", \"RestaurantsGoodForGroups\": \"True\", \"RestaurantsReservations\": \"True\", \"RestaurantsTableService\": \"False\", \"WheelchairAccessible\": \"True\", \"WiFi\": \"'free'\"}\n", + "cuisine=>\"Tex-Mex\"\n", + "DogsAllowed=>None\n", + "OutdoorSeating=>True\n", + "borough=>\"Manhattan\"\n", + "address=>{\"building\": \"627\", \"coord\": [-73.975981, 40.745132], \"street\": \"2 Avenue\", \"zipcode\": \"10016\"}\n", + "_id=>{'$oid': '6095a34a7c34416a90d3206b'}\n", + "name=>\"Baby Bo'S Burritos\"\n", + "menu=>null\n", + "TakeOut=>True\n", + "location=>{'coordinates': [-73.975981, 40.745132], 'type': 'Point'}\n", + "PriceRange=>1.0\n", + "HappyHour=>null\n", + "review_count=>10\n", + "sponsored=>None\n", + "stars=>2.5\n", + "-----\n", + "Content: {\"restaurant_id\": \"40366661\", \"attributes\": \"{\\\"Alcohol\\\": \\\"'none'\\\", \\\"Ambience\\\": \\\"{'romantic': False, 'intimate': False, 'classy': False, 'hipster': False, 'divey': False, 'touristy': False, 'trendy': False, 'upscale': False, 'casual': False}\\\", \\\"BYOB\\\": null, \\\"BestNights\\\": null, \\\"BikeParking\\\": null, \\\"BusinessAcceptsBitcoin\\\": null, \\\"BusinessAcceptsCreditCards\\\": null, \\\"BusinessParking\\\": \\\"None\\\", \\\"Caters\\\": \\\"True\\\", \\\"DriveThru\\\": null, \\\"GoodForDancing\\\": null, \\\"GoodForKids\\\": \\\"True\\\", \\\"GoodForMeal\\\": null, \\\"HasTV\\\": \\\"True\\\", \\\"Music\\\": null, \\\"NoiseLevel\\\": \\\"'average'\\\", \\\"RestaurantsAttire\\\": \\\"'casual'\\\", \\\"RestaurantsDelivery\\\": \\\"True\\\", \\\"RestaurantsGoodForGroups\\\": \\\"True\\\", \\\"RestaurantsReservations\\\": \\\"True\\\", \\\"RestaurantsTableService\\\": \\\"False\\\", \\\"WheelchairAccessible\\\": \\\"True\\\", \\\"WiFi\\\": \\\"'free'\\\"}\", \"cuisine\": \"\\\"Tex-Mex\\\"\", \"DogsAllowed\": null, \"OutdoorSeating\": true, \"borough\": \"\\\"Manhattan\\\"\", \"address\": \"{\\\"building\\\": \\\"627\\\", \\\"coord\\\": [-73.975981, 40.745132], \\\"street\\\": \\\"2 Avenue\\\", \\\"zipcode\\\": \\\"10016\\\"}\", \"_id\": {\"$oid\": \"6095a34a7c34416a90d3206b\"}, \"name\": \"\\\"Baby Bo'S Burritos\\\"\", \"menu\": \"null\", \"TakeOut\": true, \"location\": {\"coordinates\": [-73.975981, 40.745132], \"type\": \"Point\"}, \"PriceRange\": \"1.0\", \"HappyHour\": \"null\", \"review_count\": \"10\", \"sponsored\": null, \"stars\": 2.5}\n", + "\n", + "The Embedding model sees this: \n", + " Metadata: restaurant_id=>40366661\n", + "attributes=>{\"Alcohol\": \"'none'\", \"Ambience\": \"{'romantic': False, 'intimate': False, 'classy': False, 'hipster': False, 'divey': False, 'touristy': False, 'trendy': False, 'upscale': False, 'casual': False}\", \"BYOB\": null, \"BestNights\": null, \"BikeParking\": null, \"BusinessAcceptsBitcoin\": null, \"BusinessAcceptsCreditCards\": null, \"BusinessParking\": \"None\", \"Caters\": \"True\", \"DriveThru\": null, \"GoodForDancing\": null, \"GoodForKids\": \"True\", \"GoodForMeal\": null, \"HasTV\": \"True\", \"Music\": null, \"NoiseLevel\": \"'average'\", \"RestaurantsAttire\": \"'casual'\", \"RestaurantsDelivery\": \"True\", \"RestaurantsGoodForGroups\": \"True\", \"RestaurantsReservations\": \"True\", \"RestaurantsTableService\": \"False\", \"WheelchairAccessible\": \"True\", \"WiFi\": \"'free'\"}\n", + "cuisine=>\"Tex-Mex\"\n", + "DogsAllowed=>None\n", + "OutdoorSeating=>True\n", + "borough=>\"Manhattan\"\n", + "address=>{\"building\": \"627\", \"coord\": [-73.975981, 40.745132], \"street\": \"2 Avenue\", \"zipcode\": \"10016\"}\n", + "_id=>{'$oid': '6095a34a7c34416a90d3206b'}\n", + "name=>\"Baby Bo'S Burritos\"\n", + "menu=>null\n", + "TakeOut=>True\n", + "location=>{'coordinates': [-73.975981, 40.745132], 'type': 'Point'}\n", + "PriceRange=>1.0\n", + "HappyHour=>null\n", + "review_count=>10\n", + "sponsored=>None\n", + "stars=>2.5\n", + "-----\n", + "Content: {\"restaurant_id\": \"40366661\", \"attributes\": \"{\\\"Alcohol\\\": \\\"'none'\\\", \\\"Ambience\\\": \\\"{'romantic': False, 'intimate': False, 'classy': False, 'hipster': False, 'divey': False, 'touristy': False, 'trendy': False, 'upscale': False, 'casual': False}\\\", \\\"BYOB\\\": null, \\\"BestNights\\\": null, \\\"BikeParking\\\": null, \\\"BusinessAcceptsBitcoin\\\": null, \\\"BusinessAcceptsCreditCards\\\": null, \\\"BusinessParking\\\": \\\"None\\\", \\\"Caters\\\": \\\"True\\\", \\\"DriveThru\\\": null, \\\"GoodForDancing\\\": null, \\\"GoodForKids\\\": \\\"True\\\", \\\"GoodForMeal\\\": null, \\\"HasTV\\\": \\\"True\\\", \\\"Music\\\": null, \\\"NoiseLevel\\\": \\\"'average'\\\", \\\"RestaurantsAttire\\\": \\\"'casual'\\\", \\\"RestaurantsDelivery\\\": \\\"True\\\", \\\"RestaurantsGoodForGroups\\\": \\\"True\\\", \\\"RestaurantsReservations\\\": \\\"True\\\", \\\"RestaurantsTableService\\\": \\\"False\\\", \\\"WheelchairAccessible\\\": \\\"True\\\", \\\"WiFi\\\": \\\"'free'\\\"}\", \"cuisine\": \"\\\"Tex-Mex\\\"\", \"DogsAllowed\": null, \"OutdoorSeating\": true, \"borough\": \"\\\"Manhattan\\\"\", \"address\": \"{\\\"building\\\": \\\"627\\\", \\\"coord\\\": [-73.975981, 40.745132], \\\"street\\\": \\\"2 Avenue\\\", \\\"zipcode\\\": \\\"10016\\\"}\", \"_id\": {\"$oid\": \"6095a34a7c34416a90d3206b\"}, \"name\": \"\\\"Baby Bo'S Burritos\\\"\", \"menu\": \"null\", \"TakeOut\": true, \"location\": {\"coordinates\": [-73.975981, 40.745132], \"type\": \"Point\"}, \"PriceRange\": \"1.0\", \"HappyHour\": \"null\", \"review_count\": \"10\", \"sponsored\": null, \"stars\": 2.5}\n" + ] + } + ], + "source": [ + "import json\n", + "from llama_index.core import Document\n", + "from llama_index.core.schema import MetadataMode\n", + "\n", + "# Convert the DataFrame to a JSON string representation\n", + "documents_json = dataset_df.to_json(orient=\"records\")\n", + "# Load the JSON string into a Python list of dictionaries\n", + "documents_list = json.loads(documents_json)\n", + "\n", + "llama_documents = []\n", + "\n", + "for document in documents_list:\n", + " # Value for metadata must be one of (str, int, float, None)\n", + " document[\"name\"] = json.dumps(document[\"name\"])\n", + " document[\"cuisine\"] = json.dumps(document[\"cuisine\"])\n", + " document[\"attributes\"] = json.dumps(document[\"attributes\"])\n", + " document[\"menu\"] = json.dumps(document[\"menu\"])\n", + " document[\"borough\"] = json.dumps(document[\"borough\"])\n", + " document[\"address\"] = json.dumps(document[\"address\"])\n", + " document[\"PriceRange\"] = json.dumps(document[\"PriceRange\"])\n", + " document[\"HappyHour\"] = json.dumps(document[\"HappyHour\"])\n", + " document[\"review_count\"] = json.dumps(document[\"review_count\"])\n", + " del document[\"embedding\"]\n", + "\n", + " # Create a Document object with the text and excluded metadata for llm and embedding models\n", + " llama_document = Document(\n", + " text=json.dumps(document),\n", + " metadata=document,\n", + " # excluded_llm_metadata_keys=[\"embedding\"],\n", + " # excluded_embed_metadata_keys=[\n", + " # \"fullplot\",\n", + " # \"metacritic\",\n", + " # \"poster\",\n", + " # \"num_mflix_comments\",\n", + " # \"runtime\",\n", + " # \"rated\",\n", + " # ],\n", + " metadata_template=\"{key}=>{value}\",\n", + " text_template=\"Metadata: {metadata_str}\\n-----\\nContent: {content}\",\n", + " )\n", + "\n", + " llama_documents.append(llama_document)\n", + "\n", + "# Observing an example of what the LLM and Embedding model receive as input\n", + "print(\n", + " \"\\nThe LLM sees this: \\n\",\n", + " llama_documents[0].get_content(metadata_mode=MetadataMode.LLM),\n", + ")\n", + "print(\n", + " \"\\nThe Embedding model sees this: \\n\",\n", + " llama_documents[0].get_content(metadata_mode=MetadataMode.EMBED),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Document(id_='a4e02dc9-3370-4bbd-8207-b7cb84f802ea', embedding=None, metadata={'restaurant_id': '40366661', 'attributes': '{\"Alcohol\": \"\\'none\\'\", \"Ambience\": \"{\\'romantic\\': False, \\'intimate\\': False, \\'classy\\': False, \\'hipster\\': False, \\'divey\\': False, \\'touristy\\': False, \\'trendy\\': False, \\'upscale\\': False, \\'casual\\': False}\", \"BYOB\": null, \"BestNights\": null, \"BikeParking\": null, \"BusinessAcceptsBitcoin\": null, \"BusinessAcceptsCreditCards\": null, \"BusinessParking\": \"None\", \"Caters\": \"True\", \"DriveThru\": null, \"GoodForDancing\": null, \"GoodForKids\": \"True\", \"GoodForMeal\": null, \"HasTV\": \"True\", \"Music\": null, \"NoiseLevel\": \"\\'average\\'\", \"RestaurantsAttire\": \"\\'casual\\'\", \"RestaurantsDelivery\": \"True\", \"RestaurantsGoodForGroups\": \"True\", \"RestaurantsReservations\": \"True\", \"RestaurantsTableService\": \"False\", \"WheelchairAccessible\": \"True\", \"WiFi\": \"\\'free\\'\"}', 'cuisine': '\"Tex-Mex\"', 'DogsAllowed': None, 'OutdoorSeating': True, 'borough': '\"Manhattan\"', 'address': '{\"building\": \"627\", \"coord\": [-73.975981, 40.745132], \"street\": \"2 Avenue\", \"zipcode\": \"10016\"}', '_id': {'$oid': '6095a34a7c34416a90d3206b'}, 'name': '\"Baby Bo\\'S Burritos\"', 'menu': 'null', 'TakeOut': True, 'location': {'coordinates': [-73.975981, 40.745132], 'type': 'Point'}, 'PriceRange': '1.0', 'HappyHour': 'null', 'review_count': '10', 'sponsored': None, 'stars': 2.5}, excluded_embed_metadata_keys=[], excluded_llm_metadata_keys=[], relationships={}, text='{\"restaurant_id\": \"40366661\", \"attributes\": \"{\\\\\"Alcohol\\\\\": \\\\\"\\'none\\'\\\\\", \\\\\"Ambience\\\\\": \\\\\"{\\'romantic\\': False, \\'intimate\\': False, \\'classy\\': False, \\'hipster\\': False, \\'divey\\': False, \\'touristy\\': False, \\'trendy\\': False, \\'upscale\\': False, \\'casual\\': False}\\\\\", \\\\\"BYOB\\\\\": null, \\\\\"BestNights\\\\\": null, \\\\\"BikeParking\\\\\": null, \\\\\"BusinessAcceptsBitcoin\\\\\": null, \\\\\"BusinessAcceptsCreditCards\\\\\": null, \\\\\"BusinessParking\\\\\": \\\\\"None\\\\\", \\\\\"Caters\\\\\": \\\\\"True\\\\\", \\\\\"DriveThru\\\\\": null, \\\\\"GoodForDancing\\\\\": null, \\\\\"GoodForKids\\\\\": \\\\\"True\\\\\", \\\\\"GoodForMeal\\\\\": null, \\\\\"HasTV\\\\\": \\\\\"True\\\\\", \\\\\"Music\\\\\": null, \\\\\"NoiseLevel\\\\\": \\\\\"\\'average\\'\\\\\", \\\\\"RestaurantsAttire\\\\\": \\\\\"\\'casual\\'\\\\\", \\\\\"RestaurantsDelivery\\\\\": \\\\\"True\\\\\", \\\\\"RestaurantsGoodForGroups\\\\\": \\\\\"True\\\\\", \\\\\"RestaurantsReservations\\\\\": \\\\\"True\\\\\", \\\\\"RestaurantsTableService\\\\\": \\\\\"False\\\\\", \\\\\"WheelchairAccessible\\\\\": \\\\\"True\\\\\", \\\\\"WiFi\\\\\": \\\\\"\\'free\\'\\\\\"}\", \"cuisine\": \"\\\\\"Tex-Mex\\\\\"\", \"DogsAllowed\": null, \"OutdoorSeating\": true, \"borough\": \"\\\\\"Manhattan\\\\\"\", \"address\": \"{\\\\\"building\\\\\": \\\\\"627\\\\\", \\\\\"coord\\\\\": [-73.975981, 40.745132], \\\\\"street\\\\\": \\\\\"2 Avenue\\\\\", \\\\\"zipcode\\\\\": \\\\\"10016\\\\\"}\", \"_id\": {\"$oid\": \"6095a34a7c34416a90d3206b\"}, \"name\": \"\\\\\"Baby Bo\\'S Burritos\\\\\"\", \"menu\": \"null\", \"TakeOut\": true, \"location\": {\"coordinates\": [-73.975981, 40.745132], \"type\": \"Point\"}, \"PriceRange\": \"1.0\", \"HappyHour\": \"null\", \"review_count\": \"10\", \"sponsored\": null, \"stars\": 2.5}', start_char_idx=None, end_char_idx=None, text_template='Metadata: {metadata_str}\\n-----\\nContent: {content}', metadata_template='{key}=>{value}', metadata_seperator='\\n')" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "llama_documents[0]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from llama_index.core.node_parser import SentenceSplitter\n", + "\n", + "parser = SentenceSplitter()\n", + "nodes = parser.get_nodes_from_documents(llama_documents)\n", + "\n", + "# There are 25k documents, so we need to do batching. Fortunately LlamaIndex provides good batching\n", + "# for embedding models, and we are going to rely on the __call__ method for the model to handle this\n", + "node_embeddings = embed_model(nodes)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ensure your databse, collection and vector store index is setup on MongoDB Atlas for the collection or the following step won't work appropriately on MongoDB.\n", + "\n", + "\n", + " - For assistance with database cluster setup and obtaining the URI, refer to this [guide](https://www.mongodb.com/docs/guides/atlas/cluster/) for setting up a MongoDB cluster, and this [guide](https://www.mongodb.com/docs/guides/atlas/connection-string/) to get your connection string. \n", + "\n", + " - Once you have successfully created a cluster, create the database and collection within the MongoDB Atlas cluster by clicking “+ Create Database”. The database will be named movies, and the collection will be named movies_records.\n", + "\n", + " - Creating a vector search index within the movies_records collection is essential for efficient document retrieval from MongoDB into our development environment. To achieve this, refer to the official [guide](https://www.mongodb.com/docs/atlas/atlas-vector-search/create-index/) on vector search index creation.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Connection to MongoDB successful\n" + ] + } + ], + "source": [ + "import pymongo\n", + "from google.colab import userdata\n", + "\n", + "\n", + "def get_mongo_client(mongo_uri):\n", + " \"\"\"Establish connection to the MongoDB.\"\"\"\n", + " try:\n", + " client = pymongo.MongoClient(mongo_uri)\n", + " print(\"Connection to MongoDB successful\")\n", + " return client\n", + " except pymongo.errors.ConnectionFailure as e:\n", + " print(f\"Connection failed: {e}\")\n", + " return None\n", + "\n", + "\n", + "mongo_uri = userdata.get(\"MONGO_URI\")\n", + "if not mongo_uri:\n", + " print(\"MONGO_URI not set in environment variables\")\n", + "\n", + "mongo_client = get_mongo_client(mongo_uri)\n", + "\n", + "DB_NAME = \"movies\"\n", + "COLLECTION_NAME = \"movies_records\"\n", + "\n", + "db = mongo_client[DB_NAME]\n", + "collection = db[COLLECTION_NAME]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "DeleteResult({'n': 0, 'electionId': ObjectId('7fffffff000000000000000a'), 'opTime': {'ts': Timestamp(1708000722, 1), 't': 10}, 'ok': 1.0, '$clusterTime': {'clusterTime': Timestamp(1708000722, 1), 'signature': {'hash': b'\\xd8\\x1a\\xaci\\xf5EN+\\xe2\\xd1\\xb3y8.${u5P\\xf3', 'keyId': 7320226449804230661}}, 'operationTime': Timestamp(1708000722, 1)}, acknowledged=True)" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# To ensure we are working with a fresh collection\n", + "# delete any existing records in the collection\n", + "collection.delete_many({})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from llama_index.vector_stores.mongodb import MongoDBAtlasVectorSearch\n", + "\n", + "vector_store = MongoDBAtlasVectorSearch(\n", + " mongo_client,\n", + " db_name=DB_NAME,\n", + " collection_name=COLLECTION_NAME,\n", + " index_name=\"vector_index\",\n", + ")\n", + "vector_store.add(nodes)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from llama_index.core import VectorStoreIndex, StorageContext\n", + "\n", + "index = VectorStoreIndex.from_vector_store(vector_store)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/markdown": [ + "**`Final Response:`** The movie \"Romancing the Stone\" would be a suitable romantic movie for the Christmas season. It is a romantic adventure film that follows a romance writer who sets off on a dangerous adventure to rescue her kidnapped sister. The movie has elements of romance, adventure, and comedy, making it an entertaining choice for the holiday season. Additionally, the movie has received positive reviews and has been nominated for awards, indicating its quality." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NodeWithScore(node=TextNode(id_='c6bbc236-e21d-49ab-b43d-db920b4946e6', embedding=None, metadata={'awards': '{\"nominations\": 2, \"text\": \"Nominated for 1 Oscar. Another 6 wins & 2 nominations.\", \"wins\": 7}', 'metacritic': None, 'rated': 'PG', 'fullplot': \"Joan Wilder, a mousy romance novelist, receives a treasure map in the mail from her recently murdered brother-in-law. Meanwhile, her sister Elaine is kidnapped in Colombia and the two criminals responsible demand that she travel to Colombia to exchange the map for her sister. Joan does, and quickly becomes lost in the jungle after being waylayed by Zolo, a vicious and corrupt Colombian cop who will stop at nothing to obtain the map. There, she meets an irreverent soldier-of-fortune named Jack Colton who agrees to bring her back to civilization. Together, they embark upon an adventure that could be straight out of Joan's novels.\", 'title': 'Romancing the Stone', 'writers': '[\"Diane Thomas\"]', 'languages': '[\"English\", \"Spanish\", \"French\"]', 'plot': 'A romance writer sets off to Colombia to ransom her kidnapped sister, and soon finds herself in the middle of a dangerous adventure.', 'runtime': 106.0, 'countries': '[\"USA\", \"Mexico\"]', 'genres': '[\"Action\", \"Adventure\", \"Comedy\"]', 'directors': '[\"Robert Zemeckis\"]', 'cast': '[\"Michael Douglas\", \"Kathleen Turner\", \"Danny DeVito\", \"Zack Norman\"]', 'type': 'movie', 'imdb': '{\"id\": 88011, \"rating\": 6.9, \"votes\": 59403}', 'poster': 'https://m.media-amazon.com/images/M/MV5BMDAwNjljMzEtMTc3Yy00NDg2LThjNDAtNjc0NGYyYjM2M2I1XkEyXkFqcGdeQXVyNDE5MTU2MDE@._V1_SY1000_SX677_AL_.jpg', 'num_mflix_comments': 0}, excluded_embed_metadata_keys=['fullplot', 'metacritic', 'poster', 'num_mflix_comments', 'runtime', 'rated'], excluded_llm_metadata_keys=['fullplot', 'metacritic'], relationships={: RelatedNodeInfo(node_id='e50144b0-96ba-4a5a-b90a-3a2419f5b380', node_type=, metadata={'awards': '{\"nominations\": 2, \"text\": \"Nominated for 1 Oscar. 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When Pete finally falls for her and she turns down Jefty\\'s marriage proposal, they must face Jefty\\'s murderous jealousy and his twisted plots to \"punish\" the two.', 'title': 'Road House', 'writers': '[\"Edward Chodorov (screen play)\", \"Margaret Gruen (story)\", \"Oscar Saul (story)\"]', 'languages': '[\"English\"]', 'plot': 'A night club owner becomes infatuated with a torch singer and frames his best friend/manager for embezzlement when the chanteuse falls in love with him.', 'runtime': 95.0, 'countries': '[\"USA\"]', 'genres': '[\"Action\", \"Drama\", \"Film-Noir\"]', 'directors': '[\"Jean Negulesco\"]', 'cast': '[\"Ida Lupino\", \"Cornel Wilde\", \"Celeste Holm\", \"Richard Widmark\"]', 'type': 'movie', 'imdb': '{\"id\": 40740, \"rating\": 7.3, \"votes\": 1353}', 'poster': 'https://m.media-amazon.com/images/M/MV5BMjc1ZTNkM2UtYzY3Yi00ZWZmLTljYmEtNjYxZDNmYzk2ZjkzXkEyXkFqcGdeQXVyMjUxODE0MDY@._V1_SY1000_SX677_AL_.jpg', 'num_mflix_comments': 2}, hash='040b4a77fcc8fbb5347620e99a217d67b85dcdbd370d91bd23877722a499079f'), : RelatedNodeInfo(node_id='75f37fbc-d75e-4a76-b86f-f15d9260afd1', node_type=, metadata={}, hash='9941706d03783561f3fc3200c26527493a62307f8532dcda60b20948c886b330')}, text=\"Dick Powell stars as Haven, a government private investigator assigned to investigate the murders of two cavalrymen. Travelling incognito, Haven arrives in a small frontier outpost, where saloon singer Charlie controls all illegal activities. After making short work of Charlie's burly henchman, Haven gets a job at her gambling emporium, biding his time and gathering evidence against the gorgeous crime chieftain Cast as a philosophical bartender, Burl Ives is afforded at least one opportunity to sing.