From 53e9f5233bf45f752ffe6bd9cd5cb011b5137970 Mon Sep 17 00:00:00 2001 From: Shorthills AI <141953346+ShorthillsAI@users.noreply.github.com> Date: Fri, 1 Mar 2024 12:54:43 +0530 Subject: [PATCH] Fixed some minor gramatical issues (#11530) * Fixed some gramatical mistakes (#82) * Update discover_llamaindex.md * Update installation.md * Update reading.md * Update starter_example.md * Update starter_example_local.md * Update v0_10_0_migration.md * Update 2024-02-28-rag-bootcamp-vector-institute.ipynb * Update multimodal.md * Update chatbots.md --- .../2024-02-28-rag-bootcamp-vector-institute.ipynb | 4 ++-- docs/use_cases/chatbots.md | 2 +- docs/use_cases/multimodal.md | 8 ++++---- 3 files changed, 7 insertions(+), 7 deletions(-) diff --git a/docs/presentations/materials/2024-02-28-rag-bootcamp-vector-institute.ipynb b/docs/presentations/materials/2024-02-28-rag-bootcamp-vector-institute.ipynb index 4524113a39298..073e5a818b24e 100644 --- a/docs/presentations/materials/2024-02-28-rag-bootcamp-vector-institute.ipynb +++ b/docs/presentations/materials/2024-02-28-rag-bootcamp-vector-institute.ipynb @@ -121,7 +121,7 @@ "\n", "3. Declaration of Research Assessment: In academia, this could refer to a statement or policy regarding how research is evaluated.\n", "\n", - "4. Digital on-Ramp's Assessment: In the field of digital technology, this could refer to an assessment tool used by the Digital On-Ramps program.\n", + "4. Digital On-Ramp's Assessment: In the field of digital technology, this could refer to an assessment tool used by the Digital On-Ramps program.\n", "\n", "Please provide more context for a more accurate definition.\n" ] @@ -371,7 +371,7 @@ "source": [ "## In Summary\n", "\n", - "- LLMs as powerful as they are, don't perform too well with knowledge-intensive tasks (domain specific, updated data, long-tail)\n", + "- LLMs as powerful as they are, don't perform too well with knowledge-intensive tasks (domain-specific, updated data, long-tail)\n", "- Context augmentation has been shown (in a few studies) to outperform LLMs without augmentation\n", "- In this notebook, we showed one such example that follows that pattern." ] diff --git a/docs/use_cases/chatbots.md b/docs/use_cases/chatbots.md index f2b37b6320b31..727884c2b1bb4 100644 --- a/docs/use_cases/chatbots.md +++ b/docs/use_cases/chatbots.md @@ -10,7 +10,7 @@ Here are some relevant resources: - [create-llama](https://blog.llamaindex.ai/create-llama-a-command-line-tool-to-generate-llamaindex-apps-8f7683021191), a command line tool that generates a full-stack chatbot application for you - [SECinsights.ai](https://www.secinsights.ai/), an open-source application that uses LlamaIndex to build a chatbot that answers questions about SEC filings - [RAGs](https://blog.llamaindex.ai/introducing-rags-your-personalized-chatgpt-experience-over-your-data-2b9d140769b1), a project inspired by OpenAI's GPTs that lets you build a low-code chatbot over your data using Streamlit -- Our [OpenAI agents](/module_guides/deploying/agents/modules.md) are all chat bots in nature +- Our [OpenAI agents](/module_guides/deploying/agents/modules.md) are all chatbots in nature ## External sources diff --git a/docs/use_cases/multimodal.md b/docs/use_cases/multimodal.md index 5aa7fba00a400..42c5e837439b6 100644 --- a/docs/use_cases/multimodal.md +++ b/docs/use_cases/multimodal.md @@ -1,10 +1,10 @@ # Multi-modal -LlamaIndex offers capabilities to not only build language-based applications, but also **multi-modal** applications - combining language and images. +LlamaIndex offers capabilities to not only build language-based applications but also **multi-modal** applications - combining language and images. ## Types of Multi-modal Use Cases -This space is actively being explored right now, but there are some fascinating use cases popping up. +This space is actively being explored right now, but some fascinating use cases are popping up. ### RAG (Retrieval Augmented Generation) @@ -73,7 +73,7 @@ maxdepth: 1 These sections show comparisons between different multi-modal models for different use cases. -### LLaVa-13, Fuyu-8B and MiniGPT-4 Multi-Modal LLM Models Comparison for Image Reasoning +### LLaVa-13, Fuyu-8B, and MiniGPT-4 Multi-Modal LLM Models Comparison for Image Reasoning These notebooks show how to use different Multi-Modal LLM models for image understanding/reasoning. The various model inferences are supported by Replicate or OpenAI GPT4-V API. We compared several popular Multi-Modal LLMs: @@ -97,7 +97,7 @@ GPT4-V: ### Simple Evaluation of Multi-Modal RAG -In this notebook guide, we'll demonstrate how to evaluate a Multi-Modal RAG system. As in the text-only case, we will consider the evaluation of Retrievers and Generators separately. As we alluded in our blog on the topic of Evaluating Multi-Modal RAGs, our approach here involves the application of adapted versions of the usual techniques for evaluating both Retriever and Generator (used for the text-only case). These adapted versions are part of the llama-index library (i.e., evaluation module), and this notebook will walk you through how you can apply them to your evaluation use-cases. +In this notebook guide, we'll demonstrate how to evaluate a Multi-Modal RAG system. As in the text-only case, we will consider the evaluation of Retrievers and Generators separately. As we alluded to in our blog on the topic of Evaluating Multi-Modal RAGs, our approach here involves the application of adapted versions of the usual techniques for evaluating both Retriever and Generator (used for the text-only case). These adapted versions are part of the llama-index library (i.e., evaluation module), and this notebook will walk you through how you can apply them to your evaluation use cases. ```{toctree} ---