From 94d907b8b978a0cfc1b12cbb90b009e08fb046c3 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Mon, 3 Jul 2023 11:11:23 +0530 Subject: [PATCH 01/36] add WIP for preparatory refactor --- knowledge_gpt/{utils => }/QA.py | 2 +- knowledge_gpt/{utils => core}/__init__.py | 0 knowledge_gpt/core/chunking.py | 32 ++++++++ knowledge_gpt/core/embedding.py | 25 ++++++ knowledge_gpt/core/parsing.py | 73 ++++++++++++++++++ knowledge_gpt/{ => core}/prompts.py | 0 knowledge_gpt/core/qa.py | 47 ++++++++++++ knowledge_gpt/main.py | 94 ++++++++++------------- knowledge_gpt/{utils/UI.py => ui.py} | 6 +- tests/test_utils.py | 2 +- 10 files changed, 225 insertions(+), 56 deletions(-) rename knowledge_gpt/{utils => }/QA.py (98%) rename knowledge_gpt/{utils => core}/__init__.py (100%) create mode 100644 knowledge_gpt/core/chunking.py create mode 100644 knowledge_gpt/core/embedding.py create mode 100644 knowledge_gpt/core/parsing.py rename knowledge_gpt/{ => core}/prompts.py (100%) create mode 100644 knowledge_gpt/core/qa.py rename knowledge_gpt/{utils/UI.py => ui.py} (72%) diff --git a/knowledge_gpt/utils/QA.py b/knowledge_gpt/QA.py similarity index 98% rename from knowledge_gpt/utils/QA.py rename to knowledge_gpt/QA.py index 1cc8e835..32b68286 100644 --- a/knowledge_gpt/utils/QA.py +++ b/knowledge_gpt/QA.py @@ -14,7 +14,7 @@ from pypdf import PdfReader from langchain.embeddings import OpenAIEmbeddings -from knowledge_gpt.prompts import STUFF_PROMPT +from knowledge_gpt.core.prompts import STUFF_PROMPT from hashlib import md5 diff --git a/knowledge_gpt/utils/__init__.py b/knowledge_gpt/core/__init__.py similarity index 100% rename from knowledge_gpt/utils/__init__.py rename to knowledge_gpt/core/__init__.py diff --git a/knowledge_gpt/core/chunking.py b/knowledge_gpt/core/chunking.py new file mode 100644 index 00000000..f12cfd0d --- /dev/null +++ b/knowledge_gpt/core/chunking.py @@ -0,0 +1,32 @@ +from langchain.docstore.document import Document +from langchain.text_splitter import RecursiveCharacterTextSplitter +from knowledge_gpt.core.parsing import File + + +def chunk_file(file: File, chunk_size: int, chunk_overlap: int = 0) -> File: + """Chunks each document in a file into smaller documents""" + + # split each document into chunks + chunked_docs = [] + for doc in file.docs: + text_splitter = RecursiveCharacterTextSplitter( + chunk_size=chunk_size, + separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""], + chunk_overlap=chunk_overlap, + ) + + chunks = text_splitter.split_text(doc.page_content) + + for i, chunk in enumerate(chunks): + doc = Document( + page_content=chunk, + metadata={ + "page": doc.metadata.get("page", 1), + "chunk": i, + "source": f"{doc.metadata.get('page', 1)}-{i}", + }, + ) + chunked_docs.append(doc) + + file.docs = chunked_docs + return file diff --git a/knowledge_gpt/core/embedding.py b/knowledge_gpt/core/embedding.py new file mode 100644 index 00000000..acec74be --- /dev/null +++ b/knowledge_gpt/core/embedding.py @@ -0,0 +1,25 @@ +from langchain.vectorstores import VectorStore +from knowledge_gpt.core.parsing import File +from langchain.vectorstores.faiss import FAISS +from langchain.embeddings import OpenAIEmbeddings +from typing import Literal + + +def embed_docs( + file: File, embeddings: Literal["openai"], vector_store: Literal["faiss"] +) -> VectorStore: + """Embeds a File and returns the vector store""" + if embeddings == "openai": + embedding_model = OpenAIEmbeddings() # type: ignore + else: + raise NotImplementedError + + if vector_store == "faiss": + index = FAISS.from_documents( + documents=file.docs, + embedding=embedding_model, + ) + else: + raise NotImplementedError + + return index diff --git a/knowledge_gpt/core/parsing.py b/knowledge_gpt/core/parsing.py new file mode 100644 index 00000000..c88cfadf --- /dev/null +++ b/knowledge_gpt/core/parsing.py @@ -0,0 +1,73 @@ +import re +from io import BytesIO +from typing import List + +import docx2txt +from langchain.docstore.document import Document +from pypdf import PdfReader +from pydantic import BaseModel + + +class File(BaseModel): + """Represents an uploaded file comprised of Documents""" + + name: str + metadata: dict[str, str | float | int] = {} + docs: List[Document] = [] + + +def parse_docx(file: BytesIO) -> str: + text = docx2txt.process(file) + # Remove multiple newlines + text = re.sub(r"\n\s*\n", "\n\n", text) + return text + + +def parse_pdf(file: BytesIO) -> List[str]: + pdf = PdfReader(file) + output = [] + for page in pdf.pages: + text = page.extract_text() + # Merge hyphenated words + text = re.sub(r"(\w+)-\n(\w+)", r"\1\2", text) + # Fix newlines in the middle of sentences + text = re.sub(r"(? str: + text = file.read().decode("utf-8") + # Remove multiple newlines + text = re.sub(r"\n\s*\n", "\n\n", text) + return text + + +def to_file(uploaded_file: BytesIO) -> File: + """Parses an uploaded file and returns a File object with Documents""" + docs = [] + file = File(name=uploaded_file.name) + + if uploaded_file.name.endswith(".pdf"): + texts = parse_pdf(uploaded_file) + for i, text in enumerate(texts): + doc = Document(page_content=text) + doc.metadata["page"] = i + 1 + docs.append(doc) + + elif uploaded_file.name.endswith(".docx"): + # No page numbers for docx + text = parse_docx(uploaded_file) + docs = [Document(page_content=text)] + + elif uploaded_file.name.endswith(".txt"): + # No page numbers for txt + text = parse_txt(uploaded_file) + docs = [Document(page_content=text)] + + file.docs = docs + return file diff --git a/knowledge_gpt/prompts.py b/knowledge_gpt/core/prompts.py similarity index 100% rename from knowledge_gpt/prompts.py rename to knowledge_gpt/core/prompts.py diff --git a/knowledge_gpt/core/qa.py b/knowledge_gpt/core/qa.py new file mode 100644 index 00000000..79614629 --- /dev/null +++ b/knowledge_gpt/core/qa.py @@ -0,0 +1,47 @@ +from typing import Any, Dict, List, Tuple +from knowledge_gpt.core.parsing import File +from langchain.chains.qa_with_sources import load_qa_with_sources_chain +from knowledge_gpt.core.prompts import STUFF_PROMPT +from langchain.docstore.document import Document +from typing import Literal +from langchain.chat_models import ChatOpenAI +from langchain.vectorstores import VectorStore + + +def get_answer( + query: str, model: Literal["openai"], index: VectorStore +) -> Tuple[Dict[str, Any], List[Document]]: + """Gets an answer to a question from a file.""" + + if model == "openai": + _model = ChatOpenAI(temperature=0) # type: ignore + else: + raise NotImplementedError + + # Get the answer + chain = load_qa_with_sources_chain( + llm=_model, + chain_type="stuff", + prompt=STUFF_PROMPT, + ) + + relevant_docs = index.similarity_search(query, k=5) + + answer = chain( + {"input_documents": relevant_docs, "question": query}, return_only_outputs=True + ) + return answer, relevant_docs + + +def get_sources(answer: Dict[str, Any], file: File) -> List[Document]: + """Gets the source documents for an answer.""" + + # Get sources for the answer + source_keys = [s for s in answer["output_text"].split("SOURCES: ")[-1].split(", ")] + + source_docs = [] + for doc in file.docs: + if doc.metadata["source"] in source_keys: + source_docs.append(doc) + + return source_docs diff --git a/knowledge_gpt/main.py b/knowledge_gpt/main.py index 18a0ee8b..2bb64548 100644 --- a/knowledge_gpt/main.py +++ b/knowledge_gpt/main.py @@ -1,20 +1,13 @@ import streamlit as st -from openai.error import OpenAIError from knowledge_gpt.components.sidebar import sidebar -from knowledge_gpt.utils.QA import ( - embed_docs, - get_answer, - get_sources, - parse_file, - text_to_docs, -) - -from knowledge_gpt.utils.UI