\", start_char_idx=0, end_char_idx=505, text_template='Metadata: {metadata_str}\\n-----\\nContent: {content}', metadata_template='{key}=>{value}', metadata_seperator='\\n'), score=0.7337073087692261)]\n" + ] + } + ], + "source": [ + "import pprint\n", + "from llama_index.core.response.notebook_utils import display_response\n", + "\n", + "query_engine = index.as_query_engine(similarity_top_k=3)\n", + "\n", + "query = \"Recommend a restaurants suitable for the christmas season and justify your selecton\"\n", + "\n", + "response = query_engine.query(query)\n", + "display_response(response)\n", + "pprint.pprint(response.source_nodes)" + ] + } + ], + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} From f494c0f08da8fb12a7d510aa1980a7a33eb81e42 Mon Sep 17 00:00:00 2001 From: Logan Date: Fri, 23 Feb 2024 23:16:44 -0600 Subject: [PATCH 16/30] Logan/updates (#11342) --- .../llama-index-embeddings-fastembed/pyproject.toml | 2 +- .../llama-index-embeddings-fireworks/pyproject.toml | 3 ++- .../llama-index-embeddings-instructor/pyproject.toml | 2 +- .../llms/llama-index-llms-maritalk/pyproject.toml | 2 +- .../llms/llama-index-llms-mymagic/pyproject.toml | 2 +- .../llama-index-postprocessor-colbert-rerank/pyproject.toml | 5 +++-- .../llama-index-vector-stores-milvus/pyproject.toml | 2 +- 7 files changed, 10 insertions(+), 8 deletions(-) diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-fastembed/pyproject.toml b/llama-index-integrations/embeddings/llama-index-embeddings-fastembed/pyproject.toml index e43bf035ece9e..0537c369a6d9a 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-fastembed/pyproject.toml +++ b/llama-index-integrations/embeddings/llama-index-embeddings-fastembed/pyproject.toml @@ -27,7 +27,7 @@ exclude = ["**/BUILD"] license = "MIT" name = "llama-index-embeddings-fastembed" readme = "README.md" -version = "0.1.3" +version = "0.1.4" [tool.poetry.dependencies] python = ">=3.8.1,<3.12" diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-fireworks/pyproject.toml b/llama-index-integrations/embeddings/llama-index-embeddings-fireworks/pyproject.toml index 4eb400aa05e7b..36189597d5196 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-fireworks/pyproject.toml +++ b/llama-index-integrations/embeddings/llama-index-embeddings-fireworks/pyproject.toml @@ -23,10 +23,11 @@ python_version = "3.8" [tool.poetry] authors = ["benjibc"] description = "llama-index embeddings fireworks integration" +exclude = ["**/BUILD"] license = "MIT" name = "llama-index-embeddings-fireworks" readme = "README.md" -version = "0.1.1" +version = "0.1.2" [tool.poetry.dependencies] python = ">=3.8.1,<3.12" diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-instructor/pyproject.toml b/llama-index-integrations/embeddings/llama-index-embeddings-instructor/pyproject.toml index f4ccf427091d5..6555b8215e797 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-instructor/pyproject.toml +++ b/llama-index-integrations/embeddings/llama-index-embeddings-instructor/pyproject.toml @@ -27,7 +27,7 @@ exclude = ["**/BUILD"] license = "MIT" name = "llama-index-embeddings-instructor" readme = "README.md" -version = "0.1.2" +version = "0.1.3" [tool.poetry.dependencies] python = ">=3.8.1,<4.0" diff --git a/llama-index-integrations/llms/llama-index-llms-maritalk/pyproject.toml b/llama-index-integrations/llms/llama-index-llms-maritalk/pyproject.toml index 6c1909dbc5827..7724410818352 100644 --- a/llama-index-integrations/llms/llama-index-llms-maritalk/pyproject.toml +++ b/llama-index-integrations/llms/llama-index-llms-maritalk/pyproject.toml @@ -30,7 +30,7 @@ license = "MIT" name = "llama-index-llms-maritalk" packages = [{include = "llama_index/"}] readme = "README.md" -version = "0.1.0" +version = "0.1.1" [tool.poetry.dependencies] python = ">=3.8.1,<3.12" diff --git a/llama-index-integrations/llms/llama-index-llms-mymagic/pyproject.toml b/llama-index-integrations/llms/llama-index-llms-mymagic/pyproject.toml index 7cf3aba5d42c7..a5450ebf56ecf 100644 --- a/llama-index-integrations/llms/llama-index-llms-mymagic/pyproject.toml +++ b/llama-index-integrations/llms/llama-index-llms-mymagic/pyproject.toml @@ -27,7 +27,7 @@ exclude = ["**/BUILD"] license = "MIT" name = "llama-index-llms-mymagic" readme = "README.md" -version = "0.1.2" +version = "0.1.3" [tool.poetry.dependencies] python = ">=3.8.1,<4.0" diff --git a/llama-index-integrations/postprocessor/llama-index-postprocessor-colbert-rerank/pyproject.toml b/llama-index-integrations/postprocessor/llama-index-postprocessor-colbert-rerank/pyproject.toml index cc2f631cc4846..8c7f0176a4ae5 100644 --- a/llama-index-integrations/postprocessor/llama-index-postprocessor-colbert-rerank/pyproject.toml +++ b/llama-index-integrations/postprocessor/llama-index-postprocessor-colbert-rerank/pyproject.toml @@ -26,14 +26,15 @@ python_version = "3.8" [tool.poetry] authors = ["Your Name "] description = "llama-index postprocessor colbert-rerank integration" +exclude = ["**/BUILD"] license = "MIT" name = "llama-index-postprocessor-colbert-rerank" packages = [{include = "llama_index/"}] readme = "README.md" -version = "0.1.0" +version = "0.1.1" [tool.poetry.dependencies] -python = ">=3.8.1,<3.12" +python = ">=3.8.1,<4.0" llama-index-core = "^0.10.0" torch = "^2.2.0" transformers = "^4.37.2" diff --git a/llama-index-integrations/vector_stores/llama-index-vector-stores-milvus/pyproject.toml b/llama-index-integrations/vector_stores/llama-index-vector-stores-milvus/pyproject.toml index 189b0cd02dbd4..0787ba564778f 100644 --- a/llama-index-integrations/vector_stores/llama-index-vector-stores-milvus/pyproject.toml +++ b/llama-index-integrations/vector_stores/llama-index-vector-stores-milvus/pyproject.toml @@ -27,7 +27,7 @@ exclude = ["**/BUILD"] license = "MIT" name = "llama-index-vector-stores-milvus" readme = "README.md" -version = "0.1.2" +version = "0.1.3" [tool.poetry.dependencies] python = ">=3.8.1,<4.0" From 112468d052b8bd60dc019ed4fc6d9db48de4687f Mon Sep 17 00:00:00 2001 From: Dale McDiarmid Date: Sat, 24 Feb 2024 05:35:18 +0000 Subject: [PATCH 17/30] fix clickhouse vector store in hub (#10986) --- .../llama-index-vector-stores-clickhouse/pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/llama-index-integrations/vector_stores/llama-index-vector-stores-clickhouse/pyproject.toml b/llama-index-integrations/vector_stores/llama-index-vector-stores-clickhouse/pyproject.toml index 354147d338b71..3989d9967b141 100644 --- a/llama-index-integrations/vector_stores/llama-index-vector-stores-clickhouse/pyproject.toml +++ b/llama-index-integrations/vector_stores/llama-index-vector-stores-clickhouse/pyproject.toml @@ -12,7 +12,7 @@ contains_example = false import_path = "llama_index.vector_stores.clickhouse" [tool.llamahub.class_authors] -ClickHouseVectorStore = "llama-index" +ClickHouseVectorStore = "ClickHouse" [tool.mypy] disallow_untyped_defs = true From 1723277022c7e135e8544d2c6b439d5930fcb4d3 Mon Sep 17 00:00:00 2001 From: Ishan <345ishaan@gmail.com> Date: Fri, 23 Feb 2024 21:45:38 -0800 Subject: [PATCH 18/30] Add Tool for hierarchical finance agent (#10924) --- .../llama-index-tools-finance/.gitignore | 153 + .../tools/llama-index-tools-finance/BUILD | 4 + .../tools/llama-index-tools-finance/Makefile | 17 + .../tools/llama-index-tools-finance/README.md | 62 + .../examples/finance_agent.ipynb | 112 + .../llama_index/tools/finance/BUILD | 1 + .../llama_index/tools/finance/__init__.py | 6 + .../llama_index/tools/finance/base.py | 167 + .../llama_index/tools/finance/comparisons.py | 29 + .../llama_index/tools/finance/earnings.py | 81 + .../llama_index/tools/finance/news.py | 195 + .../llama_index/tools/finance/util.py | 29 + .../llama-index-tools-finance/poetry.lock | 4782 +++++++++++++++++ .../llama-index-tools-finance/pyproject.toml | 57 + .../llama-index-tools-finance/tests/BUILD | 1 + .../tests/__init__.py | 0 .../tests/test_finance_tools.py | 7 + 17 files changed, 5703 insertions(+) create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/.gitignore create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/BUILD create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/Makefile create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/README.md create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/examples/finance_agent.ipynb create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/BUILD create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/__init__.py create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/comparisons.py create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/earnings.py create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/news.py create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/util.py create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/poetry.lock create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/pyproject.toml create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/tests/BUILD create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/tests/__init__.py create mode 100644 llama-index-integrations/tools/llama-index-tools-finance/tests/test_finance_tools.py diff --git a/llama-index-integrations/tools/llama-index-tools-finance/.gitignore b/llama-index-integrations/tools/llama-index-tools-finance/.gitignore new file mode 100644 index 0000000000000..990c18de22908 --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/.gitignore @@ -0,0 +1,153 @@ +llama_index/_static +.DS_Store +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +bin/ +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +etc/ +include/ +lib/ +lib64/ +parts/ +sdist/ +share/ +var/ +wheels/ +pip-wheel-metadata/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +.ruff_cache + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +target/ + +# Jupyter Notebook +.ipynb_checkpoints +notebooks/ + +# IPython +profile_default/ +ipython_config.py + +# pyenv +.python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ +pyvenv.cfg + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# Jetbrains +.idea +modules/ +*.swp + +# VsCode +.vscode + +# pipenv +Pipfile +Pipfile.lock + +# pyright +pyrightconfig.json diff --git a/llama-index-integrations/tools/llama-index-tools-finance/BUILD b/llama-index-integrations/tools/llama-index-tools-finance/BUILD new file mode 100644 index 0000000000000..dd7fb98b2574f --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/BUILD @@ -0,0 +1,4 @@ +poetry_requirements( + name="poetry", + module_mapping={"newsapi-python": ["newsapi"]} +) diff --git a/llama-index-integrations/tools/llama-index-tools-finance/Makefile b/llama-index-integrations/tools/llama-index-tools-finance/Makefile new file mode 100644 index 0000000000000..b9eab05aa3706 --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/Makefile @@ -0,0 +1,17 @@ +GIT_ROOT ?= $(shell git rev-parse --show-toplevel) + +help: ## Show all Makefile targets. + @grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[33m%-30s\033[0m %s\n", $$1, $$2}' + +format: ## Run code autoformatters (black). + pre-commit install + git ls-files | xargs pre-commit run black --files + +lint: ## Run linters: pre-commit (black, ruff, codespell) and mypy + pre-commit install && git ls-files | xargs pre-commit run --show-diff-on-failure --files + +test: ## Run tests via pytest. + pytest tests + +watch-docs: ## Build and watch documentation. + sphinx-autobuild docs/ docs/_build/html --open-browser --watch $(GIT_ROOT)/llama_index/ diff --git a/llama-index-integrations/tools/llama-index-tools-finance/README.md b/llama-index-integrations/tools/llama-index-tools-finance/README.md new file mode 100644 index 0000000000000..579dc78eb14a3 --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/README.md @@ -0,0 +1,62 @@ +# Finance Agent Tool + +This tool connects to various open finance apis and libraries to gather news, earnings information and doing fundamental analysis. + +To use this tool, you'll need a few API keys: + +- POLYGON_API_KEY -- +- FINNHUB_API_KEY -- +- ALPHA_VANTAGE_API_KEY -- +- NEWSAPI_API_KEY -- + +## Installation + +``` +pip install llama-index-tools-finance +``` + +## Usage + +```python +from llama_index.agent.openai import OpenAIAgent +from llama_index.llms.openai import OpenAI +from llama_index.tools.finance import FinanceAgentToolSpec + +POLYGON_API_KEY = "" +FINNHUB_API_KEY = "" +ALPHA_VANTAGE_API_KEY = "" +NEWSAPI_API_KEY = "" +OPENAI_API_KEY = "" + +GPT_MODEL_NAME = "gpt-4-0613" + + +def create_agent( + polygon_api_key: str, + finnhub_api_key: str, + alpha_vantage_api_key: str, + newsapi_api_key: str, + openai_api_key: str, +) -> OpenAIAgent: + tool_spec = FinanceAgentToolSpec( + polygon_api_key, + finnhub_api_key, + alpha_vantage_api_key, + newsapi_api_key, + ) + llm = OpenAI(temperature=0, model=GPT_MODEL_NAME, api_key=openai_api_key) + return OpenAIAgent.from_tools( + tool_spec.to_tool_list(), llm=llm, verbose=True + ) + + +agent = create_agent( + POLYGON_API_KEY, + FINNHUB_API_KEY, + ALPHA_VANTAGE_API_KEY, + NEWSAPI_API_KEY, + OPENAI_API_KEY, +) + +response = agent.chat("What happened to AAPL stock on February 19th, 2024?") +``` diff --git a/llama-index-integrations/tools/llama-index-tools-finance/examples/finance_agent.ipynb b/llama-index-integrations/tools/llama-index-tools-finance/examples/finance_agent.ipynb new file mode 100644 index 0000000000000..c530f69680d48 --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/examples/finance_agent.ipynb @@ -0,0 +1,112 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Finance Agent Tool Spec\n", + "\n", + "This tool connects to various open finance apis and libraries to gather news, earnings information and doing fundamental analysis.\n", + "\n", + "To use this tool, you'll need a few API keys:\n", + "\n", + "- POLYGON_API_KEY -- \n", + "- FINNHUB_API_KEY -- \n", + "- ALPHA_VANTAGE_API_KEY -- \n", + "- NEWSAPI_API_KEY -- " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Installation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "!pip install llama-index-tools-finance" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Usage" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from llama_index.agent.openai import OpenAIAgent\n", + "from llama_index.llms.openai import OpenAI\n", + "from llama_index.tools.finance import FinanceAgentToolSpec\n", + "\n", + "POLYGON_API_KEY = \"\"\n", + "FINNHUB_API_KEY = \"\"\n", + "ALPHA_VANTAGE_API_KEY = \"\"\n", + "NEWSAPI_API_KEY = \"\"\n", + "OPENAI_API_KEY = \"\"\n", + "\n", + "GPT_MODEL_NAME = \"gpt-4-0613\"\n", + "\n", + "\n", + "def create_agent(\n", + " polygon_api_key: str,\n", + " finnhub_api_key: str,\n", + " alpha_vantage_api_key: str,\n", + " newsapi_api_key: str,\n", + " openai_api_key: str,\n", + ") -> OpenAIAgent:\n", + " tool_spec = FinanceAgentToolSpec(\n", + " polygon_api_key, finnhub_api_key, alpha_vantage_api_key, newsapi_api_key\n", + " )\n", + " llm = OpenAI(temperature=0, model=GPT_MODEL_NAME, api_key=openai_api_key)\n", + " return OpenAIAgent.from_tools(tool_spec.to_tool_list(), llm=llm, verbose=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "agent = create_agent(\n", + " POLYGON_API_KEY,\n", + " FINNHUB_API_KEY,\n", + " ALPHA_VANTAGE_API_KEY,\n", + " NEWSAPI_API_KEY,\n", + " OPENAI_API_KEY,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "response = agent.chat(\"What happened to AAPL stock on February 19th, 2024?\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "llama-index-4aB9_5sa-py3.10", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/BUILD b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/BUILD new file mode 100644 index 0000000000000..db46e8d6c978c --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/BUILD @@ -0,0 +1 @@ +python_sources() diff --git a/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/__init__.py b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/__init__.py new file mode 100644 index 0000000000000..aa93264230df1 --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/__init__.py @@ -0,0 +1,6 @@ +## init +from llama_index.tools.finance.base import ( + FinanceAgentToolSpec, +) + +__all__ = ["FinanceAgentToolSpec"] diff --git a/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py new file mode 100644 index 0000000000000..ea2aaf4084799 --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/base.py @@ -0,0 +1,167 @@ +from typing import List, Optional, Any, Dict + +import pandas as pd + +from llama_index.tools.finance import comparisons, earnings, news +from llama_index.core.tools.tool_spec.base import BaseToolSpec + + +class FinanceAgentToolSpec(BaseToolSpec): + spec_functions = [ + "find_similar_companies", + "get_earnings_history", + "get_stocks_with_upcoming_earnings", + "get_current_gainer_stocks", + "get_current_loser_stocks", + "get_current_undervalued_growth_stocks", + "get_current_technology_growth_stocks", + "get_current_most_traded_stocks", + "get_current_undervalued_large_cap_stocks", + "get_current_aggressive_small_cap_stocks", + "get_trending_finance_news", + "get_google_trending_searches", + "get_google_trends_for_query", + "get_latest_news_for_stock", + "get_current_stock_price_info", + ] + + def __init__( + self, + polygon_api_key: str, + finnhub_api_key: str, + alpha_vantage_api_key: str, + newsapi_api_key: str, + ): + self._api_key = { + "ALPHA_VANTAGE": alpha_vantage_api_key, + "POLYGON": polygon_api_key, + "FINNHUB": finnhub_api_key, + "NEWSAPI": newsapi_api_key, + } + + def find_similar_companies(self, symbol: str) -> List[str]: + """Given a stock's ticker symbol, returns a list of similar companies.""" + return comparisons.find_similar_companies(self._api_key, symbol) + + def get_earnings_history(self, symbol: str) -> pd.DataFrame: + """Given a stock's ticker symbol, returns a dataframe storing actual and estimated earnings over past K quarterly reports.""" + return earnings.get_earnings_history(self._api_key, symbol) + + def get_latest_earning_estimate(self, symbol: str) -> float: + """Given a stock's ticker symbol, returns it's earnings estimate for the upcoming quarterly report.""" + return earnings.get_latest_earning_estimate(symbol) + + def get_stocks_with_upcoming_earnings( + self, num_days_from_now: int, only_sp500: bool + ) -> pd.DataFrame: + """Returns a pandas dataframe containing all stocks which are announcing earnings in upcoming days. + + Arguments: + num_days_from_now: only returns stocks which announcing earnings from today's date to num_days_from_now. + only_sp500: only returns sp500 stocks. + + """ + start_date = datetime.now().strftime("%Y-%m-%d") + end_date = (datetime.now() + timedelta(num_days_from_now)).strftime("%Y-%m-%d") + return earnings.get_upcoming_earnings( + self._api_key, + start_date=start_date, + end_date=end_date, + country="USD", + only_sp500=only_sp500, + ) + + def get_current_gainer_stocks(self) -> pd.DataFrame: + """Return US stocks which are classified as day gainers as per Yahoo Finance. + + A US stock is classified as day gainer if %change in price > 3, price >=5, volume > 15_000 + + """ + return news.get_current_gainer_stocks() + + def get_current_loser_stocks(self) -> pd.DataFrame: + """Returns US stocks which are classified as day losers as per Yahoo Finance. + + A US stock is classified as day loser if %change in price < -2.5, price >=5, volume > 20_000 + + """ + return news.get_current_loser_stocks() + + def get_current_undervalued_growth_stocks(self) -> pd.DataFrame: + """Get list of undervalued growth stocks in US market as per Yahoo Finance. + + A stock with Price to Earnings ratio between 0-20, Price / Earnings to Growth < 1 + + """ + return news.get_current_undervalued_growth_stocks() + + def get_current_technology_growth_stocks(self) -> pd.DataFrame: + """Returns a data frame of growth stocks in technology sector in US market. + + If a stocks's quarterly revenue growth YoY% > 25%. + + """ + return news.get_current_technology_growth_stocks() + + def get_current_most_traded_stocks(self) -> pd.DataFrame: + """Returns a dataframe storing stocks which were traded the most in current market. + + Stocks are ordered in decreasing order of activity i.e stock traded the most on top. + + """ + return news.get_current_most_traded_stocks() + + def get_current_undervalued_large_cap_stocks(self) -> pd.DataFrame: + """Returns a dataframe storing US market large cap stocks with P/E < 20.""" + return news.get_current_undervalued_large_cap_stocks() + + def get_current_aggressive_small_cap_stocks(self) -> pd.DataFrame: + """Returns a dataframe storing US market small cap stocks with 1 yr % change in earnings per share > 25.""" + return news.get_current_aggressive_small_cap_stocks() + + def get_trending_finance_news(self) -> List[str]: + """Returns a list of top 10 trending news in financial market as per seekingalpha.""" + trends = news.get_topk_trending_news() + return [t["title"] for t in trends] + + def get_google_trending_searches(self) -> Optional[pd.DataFrame]: + """Returns trending searches in US as per google trends. + + If unable to find any trends, returns None. + + """ + return news.get_google_trending_searches(region="united_states") + + def get_google_trends_for_query(self, query: str) -> Optional[pd.DataFrame]: + """Finds google search trends for a given query in United States. + + Returns None if unable to find any trends. + + """ + return news.get_google_trends_for_query(query=query, region="united_states") + + def get_latest_news_for_stock(self, stock_id: str) -> List[str]: + """Given a stock_id representing the name of a company or the stock ticker symbol, Returns a list of news published related to top business articles in US in last 7 days from now.""" + articles = news.get_latest_news_for_stock(stock_id=stock_id) + return [a["title"] for a in articles] + + def get_current_stock_price_info( + self, stock_ticker_symbol: str + ) -> Optional[Dict[str, Any]]: + """ + Given a stock's ticker symbol, returns current price information of the stock. + + Returns None if the provided stock ticker symbol is invalid. + """ + price_info = news.get_current_stock_price_info( + self._api_key, stock_ticker_symbol + ) + if price_info is not None: + return { + "Current Price": price_info["c"], + "High Price of the day": price_info["h"], + "Low Price of the day": price_info["l"], + "Open Price of the day": price_info["o"], + "Percentage change": price_info["dp"], + } + return None diff --git a/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/comparisons.py b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/comparisons.py new file mode 100644 index 0000000000000..4b1e5312d9859 --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/comparisons.py @@ -0,0 +1,29 @@ +""" Find similar companies across different indexes based on available open source models.""" + +from typing import Dict + +from llama_index.tools.finance.util import request + + +def find_similar_companies(api_key: Dict[str, str], symbol: str, country=None): + """ + Returns a list of companies similar to provided stock symbol. + If country is None, performs a global search across all indices. + """ + similar = [] + + if "POLYGON" in api_key: + key = api_key["POLYGON"] + result = request( + f"https://api.polygon.io/v1/meta/symbols/{symbol.upper()}/company?