import wrap_text_in_html, is_valid +from knowledge_gpt.ui import wrap_doc_in_html, is_valid -def clear_submit(): - st.session_state["submit"] = False +from knowledge_gpt.core.parsing import to_file +from knowledge_gpt.core.chunking import chunk_file +from knowledge_gpt.core.embedding import embed_docs +from knowledge_gpt.core.qa import get_answer, get_sources st.set_page_config(page_title="KnowledgeGPT", page_icon="📖", layout="wide") @@ -26,58 +19,55 @@ def clear_submit(): "Upload a pdf, docx, or txt file", type=["pdf", "docx", "txt"], help="Scanned documents are not supported yet!", - on_change=clear_submit, ) -index = None -texts = None -if uploaded_file is not None: - texts = parse_file(uploaded_file) - docs = text_to_docs(texts) +if not uploaded_file: + st.stop() + + +file = to_file(uploaded_file) +file = chunk_file(file, chunk_size=800, chunk_overlap=0) - try: - with st.spinner("Indexing document... This may take a while⏳"): - index = embed_docs(docs) - except OpenAIError as e: - st.error(e._message) -query = st.text_area("Ask a question about the document", on_change=clear_submit) +with st.spinner("Indexing document... This may take a while⏳"): + index = embed_docs(file=file, embeddings="openai", vector_store="faiss") + +with st.form(key="qa_form"): + query = st.text_area("Ask a question about the document") + submit = st.form_submit_button("Submit") + with st.expander("Advanced Options"): show_all_chunks = st.checkbox("Show all chunks retrieved from vector search") show_full_doc = st.checkbox("Show parsed contents of the document") -if show_full_doc and texts: +if not is_valid(index, query): + st.stop() + +if show_full_doc: with st.expander("Document"): # Hack to get around st.markdown rendering LaTeX - st.markdown(f"

{wrap_text_in_html(texts)}

", unsafe_allow_html=True) + st.markdown(f"

{wrap_doc_in_html(file.docs)}

", unsafe_allow_html=True) -button = st.button("Submit") -if button or st.session_state.get("submit"): - if not is_valid(index, query): - st.stop() - st.session_state["submit"] = True +if submit: # Output Columns answer_col, sources_col = st.columns(2) - sources = index.similarity_search(query, k=5) # type: ignore - - try: - answer = get_answer(sources, query) - if not show_all_chunks: - # Get the sources for the answer - sources = get_sources(answer, sources) - - with answer_col: - st.markdown("#### Answer") - st.markdown(answer["output_text"].split("SOURCES: ")[0]) - - with sources_col: - st.markdown("#### Sources") - for source in sources: - st.markdown(source.page_content) - st.markdown(source.metadata["source"]) - st.markdown("---") - - except OpenAIError as e: - st.error(e._message) + + answer, relevant_docs = get_answer(query, model="openai", index=index) + if not show_all_chunks: + # Get the sources for the answer + sources = get_sources(answer, file) + else: + sources = relevant_docs + + with answer_col: + st.markdown("#### Answer") + st.markdown(answer["output_text"].split("SOURCES: ")[0]) + + with sources_col: + st.markdown("#### Sources") + for source in sources: + st.markdown(source.page_content) + st.markdown(source.metadata["source"]) + st.markdown("---") diff --git a/knowledge_gpt/utils/UI.py b/knowledge_gpt/ui.py similarity index 72% rename from knowledge_gpt/utils/UI.py rename to knowledge_gpt/ui.py index 5635272e..33447474 100644 --- a/knowledge_gpt/utils/UI.py +++ b/knowledge_gpt/ui.py @@ -1,9 +1,11 @@ from typing import List import streamlit as st +from langchain.docstore.document import Document -def wrap_text_in_html(text: str | List[str]) -> str: - """Wraps each text block separated by newlines in

tags""" +def wrap_doc_in_html(docs: List[Document]) -> str: + """Wraps each page in document separated by newlines in

tags""" + text = [doc.page_content for doc in docs] if isinstance(text, list): # Add horizontal rules between pages text = "\n