&apiKey={key}" + ) + if result.status_code == 200: + similar.extend(result.json()["similar"]) + if "FINNHUB" in api_key: + result = request( + f"https://finnhub.io/api/v1/stock/peers?symbol={symbol}&token={api_key['FINNHUB']}" + ) + if result.status_code == 200: + similar.extend(result.json()) + + return similar diff --git a/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/earnings.py b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/earnings.py new file mode 100644 index 0000000000000..72dccd4ac1336 --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/earnings.py @@ -0,0 +1,81 @@ +import csv +import requests +import pandas as pd +import yfinance as yf + +from typing import Dict + + +def get_earnings_history(api_key: Dict[str, str], symbol: str) -> pd.DataFrame: + """ + Get actual, estimated earnings and surprise history for a given stock ticker symbol. + + If somehow api response is not found, returns an empty dataframe. + """ + ALPHA_VANTAGE_API_KEY = api_key["ALPHA_VANTAGE"] + + earnings_df = pd.DataFrame() + + response = requests.request( + "GET", + f"https://www.alphavantage.co/query?function=EARNINGS&symbol={symbol}&apikey={ALPHA_VANTAGE_API_KEY}", + ) + if response.status_code != 200: + return earnings_df + + earnings_df = pd.json_normalize(response.json()) + + earnings_df = pd.DataFrame(earnings_df["quarterlyEarnings"][0]) + earnings_df = earnings_df[ + [ + "fiscalDateEnding", + "reportedDate", + "reportedEPS", + "estimatedEPS", + "surprise", + "surprisePercentage", + ] + ] + return earnings_df.rename( + columns={ + "fiscalDateEnding": "Fiscal Date Ending", + "reportedEPS": "Reported EPS", + "estimatedEPS": "Estimated EPS", + "reportedDate": "Reported Date", + "surprise": "Surprise", + "surprisePercentage": "Surprise Percentage", + } + ) + + +def get_latest_earning_estimate(symbol: str) -> float: + """Gets latest actual and estimated earning estimate for a stock symbol.""" + df = yf.Ticker(symbol).earnings_dates + return df["EPS Estimate"].loc[df["EPS Estimate"].first_valid_index()] + + +def get_upcoming_earnings( + api_key: Dict[str, str], + start_date: str, + end_date: str, + country: str, + only_sp500: bool, +): + """Returns stocks announcing there earnings in next 3 months.""" + CSV_URL = f"https://www.alphavantage.co/query?function=EARNINGS_CALENDAR&horizon=3month&apikey={api_key}" + with requests.Session() as s: + download = s.get(CSV_URL) + decoded_content = download.content.decode("utf-8") + cr = list(csv.reader(decoded_content.splitlines(), delimiter=",")) + df = pd.DataFrame(columns=cr[0], data=cr[1:]) + sd = pd.to_datetime(start_date, format="%Y-%m-%d") + ed = pd.to_datetime(end_date, format="%Y-%m-%d") + df["reportDate"] = pd.to_datetime(df["reportDate"]) + df = df[df["currency"] == country][df["reportDate"] > sd][df["reportDate"] < ed] + if only_sp500: + sp500 = pd.read_html( + "https://en.wikipedia.org/wiki/List_of_S%26P_500_companies" + )[0] + sp500_tickers = list(sp500["Symbol"]) + df = df[df["symbol"].isin(sp500_tickers)] + return df[["symbol", "name", "reportDate"]] diff --git a/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/news.py b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/news.py new file mode 100644 index 0000000000000..abc07cad3e7ea --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/news.py @@ -0,0 +1,195 @@ +import pandas as pd + +from collections import defaultdict +from datetime import datetime, timedelta +from bs4 import BeautifulSoup +from pytrends.request import TrendReq +from typing import List, Dict, Optional, Any +from newsapi import NewsApiClient + +from llama_index.tools.finance.util import get_df, request + + +def get_current_gainer_stocks() -> pd.DataFrame: + """Return gainers of the day from yahoo finace including all cap stocks.""" + df_gainers = get_df("https://finance.yahoo.com/screener/predefined/day_gainers")[0] + df_gainers.dropna(how="all", axis=1, inplace=True) + return df_gainers.replace(float("NaN"), "") + + +def get_current_loser_stocks() -> pd.DataFrame: + """Get data for today's losers from yahoo finance including all cap stocks.""" + df_losers = get_df("https://finance.yahoo.com/screener/predefined/day_losers")[0] + df_losers.dropna(how="all", axis=1, inplace=True) + return df_losers.replace(float("NaN"), "") + + +def get_current_undervalued_growth_stocks() -> pd.DataFrame: + """Get data for today's stocks with low PR ratio and growth rate better than 25%.""" + df = get_df( + "https://finance.yahoo.com/screener/predefined/undervalued_growth_stocks" + )[0] + df.dropna(how="all", axis=1, inplace=True) + return df.replace(float("NaN"), "") + + +def get_current_technology_growth_stocks() -> pd.DataFrame: + """Get data for today's stocks with low PR ratio and growth rate better than 25%.""" + df = get_df( + "https://finance.yahoo.com/screener/predefined/growth_technology_stocks" + )[0] + df.dropna(how="all", axis=1, inplace=True) + return df.replace(float("NaN"), "") + + +def get_current_most_traded_stocks() -> pd.DataFrame: + """Get data for today's stocks in descending order based on intraday trading volume.""" + df = get_df("https://finance.yahoo.com/screener/predefined/most_active")[0] + df.dropna(how="all", axis=1, inplace=True) + return df.replace(float("NaN"), "") + + +def get_current_undervalued_large_cap_stocks() -> pd.DataFrame: + """Get data for today's potentially undervalued large cap stocks from Yahoo finance.""" + df = get_df("https://finance.yahoo.com/screener/predefined/undervalued_large_caps")[ + 0 + ] + df.dropna(how="all", axis=1, inplace=True) + return df.replace(float("NaN"), "") + + +def get_current_aggressive_small_cap_stocks() -> pd.DataFrame: + """Get data for today'sagressive / high growth small cap stocks from Yahoo finance.""" + df = get_df("https://finance.yahoo.com/screener/predefined/aggressive_small_caps")[ + 0 + ] + df.dropna(how="all", axis=1, inplace=True) + return df.replace(float("NaN"), "") + + +def get_current_hot_penny_stocks() -> pd.DataFrame: + """Return data for today's hot penny stocks from pennystockflow.com.""" + df = get_df("https://www.pennystockflow.com", 0)[1] + return df.drop([10]) + + +def get_current_stock_price_info( + api_key: Dict[str, str], stock_ticker: str +) -> Optional[Dict[str, Any]]: + """ + Return current price information given a stock ticker symbol. + """ + result = request( + f"https://finnhub.io/api/v1/quote?symbol={stock_ticker}&token={api_key['FINNHUB']}" + ) + if result.status_code != 200: + return None + return result.json() + + +def get_latest_news_for_stock( + api_key: Dict[str, str], stock_id: str, limit: int = 10 +) -> List[Dict[str, Any]]: + """Returns latest news for a given stock_name by querying results via newsapi.""" + newsapi = NewsApiClient(api_key=api_key["NEWSAPI"]) + cat_to_id = defaultdict(list) + for source in newsapi.get_sources()["sources"]: + cat_to_id[source["category"]].append(source["id"]) + business_sources = [ + "bloomberg", + "business-insider", + "financial-post", + "fortune", + "info-money", + "the-wall-street-journal", + ] + for source in business_sources: + assert source in cat_to_id["business"] + + start_date = (datetime.now() - timedelta(days=7)).strftime("%Y-%m-%d") + end_date = datetime.now().strftime("%Y-%m-%d") + articles = newsapi.get_everything( + q=stock_id, + sources=",".join(business_sources), + from_param=start_date, + to=end_date, + language="en", + sort_by="relevancy", + page=1, + )["articles"] + return articles[:limit] + + +def get_topk_trending_news( + limit: int = 10, extract_content: bool = False +) -> List[Dict[str, Any]]: + """Returns top Kk trending news from seekingalpha.""" + articles = [] + URL = "https://seekingalpha.com/news/trending_news" + response = request(URL) + if response.status_code == 200: + for item in response.json(): + article_url = item["uri"] + if not article_url.startswith("/news/"): + continue + + article_id = article_url.split("/")[2].split("-")[0] + + content = "" + if extract_content: + article_url = f"https://seekingalpha.com/api/v3/news/{article_id}" + article_response = request(article_url) + jdata = article_response.json() + try: + content = jdata["data"]["attributes"]["content"].replace( + "", "\n" + ) + content = BeautifulSoup(content, features="html.parser").get_text() + except Exception as e: + print(f"Unable to extract content for: {article_url}") + + articles.append( + { + "title": item["title"], + "publishedAt": item["publish_on"][: item["publish_on"].rfind(".")], + "url": "https://seekingalpha.com" + article_url, + "id": article_id, + "content": content, + } + ) + + if len(articles) > limit: + break + + return articles[:limit] + + +def get_google_trending_searches(region: str = "") -> Optional[pd.DataFrame]: + """Returns overall trending searches in US unless region is provided.""" + # TODO(ishan): Can we filter by category? + try: + pytrend = TrendReq() + return pytrend.trending_searches(pn=region if region else "united_states") + except Exception as e: + print(f"Unable to find google trending searches, error: {e}") + return None + + +def get_google_trends_for_query( + query: str, find_related: bool = False, region: str = "" +) -> Optional[pd.DataFrame]: + """Find google search trends for a given query filtered by region if provided.""" + try: + pytrend = TrendReq() + # 12 is the category for Business and Industrial which covers most of the related + # topics related to fin-gpt + # Ref: https://github.com/pat310/google-trends-api/wiki/Google-Trends-Categories + + # Only search for last 30 days from now + pytrend.build_payload( + kw_list=[query], timeframe="today 1-m", geo=region, cat=12 + ) + return pytrend.interest_over_time() + except Exception as e: + print(f"Unable to find google trend for {query}, error: {e}") + return None diff --git a/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/util.py b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/util.py new file mode 100644 index 0000000000000..157b6e253b13a --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/llama_index/tools/finance/util.py @@ -0,0 +1,29 @@ +import requests +import pandas as pd +import re + +from typing import Optional + + +def request(url: str, method: str = "get", timeout: int = 10, **kwargs): + """Helper to make requests 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b/llama-index-integrations/tools/llama-index-tools-finance/pyproject.toml @@ -0,0 +1,57 @@ +[build-system] +build-backend = "poetry.core.masonry.api" +requires = ["poetry-core"] + +[tool.codespell] +check-filenames = true +check-hidden = true +skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb" + +[tool.llamahub] +contains_example = false +import_path = "llama_index.tools.finance" + +[tool.llamahub.class_authors] +FinanceAgentToolSpec = "345ishaan" + +[tool.mypy] +disallow_untyped_defs = true +# Remove venv skip when integrated with pre-commit +exclude = ["_static", "build", "examples", "notebooks", "venv"] +ignore_missing_imports = true +python_version = "3.8" + +[tool.poetry] +authors = ["Your Name "] +description = "llama-index finance-tools integration" +license = "MIT" +name = "llama-index-tools-finance" +packages = [{include = "llama_index/"}] +readme = "README.md" +version = "0.1.0" + +[tool.poetry.dependencies] +python = ">=3.8.1,<3.12" +llama-index-core = "^0.10.0" +yfinance = "^0.2.36" +newsapi-python = "^0.2.7" +pytrends = "^4.9.2" + +[tool.poetry.group.dev.dependencies] +black = {extras = ["jupyter"], version = "<=23.9.1,>=23.7.0"} +codespell = {extras = ["toml"], version = ">=v2.2.6"} +ipython = "8.10.0" +jupyter = "^1.0.0" +mypy = "0.991" +pre-commit = "3.2.0" +pylint = "2.15.10" +pytest = "7.2.1" +pytest-mock = "3.11.1" +ruff = "0.0.292" +tree-sitter-languages = "^1.8.0" +types-Deprecated = ">=0.1.0" +types-PyYAML = "^6.0.12.12" +types-protobuf = "^4.24.0.4" +types-redis = "4.5.5.0" +types-requests = "2.28.11.8" +types-setuptools = "67.1.0.0" diff --git a/llama-index-integrations/tools/llama-index-tools-finance/tests/BUILD b/llama-index-integrations/tools/llama-index-tools-finance/tests/BUILD new file mode 100644 index 0000000000000..dabf212d7e716 --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/tests/BUILD @@ -0,0 +1 @@ +python_tests() diff --git a/llama-index-integrations/tools/llama-index-tools-finance/tests/__init__.py b/llama-index-integrations/tools/llama-index-tools-finance/tests/__init__.py new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/llama-index-integrations/tools/llama-index-tools-finance/tests/test_finance_tools.py b/llama-index-integrations/tools/llama-index-tools-finance/tests/test_finance_tools.py new file mode 100644 index 0000000000000..54efb9670e703 --- /dev/null +++ b/llama-index-integrations/tools/llama-index-tools-finance/tests/test_finance_tools.py @@ -0,0 +1,7 @@ +from llama_index.core.tools.tool_spec.base import BaseToolSpec +from llama_index.tools.finance import FinanceAgentToolSpec + + +def test_class(): + name_of_base_classes = [b.__name__ for b in FinanceAgentToolSpec.__mro__] + assert BaseToolSpec.__name__ in name_of_base_classes From ab61b32d8a8c6969f907818859170395ec80bf5e Mon Sep 17 00:00:00 2001 From: Logan Date: Sat, 24 Feb 2024 00:17:19 -0600 Subject: [PATCH 19/30] Logan/fix vuls (#11347) --- .../core/query_engine/cogniswitch_query_engine.py | 1 - .../llama_index/llms/rungpt/base.py | 5 ++--- .../llms/llama-index-llms-rungpt/pyproject.toml | 2 +- .../llama_index/tools/cogniswitch/base.py | 11 +++-------- .../llama-index-tools-cogniswitch/pyproject.toml | 2 +- 5 files changed, 7 insertions(+), 14 deletions(-) diff --git a/llama-index-core/llama_index/core/query_engine/cogniswitch_query_engine.py b/llama-index-core/llama_index/core/query_engine/cogniswitch_query_engine.py index a9c6a06d43f3f..dcbd7754f8819 100644 --- a/llama-index-core/llama_index/core/query_engine/cogniswitch_query_engine.py +++ b/llama-index-core/llama_index/core/query_engine/cogniswitch_query_engine.py @@ -41,7 +41,6 @@ def query_knowledge(self, query: str) -> Response: response = requests.post( self.knowledge_request_endpoint, headers=self.headers, - verify=False, data=data, ) if response.status_code == 200: diff --git a/llama-index-integrations/llms/llama-index-llms-rungpt/llama_index/llms/rungpt/base.py b/llama-index-integrations/llms/llama-index-llms-rungpt/llama_index/llms/rungpt/base.py index 97a7585e50985..773098d66b5c0 100644 --- a/llama-index-integrations/llms/llama-index-llms-rungpt/llama_index/llms/rungpt/base.py +++ b/llama-index-integrations/llms/llama-index-llms-rungpt/llama_index/llms/rungpt/base.py @@ -1,4 +1,3 @@ -import json from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union from llama_index.core.base.llms.types import ( @@ -153,7 +152,7 @@ def stream_complete( def gen() -> CompletionResponseGen: text = "" for item in response_iter: - item_dict = json.loads(json.dumps(eval(item.data))) + item_dict = dict(item.data) delta = item_dict["choices"][0]["text"] additional_kwargs = item_dict["usage"] text = text + self._space_handler(delta) @@ -214,7 +213,7 @@ def stream_chat( def gen() -> ChatResponseGen: content = "" for item in chat_iter: - item_dict = json.loads(json.dumps(eval(item.data))) + item_dict = dict(item.data) chat_message, delta = self._message_unpacker(item_dict) content = content + self._space_handler(delta) chat_message.content = content diff --git a/llama-index-integrations/llms/llama-index-llms-rungpt/pyproject.toml b/llama-index-integrations/llms/llama-index-llms-rungpt/pyproject.toml index 1608307cf937d..365d1e32fc65e 100644 --- a/llama-index-integrations/llms/llama-index-llms-rungpt/pyproject.toml +++ b/llama-index-integrations/llms/llama-index-llms-rungpt/pyproject.toml @@ -27,7 +27,7 @@ exclude = ["**/BUILD"] license = "MIT" name = "llama-index-llms-rungpt" readme = "README.md" -version = "0.1.2" +version = "0.1.3" [tool.poetry.dependencies] python = ">=3.8.1,<4.0" diff --git a/llama-index-integrations/tools/llama-index-tools-cogniswitch/llama_index/tools/cogniswitch/base.py b/llama-index-integrations/tools/llama-index-tools-cogniswitch/llama_index/tools/cogniswitch/base.py index a931c2dcaddc5..e8cb315adde4d 100644 --- a/llama-index-integrations/tools/llama-index-tools-cogniswitch/llama_index/tools/cogniswitch/base.py +++ b/llama-index-integrations/tools/llama-index-tools-cogniswitch/llama_index/tools/cogniswitch/base.py @@ -91,9 +91,7 @@ def store_data( "documentName": document_name, "documentDescription": document_description, } - response = requests.post( - api_url, headers=headers, verify=False, data=data, files=files - ) + response = requests.post(api_url, headers=headers, data=data, files=files) elif file: api_url = self.source_file_endpoint @@ -108,9 +106,7 @@ def store_data( "documentName": document_name, "documentDescription": document_description, } - response = requests.post( - api_url, headers=headers, verify=False, data=data, files=files - ) + response = requests.post(api_url, headers=headers, data=data, files=files) if response.status_code == 200: return response.json() else: @@ -134,7 +130,7 @@ def query_knowledge(self, query: str) -> dict: headers = self.headers data = {"query": query} - response = requests.post(api_url, headers=headers, verify=False, data=data) + response = requests.post(api_url, headers=headers, data=data) if response.status_code == 200: return response.json() else: @@ -157,7 +153,6 @@ def knowledge_status(self, document_name: str) -> dict: self.knowledge_status_endpoint, headers=self.headers, params=params, - verify=False, ) if response.status_code == 200: source_info = response.json() diff --git a/llama-index-integrations/tools/llama-index-tools-cogniswitch/pyproject.toml b/llama-index-integrations/tools/llama-index-tools-cogniswitch/pyproject.toml index d6da56b108b4a..f81bda93ea49d 100644 --- a/llama-index-integrations/tools/llama-index-tools-cogniswitch/pyproject.toml +++ b/llama-index-integrations/tools/llama-index-tools-cogniswitch/pyproject.toml @@ -29,7 +29,7 @@ license = "MIT" maintainers = ["cogniswitch"] name = "llama-index-tools-cogniswitch" readme = "README.md" -version = "0.1.3" +version = "0.1.4" [tool.poetry.dependencies] python = ">=3.8.1,<4.0" From f470398e99a97293bd242bb7ea6083d326484f6e Mon Sep 17 00:00:00 2001 From: Andrei Fajardo <92402603+nerdai@users.noreply.github.com> Date: Sat, 24 Feb 2024 10:46:49 -0500 Subject: [PATCH 20/30] remove helper classes (#11354) --- .../pyproject.toml | 2 - .../llama-index-agent-openai/pyproject.toml | 1 - .../pyproject.toml | 2 - .../pyproject.toml | 2 - .../pyproject.toml | 1 - .../pyproject.toml | 1 - .../pyproject.toml | 1 - .../pyproject.toml | 3 - .../pyproject.toml | 2 + .../pyproject.toml | 4 +- .../pyproject.toml | 2 + .../llama-index-llms-bedrock/pyproject.toml | 2 - .../llama-index-llms-dashscope/pyproject.toml | 1 - .../llama-index-llms-openai/pyproject.toml | 1 - .../pyproject.toml | 1 - .../.gitignore | 153 ---------- .../BUILD | 3 - .../Makefile | 17 -- .../README.md | 1 - .../replicate_multi_modal/BUILD | 1 - .../replicate_multi_modal/__init__.py | 3 - .../replicate_multi_modal/base.py | 288 ------------------ .../pyproject.toml | 62 ---- .../tests/BUILD | 1 - .../tests/__init__.py | 0 ..._multi-modal-llms_replicate_multi_modal.py | 7 - .../pyproject.toml | 1 - .../pyproject.toml | 2 - .../pyproject.toml | 3 - .../llama-index-readers-joplin/pyproject.toml | 1 - .../pyproject.toml | 2 - .../pyproject.toml | 2 - .../llama-index-tools-azure-cv/pyproject.toml | 1 - .../pyproject.toml | 1 - .../pyproject.toml | 1 - .../llama-index-tools-google/pyproject.toml | 1 - .../llama-index-tools-requests/pyproject.toml | 1 - .../pyproject.toml | 1 - .../pyproject.toml | 1 - .../llama-index-tools-zapier/pyproject.toml | 1 - .../pyproject.toml | 2 - .../pyproject.toml | 1 - .../pyproject.toml | 1 - .../pyproject.toml | 1 - .../llama-index-packs-self-rag/pyproject.toml | 1 - .../llama-index-packs-vanna/pyproject.toml | 1 - 46 files changed, 7 insertions(+), 581 deletions(-) delete mode 100644 llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/.gitignore delete mode 100644 llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/BUILD delete mode 100644 llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/Makefile delete mode 100644 llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/README.md delete mode 100644 llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/llama_index/multi_modal_llms/replicate_multi_modal/BUILD delete mode 100644 llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/llama_index/multi_modal_llms/replicate_multi_modal/__init__.py delete mode 100644 llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/llama_index/multi_modal_llms/replicate_multi_modal/base.py delete mode 100644 llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/pyproject.toml delete mode 100644 llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/tests/BUILD delete mode 100644 llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/tests/__init__.py delete mode 100644 llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/tests/test_multi-modal-llms_replicate_multi_modal.py diff --git a/llama-index-integrations/agent/llama-index-agent-openai-legacy/pyproject.toml b/llama-index-integrations/agent/llama-index-agent-openai-legacy/pyproject.toml index 119cfa4ba89f4..3ab4916648290 100644 --- a/llama-index-integrations/agent/llama-index-agent-openai-legacy/pyproject.toml +++ b/llama-index-integrations/agent/llama-index-agent-openai-legacy/pyproject.toml @@ -12,10 +12,8 @@ contains_example = false import_path = "llama_index.agent.openai_legacy" [tool.llamahub.class_authors] -BaseOpenAIAgent = "llama-index" ContextRetrieverOpenAIAgent = "llama-index" FnRetrieverOpenAIAgent = "llama-index" -OpenAIAgent = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/agent/llama-index-agent-openai/pyproject.toml b/llama-index-integrations/agent/llama-index-agent-openai/pyproject.toml index b15d5612a7d31..24b1ee7799e5f 100644 --- a/llama-index-integrations/agent/llama-index-agent-openai/pyproject.toml +++ b/llama-index-integrations/agent/llama-index-agent-openai/pyproject.toml @@ -13,7 +13,6 @@ import_path = "llama_index.agent.openai" [tool.llamahub.class_authors] OpenAIAgent = "llama-index" -OpenAIAgentWorker = "llama-index" OpenAIAssistantAgent = "llama-index" [tool.mypy] diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-adapter/pyproject.toml b/llama-index-integrations/embeddings/llama-index-embeddings-adapter/pyproject.toml index 8a114c0da3122..6ad492dfb7e2d 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-adapter/pyproject.toml +++ b/llama-index-integrations/embeddings/llama-index-embeddings-adapter/pyproject.toml @@ -13,9 +13,7 @@ import_path = "llama_index.embeddings.adapter" [tool.llamahub.class_authors] AdapterEmbeddingModel = "llama-index" -BaseAdapter = "llama-index" LinearAdapterEmbeddingModel = "llama-index" -LinearLayer = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-azure-openai/pyproject.toml b/llama-index-integrations/embeddings/llama-index-embeddings-azure-openai/pyproject.toml index 1187a98253b51..db868c19b4378 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-azure-openai/pyproject.toml +++ b/llama-index-integrations/embeddings/llama-index-embeddings-azure-openai/pyproject.toml @@ -12,8 +12,6 @@ contains_example = false import_path = "llama_index.embeddings.azure_openai" [tool.llamahub.class_authors] -AsyncAzureOpenAI = "llama-index" -AzureOpenAI = "llama-index" AzureOpenAIEmbedding = "llama-index" [tool.mypy] diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-bedrock/pyproject.toml b/llama-index-integrations/embeddings/llama-index-embeddings-bedrock/pyproject.toml index d8cf560d59ad8..3cf9cc1ffe24b 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-bedrock/pyproject.toml +++ b/llama-index-integrations/embeddings/llama-index-embeddings-bedrock/pyproject.toml @@ -13,7 +13,6 @@ import_path = "llama_index.embeddings.bedrock" [tool.llamahub.class_authors] BedrockEmbedding = "llama-index" -Models = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-huggingface/pyproject.toml b/llama-index-integrations/embeddings/llama-index-embeddings-huggingface/pyproject.toml index eae37b0671dfa..a454d61ae3740 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-huggingface/pyproject.toml +++ b/llama-index-integrations/embeddings/llama-index-embeddings-huggingface/pyproject.toml @@ -14,7 +14,6 @@ import_path = "llama_index.embeddings.huggingface" [tool.llamahub.class_authors] HuggingFaceEmbedding = "llama-index" HuggingFaceInferenceAPIEmbedding = "llama-index" -HuggingFaceInferenceAPIEmbeddings = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-llm-rails/pyproject.toml b/llama-index-integrations/embeddings/llama-index-embeddings-llm-rails/pyproject.toml index d5e5a6b027d83..4217635f0fd93 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-llm-rails/pyproject.toml +++ b/llama-index-integrations/embeddings/llama-index-embeddings-llm-rails/pyproject.toml @@ -13,7 +13,6 @@ import_path = "llama_index.embeddings.llm_rails" [tool.llamahub.class_authors] LLMRailsEmbedding = "llama-index" -LLMRailsEmbeddings = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-openai/pyproject.toml b/llama-index-integrations/embeddings/llama-index-embeddings-openai/pyproject.toml index e022877b7c9d7..383f7b9487d3f 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-openai/pyproject.toml +++ b/llama-index-integrations/embeddings/llama-index-embeddings-openai/pyproject.toml @@ -13,9 +13,6 @@ import_path = "llama_index.embeddings.openai" [tool.llamahub.class_authors] OpenAIEmbedding = "llama-index" -OpenAIEmbeddingMode = "llama-index" -OpenAIEmbeddingModeModel = "llama-index" -OpenAIEmbeddingModelType = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/indices/llama-index-indices-managed-llama-cloud/pyproject.toml b/llama-index-integrations/indices/llama-index-indices-managed-llama-cloud/pyproject.toml index 2b969a07843e7..65c5805db8a8c 100644 --- a/llama-index-integrations/indices/llama-index-indices-managed-llama-cloud/pyproject.toml +++ b/llama-index-integrations/indices/llama-index-indices-managed-llama-cloud/pyproject.toml @@ -13,6 +13,8 @@ import_path = "llama_index.indices.managed.llama_cloud" [tool.llamahub.class_authors] LlamaCloudIndex = "llama-index" + +[tool.llamahub.secondary_class_authors] LlamaCloudRetriever = "llama-index" [tool.mypy] diff --git a/llama-index-integrations/indices/llama-index-indices-managed-vectara/pyproject.toml b/llama-index-integrations/indices/llama-index-indices-managed-vectara/pyproject.toml index 6dd2208789ecb..30a7071e64cf0 100644 --- a/llama-index-integrations/indices/llama-index-indices-managed-vectara/pyproject.toml +++ b/llama-index-integrations/indices/llama-index-indices-managed-vectara/pyproject.toml @@ -12,8 +12,10 @@ contains_example = false import_path = "llama_index.indices.managed.vectara" [tool.llamahub.class_authors] -VectaraAutoRetriever = "llama-index" VectaraIndex = "llama-index" + +[tool.llamahub.secondary_class_authors] +VectaraAutoRetriever = "llama-index" VectaraRetriever = "llama-index" [tool.mypy] diff --git a/llama-index-integrations/indices/llama-index-indices-managed-zilliz/pyproject.toml b/llama-index-integrations/indices/llama-index-indices-managed-zilliz/pyproject.toml index aa7c2433d9831..8b157dcca8dd5 100644 --- a/llama-index-integrations/indices/llama-index-indices-managed-zilliz/pyproject.toml +++ b/llama-index-integrations/indices/llama-index-indices-managed-zilliz/pyproject.toml @@ -13,6 +13,8 @@ import_path = "llama_index.indices.managed.zilliz" [tool.llamahub.class_authors] ZillizCloudPipelineIndex = "llama-index" + +[tool.llamahub.secondary_class_authors] ZillizCloudPipelineRetriever = "llama-index" [tool.mypy] diff --git a/llama-index-integrations/llms/llama-index-llms-bedrock/pyproject.toml b/llama-index-integrations/llms/llama-index-llms-bedrock/pyproject.toml index eef1a573efa72..d2320280a67cd 100644 --- a/llama-index-integrations/llms/llama-index-llms-bedrock/pyproject.toml +++ b/llama-index-integrations/llms/llama-index-llms-bedrock/pyproject.toml @@ -13,8 +13,6 @@ import_path = "llama_index.llms.bedrock" [tool.llamahub.class_authors] Bedrock = "llama-index" -completion_response_to_chat_response = "llama-index" -completion_with_retry = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/llms/llama-index-llms-dashscope/pyproject.toml b/llama-index-integrations/llms/llama-index-llms-dashscope/pyproject.toml index 75231d5c45d64..5daa07408fc0a 100644 --- a/llama-index-integrations/llms/llama-index-llms-dashscope/pyproject.toml +++ b/llama-index-integrations/llms/llama-index-llms-dashscope/pyproject.toml @@ -13,7 +13,6 @@ import_path = "llama_index.llms.dashscope" [tool.llamahub.class_authors] DashScope = "llama-index" -DashScopeGenerationModels = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/llms/llama-index-llms-openai/pyproject.toml b/llama-index-integrations/llms/llama-index-llms-openai/pyproject.toml index 0e7965912b908..1319956ecd567 100644 --- a/llama-index-integrations/llms/llama-index-llms-openai/pyproject.toml +++ b/llama-index-integrations/llms/llama-index-llms-openai/pyproject.toml @@ -15,7 +15,6 @@ import_path = "llama_index.llms.openai" AsyncOpenAI = "llama-index" OpenAI = "llama-index" SyncOpenAI = "llama-index" -Tokenizer = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-dashscope/pyproject.toml b/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-dashscope/pyproject.toml index 9ba99d8510ad4..ee2f2331a09ef 100644 --- a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-dashscope/pyproject.toml +++ b/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-dashscope/pyproject.toml @@ -13,7 +13,6 @@ import_path = "llama_index.multi_modal_llms.dashscope" [tool.llamahub.class_authors] DashScopeMultiModal = "llama-index" -DashScopeMultiModalModels = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/.gitignore b/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/.gitignore deleted file mode 100644 index 990c18de22908..0000000000000 --- a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/.gitignore +++ /dev/null @@ -1,153 +0,0 @@ -llama_index/_static -.DS_Store -# Byte-compiled / optimized / DLL files -__pycache__/ -*.py[cod] -*$py.class - -# C extensions -*.so - -# Distribution / packaging -.Python -bin/ -build/ -develop-eggs/ -dist/ -downloads/ -eggs/ -.eggs/ -etc/ -include/ -lib/ -lib64/ -parts/ -sdist/ -share/ -var/ -wheels/ -pip-wheel-metadata/ -share/python-wheels/ -*.egg-info/ -.installed.cfg -*.egg -MANIFEST - -# PyInstaller -# Usually these files are written by a python script from a template -# before PyInstaller builds the exe, so as to inject date/other infos into it. -*.manifest -*.spec - -# Installer logs -pip-log.txt -pip-delete-this-directory.txt - -# Unit test / coverage reports -htmlcov/ -.tox/ -.nox/ -.coverage -.coverage.* -.cache -nosetests.xml -coverage.xml -*.cover -*.py,cover -.hypothesis/ -.pytest_cache/ -.ruff_cache - -# Translations -*.mo -*.pot - -# Django stuff: -*.log -local_settings.py -db.sqlite3 -db.sqlite3-journal - -# Flask stuff: -instance/ -.webassets-cache - -# Scrapy stuff: -.scrapy - -# Sphinx documentation -docs/_build/ - -# PyBuilder -target/ - -# Jupyter Notebook -.ipynb_checkpoints -notebooks/ - -# IPython -profile_default/ -ipython_config.py - -# pyenv -.python-version - -# pipenv -# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. -# However, in case of collaboration, if having platform-specific dependencies or dependencies -# having no cross-platform support, pipenv may install dependencies that don't work, or not -# install all needed dependencies. -#Pipfile.lock - -# PEP 582; used by e.g. github.com/David-OConnor/pyflow -__pypackages__/ - -# Celery stuff -celerybeat-schedule -celerybeat.pid - -# SageMath parsed files -*.sage.py - -# Environments -.env -.venv -env/ -venv/ -ENV/ -env.bak/ -venv.bak/ -pyvenv.cfg - -# Spyder project settings -.spyderproject -.spyproject - -# Rope project settings -.ropeproject - -# mkdocs documentation -/site - -# mypy -.mypy_cache/ -.dmypy.json -dmypy.json - -# Pyre type checker -.pyre/ - -# Jetbrains -.idea -modules/ -*.swp - -# VsCode -.vscode - -# pipenv -Pipfile -Pipfile.lock - -# pyright -pyrightconfig.json diff --git a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/BUILD b/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/BUILD deleted file mode 100644 index 0896ca890d8bf..0000000000000 --- a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/BUILD +++ /dev/null @@ -1,3 +0,0 @@ -poetry_requirements( - name="poetry", -) diff --git a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/Makefile b/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/Makefile deleted file mode 100644 index b9eab05aa3706..0000000000000 --- a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/Makefile +++ /dev/null @@ -1,17 +0,0 @@ -GIT_ROOT ?= $(shell git rev-parse --show-toplevel) - -help: ## Show all Makefile targets. - @grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[33m%-30s\033[0m %s\n", $$1, $$2}' - -format: ## Run code autoformatters (black). - pre-commit install - git ls-files | xargs pre-commit run black --files - -lint: ## Run linters: pre-commit (black, ruff, codespell) and mypy - pre-commit install && git ls-files | xargs pre-commit run --show-diff-on-failure --files - -test: ## Run tests via pytest. - pytest tests - -watch-docs: ## Build and watch documentation. - sphinx-autobuild docs/ docs/_build/html --open-browser --watch $(GIT_ROOT)/llama_index/ diff --git a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/README.md b/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/README.md deleted file mode 100644 index 0a724061ee16c..0000000000000 --- a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/README.md +++ /dev/null @@ -1 +0,0 @@ -# LlamaIndex Multi-Modal-Llms Integration: Replicate Multi Modal diff --git a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/llama_index/multi_modal_llms/replicate_multi_modal/BUILD b/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/llama_index/multi_modal_llms/replicate_multi_modal/BUILD deleted file mode 100644 index db46e8d6c978c..0000000000000 --- a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/llama_index/multi_modal_llms/replicate_multi_modal/BUILD +++ /dev/null @@ -1 +0,0 @@ -python_sources() diff --git a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/llama_index/multi_modal_llms/replicate_multi_modal/__init__.py b/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/llama_index/multi_modal_llms/replicate_multi_modal/__init__.py deleted file mode 100644 index f7258fb831443..0000000000000 --- a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/llama_index/multi_modal_llms/replicate_multi_modal/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from llama_index.multi_modal_llms.replicate_multi_modal.base import ReplicateMultiModal - -__all__ = ["ReplicateMultiModal"] diff --git a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/llama_index/multi_modal_llms/replicate_multi_modal/base.py b/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/llama_index/multi_modal_llms/replicate_multi_modal/base.py deleted file mode 100644 index 734c9a3e9fc9e..0000000000000 --- a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/llama_index/multi_modal_llms/replicate_multi_modal/base.py +++ /dev/null @@ -1,288 +0,0 @@ -import logging -from typing import Any, Callable, Dict, Optional, Sequence - -from llama_index.core.base.llms.types import ( - ChatMessage, - ChatResponse, - ChatResponseAsyncGen, - ChatResponseGen, - CompletionResponse, - CompletionResponseAsyncGen, - CompletionResponseGen, -) -from llama_index.core.bridge.pydantic import Field, PrivateAttr -from llama_index.core.callbacks import CallbackManager -from llama_index.core.constants import DEFAULT_CONTEXT_WINDOW, DEFAULT_NUM_OUTPUTS -from llama_index.core.base.llms.generic_utils import ( - messages_to_prompt as generic_messages_to_prompt, -) -from llama_index.core.multi_modal_llms import ( - MultiModalLLM, - MultiModalLLMMetadata, -) -from llama_index.core.schema import ImageDocument - -_logger = logging.getLogger(__name__) - -REPLICATE_MULTI_MODAL_LLM_MODELS = { - "llava-13b": "yorickvp/llava-13b:e272157381e2a3bf12df3a8edd1f38d1dbd736bbb7437277c8b34175f8fce358", - "fuyu-8b": "lucataco/fuyu-8b:42f23bc876570a46f5a90737086fbc4c3f79dd11753a28eaa39544dd391815e9", - "minigpt-4": "daanelson/minigpt-4:b96a2f33cc8e4b0aa23eacfce731b9c41a7d9466d9ed4e167375587b54db9423", - "cogvlm": "naklecha/cogvlm:ec3886f9ea85dd0aee216585be5e6d07b04c9650f7b8b08363a14eb89e207eb2", -} - - -class ReplicateMultiModal(MultiModalLLM): - model: str = Field(description="The Multi-Modal model to use from Replicate.") - temperature: float = Field( - description="The temperature to use for sampling. Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic." - ) - max_new_tokens: int = Field( - description=" The maximum numbers of tokens to generate, ignoring the number of tokens in the prompt" - ) - context_window: int = Field( - description="The maximum number of context tokens for the model." - ) - prompt_key: str = Field(description="The key to use for the prompt in API calls.") - image_key: str = Field(description="The key to use for the image in API calls.") - top_p: float = Field( - description="When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens." - ) - num_beams: int = Field(description="Number of beams for beam search decoding.") - repetition_penalty: float = Field( - description="Penalty for repeated words in generated text; 1 is no penalty, values greater than 1 discourage repetition, less than 1 encourage it." - ) - additional_kwargs: Dict[str, Any] = Field( - default_factory=dict, description="Additional kwargs for the Replicate API." - ) - - _messages_to_prompt: Callable = PrivateAttr() - _completion_to_prompt: Callable = PrivateAttr() - - def __init__( - self, - model: str = REPLICATE_MULTI_MODAL_LLM_MODELS["fuyu-8b"], - temperature: float = 0.75, - max_new_tokens: int = 512, - num_input_files: int = 1, - additional_kwargs: Optional[Dict[str, Any]] = None, - context_window: int = DEFAULT_CONTEXT_WINDOW, - prompt_key: str = "prompt", - image_key: str = "image", - repetition_penalty: Optional[float] = 1.0, - num_beams: Optional[int] = 1, - top_p: Optional[float] = 0.9, - messages_to_prompt: Optional[Callable] = None, - completion_to_prompt: Optional[Callable] = None, - callback_manager: Optional[CallbackManager] = None, - ) -> None: - self._messages_to_prompt = messages_to_prompt or generic_messages_to_prompt - self._completion_to_prompt = completion_to_prompt or (lambda x: x) - - super().__init__( - model=model, - temperature=temperature, - max_new_tokens=max_new_tokens, - num_input_files=num_input_files, - repetition_penalty=repetition_penalty, - num_beams=num_beams, - top_p=top_p, - additional_kwargs=additional_kwargs or {}, - context_window=context_window, - prompt_key=prompt_key, - image_key=image_key, - callback_manager=callback_manager, - ) - - @classmethod - def class_name(cls) -> str: - return "replicate_multi_modal_llm" - - @property - def metadata(self) -> MultiModalLLMMetadata: - """Multi Modal LLM metadata.""" - return MultiModalLLMMetadata( - context_window=self.context_window, - num_output=DEFAULT_NUM_OUTPUTS, - model_name=self.model, - ) - - @property - def _model_kwargs(self) -> Dict[str, Any]: - base_kwargs: Dict[str, Any] = { - "temperature": self.temperature, - "max_length": self.context_window, - "max_new_tokens": self.max_new_tokens, - "num_beams": self.num_beams, - "repetition_penalty": self.repetition_penalty, - "top_p": self.top_p, - } - return { - **base_kwargs, - **self.additional_kwargs, - } - - def _get_multi_modal_chat_messages( - self, prompt: str, image_document: ImageDocument, **kwargs: Any - ) -> Dict[str, Any]: - if image_document.image_path: - # load local image file and pass file handler to replicate - try: - return { - self.prompt_key: prompt, - self.image_key: open(image_document.image_path, "rb"), - **self._model_kwargs, - **kwargs, - } - except FileNotFoundError: - raise FileNotFoundError( - "Could not load local image file. Please check whether the file exists" - ) - elif image_document.image_url: - # load remote image url and pass file url to replicate - return { - self.prompt_key: prompt, - self.image_key: image_document.image_url, - **self._model_kwargs, - **kwargs, - } - else: - raise FileNotFoundError( - "Could not load image file. Please check whether the file exists" - ) - - def complete( - self, prompt: str, image_documents: Sequence[ImageDocument], **kwargs: Any - ) -> CompletionResponse: - response_gen = self.stream_complete(prompt, image_documents, **kwargs) - response_list = list(response_gen) - final_response = response_list[-1] - final_response.delta = None - return final_response - - def stream_complete( - self, prompt: str, image_documents: Sequence[ImageDocument], **kwargs: Any - ) -> CompletionResponseGen: - try: - import replicate - except ImportError: - raise ImportError( - "Could not import replicate library." - "Please install replicate with `pip install replicate`" - ) - - # TODO: at the current moment, only support uploading one image document - if len(image_documents) > 1: - _logger.warning( - "ReplicateMultiModal currently only supports uploading one image document" - "we are using the first image document for completion." - ) - - prompt = self._completion_to_prompt(prompt) - input_dict = self._get_multi_modal_chat_messages( - # using the first image for single image completion - prompt, - image_documents[0], - **kwargs, - ) - if self.model not in REPLICATE_MULTI_MODAL_LLM_MODELS.values(): - raise ValueError( - f"Unknown model {self.model!r}. Please provide a valid Replicate Multi-Modal model name in:" - f" {', '.join(REPLICATE_MULTI_MODAL_LLM_MODELS.values())}" - ) - - response_iter = replicate.run(self.model, input=input_dict) - - def gen() -> CompletionResponseGen: - text = "" - for delta in response_iter: - text += delta - yield CompletionResponse( - delta=delta, - text=text, - ) - - return gen() - - def chat( - self, - messages: Sequence[ChatMessage], - **kwargs: Any, - ) -> ChatResponse: - raise NotImplementedError - - def stream_chat( - self, - messages: Sequence[ChatMessage], - **kwargs: Any, - ) -> ChatResponseGen: - raise NotImplementedError - - # ===== Async Endpoints ===== - - async def acomplete( - self, prompt: str, image_documents: Sequence[ImageDocument], **kwargs: Any - ) -> CompletionResponse: - response_gen = self.stream_complete(prompt, image_documents, **kwargs) - response_list = list(response_gen) - final_response = response_list[-1] - final_response.delta = None - return final_response - - async def astream_complete( - self, prompt: str, image_documents: Sequence[ImageDocument], **kwargs: Any - ) -> CompletionResponseAsyncGen: - try: - import replicate - except ImportError: - raise ImportError( - "Could not import replicate library." - "Please install replicate with `pip install replicate`" - ) - - # TODO: at the current moment, only support uploading one image document - if len(image_documents) > 1: - _logger.warning( - "ReplicateMultiModal currently only supports uploading one image document" - "we are using the first image document for completion." - ) - - prompt = self._completion_to_prompt(prompt) - input_dict = self._get_multi_modal_chat_messages( - # using the first image for single image completion - prompt, - image_documents[0], - **kwargs, - ) - if self.model not in REPLICATE_MULTI_MODAL_LLM_MODELS.values(): - raise ValueError( - f"Unknown model {self.model!r}. Please provide a valid Replicate Multi-Modal model name in:" - f" {', '.join(REPLICATE_MULTI_MODAL_LLM_MODELS.values())}" - ) - - response_iter = replicate.run(self.model, input=input_dict) - - async def gen() -> CompletionResponseAsyncGen: - text = "" - for delta in response_iter: - text += delta - yield CompletionResponse( - delta=delta, - text=text, - ) - - return gen() - - async def achat( - self, - messages: Sequence[ChatMessage], - **kwargs: Any, - ) -> ChatResponse: - raise NotImplementedError - - async def astream_chat( - self, - messages: Sequence[ChatMessage], - **kwargs: Any, - ) -> ChatResponseAsyncGen: - raise NotImplementedError diff --git a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/pyproject.toml b/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/pyproject.toml deleted file mode 100644 index a53086b36567e..0000000000000 --- a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/pyproject.toml +++ /dev/null @@ -1,62 +0,0 @@ -[build-system] -build-backend = "poetry.core.masonry.api" -requires = ["poetry-core"] - -[tool.codespell] -check-filenames = true -check-hidden = true -skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb" - -[tool.llamahub] -contains_example = false -import_path = "llama_index.multi_modal_llms.replicate_multi_modal" - -[tool.llamahub.class_authors] -ReplicateMultiModal = "llama-index" - -[tool.mypy] -disallow_untyped_defs = true -exclude = ["_static", "build", "examples", "notebooks", "venv"] -ignore_missing_imports = true -python_version = "3.8" - -[tool.poetry] -authors = ["Your Name "] -description = "llama-index multi-modal-llms replicate multi modal integration" -exclude = ["**/BUILD"] -license = "MIT" -name = "llama-index-multi-modal-llms-replicate-multi-modal" -readme = "README.md" -version = "0.1.3" - -[tool.poetry.dependencies] -python = ">=3.8.1,<4.0" -llama-index-core = "^0.10.1" - -[tool.poetry.group.dev.dependencies] -ipython = "8.10.0" -jupyter = "^1.0.0" -mypy = "0.991" -pre-commit = "3.2.0" -pylint = "2.15.10" -pytest = "7.2.1" -pytest-mock = "3.11.1" -ruff = "0.0.292" -tree-sitter-languages = "^1.8.0" -types-Deprecated = ">=0.1.0" -types-PyYAML = "^6.0.12.12" -types-protobuf = "^4.24.0.4" -types-redis = "4.5.5.0" -types-requests = "2.28.11.8" -types-setuptools = "67.1.0.0" - -[tool.poetry.group.dev.dependencies.black] -extras = ["jupyter"] -version = "<=23.9.1,>=23.7.0" - -[tool.poetry.group.dev.dependencies.codespell] -extras = ["toml"] -version = ">=v2.2.6" - -[[tool.poetry.packages]] -include = "llama_index/" diff --git a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/tests/BUILD b/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/tests/BUILD deleted file mode 100644 index dabf212d7e716..0000000000000 --- a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/tests/BUILD +++ /dev/null @@ -1 +0,0 @@ -python_tests() diff --git a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/tests/__init__.py b/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/tests/__init__.py deleted file mode 100644 index e69de29bb2d1d..0000000000000 diff --git a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/tests/test_multi-modal-llms_replicate_multi_modal.py b/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/tests/test_multi-modal-llms_replicate_multi_modal.py deleted file mode 100644 index fd71ffe8ba228..0000000000000 --- a/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-replicate-multi-modal/tests/test_multi-modal-llms_replicate_multi_modal.py +++ /dev/null @@ -1,7 +0,0 @@ -from llama_index.core.multi_modal_llms.base import MultiModalLLM -from llama_index.multi_modal_llms.replicate_multi_modal import ReplicateMultiModal - - -def test_embedding_class(): - names_of_base_classes = [b.__name__ for b in ReplicateMultiModal.__mro__] - assert MultiModalLLM.__name__ in names_of_base_classes diff --git a/llama-index-integrations/program/llama-index-program-evaporate/pyproject.toml b/llama-index-integrations/program/llama-index-program-evaporate/pyproject.toml index daa45bc60f59a..858fc64d6644e 100644 --- a/llama-index-integrations/program/llama-index-program-evaporate/pyproject.toml +++ b/llama-index-integrations/program/llama-index-program-evaporate/pyproject.toml @@ -12,7 +12,6 @@ contains_example = false import_path = "llama_index.program.evaporate" [tool.llamahub.class_authors] -BaseEvaporateProgram = "llama-index" DFEvaporateProgram = "llama-index" [tool.mypy] diff --git a/llama-index-integrations/readers/llama-index-readers-clickhouse/pyproject.toml b/llama-index-integrations/readers/llama-index-readers-clickhouse/pyproject.toml index 6ba06e3eb9b1b..6bde1f3539fcb 100644 --- a/llama-index-integrations/readers/llama-index-readers-clickhouse/pyproject.toml +++ b/llama-index-integrations/readers/llama-index-readers-clickhouse/pyproject.toml @@ -13,8 +13,6 @@ import_path = "llama_index.readers.clickhouse" [tool.llamahub.class_authors] ClickHouseReader = "llama-index" -escape_str = "llama-index" -format_list_to_string = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/readers/llama-index-readers-gpt-repo/pyproject.toml b/llama-index-integrations/readers/llama-index-readers-gpt-repo/pyproject.toml index 8d05f88c2e8e2..eeeb56e079e5f 100644 --- a/llama-index-integrations/readers/llama-index-readers-gpt-repo/pyproject.toml +++ b/llama-index-integrations/readers/llama-index-readers-gpt-repo/pyproject.toml @@ -13,9 +13,6 @@ import_path = "llama_index.readers.gpt_repo" [tool.llamahub.class_authors] GPTRepoReader = "mpoon" -get_ignore_list = "llama-index" -process_repository = "llama-index" -should_ignore = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/readers/llama-index-readers-joplin/pyproject.toml b/llama-index-integrations/readers/llama-index-readers-joplin/pyproject.toml index fb6773d946bd0..81e6261ac717d 100644 --- a/llama-index-integrations/readers/llama-index-readers-joplin/pyproject.toml +++ b/llama-index-integrations/readers/llama-index-readers-joplin/pyproject.toml @@ -13,7 +13,6 @@ import_path = "llama_index.readers.joplin" [tool.llamahub.class_authors] JoplinReader = "alondmnt" -LINK_NOTE_TEMPLATE = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/readers/llama-index-readers-myscale/pyproject.toml b/llama-index-integrations/readers/llama-index-readers-myscale/pyproject.toml index 7371b60f435f8..30854b07bf189 100644 --- a/llama-index-integrations/readers/llama-index-readers-myscale/pyproject.toml +++ b/llama-index-integrations/readers/llama-index-readers-myscale/pyproject.toml @@ -13,8 +13,6 @@ import_path = "llama_index.readers.myscale" [tool.llamahub.class_authors] MyScaleReader = "llama-index" -escape_str = "llama-index" -format_list_to_string = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/response_synthesizers/llama-index-response-synthesizers-google/pyproject.toml b/llama-index-integrations/response_synthesizers/llama-index-response-synthesizers-google/pyproject.toml index fb0dfccb827eb..23fce426e2f87 100644 --- a/llama-index-integrations/response_synthesizers/llama-index-response-synthesizers-google/pyproject.toml +++ b/llama-index-integrations/response_synthesizers/llama-index-response-synthesizers-google/pyproject.toml @@ -13,8 +13,6 @@ import_path = "llama_index.response_synthesizers.google" [tool.llamahub.class_authors] GoogleTextSynthesizer = "llama-index" -SynthesizedResponse = "llama-index" -set_google_config = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/tools/llama-index-tools-azure-cv/pyproject.toml b/llama-index-integrations/tools/llama-index-tools-azure-cv/pyproject.toml index c7e0fd37e7c8a..41ee0901ee965 100644 --- a/llama-index-integrations/tools/llama-index-tools-azure-cv/pyproject.toml +++ b/llama-index-integrations/tools/llama-index-tools-azure-cv/pyproject.toml @@ -13,7 +13,6 @@ import_path = "llama_index.tools.azure_cv" [tool.llamahub.class_authors] AzureCVToolSpec = "ajhofmann" -CV_URL_TMPL = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/tools/llama-index-tools-azure-translate/pyproject.toml b/llama-index-integrations/tools/llama-index-tools-azure-translate/pyproject.toml index 0a9d6b61c3a3b..cef3094efcf81 100644 --- a/llama-index-integrations/tools/llama-index-tools-azure-translate/pyproject.toml +++ b/llama-index-integrations/tools/llama-index-tools-azure-translate/pyproject.toml @@ -13,7 +13,6 @@ import_path = "llama_index.tools.azure_translate" [tool.llamahub.class_authors] AzureTranslateToolSpec = "ajhofmann" -ENDPOINT_BASE_URL = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/tools/llama-index-tools-bing-search/pyproject.toml b/llama-index-integrations/tools/llama-index-tools-bing-search/pyproject.toml index a850d18c52b4a..3cc4bf5e19e10 100644 --- a/llama-index-integrations/tools/llama-index-tools-bing-search/pyproject.toml +++ b/llama-index-integrations/tools/llama-index-tools-bing-search/pyproject.toml @@ -13,7 +13,6 @@ import_path = "llama_index.tools.bing_search" [tool.llamahub.class_authors] BingSearchToolSpec = "ajhofmann" -ENDPOINT_BASE_URL = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/tools/llama-index-tools-google/pyproject.toml b/llama-index-integrations/tools/llama-index-tools-google/pyproject.toml index 1518feb3c1e89..ab15d7e1bb3af 100644 --- a/llama-index-integrations/tools/llama-index-tools-google/pyproject.toml +++ b/llama-index-integrations/tools/llama-index-tools-google/pyproject.toml @@ -15,7 +15,6 @@ import_path = "llama_index.tools.google" GmailToolSpec = "ajhofmann" GoogleCalendarToolSpec = "ajhofmann" GoogleSearchToolSpec = "ajhofmann" -QUERY_URL_TMPL = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/tools/llama-index-tools-requests/pyproject.toml b/llama-index-integrations/tools/llama-index-tools-requests/pyproject.toml index c9bff451cdb87..e95b74d852400 100644 --- a/llama-index-integrations/tools/llama-index-tools-requests/pyproject.toml +++ b/llama-index-integrations/tools/llama-index-tools-requests/pyproject.toml @@ -12,7 +12,6 @@ contains_example = false import_path = "llama_index.tools.requests" [tool.llamahub.class_authors] -INVALID_URL_PROMPT = "llama-index" RequestsToolSpec = "ajhofmann" [tool.mypy] diff --git a/llama-index-integrations/tools/llama-index-tools-vector-db/pyproject.toml b/llama-index-integrations/tools/llama-index-tools-vector-db/pyproject.toml index ee08c4ebeba49..247206d735314 100644 --- a/llama-index-integrations/tools/llama-index-tools-vector-db/pyproject.toml +++ b/llama-index-integrations/tools/llama-index-tools-vector-db/pyproject.toml @@ -12,7 +12,6 @@ contains_example = false import_path = "llama_index.tools.vector_db" [tool.llamahub.class_authors] -VectorDB = "llama-index" VectorDBToolSpec = "jerryjliu" [tool.mypy] diff --git a/llama-index-integrations/tools/llama-index-tools-wolfram-alpha/pyproject.toml b/llama-index-integrations/tools/llama-index-tools-wolfram-alpha/pyproject.toml index 1b84cd6ccbbfb..0ab126fedaf09 100644 --- a/llama-index-integrations/tools/llama-index-tools-wolfram-alpha/pyproject.toml +++ b/llama-index-integrations/tools/llama-index-tools-wolfram-alpha/pyproject.toml @@ -12,7 +12,6 @@ contains_example = false import_path = "llama_index.tools.wolfram_alpha" [tool.llamahub.class_authors] -QUERY_URL_TMPL = "llama-index" WolframAlphaToolSpec = "ajhofmann" [tool.mypy] diff --git a/llama-index-integrations/tools/llama-index-tools-zapier/pyproject.toml b/llama-index-integrations/tools/llama-index-tools-zapier/pyproject.toml index b3f516904fc32..8bc4a661605c8 100644 --- a/llama-index-integrations/tools/llama-index-tools-zapier/pyproject.toml +++ b/llama-index-integrations/tools/llama-index-tools-zapier/pyproject.toml @@ -12,7 +12,6 @@ contains_example = false import_path = "llama_index.tools.zapier" [tool.llamahub.class_authors] -ACTION_URL_TMPL = "llama-index" ZapierToolSpec = "ajhofmann" [tool.mypy] diff --git a/llama-index-integrations/vector_stores/llama-index-vector-stores-azureaisearch/pyproject.toml b/llama-index-integrations/vector_stores/llama-index-vector-stores-azureaisearch/pyproject.toml index 0aaf35cafb75b..bc7278d31edb6 100644 --- a/llama-index-integrations/vector_stores/llama-index-vector-stores-azureaisearch/pyproject.toml +++ b/llama-index-integrations/vector_stores/llama-index-vector-stores-azureaisearch/pyproject.toml @@ -14,8 +14,6 @@ import_path = "llama_index.vector_stores.azureaisearch" [tool.llamahub.class_authors] AzureAISearchVectorStore = "llama-index" CognitiveSearchVectorStore = "llama-index" -IndexManagement = "llama-index" -MetadataIndexFieldType = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/vector_stores/llama-index-vector-stores-google/pyproject.toml b/llama-index-integrations/vector_stores/llama-index-vector-stores-google/pyproject.toml index a2afc489f23d8..dfe95c3f5be9e 100644 --- a/llama-index-integrations/vector_stores/llama-index-vector-stores-google/pyproject.toml +++ b/llama-index-integrations/vector_stores/llama-index-vector-stores-google/pyproject.toml @@ -13,7 +13,6 @@ import_path = "llama_index.vector_stores.google" [tool.llamahub.class_authors] GoogleVectorStore = "llama-index" -set_google_config = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/pyproject.toml b/llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/pyproject.toml index c766769a1e271..1d837dd279f49 100644 --- a/llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/pyproject.toml +++ b/llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/pyproject.toml @@ -12,7 +12,6 @@ contains_example = false import_path = "llama_index.vector_stores.opensearch" [tool.llamahub.class_authors] -OpensearchVectorClient = "llama-index" OpensearchVectorStore = "llama-index" [tool.mypy] diff --git a/llama-index-packs/llama-index-packs-agent-search-retriever/pyproject.toml b/llama-index-packs/llama-index-packs-agent-search-retriever/pyproject.toml index 2463d516f1929..f46a14bf17048 100644 --- a/llama-index-packs/llama-index-packs-agent-search-retriever/pyproject.toml +++ b/llama-index-packs/llama-index-packs-agent-search-retriever/pyproject.toml @@ -12,7 +12,6 @@ contains_example = true import_path = "llama_index.packs.agent_search_retriever" [tool.llamahub.class_authors] -AgentSearchRetriever = "llama-index" AgentSearchRetrieverPack = "logan-markewich" [tool.mypy] diff --git a/llama-index-packs/llama-index-packs-self-rag/pyproject.toml b/llama-index-packs/llama-index-packs-self-rag/pyproject.toml index 71edfaf0e4c38..4dd1561fbb3db 100644 --- a/llama-index-packs/llama-index-packs-self-rag/pyproject.toml +++ b/llama-index-packs/llama-index-packs-self-rag/pyproject.toml @@ -13,7 +13,6 @@ import_path = "llama_index.packs.self_rag" [tool.llamahub.class_authors] SelfRAGPack = "mmaatouk" -SelfRAGQueryEngine = "llama-index" [tool.mypy] disallow_untyped_defs = true diff --git a/llama-index-packs/llama-index-packs-vanna/pyproject.toml b/llama-index-packs/llama-index-packs-vanna/pyproject.toml index d14821a5fd941..bc73b75816600 100644 --- a/llama-index-packs/llama-index-packs-vanna/pyproject.toml +++ b/llama-index-packs/llama-index-packs-vanna/pyproject.toml @@ -13,7 +13,6 @@ import_path = "llama_index.packs.vanna" [tool.llamahub.class_authors] VannaPack = "jerryjliu" -VannaQueryEngine = "llama-index" [tool.mypy] disallow_untyped_defs = true From 0ccb11ee9eae2e90981c188b67a4812114b46be9 Mon Sep 17 00:00:00 2001 From: Jerry Liu Date: Sat, 24 Feb 2024 13:43:04 -0800 Subject: [PATCH 21/30] add fireworks cookbook (#11360) --- docs/examples/llm/fireworks_cookbook.ipynb | 300 ++++++++++++++++++ .../llama_index/llms/fireworks/base.py | 1 + .../llama-index-llms-fireworks/pyproject.toml | 2 +- 3 files changed, 302 insertions(+), 1 deletion(-) create mode 100644 docs/examples/llm/fireworks_cookbook.ipynb diff --git a/docs/examples/llm/fireworks_cookbook.ipynb b/docs/examples/llm/fireworks_cookbook.ipynb new file mode 100644 index 0000000000000..82bf070710893 --- /dev/null +++ b/docs/examples/llm/fireworks_cookbook.ipynb @@ -0,0 +1,300 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "9fd54a32", + "metadata": {}, + "source": [ + "\"Open" + ] + }, + { + "cell_type": "markdown", + "id": "9e3a8796-edc8-43f2-94ad-fe4fb20d70ed", + "metadata": {}, + "source": [ + "# Fireworks Function Calling Cookbook\n", + "\n", + "Fireworks.ai supports function calling for its LLMs, similar to OpenAI. This lets users directly describe the set of tools/functions available and have the model dynamically pick the right function calls to invoke, without complex prompting on the user's part.