\n".join(text) diff --git a/tests/test_utils.py b/tests/test_utils.py index 6636adb4..dbb4e0ee 100644 --- a/tests/test_utils.py +++ b/tests/test_utils.py @@ -1,6 +1,6 @@ from langchain.docstore.document import Document -from knowledge_gpt.utils.QA import get_sources +from knowledge_gpt.QA import get_sources def test_get_sources(): From 826aaf48f08ab8a664ef030241f4137a1eb4cc1f Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Mon, 3 Jul 2023 11:33:03 +0530 Subject: [PATCH 02/36] pass API key as kwargs to models --- knowledge_gpt/components/sidebar.py | 7 +------ knowledge_gpt/core/embedding.py | 9 ++++++--- knowledge_gpt/core/qa.py | 4 ++-- knowledge_gpt/main.py | 23 +++++++++++++++++++++-- 4 files changed, 30 insertions(+), 13 deletions(-) diff --git a/knowledge_gpt/components/sidebar.py b/knowledge_gpt/components/sidebar.py index 22ba156e..8461d029 100644 --- a/knowledge_gpt/components/sidebar.py +++ b/knowledge_gpt/components/sidebar.py @@ -7,10 +7,6 @@ load_dotenv() -def set_openai_api_key(api_key: str): - st.session_state["OPENAI_API_KEY"] = api_key - - def sidebar(): with st.sidebar: st.markdown( @@ -28,8 +24,7 @@ def sidebar(): or st.session_state.get("OPENAI_API_KEY", ""), ) - if api_key_input: - set_openai_api_key(api_key_input) + st.session_state["OPENAI_API_KEY"] = api_key_input st.markdown("---") st.markdown("# About") diff --git a/knowledge_gpt/core/embedding.py b/knowledge_gpt/core/embedding.py index acec74be..39f2217c 100644 --- a/knowledge_gpt/core/embedding.py +++ b/knowledge_gpt/core/embedding.py @@ -2,15 +2,18 @@ from knowledge_gpt.core.parsing import File from langchain.vectorstores.faiss import FAISS from langchain.embeddings import OpenAIEmbeddings -from typing import Literal +from typing import Literal, Any def embed_docs( - file: File, embeddings: Literal["openai"], vector_store: Literal["faiss"] + file: File, + embeddings: Literal["openai"], + vector_store: Literal["faiss"], + **kwargs: Any ) -> VectorStore: """Embeds a File and returns the vector store""" if embeddings == "openai": - embedding_model = OpenAIEmbeddings() # type: ignore + embedding_model = OpenAIEmbeddings(**kwargs) # type: ignore else: raise NotImplementedError diff --git a/knowledge_gpt/core/qa.py b/knowledge_gpt/core/qa.py index 79614629..f2d9bad7 100644 --- a/knowledge_gpt/core/qa.py +++ b/knowledge_gpt/core/qa.py @@ -9,12 +9,12 @@ def get_answer( - query: str, model: Literal["openai"], index: VectorStore + query: str, model: Literal["openai"], index: VectorStore, **kwargs: Any ) -> Tuple[Dict[str, Any], List[Document]]: """Gets an answer to a question from a file.""" if model == "openai": - _model = ChatOpenAI(temperature=0) # type: ignore + _model = ChatOpenAI(**kwargs) # type: ignore else: raise NotImplementedError diff --git a/knowledge_gpt/main.py b/knowledge_gpt/main.py index 2bb64548..357d755f 100644 --- a/knowledge_gpt/main.py +++ b/knowledge_gpt/main.py @@ -13,6 +13,14 @@ st.set_page_config(page_title="KnowledgeGPT", page_icon="📖", layout="wide") st.header("📖KnowledgeGPT") +openai_api_key = st.session_state.get("OPENAI_API_KEY") + +if not openai_api_key: + st.warning( + "Enter your OpenAI API key in the sidebar. You can get a key at" + " https://platform.openai.com/account/api-keys." + ) + sidebar() uploaded_file = st.file_uploader( @@ -30,7 +38,12 @@ with st.spinner("Indexing document... This may take a while⏳"): - index = embed_docs(file=file, embeddings="openai", vector_store="faiss") + index = embed_docs( + file=file, + embeddings="openai", + vector_store="faiss", + openai_api_key=openai_api_key, + ) with st.form(key="qa_form"): query = st.text_area("Ask a question about the document") @@ -54,7 +67,13 @@ # Output Columns answer_col, sources_col = st.columns(2) - answer, relevant_docs = get_answer(query, model="openai", index=index) + answer, relevant_docs = get_answer( + query, + model="openai", + index=index, + openai_api_key=openai_api_key, + temperature=0, + ) if not show_all_chunks: # Get the sources for the answer sources = get_sources(answer, file) From d777ca14a73ea9e973fa39462631f9b7ab81e7b8 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Mon, 3 Jul 2023 12:12:21 +0530 Subject: [PATCH 03/36] fix api key warning when key is set via env vars --- knowledge_gpt/main.