\n", + "\n", + "Since our Fireworks LLM directly subclasses OpenAI, we can use our existing abstractions with Fireworks.\n", + "\n", + "We show this on three levels: directly on the model API, as part of a Pydantic Program (structured output extraction), and as part of an agent." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3f6f8702", + "metadata": {}, + "outputs": [], + "source": [ + "%pip install llama-index-llms-fireworks" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "83ea30ee", + "metadata": {}, + "outputs": [], + "source": [ + "%pip install llama-index" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b070abb8-fa3f-4892-b23e-3ae91d0bf340", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "\n", + "os.environ[\"FIREWORKS_API_KEY\"] = \"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5497a17f-1099-4baf-884a-3620705be350", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/jerryliu/Programming/gpt_index/.venv/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + } + ], + "source": [ + "from llama_index.llms.fireworks import Fireworks\n", + "\n", + "## define fireworks model\n", + "llm = Fireworks(\n", + " model=\"accounts/fireworks/models/firefunction-v1\", temperature=0\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "b007403c-6b7a-420c-92f1-4171d05ed9bb", + "metadata": {}, + "source": [ + "## Function Calling on the LLM Module\n", + "\n", + "You can directly input function calls on the LLM module." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "015c2d39", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ChatCompletionMessageToolCall(id='call_34ZaM0xPl1cveODjVUpO78ra', function=Function(arguments='{\"name\": \"Crazy in Love\", \"artist\": \"Beyonce\"}', name='Song'), type='function', index=0)]\n" + ] + } + ], + "source": [ + "from pydantic import BaseModel\n", + "from llama_index.llms.openai.utils import to_openai_tool\n", + "\n", + "\n", + "class Song(BaseModel):\n", + " \"\"\"A song with name and artist\"\"\"\n", + "\n", + " name: str\n", + " artist: str\n", + "\n", + "\n", + "# this converts pydantic model into function to extract structured outputs\n", + "song_fn = to_openai_tool(Song)\n", + "\n", + "\n", + "response = llm.complete(\"Generate a song from Beyonce\", tools=[song_fn])\n", + "tool_calls = response.additional_kwargs[\"tool_calls\"]\n", + "print(tool_calls)" + ] + }, + { + "cell_type": "markdown", + "id": "1f3e9bbe-e1ee-4396-8e03-0bb6455761fa", + "metadata": {}, + "source": [ + "## Using a Pydantic Program\n", + "\n", + "Our Pydantic programs allow structured output extraction into a Pydantic object. `OpenAIPydanticProgram` takes advantage of function calling for structured output extraction." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b1332454-6aff-464b-a428-e4c94bd24fb9", + "metadata": {}, + "outputs": [], + "source": [ + "from llama_index.program.openai import OpenAIPydanticProgram" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "40de5e32-e015-419a-8faf-01ffd0e45222", + "metadata": {}, + "outputs": [], + "source": [ + "prompt_template_str = \"Generate a song about {artist_name}\"\n", + "program = OpenAIPydanticProgram.from_defaults(\n", + " output_cls=Song, prompt_template_str=prompt_template_str, llm=llm\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "247c9c74-86c3-41a6-9579-93db817557c6", + "metadata": {}, + "outputs": [], + "source": [ + "output = program(artist_name=\"Eminem\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c1ebc517-469e-49b0-9197-708cf34b8454", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Song(name='Rap God', artist='Eminem')" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "output" + ] + }, + { + "cell_type": "markdown", + "id": "af7d9e57-5fa6-43ed-93f1-36841b688289", + "metadata": {}, + "source": [ + "## Using An OpenAI Agent" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a8347ca9-98fb-4f65-a644-dc50abeb39fb", + "metadata": {}, + "outputs": [], + "source": [ + "from llama_index.agent.openai import OpenAIAgent" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8340c355-5e05-4c90-a1f7-719111ad4cd1", + "metadata": {}, + "outputs": [], + "source": [ + "from llama_index.core.tools import BaseTool, FunctionTool\n", + "\n", + "\n", + "def multiply(a: int, b: int) -> int:\n", + " \"\"\"Multiple two integers and returns the result integer\"\"\"\n", + " return a * b\n", + "\n", + "\n", + "multiply_tool = FunctionTool.from_defaults(fn=multiply)\n", + "\n", + "\n", + "def add(a: int, b: int) -> int:\n", + " \"\"\"Add two integers and returns the result integer\"\"\"\n", + " return a + b\n", + "\n", + "\n", + "add_tool = FunctionTool.from_defaults(fn=add)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1f96ada4-f117-4dd4-b726-6c02a6093eae", + "metadata": {}, + "outputs": [], + "source": [ + "agent = OpenAIAgent.from_tools(\n", + " [multiply_tool, add_tool], llm=llm, verbose=True\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "29df7ebd-74e4-4cd9-aedf-a4e63bd28857", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Added user message to memory: What is (121 * 3) + 42?\n", + "=== Calling Function ===\n", + "Calling function: multiply with args: {\"a\": 121, \"b\": 3}\n", + "Got output: 363\n", + "========================\n", + "\n", + "=== Calling Function ===\n", + "Calling function: add with args: {\"a\": 363, \"b\": 42}\n", + "Got output: 405\n", + "========================\n", + "\n", + "The result of (121 * 3) + 42 is 405.\n" + ] + } + ], + "source": [ + "response = agent.chat(\"What is (121 * 3) + 42?\")\n", + "print(str(response))" + ] + } + ], + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "display_name": "llama_index_v3", + "language": "python", + "name": "llama_index_v3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/llama-index-integrations/llms/llama-index-llms-fireworks/llama_index/llms/fireworks/base.py b/llama-index-integrations/llms/llama-index-llms-fireworks/llama_index/llms/fireworks/base.py index 984ea23b3ab00..3812350f48523 100644 --- a/llama-index-integrations/llms/llama-index-llms-fireworks/llama_index/llms/fireworks/base.py +++ b/llama-index-integrations/llms/llama-index-llms-fireworks/llama_index/llms/fireworks/base.py @@ -64,6 +64,7 @@ def metadata(self) -> LLMMetadata: num_output=self.max_tokens, is_chat_model=True, model_name=self.model, + is_function_calling_model=True, ) @property diff --git a/llama-index-integrations/llms/llama-index-llms-fireworks/pyproject.toml b/llama-index-integrations/llms/llama-index-llms-fireworks/pyproject.toml index 538829465ed64..fdc5bf6af3d9c 100644 --- a/llama-index-integrations/llms/llama-index-llms-fireworks/pyproject.toml +++ b/llama-index-integrations/llms/llama-index-llms-fireworks/pyproject.toml @@ -26,7 +26,7 @@ description = "llama-index llms fireworks integration" license = "MIT" name = "llama-index-llms-fireworks" readme = "README.md" -version = "0.1.1" +version = "0.1.2" [tool.poetry.dependencies] python = ">=3.8.1,<3.12" From 248055256feabc00dbcefe489a6dcde25868b619 Mon Sep 17 00:00:00 2001 From: Shirokov Artemii Date: Sun, 25 Feb 2024 04:07:59 +0100 Subject: [PATCH 22/30] FIx JSON Query Engine (#11361) FIx JSON Query --- .../llama_index/core/indices/struct_store/json_query.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/llama-index-core/llama_index/core/indices/struct_store/json_query.py b/llama-index-core/llama_index/core/indices/struct_store/json_query.py index 9ae4ed84a6c21..4a76dcf513511 100644 --- a/llama-index-core/llama_index/core/indices/struct_store/json_query.py +++ b/llama-index-core/llama_index/core/indices/struct_store/json_query.py @@ -64,7 +64,7 @@ def default_output_processor(llm_output: str, json_value: JSONType) -> JSONType: key = expression.split(".")[ -1 ] # Extracting "title" from "$.title", for example - results[key] = datum[0].value + results[key] = ", ".join(str(i.value) for i in datum) except Exception as exc: raise ValueError(f"Invalid JSON Path: {expression}") from exc From 6ad5ecdf7a7782c9703a12a0eaec0a9ff634c703 Mon Sep 17 00:00:00 2001 From: nabila <36169471+nabsabraham@users.noreply.github.com> Date: Sat, 24 Feb 2024 22:14:01 -0500 Subject: [PATCH 23/30] Changing CohereEmbedding to _embed with input_types (#11288) * setting _embed with input_types * bring back override * fix validation for tests --------- Co-authored-by: Logan Markewich --- .../llama_index/embeddings/cohere/base.py | 94 ++++++++++++------- 1 file changed, 58 insertions(+), 36 deletions(-) diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-cohere/llama_index/embeddings/cohere/base.py b/llama-index-integrations/embeddings/llama-index-embeddings-cohere/llama_index/embeddings/cohere/base.py index 39b7c11501a4a..026de4d22b6b6 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-cohere/llama_index/embeddings/cohere/base.py +++ b/llama-index-integrations/embeddings/llama-index-embeddings-cohere/llama_index/embeddings/cohere/base.py @@ -42,27 +42,39 @@ class CohereAITruncate(str, Enum): CAT = CohereAITruncate # This list would be used for model name and input type validation -VALID_MODEL_INPUT_TYPES = [ - (CAMN.ENGLISH_V3, CAIT.SEARCH_QUERY), - (CAMN.ENGLISH_LIGHT_V3, CAIT.SEARCH_QUERY), - (CAMN.MULTILINGUAL_V3, CAIT.SEARCH_QUERY), - (CAMN.MULTILINGUAL_LIGHT_V3, CAIT.SEARCH_QUERY), - (CAMN.ENGLISH_V3, CAIT.SEARCH_DOCUMENT), - (CAMN.ENGLISH_LIGHT_V3, CAIT.SEARCH_DOCUMENT), - (CAMN.MULTILINGUAL_V3, CAIT.SEARCH_DOCUMENT), - (CAMN.MULTILINGUAL_LIGHT_V3, CAIT.SEARCH_DOCUMENT), - (CAMN.ENGLISH_V3, CAIT.CLASSIFICATION), - (CAMN.ENGLISH_LIGHT_V3, CAIT.CLASSIFICATION), - (CAMN.MULTILINGUAL_V3, CAIT.CLASSIFICATION), - (CAMN.MULTILINGUAL_LIGHT_V3, CAIT.CLASSIFICATION), - (CAMN.ENGLISH_V3, CAIT.CLUSTERING), - (CAMN.ENGLISH_LIGHT_V3, CAIT.CLUSTERING), - (CAMN.MULTILINGUAL_V3, CAIT.CLUSTERING), - (CAMN.MULTILINGUAL_LIGHT_V3, CAIT.CLUSTERING), - (CAMN.ENGLISH_V2, None), - (CAMN.ENGLISH_LIGHT_V2, None), - (CAMN.MULTILINGUAL_V2, None), -] +VALID_MODEL_INPUT_TYPES = { + CAMN.ENGLISH_V3: [ + None, + CAIT.SEARCH_QUERY, + CAIT.SEARCH_DOCUMENT, + CAIT.CLASSIFICATION, + CAIT.CLUSTERING, + ], + CAMN.ENGLISH_LIGHT_V3: [ + None, + CAIT.SEARCH_QUERY, + CAIT.SEARCH_DOCUMENT, + CAIT.CLASSIFICATION, + CAIT.CLUSTERING, + ], + CAMN.MULTILINGUAL_V3: [ + None, + CAIT.SEARCH_QUERY, + CAIT.SEARCH_DOCUMENT, + CAIT.CLASSIFICATION, + CAIT.CLUSTERING, + ], + CAMN.MULTILINGUAL_LIGHT_V3: [ + None, + CAIT.SEARCH_QUERY, + CAIT.SEARCH_DOCUMENT, + CAIT.CLASSIFICATION, + CAIT.CLUSTERING, + ], + CAMN.ENGLISH_V2: [None], + CAMN.ENGLISH_LIGHT_V2: [None], + CAMN.MULTILINGUAL_V2: [None], +} VALID_TRUNCATE_OPTIONS = [CAT.START, CAT.END, CAT.NONE] @@ -74,12 +86,14 @@ class CohereEmbedding(BaseEmbedding): # Instance variables initialized via Pydantic's mechanism cohere_client: Any = Field(description="CohereAI client") truncate: str = Field(description="Truncation type - START/ END/ NONE") - input_type: Optional[str] = Field(description="Model Input type") + input_type: Optional[str] = Field( + description="Model Input type. If not provided, search_document and search_query are used when needed." + ) def __init__( self, cohere_api_key: Optional[str] = None, - model_name: str = "embed-english-v2.0", + model_name: str = "embed-english-v3.0", truncate: str = "END", input_type: Optional[str] = None, embed_batch_size: int = DEFAULT_EMBED_BATCH_SIZE, @@ -99,9 +113,12 @@ def __init__( this model is supported and that the input type provided is compatible with the model. """ # Validate model_name and input_type - if (model_name, input_type) not in VALID_MODEL_INPUT_TYPES: + if model_name not in VALID_MODEL_INPUT_TYPES: + raise ValueError(f"{model_name} is not a valid model name") + + if input_type not in VALID_MODEL_INPUT_TYPES[model_name]: raise ValueError( - f"{(model_name, input_type)} is not valid for model '{model_name}'" + f"{input_type} is not a valid input type for the provided model." ) if truncate not in VALID_TRUNCATE_OPTIONS: @@ -111,8 +128,8 @@ def __init__( cohere_client=cohere.Client(cohere_api_key, client_name="llama_index"), cohere_api_key=cohere_api_key, model_name=model_name, - truncate=truncate, input_type=input_type, + truncate=truncate, embed_batch_size=embed_batch_size, callback_manager=callback_manager, ) @@ -121,12 +138,17 @@ def __init__( def class_name(cls) -> str: return "CohereEmbedding" - def _embed(self, texts: List[str]) -> List[List[float]]: + def _embed(self, texts: List[str], input_type: str) -> List[List[float]]: """Embed sentences using Cohere.""" - if self.input_type: + if self.model_name in [ + CAMN.ENGLISH_V3, + CAMN.ENGLISH_LIGHT_V3, + CAMN.MULTILINGUAL_V3, + CAMN.MULTILINGUAL_LIGHT_V3, + ]: result = self.cohere_client.embed( texts=texts, - input_type=self.input_type, + input_type=self.input_type or input_type, model=self.model_name, truncate=self.truncate, ).embeddings @@ -137,21 +159,21 @@ def _embed(self, texts: List[str]) -> List[List[float]]: return [list(map(float, e)) for e in result] def _get_query_embedding(self, query: str) -> List[float]: - """Get query embedding.""" - return self._embed([query])[0] + """Get query embedding. For query embeddings, input_type='search_query'.""" + return self._embed([query], input_type="search_query")[0] async def _aget_query_embedding(self, query: str) -> List[float]: - """Get query embedding async.""" - return self._get_query_embedding(query) + """Get query embedding async. For query embeddings, input_type='search_query'.""" + return self._get_query_embedding(query, input_type="search_query") def _get_text_embedding(self, text: str) -> List[float]: """Get text embedding.""" - return self._embed([text])[0] + return self._embed([text], input_type="search_document")[0] async def _aget_text_embedding(self, text: str) -> List[float]: """Get text embedding async.""" - return self._get_text_embedding(text) + return self._get_text_embedding(text, input_type="search_document") def _get_text_embeddings(self, texts: List[str]) -> List[List[float]]: """Get text embeddings.""" - return self._embed(texts) + return self._embed(texts, input_type="search_document") From df92320b1dce5f96e431650964e2e913bda646e2 Mon Sep 17 00:00:00 2001 From: theblackcat102 <13172147+theblackcat102@users.noreply.github.com> Date: Sun, 25 Feb 2024 19:33:39 +0800 Subject: [PATCH 24/30] [fix] remove redundant line (#11365) * [fix] remove redundant line * [fix] remove useless import in sentence window --------- Co-authored-by: theblackcat102 --- .../llama_index/core/node_parser/text/sentence_window.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/llama-index-core/llama_index/core/node_parser/text/sentence_window.py b/llama-index-core/llama_index/core/node_parser/text/sentence_window.py index 0adf48e995f31..67976eba3fd3b 100644 --- a/llama-index-core/llama_index/core/node_parser/text/sentence_window.py +++ b/llama-index-core/llama_index/core/node_parser/text/sentence_window.py @@ -10,7 +10,7 @@ default_id_func, ) from llama_index.core.node_parser.text.utils import split_by_sentence_tokenizer -from llama_index.core.schema import BaseNode, Document, MetadataMode +from llama_index.core.schema import BaseNode, Document from llama_index.core.utils import get_tqdm_iterable DEFAULT_WINDOW_SIZE = 3 @@ -93,7 +93,6 @@ def _parse_nodes( nodes_with_progress = get_tqdm_iterable(nodes, show_progress, "Parsing nodes") for node in nodes_with_progress: - self.sentence_splitter(node.get_content(metadata_mode=MetadataMode.NONE)) nodes = self.build_window_nodes_from_documents([node]) all_nodes.extend(nodes) From d2e86b4f32f2043d062d109026fa49b32ff052aa Mon Sep 17 00:00:00 2001 From: Raoof Naushad Date: Sun, 25 Feb 2024 17:04:29 +0530 Subject: [PATCH 25/30] =?UTF-8?q?[FIX]=20ModuleNotFoundError:=20No=20modul?= =?UTF-8?q?e=20named=20'llama=5Findex.img=5Futils'=20-=20=E2=80=A6=20(#113?= =?UTF-8?q?68)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit [FIX] ModuleNotFoundError: No module named 'llama_index.img_utils' - BUG(#11367) Co-authored-by: Raoof Naushad --- .../llama_index/readers/file/image_deplot/base.py | 2 +- .../llama-index-readers-file/tests/test_readers_file.py | 4 ++++ 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/image_deplot/base.py b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/image_deplot/base.py index c3b4fbb9a672e..c775ea06ed509 100644 --- a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/image_deplot/base.py +++ b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/image_deplot/base.py @@ -57,7 +57,7 @@ def load_data( self, file: Path, extra_info: Optional[Dict] = None ) -> List[Document]: """Parse file.""" - from llama_index.img_utils import img_2_b64 + from llama_index.core.img_utils import img_2_b64 from PIL import Image # load document image diff --git a/llama-index-integrations/readers/llama-index-readers-file/tests/test_readers_file.py b/llama-index-integrations/readers/llama-index-readers-file/tests/test_readers_file.py index 11fddd05a7b35..55cc5918ef08b 100644 --- a/llama-index-integrations/readers/llama-index-readers-file/tests/test_readers_file.py +++ b/llama-index-integrations/readers/llama-index-readers-file/tests/test_readers_file.py @@ -15,6 +15,7 @@ PptxReader, VideoAudioReader, XMLReader, + ImageTabularChartReader, ) @@ -63,3 +64,6 @@ def test_classes(): names_of_base_classes = [b.__name__ for b in XMLReader.__mro__] assert BaseReader.__name__ in names_of_base_classes + + names_of_base_classes = [b.__name__ for b in ImageTabularChartReader.__mro__] + assert BaseReader.__name__ in names_of_base_classes From 08377acf3d00cf2f3cabcdf4d8b4273f57c4109d Mon Sep 17 00:00:00 2001 From: Daniel Fleischer Date: Sun, 25 Feb 2024 18:21:56 +0200 Subject: [PATCH 26/30] Intel Optimization Backend Update (#11370) * IPEX backend Update the backend to IPEX (Intel extension to PyTorch). * Cleaner error --- docs/examples/embeddings/optimum_intel.ipynb | 6 ++++-- .../embeddings/huggingface_optimum_intel/base.py | 7 ++++--- .../pyproject.toml | 1 + ...mum.py => test_embeddings_huggingface_optimum_intel.py} | 0 4 files changed, 9 insertions(+), 5 deletions(-) rename llama-index-integrations/embeddings/llama-index-embeddings-huggingface-optimum-intel/tests/{test_embeddings_huggingface_optimum.py => test_embeddings_huggingface_optimum_intel.py} (100%) diff --git a/docs/examples/embeddings/optimum_intel.ipynb b/docs/examples/embeddings/optimum_intel.ipynb index 3a3c78cb0d9f3..cf5fb060de34f 100644 --- a/docs/examples/embeddings/optimum_intel.ipynb +++ b/docs/examples/embeddings/optimum_intel.ipynb @@ -18,9 +18,11 @@ "\n", "Optimized models are smaller and faster, with minimal accuracy loss, see the [documentation](https://huggingface.co/docs/optimum/main/en/intel/optimization_inc) and an [optimization guide](https://huggingface.co/docs/optimum/main/en/intel/optimization_inc) using the IntelLabs/fastRAG library. \n", "\n", - "In order to be able to load and use the quantized models, install the required dependency `pip install optimum[exporters] optimum-intel neural-compressor`. \n", + "Optimization is based on math instructions in the Xeon® 4th generation or newer processors. \n", "\n", - "Loading is done using the class `IntelEmbedding`; usage is similar to any HuggingFace local embedding model. See example." + "In order to be able to load and use the quantized models, install the required dependency `pip install optimum[exporters] optimum-intel neural-compressor intel_extension_for_pytorch`. \n", + "\n", + "Loading is done using the class `IntelEmbedding`; usage is similar to any HuggingFace local embedding model; See example:" ] }, { diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-huggingface-optimum-intel/llama_index/embeddings/huggingface_optimum_intel/base.py b/llama-index-integrations/embeddings/llama-index-embeddings-huggingface-optimum-intel/llama_index/embeddings/huggingface_optimum_intel/base.py index 719a559e5a870..6dae8bcbbc70e 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-huggingface-optimum-intel/llama_index/embeddings/huggingface_optimum_intel/base.py +++ b/llama-index-integrations/embeddings/llama-index-embeddings-huggingface-optimum-intel/llama_index/embeddings/huggingface_optimum_intel/base.py @@ -45,14 +45,15 @@ def __init__( device: Optional[str] = None, ): try: - from optimum.intel import INCModel + from optimum.intel import IPEXModel except ImportError: raise ImportError( "Optimum-Intel requires the following dependencies; please install with " - "`pip install optimum[exporters] optimum-intel neural-compressor`." + "`pip install optimum[exporters] " + "optimum-intel neural-compressor intel_extension_for_pytorch`" ) - self._model = model or INCModel.from_pretrained(folder_name) + self._model = model or IPEXModel.from_pretrained(folder_name) self._tokenizer = tokenizer or AutoTokenizer.from_pretrained(folder_name) self._device = device or infer_torch_device() diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-huggingface-optimum-intel/pyproject.toml b/llama-index-integrations/embeddings/llama-index-embeddings-huggingface-optimum-intel/pyproject.toml index b665d0d0a4f20..cd204454198c1 100644 --- a/llama-index-integrations/embeddings/llama-index-embeddings-huggingface-optimum-intel/pyproject.toml +++ b/llama-index-integrations/embeddings/llama-index-embeddings-huggingface-optimum-intel/pyproject.toml @@ -34,6 +34,7 @@ python = ">=3.8.1,<4.0" llama-index-core = "^0.10.1" llama-index-embeddings-huggingface = "^0.1.3" optimum-intel = "^1.14.0" +intel_extension_for_pytorch = "^2.2.0" neural-compressor = "^2.4.1" [tool.poetry.dependencies.optimum] diff --git a/llama-index-integrations/embeddings/llama-index-embeddings-huggingface-optimum-intel/tests/test_embeddings_huggingface_optimum.py b/llama-index-integrations/embeddings/llama-index-embeddings-huggingface-optimum-intel/tests/test_embeddings_huggingface_optimum_intel.py similarity index 100% rename from llama-index-integrations/embeddings/llama-index-embeddings-huggingface-optimum-intel/tests/test_embeddings_huggingface_optimum.py rename to llama-index-integrations/embeddings/llama-index-embeddings-huggingface-optimum-intel/tests/test_embeddings_huggingface_optimum_intel.py From 95655c1ecd68d32f70c1835283f83487e3ccf209 Mon Sep 17 00:00:00 2001 From: Sourabh Desai Date: Sun, 25 Feb 2024 09:10:07 -0800 Subject: [PATCH 27/30] add fsspec support to SimpleDirectoryReader + default file readers (#11303) * add fsspec support to SimpleDirectoryReader + default file readers * dont print warning if using default local fs * add fs kwarg to SimpleDirectoryReader.load_data for consistency * indent * add notebook for SimpleDirectoryReader with remote filesystem + fixes * pickleable metadata func --- .../simple_directory_reader.ipynb | 173 ++++++- .../simple_directory_reader_remote_fs.ipynb | 476 ++++++++++++++++++ .../llama_index/core/readers/base.py | 3 +- .../llama_index/core/readers/file/base.py | 105 +++- .../llama_index/readers/file/docs/base.py | 36 +- .../llama_index/readers/file/epub/base.py | 14 +- .../llama_index/readers/file/image/base.py | 13 +- .../llama_index/readers/file/ipynb/base.py | 12 +- .../llama_index/readers/file/markdown/base.py | 20 +- .../llama_index/readers/file/mbox/base.py | 13 +- .../llama_index/readers/file/slides/base.py | 8 +- .../llama_index/readers/file/tabular/base.py | 13 +- .../readers/file/video_audio/base.py | 18 +- 13 files changed, 836 insertions(+), 68 deletions(-) create mode 100644 docs/examples/data_connectors/simple_directory_reader_remote_fs.ipynb diff --git a/docs/examples/data_connectors/simple_directory_reader.ipynb b/docs/examples/data_connectors/simple_directory_reader.ipynb index 3f8bc97fe1ab3..cbbbc9d7f0879 100644 --- a/docs/examples/data_connectors/simple_directory_reader.ipynb +++ b/docs/examples/data_connectors/simple_directory_reader.ipynb @@ -46,7 +46,144 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement 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(3.17.0)\n", + "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /Users/sourabhdesai/Library/Caches/pypoetry/virtualenvs/llama-index-cXQhuK8v-py3.11/lib/python3.11/site-packages (from pyasn1-modules>=0.2.1->google-auth>=1.0.1->kubernetes>=28.1.0->chromadb<0.5.0,>=0.4.22->llama-index-vector-stores-chroma<0.2.0,>=0.1.1->llama-index-cli<0.2.0,>=0.1.2->llama-index) (0.5.1)\n", + "\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.3.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.0\u001b[0m\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n" + ] + } + ], "source": [ "!pip install llama-index" ] @@ -68,44 +205,38 @@ "name": "stdout", "output_type": "stream", "text": [ - "Will not apply HSTS. The HSTS database must be a regular and non-world-writable file.\n", - "ERROR: could not open HSTS store at '/home/loganm/.wget-hsts'. HSTS will be disabled.\n", - "--2023-12-21 16:34:53-- https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt\n", - "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.111.133, 185.199.108.133, 185.199.109.133, ...\n", - "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.111.133|:443... connected.\n", + "--2024-02-24 19:30:28-- https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt\n", + "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 2606:50c0:8000::154, 2606:50c0:8003::154, 2606:50c0:8002::154, ...\n", + "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|2606:50c0:8000::154|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 75042 (73K) [text/plain]\n", "Saving to: ‘data/paul_graham/paul_graham_essay1.txt’\n", "\n", - "data/paul_graham/pa 100%[===================>] 73.28K --.-KB/s in 0.04s \n", + "data/paul_graham/pa 100%[===================>] 73.28K --.-KB/s in 0.05s \n", "\n", - "2023-12-21 16:34:53 (1.81 MB/s) - ‘data/paul_graham/paul_graham_essay1.txt’ saved [75042/75042]\n", + "2024-02-24 19:30:29 (1.42 MB/s) - ‘data/paul_graham/paul_graham_essay1.txt’ saved [75042/75042]\n", "\n", - "Will not apply HSTS. The HSTS database must be a regular and non-world-writable file.\n", - "ERROR: could not open HSTS store at '/home/loganm/.wget-hsts'. 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The HSTS database must be a regular and non-world-writable file.\n", - "ERROR: could not open HSTS store at '/home/loganm/.wget-hsts'. 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This is made possible through the [`fsspec`](https://filesystem-spec.readthedocs.io/en/latest/index.html) protocol.\n", + "\n", + "This notebook will take you through an example of using `SimpleDirectoryReader` to load documents from an S3 bucket. You can either run this against an actual S3 bucket, or a locally emulated S3 bucket via [LocalStack](https://www.localstack.cloud/)." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Get Started" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: llama-index in /Users/sourabhdesai/Library/Caches/pypoetry/virtualenvs/llama-index-cXQhuK8v-py3.11/lib/python3.11/site-packages (0.10.11)\n", + "Requirement already satisfied: s3fs in /Users/sourabhdesai/Library/Caches/pypoetry/virtualenvs/llama-index-cXQhuK8v-py3.11/lib/python3.11/site-packages (2024.2.0)\n", + "Requirement already satisfied: boto3 in 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"Requirement already satisfied: zipp>=0.5 in /Users/sourabhdesai/Library/Caches/pypoetry/virtualenvs/llama-index-cXQhuK8v-py3.11/lib/python3.11/site-packages (from importlib-metadata<7.0,>=6.0->opentelemetry-api>=1.2.0->chromadb<0.5.0,>=0.4.22->llama-index-vector-stores-chroma<0.2.0,>=0.1.1->llama-index-cli<0.2.0,>=0.1.2->llama-index) (3.17.0)\n", + "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /Users/sourabhdesai/Library/Caches/pypoetry/virtualenvs/llama-index-cXQhuK8v-py3.11/lib/python3.11/site-packages (from pyasn1-modules>=0.2.1->google-auth>=1.0.1->kubernetes>=28.1.0->chromadb<0.5.0,>=0.4.22->llama-index-vector-stores-chroma<0.2.0,>=0.1.1->llama-index-cli<0.2.0,>=0.1.2->llama-index) (0.5.1)\n", + "\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.3.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.0\u001b[0m\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n" + ] + } + ], + "source": [ + "!pip install llama-index s3fs boto3" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Download Data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--2024-02-24 19:30:45-- https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt\n", + "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 2606:50c0:8000::154, 2606:50c0:8003::154, 2606:50c0:8002::154, ...\n", + "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|2606:50c0:8000::154|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 75042 (73K) [text/plain]\n", + "Saving to: ‘data/paul_graham/paul_graham_essay1.txt’\n", + "\n", + "data/paul_graham/pa 100%[===================>] 73.28K --.-KB/s in 0.04s \n", + "\n", + "2024-02-24 19:30:45 (2.00 MB/s) - ‘data/paul_graham/paul_graham_essay1.txt’ saved [75042/75042]\n", + "\n", + "--2024-02-24 19:30:45-- https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt\n", + "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 2606:50c0:8003::154, 2606:50c0:8002::154, 2606:50c0:8000::154, ...\n", + "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|2606:50c0:8003::154|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 75042 (73K) [text/plain]\n", + "Saving to: ‘data/paul_graham/paul_graham_essay2.txt’\n", + "\n", + "data/paul_graham/pa 100%[===================>] 73.28K --.-KB/s in 0.05s \n", + "\n", + "2024-02-24 19:30:45 (1.50 MB/s) - ‘data/paul_graham/paul_graham_essay2.txt’ saved [75042/75042]\n", + "\n", + "--2024-02-24 19:30:45-- https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt\n", + "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 2606:50c0:8003::154, 2606:50c0:8002::154, 2606:50c0:8000::154, ...\n", + "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|2606:50c0:8003::154|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 75042 (73K) [text/plain]\n", + "Saving to: ‘data/paul_graham/paul_graham_essay3.txt’\n", + "\n", + "data/paul_graham/pa 100%[===================>] 73.28K --.-KB/s in 0.04s \n", + "\n", + "2024-02-24 19:30:45 (1.99 MB/s) - ‘data/paul_graham/paul_graham_essay3.txt’ saved [75042/75042]\n", + "\n" + ] + } + ], + "source": [ + "!mkdir -p 'data/paul_graham/'\n", + "!wget 'https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt' -O 'data/paul_graham/paul_graham_essay1.txt'\n", + "!wget 'https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt' -O 'data/paul_graham/paul_graham_essay2.txt'\n", + "!wget 'https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt' -O 'data/paul_graham/paul_graham_essay3.txt'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# create a test-bucket in S3\n", + "import boto3\n", + "\n", + "endpoint_url = (\n", + " \"http://localhost:4566\" # use this line if you are using S3 via localstack\n", + ")\n", + "# endpoint_url = None # use this line if you are using real AWS S3\n", + "bucket_name = \"llama-index-test-bucket\"\n", + "s3 = boto3.resource(\"s3\", endpoint_url=endpoint_url)\n", + "s3.create_bucket(Bucket=bucket_name)\n", + "bucket = s3.Bucket(bucket_name)\n", + "# put the paul graham essays in the test-bucket in various subdirectories\n", + "bucket.upload_file(\n", + " \"data/paul_graham/paul_graham_essay1.txt\", \"essays/paul_graham_essay1.txt\"\n", + ")\n", + "bucket.upload_file(\n", + " \"data/paul_graham/paul_graham_essay2.txt\",\n", + " \"essays/more_essays/paul_graham_essay2.txt\",\n", + ")\n", + "bucket.upload_file(\n", + " \"data/paul_graham/paul_graham_essay3.txt\",\n", + " \"essays/even_more_essays/paul_graham_essay3.txt\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from llama_index.core import SimpleDirectoryReader" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# create the filesystem using s3fs\n", + "from s3fs import S3FileSystem\n", + "\n", + "s3_fs = S3FileSystem(anon=False, endpoint_url=endpoint_url)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Load specific files " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "reader = SimpleDirectoryReader(\n", + " input_dir=bucket_name,\n", + " fs=s3_fs,\n", + " recursive=True, # recursively searches all subdirectories\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loaded 3 docs\n" + ] + } + ], + "source": [ + "docs = reader.load_data()\n", + "print(f\"Loaded {len(docs)} docs\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Load all (top-level) files from directory" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "reader = SimpleDirectoryReader(input_dir=\"./data/paul_graham/\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loaded 3 docs\n", + "0 - {'file_path': '/Users/sourabhdesai/workspace/llama_index/docs/examples/data_connectors/data/paul_graham/paul_graham_essay1.txt', 'file_name': '/Users/sourabhdesai/workspace/llama_index/docs/examples/data_connectors/data/paul_graham/paul_graham_essay1.txt', 'file_type': 'text/plain', 'file_size': 75042, 'creation_date': '2024-02-24', 'last_modified_date': '2024-02-24', 'last_accessed_date': None}\n", + "1 - {'file_path': '/Users/sourabhdesai/workspace/llama_index/docs/examples/data_connectors/data/paul_graham/paul_graham_essay2.txt', 'file_name': '/Users/sourabhdesai/workspace/llama_index/docs/examples/data_connectors/data/paul_graham/paul_graham_essay2.txt', 'file_type': 'text/plain', 'file_size': 75042, 'creation_date': '2024-02-24', 'last_modified_date': '2024-02-24', 'last_accessed_date': None}\n", + "2 - {'file_path': '/Users/sourabhdesai/workspace/llama_index/docs/examples/data_connectors/data/paul_graham/paul_graham_essay3.txt', 'file_name': '/Users/sourabhdesai/workspace/llama_index/docs/examples/data_connectors/data/paul_graham/paul_graham_essay3.txt', 'file_type': 'text/plain', 'file_size': 75042, 'creation_date': '2024-02-24', 'last_modified_date': '2024-02-24', 'last_accessed_date': None}\n" + ] + } + ], + "source": [ + "docs = reader.load_data()\n", + "print(f\"Loaded {len(docs)} docs\")\n", + "\n", + "# show the metadata of each document\n", + "for idx, doc in enumerate(docs):\n", + " print(f\"{idx} - {doc.metadata}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loaded 3 docs\n", + "0 - {'file_path': '/Users/sourabhdesai/workspace/llama_index/docs/examples/data_connectors/data/paul_graham/paul_graham_essay1.txt', 'file_name': '/Users/sourabhdesai/workspace/llama_index/docs/examples/data_connectors/data/paul_graham/paul_graham_essay1.txt', 'file_type': 'text/plain', 'file_size': 75042, 'creation_date': '2024-02-24', 'last_modified_date': '2024-02-24', 'last_accessed_date': None}\n", + "1 - {'file_path': '/Users/sourabhdesai/workspace/llama_index/docs/examples/data_connectors/data/paul_graham/paul_graham_essay2.txt', 'file_name': '/Users/sourabhdesai/workspace/llama_index/docs/examples/data_connectors/data/paul_graham/paul_graham_essay2.txt', 'file_type': 'text/plain', 'file_size': 75042, 'creation_date': '2024-02-24', 'last_modified_date': '2024-02-24', 'last_accessed_date': None}\n", + "2 - {'file_path': '/Users/sourabhdesai/workspace/llama_index/docs/examples/data_connectors/data/paul_graham/paul_graham_essay3.txt', 'file_name': '/Users/sourabhdesai/workspace/llama_index/docs/examples/data_connectors/data/paul_graham/paul_graham_essay3.txt', 'file_type': 'text/plain', 'file_size': 75042, 'creation_date': '2024-02-24', 'last_modified_date': '2024-02-24', 'last_accessed_date': None}\n" + ] + } + ], + "source": [ + "docs = reader.load_data()\n", + "print(f\"Loaded {len(docs)} docs\")\n", + "\n", + "# show the metadata of each document\n", + "for idx, doc in enumerate(docs):\n", + " print(f\"{idx} - {doc.metadata}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Create an iterator to load files and process them as they load" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "3\n" + ] + } + ], + "source": [ + "reader = SimpleDirectoryReader(\n", + " input_dir=bucket_name,\n", + " fs=s3_fs,\n", + " recursive=True,\n", + ")\n", + "\n", + "all_docs = []\n", + "for docs in reader.iter_data():\n", + " for doc in docs:\n", + " # do something with the doc\n", + " doc.text = doc.text.upper()\n", + " all_docs.append(doc)\n", + "\n", + "print(len(all_docs))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "llama", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/llama-index-core/llama_index/core/readers/base.py b/llama-index-core/llama_index/core/readers/base.py index 7e484d24f088c..75e333166c052 100644 --- a/llama-index-core/llama_index/core/readers/base.py +++ b/llama-index-core/llama_index/core/readers/base.py @@ -1,4 +1,5 @@ """Base reader class.""" + from abc import ABC from typing import TYPE_CHECKING, Any, Dict, Iterable, List @@ -28,7 +29,7 @@ def load_langchain_documents(self, **load_kwargs: Any) -> List["LCDocument"]: class BasePydanticReader(BaseReader, BaseComponent): - """Serialiable Data Loader with Pydatnic.""" + """Serialiable Data Loader with Pydantic.""" is_remote: bool = Field( default=False, diff --git a/llama-index-core/llama_index/core/readers/file/base.py b/llama-index-core/llama_index/core/readers/file/base.py index e86f6b041e7e2..585b13f723211 100644 --- a/llama-index-core/llama_index/core/readers/file/base.py +++ b/llama-index-core/llama_index/core/readers/file/base.py @@ -3,12 +3,13 @@ import logging import mimetypes import multiprocessing -import os import warnings from datetime import datetime from functools import reduce from itertools import repeat from pathlib import Path +import fsspec +from fsspec.implementations.local import LocalFileSystem from typing import Any, Callable, Dict, Generator, List, Optional, Type from llama_index.core.readers.base import BaseReader @@ -55,29 +56,61 @@ def _try_loading_included_file_formats() -> Dict[str, Type[BaseReader]]: return default_file_reader_cls -def default_file_metadata_func(file_path: str) -> Dict: +def default_file_metadata_func( + file_path: str, fs: Optional[fsspec.AbstractFileSystem] = None +) -> Dict: """Get some handy metadate from filesystem. Args: file_path: str: file path in str """ + fs = fs or get_default_fs() + stat_result = fs.stat(file_path) + creation_date = stat_result.get("created") + last_modified_date = stat_result.get("mtime") + last_accessed_date = stat_result.get("atime") + try: + creation_date = datetime.fromtimestamp(creation_date).strftime("%Y-%m-%d") + last_modified_date = datetime.fromtimestamp(last_modified_date).strftime( + "%Y-%m-%d" + ) + last_accessed_date = datetime.fromtimestamp(last_accessed_date).strftime( + "%Y-%m-%d" + ) + except Exception: + pass return { "file_path": file_path, - "file_name": os.path.basename(file_path), + "file_name": stat_result["name"], "file_type": mimetypes.guess_type(file_path)[0], - "file_size": os.path.getsize(file_path), - "creation_date": datetime.fromtimestamp( - Path(file_path).stat().st_ctime - ).strftime("%Y-%m-%d"), - "last_modified_date": datetime.fromtimestamp( - Path(file_path).stat().st_mtime - ).strftime("%Y-%m-%d"), - "last_accessed_date": datetime.fromtimestamp( - Path(file_path).stat().st_atime - ).strftime("%Y-%m-%d"), + "file_size": stat_result.get("size"), + "creation_date": creation_date, + "last_modified_date": last_modified_date, + "last_accessed_date": last_accessed_date, } +class _DefaultFileMetadataFunc: + """ + Default file metadata function wrapper which stores the fs. + Allows for pickling of the function. + """ + + def __init__(self, fs: Optional[fsspec.AbstractFileSystem] = None): + self.fs = fs or get_default_fs() + + def __call__(self, file_path: str) -> Dict: + return default_file_metadata_func(file_path, self.fs) + + +def get_default_fs() -> fsspec.AbstractFileSystem: + return LocalFileSystem() + + +def is_default_fs(fs: fsspec.AbstractFileSystem) -> bool: + return isinstance(fs, LocalFileSystem) and not fs.auto_mkdir + + logger = logging.getLogger(__name__) @@ -111,6 +144,9 @@ class SimpleDirectoryReader(BaseReader): file_metadata (Optional[Callable[str, Dict]]): A function that takes in a filename and returns a Dict of metadata for the Document. Default is None. + fs (Optional[fsspec.AbstractFileSystem]): File system to use. Defaults + to using the local file system. Can be changed to use any remote file system + exposed via the fsspec interface. """ supported_suffix_fn: Callable = _try_loading_included_file_formats @@ -129,6 +165,7 @@ def __init__( file_extractor: Optional[Dict[str, BaseReader]] = None, num_files_limit: Optional[int] = None, file_metadata: Optional[Callable[[str], Dict]] = None, + fs: Optional[fsspec.AbstractFileSystem] = None, ) -> None: """Initialize with parameters.""" super().__init__() @@ -136,6 +173,7 @@ def __init__( if not input_dir and not input_files: raise ValueError("Must provide either `input_dir` or `input_files`.") + self.fs = fs or get_default_fs() self.errors = errors self.encoding = encoding @@ -148,12 +186,12 @@ def __init__( if input_files: self.input_files = [] for path in input_files: - if not os.path.isfile(path): + if not self.fs.isfile(path): raise ValueError(f"File {path} does not exist.") input_file = Path(path) self.input_files.append(input_file) elif input_dir: - if not os.path.isdir(input_dir): + if not self.fs.isdir(input_dir): raise ValueError(f"Directory {input_dir} does not exist.") self.input_dir = Path(input_dir) self.exclude = exclude @@ -164,7 +202,7 @@ def __init__( else: self.file_extractor = {} - self.file_metadata = file_metadata or default_file_metadata_func + self.file_metadata = file_metadata or _DefaultFileMetadataFunc(self.fs) self.filename_as_id = filename_as_id def is_hidden(self, path: Path) -> bool: @@ -188,16 +226,17 @@ def _add_files(self, input_dir: Path) -> List[Path]: for file in input_dir.glob(excluded_pattern): rejected_files.add(Path(file)) - file_refs: Generator[Path, None, None] + file_refs: List[str] = [] if self.recursive: - file_refs = Path(input_dir).rglob("*") + file_refs = self.fs.glob(str(input_dir) + "/**/*") else: - file_refs = Path(input_dir).glob("*") + file_refs = self.fs.glob(str(input_dir) + "/*") for ref in file_refs: # Manually check if file is hidden or directory instead of # in glob for backwards compatibility. - is_dir = ref.is_dir() + ref = Path(ref) + is_dir = self.fs.isdir(ref) skip_because_hidden = self.exclude_hidden and self.is_hidden(ref) skip_because_bad_ext = ( self.required_exts is not None and ref.suffix not in self.required_exts @@ -271,6 +310,7 @@ def load_file( filename_as_id: bool = False, encoding: str = "utf-8", errors: str = "ignore", + fs: Optional[fsspec.AbstractFileSystem] = None, ) -> List[Document]: """Static method for loading file. @@ -283,6 +323,7 @@ def load_file( filename_as_id (bool, optional): _description_. Defaults to False. encoding (str, optional): _description_. Defaults to "utf-8". errors (str, optional): _description_. Defaults to "ignore". + fs (Optional[fsspec.AbstractFileSystem], optional): _description_. Defaults to None. input_file (Path): File path to read file_metadata ([Callable[str, Dict]]): A function that takes @@ -295,6 +336,8 @@ def load_file( Default is utf-8. errors (str): how encoding and decoding errors are to be handled, see https://docs.python.org/3/library/functions.html#open + fs (Optional[fsspec.AbstractFileSystem]): File system to use. Defaults + to using the local file system. Can be changed to use any remote file system Returns: List[Document]: loaded documents @@ -319,7 +362,10 @@ def load_file( # load data -- catch all errors except for ImportError try: - docs = reader.load_data(input_file, extra_info=metadata) + kwargs = {"extra_info": metadata} + if fs and not is_default_fs(fs): + kwargs["fs"] = fs + docs = reader.load_data(input_file, **kwargs) except ImportError as e: # ensure that ImportError is raised so user knows # about missing dependencies @@ -340,8 +386,9 @@ def load_file( documents.extend(docs) else: # do standard read - with open(input_file, errors=errors, encoding=encoding) as f: - data = f.read() + fs = fs or get_default_fs() + with fs.open(input_file, errors=errors, encoding=encoding) as f: + data = f.read().decode(encoding, errors=errors) doc = Document(text=data, metadata=metadata or {}) if filename_as_id: @@ -352,12 +399,18 @@ def load_file( return documents def load_data( - self, show_progress: bool = False, num_workers: Optional[int] = None + self, + show_progress: bool = False, + num_workers: Optional[int] = None, + fs: Optional[fsspec.AbstractFileSystem] = None, ) -> List[Document]: """Load data from the input directory. Args: show_progress (bool): Whether to show tqdm progress bars. Defaults to False. + num_workers (Optional[int]): Number of workers to parallelize data-loading over. + fs (Optional[fsspec.AbstractFileSystem]): File system to use. If fs was specified + in the constructor, it will override the fs parameter here. Returns: List[Document]: A list of documents. @@ -365,6 +418,7 @@ def load_data( documents = [] files_to_process = self.input_files + fs = fs or self.fs if num_workers and num_workers > 1: if num_workers > multiprocessing.cpu_count(): @@ -382,6 +436,7 @@ def load_data( repeat(self.filename_as_id), repeat(self.encoding), repeat(self.errors), + repeat(fs), ), ) documents = reduce(lambda x, y: x + y, results) @@ -400,6 +455,7 @@ def load_data( filename_as_id=self.filename_as_id, encoding=self.encoding, errors=self.errors, + fs=fs, ) ) @@ -429,6 +485,7 @@ def iter_data( filename_as_id=self.filename_as_id, encoding=self.encoding, errors=self.errors, + fs=self.fs, ) documents = self._exclude_metadata(documents) diff --git a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/docs/base.py b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/docs/base.py index 1e24764dcbb23..a2db764561e60 100644 --- a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/docs/base.py +++ b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/docs/base.py @@ -3,14 +3,20 @@ Contains parsers for docx, pdf files. """ + import struct import zlib from pathlib import Path from typing import Any, Dict, List, Optional +from fsspec import AbstractFileSystem +import logging from llama_index.core.readers.base import BaseReader +from llama_index.core.readers.file.base import get_default_fs from llama_index.core.schema import Document +logger = logging.getLogger(__name__) + class PDFReader(BaseReader): """PDF parser.""" @@ -22,7 +28,10 @@ def __init__(self, return_full_document: Optional[bool] = False) -> None: self.return_full_document = return_full_document def load_data( - self, file: Path, extra_info: Optional[Dict] = None + self, + file: Path, + extra_info: Optional[Dict] = None, + fs: Optional[AbstractFileSystem] = None, ) -> List[Document]: """Parse file.""" try: @@ -31,7 +40,8 @@ def load_data( raise ImportError( "pypdf is required to read PDF files: `pip install pypdf`" ) - with open(file, "rb") as fp: + fs = fs or get_default_fs() + with fs.open(file, "rb") as fp: # Create a PDF object pdf = pypdf.PdfReader(fp) @@ -74,7 +84,10 @@ class DocxReader(BaseReader): """Docx parser.""" def load_data( - self, file: Path, extra_info: Optional[Dict] = None + self, + file: Path, + extra_info: Optional[Dict] = None, + fs: Optional[AbstractFileSystem] = None, ) -> List[Document]: """Parse file.""" try: @@ -85,7 +98,11 @@ def load_data( "`pip install docx2txt`" ) - text = docx2txt.process(file) + if fs: + with fs.open(file) as f: + text = docx2txt.process(f) + else: + text = docx2txt.process(file) metadata = {"file_name": file.name} if extra_info is not None: metadata.update(extra_info) @@ -106,7 +123,10 @@ def __init__(self, *args: Any, **kwargs: Any) -> None: self.text = "" def load_data( - self, file: Path, extra_info: Optional[Dict] = None + self, + file: Path, + extra_info: Optional[Dict] = None, + fs: Optional[AbstractFileSystem] = None, ) -> List[Document]: """Load data and extract table from Hwp file. @@ -118,6 +138,12 @@ def load_data( """ import olefile + if fs: + logger.warning( + "fs was specified but HWPReader doesn't support loading " + "from fsspec filesystems. Will load from local filesystem instead." + ) + load_file = olefile.OleFileIO(file) file_dir = load_file.listdir() if self.is_valid(file_dir) is False: diff --git a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/epub/base.py b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/epub/base.py index 78753af802dd9..02b2463623b56 100644 --- a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/epub/base.py +++ b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/epub/base.py @@ -5,16 +5,23 @@ from pathlib import Path from typing import Dict, List, Optional +import logging +from fsspec import AbstractFileSystem from llama_index.core.readers.base import BaseReader from llama_index.core.schema import Document +logger = logging.getLogger(__name__) + class EpubReader(BaseReader): """Epub Parser.""" def load_data( - self, file: Path, extra_info: Optional[Dict] = None + self, + file: Path, + extra_info: Optional[Dict] = None, + fs: Optional[AbstractFileSystem] = None, ) -> List[Document]: """Parse file.""" try: @@ -27,6 +34,11 @@ def load_data( "the EpubReader: " "`pip install EbookLib html2text`" ) + if fs: + logger.warning( + "fs was specified but EpubReader doesn't support loading " + "from fsspec filesystems. Will load from local filesystem instead." + ) text_list = [] book = epub.read_epub(file, options={"ignore_ncx": True}) diff --git a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/image/base.py b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/image/base.py index 4c49dfbccf03d..8dc94744e6c07 100644 --- a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/image/base.py +++ b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/image/base.py @@ -7,6 +7,7 @@ import re from pathlib import Path from typing import Dict, List, Optional +from fsspec import AbstractFileSystem from llama_index.core.readers.base import BaseReader from llama_index.core.schema import Document, ImageDocument @@ -53,14 +54,22 @@ def __init__( self._parse_text = parse_text def load_data( - self, file: Path, extra_info: Optional[Dict] = None + self, + file: Path, + extra_info: Optional[Dict] = None, + fs: Optional[AbstractFileSystem] = None, ) -> List[Document]: """Parse file.""" from llama_index.core.img_utils import img_2_b64 from PIL import Image # load document image - image = Image.open(file) + if fs: + with fs.open(path=file) as f: + image = Image.open(f.read()) + else: + image = Image.open(file) + if image.mode != "RGB": image = image.convert("RGB") diff --git a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/ipynb/base.py b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/ipynb/base.py index d52e143219206..fdfbf863cef05 100644 --- a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/ipynb/base.py +++ b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/ipynb/base.py @@ -1,6 +1,7 @@ import re from pathlib import Path from typing import Dict, List, Optional +from fsspec import AbstractFileSystem from llama_index.core.readers.base import BaseReader from llama_index.core.schema import Document @@ -19,7 +20,10 @@ def __init__( self._concatenate = concatenate def load_data( - self, file: Path, extra_info: Optional[Dict] = None + self, + file: Path, + extra_info: Optional[Dict] = None, + fs: Optional[AbstractFileSystem] = None, ) -> List[Document]: """Parse file.""" if file.name.endswith(".ipynb"): @@ -27,7 +31,11 @@ def load_data( import nbconvert except ImportError: raise ImportError("Please install nbconvert 'pip install nbconvert' ") - string = nbconvert.exporters.ScriptExporter().from_file(file)[0] + if fs: + with fs.open(file, encoding="utf-8") as f: + string = nbconvert.exporters.ScriptExporter().from_file(f)[0] + else: + string = nbconvert.exporters.ScriptExporter().from_file(file)[0] # split each In[] cell into a separate string splits = re.split(r"In\[\d+\]:", string) # remove the first element, which is empty diff --git a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/markdown/base.py b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/markdown/base.py index e0e39e53de5cb..5e39ca4ea5282 100644 --- a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/markdown/base.py +++ b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/markdown/base.py @@ -3,8 +3,11 @@ Contains parser for md files. """ + import re from pathlib import Path +from fsspec import AbstractFileSystem +from fsspec.implementations.local import LocalFileSystem from typing import Any, Dict, List, Optional, Tuple, cast from llama_index.core.readers.base import BaseReader @@ -85,11 +88,15 @@ def _init_parser(self) -> Dict: return {} def parse_tups( - self, filepath: Path, errors: str = "ignore" + self, + filepath: Path, + errors: str = "ignore", + fs: Optional[AbstractFileSystem] = None, ) -> List[Tuple[Optional[str], str]]: """Parse file into tuples.""" - with open(filepath, encoding="utf-8") as f: - content = f.read() + fs = fs or LocalFileSystem() + with fs.open(filepath, encoding="utf-8") as f: + content = f.read().decode(encoding="utf-8") if self._remove_hyperlinks: content = self.remove_hyperlinks(content) if self._remove_images: @@ -97,10 +104,13 @@ def parse_tups( return self.markdown_to_tups(content) def load_data( - self, file: Path, extra_info: Optional[Dict] = None + self, + file: Path, + extra_info: Optional[Dict] = None, + fs: Optional[AbstractFileSystem] = None, ) -> List[Document]: """Parse file into string.""" - tups = self.parse_tups(file) + tups = self.parse_tups(file, fs=fs) results = [] # TODO: don't include headers right now for header, value in tups: diff --git a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/mbox/base.py b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/mbox/base.py index 1ce22360053b4..f32575a78638e 100644 --- a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/mbox/base.py +++ b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/mbox/base.py @@ -3,9 +3,11 @@ Contains simple parser for mbox files. """ + import logging from pathlib import Path from typing import Any, Dict, List, Optional +from fsspec import AbstractFileSystem from llama_index.core.readers.base import BaseReader from llama_index.core.schema import Document @@ -50,7 +52,10 @@ def __init__( self.message_format = message_format def load_data( - self, file: Path, extra_info: Optional[Dict] = None + self, + file: Path, + extra_info: Optional[Dict] = None, + fs: Optional[AbstractFileSystem] = None, ) -> List[Document]: """Parse file into string.""" # Import required libraries @@ -60,6 +65,12 @@ def load_data( from bs4 import BeautifulSoup + if fs: + logger.warning( + "fs was specified but MboxReader doesn't support loading " + "from fsspec filesystems. Will load from local filesystem instead." + ) + i = 0 results: List[str] = [] # Load file using mailbox diff --git a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/slides/base.py b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/slides/base.py index 6b1ab7cdc1138..2ebd1d3751905 100644 --- a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/slides/base.py +++ b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/slides/base.py @@ -7,6 +7,7 @@ import os from pathlib import Path from typing import Dict, List, Optional +from fsspec import AbstractFileSystem from llama_index.core.readers.base import BaseReader from llama_index.core.schema import Document @@ -87,11 +88,16 @@ def load_data( self, file: Path, extra_info: Optional[Dict] = None, + fs: Optional[AbstractFileSystem] = None, ) -> List[Document]: """Parse file.""" from pptx import Presentation - presentation = Presentation(file) + if fs: + with fs.open(file) as f: + presentation = Presentation(f) + else: + presentation = Presentation(file) result = "" for i, slide in enumerate(presentation.slides): result += f"\n\nSlide #{i}: \n" diff --git a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/tabular/base.py b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/tabular/base.py index 23c7f659d728f..9b1bc097b1ac8 100644 --- a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/tabular/base.py +++ b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/tabular/base.py @@ -3,8 +3,10 @@ Contains parsers for tabular data files. """ + from pathlib import Path from typing import Any, Dict, List, Optional +from fsspec import AbstractFileSystem import pandas as pd from llama_index.core.readers.base import BaseReader @@ -93,10 +95,17 @@ def __init__( self._pandas_config = pandas_config def load_data( - self, file: Path, extra_info: Optional[Dict] = None + self, + file: Path, + extra_info: Optional[Dict] = None, + fs: Optional[AbstractFileSystem] = None, ) -> List[Document]: """Parse file.""" - df = pd.read_csv(file, **self._pandas_config) + if fs: + with fs.open(file) as f: + df = pd.read_csv(f, **self._pandas_config) + else: + df = pd.read_csv(file, **self._pandas_config) text_list = df.apply( lambda row: (self._col_joiner).join(row.astype(str).tolist()), axis=1 diff --git a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/video_audio/base.py b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/video_audio/base.py index 53551ed39e1f8..ad6b844eb9e17 100644 --- a/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/video_audio/base.py +++ b/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/video_audio/base.py @@ -3,12 +3,17 @@ Contains parsers for mp3, mp4 files. """ + from pathlib import Path from typing import Any, Dict, List, Optional, cast +import logging +from fsspec import AbstractFileSystem from llama_index.core.readers.base import BaseReader from llama_index.core.schema import Document +logger = logging.getLogger(__name__) + class VideoAudioReader(BaseReader): """Video audio parser. @@ -36,7 +41,10 @@ def __init__(self, *args: Any, model_version: str = "base", **kwargs: Any) -> No self.parser_config = {"model": model} def load_data( - self, file: Path, extra_info: Optional[Dict] = None + self, + file: Path, + extra_info: Optional[Dict] = None, + fs: Optional[AbstractFileSystem] = None, ) -> List[Document]: """Parse file.""" import whisper @@ -46,8 +54,12 @@ def load_data( from pydub import AudioSegment except ImportError: raise ImportError("Please install pydub 'pip install pydub' ") - # open file - video = AudioSegment.from_file(file, format="mp4") + if fs: + with fs.open(file, "rb") as f: + video = AudioSegment.from_file(f, format="mp4") + else: + # open file + video = AudioSegment.from_file(file, format="mp4") # Extract audio from video audio = video.split_to_mono()[0] From c96bc5069c1bb34fab53174f52cdb31111db54a6 Mon Sep 17 00:00:00 2001 From: Anoop Sharma Date: Mon, 26 Feb 2024 06:51:20 +0530 Subject: [PATCH 28/30] MockLLM (#11376) Update __init__.py --- llama-index-core/llama_index/core/llms/__init__.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/llama-index-core/llama_index/core/llms/__init__.py b/llama-index-core/llama_index/core/llms/__init__.py index 5e480086f76e9..d09954b1306c1 100644 --- a/llama-index-core/llama_index/core/llms/__init__.py +++ b/llama-index-core/llama_index/core/llms/__init__.py @@ -11,6 +11,7 @@ ) from llama_index.core.llms.custom import CustomLLM from llama_index.core.llms.llm import LLM +from llama_index.core.llms.mock import MockLLM __all__ = [ "CustomLLM", @@ -24,4 +25,5 @@ "CompletionResponseGen", "LLMMetadata", "MessageRole", + "MockLLM", ] From 14c52d42a4a12bc63db7f582e9a17c91f5984f15 Mon Sep 17 00:00:00 2001 From: Maxime Alardo Date: Sun, 25 Feb 2024 17:25:02 -0800 Subject: [PATCH 29/30] fix: add back support for python 3.12 (#11377) --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 73ba0ceacbe1f..4485f445e2671 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -47,7 +47,7 @@ repository = "https://github.com/run-llama/llama_index" version = "0.10.12" [tool.poetry.dependencies] -python = ">=3.8.1,<3.12" +python = ">=3.8.1,<4.0" llama-index-legacy = "^0.9.48" llama-index-llms-openai = "^0.1.5" llama-index-embeddings-openai = "^0.1.5" From cc8e1ee48c67dc26caf3e7b7a75a10ad44874dc2 Mon Sep 17 00:00:00 2001 From: "Huu Le (Lee)" <39040748+leehuwuj@users.noreply.github.com> Date: Mon, 26 Feb 2024 10:55:44 +0700 Subject: [PATCH 30/30] fix checking final chunk in ReAct agent (#11280) --- llama-index-core/llama_index/core/agent/react/step.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/llama-index-core/llama_index/core/agent/react/step.py b/llama-index-core/llama_index/core/agent/react/step.py index 69df6ed4dca3d..beee2fdc55e1c 100644 --- a/llama-index-core/llama_index/core/agent/react/step.py +++ b/llama-index-core/llama_index/core/agent/react/step.py @@ -341,13 +341,13 @@ def _infer_stream_chunk_is_final(self, chunk: ChatResponse) -> bool: """ latest_content = chunk.message.content if latest_content: - if not latest_content.startswith( + # doesn't follow thought-action format + if len(latest_content) > len("Thought") and not latest_content.startswith( "Thought" - ): # doesn't follow thought-action format + ): + return True + elif "Answer: " in latest_content: return True - else: - if "Answer: " in latest_content: - return True return False def _add_back_chunk_to_stream(