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/knowledge_gpt/main.py b/knowledge_gpt/main.py index 357d755f..2c2b4788 100644 --- a/knowledge_gpt/main.py +++ b/knowledge_gpt/main.py @@ -13,15 +13,17 @@ st.set_page_config(page_title="KnowledgeGPT", page_icon="📖", layout="wide") st.header("📖KnowledgeGPT") +sidebar() + openai_api_key = st.session_state.get("OPENAI_API_KEY") + if not openai_api_key: st.warning( "Enter your OpenAI API key in the sidebar. You can get a key at" " https://platform.openai.com/account/api-keys." ) -sidebar() uploaded_file = st.file_uploader( "Upload a pdf, docx, or txt file", From 8ef4a6de1282db926a4ce63ac3f982b962e76a75 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Mon, 3 Jul 2023 14:33:51 +0530 Subject: [PATCH 04/36] purge obsolete code post-refactor --- knowledge_gpt/QA.py | 158 -------------------------------------------- 1 file changed, 158 deletions(-) delete mode 100644 knowledge_gpt/QA.py diff --git a/knowledge_gpt/QA.py b/knowledge_gpt/QA.py deleted file mode 100644 index 32b68286..00000000 --- a/knowledge_gpt/QA.py +++ /dev/null @@ -1,158 +0,0 @@ -import re -from io import BytesIO -from typing import Any, Dict, List - -import docx2txt -import streamlit as st -from langchain.chains.qa_with_sources import load_qa_with_sources_chain -from langchain.docstore.document import Document -from langchain.chat_models import ChatOpenAI -from langchain.text_splitter import RecursiveCharacterTextSplitter -from langchain.vectorstores import VectorStore -from langchain.vectorstores.faiss import FAISS -from openai.error import AuthenticationError -from pypdf import PdfReader - -from langchain.embeddings import OpenAIEmbeddings -from knowledge_gpt.core.prompts import STUFF_PROMPT - -from hashlib import md5 - - -def hash_func(doc: Document) -> str: - """Hash function for caching Documents""" - return md5(doc.page_content.encode("utf-8")).hexdigest() - - -@st.cache_data() -def parse_docx(file: BytesIO) -> str: - text = docx2txt.process(file) - # Remove multiple newlines - text = re.sub(r"\n\s*\n", "\n\n", text) - return text - - -@st.cache_data() -def parse_pdf(file: BytesIO) -> List[str]: - pdf = PdfReader(file) - output = [] - for page in pdf.pages: - text = page.extract_text() - # Merge hyphenated words - text = re.sub(r"(\w+)-\n(\w+)", r"\1\2", text) - # Fix newlines in the middle of sentences - text = re.sub(r"(? str: - text = file.read().decode("utf-8") - # Remove multiple newlines - text = re.sub(r"\n\s*\n", "\n\n", text) - return text - - -@st.cache_data() -def text_to_docs(text: str | List[str]) -> List[Document]: - """Converts a string or list of strings to a list of Documents - with metadata.""" - if isinstance(text, str): - # Take a single string as one page - text = [text] - page_docs = [Document(page_content=page) for page in text] - - # Add page numbers as metadata - for i, doc in enumerate(page_docs): - doc.metadata["page"] = i + 1 - - # Split pages into chunks - doc_chunks = [] - - for doc in page_docs: - text_splitter = RecursiveCharacterTextSplitter( - chunk_size=800, - separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""], - chunk_overlap=0, - ) - chunks = text_splitter.split_text(doc.page_content) - for i, chunk in enumerate(chunks): - doc = Document( - page_content=chunk, metadata={"page": doc.metadata["page"], "chunk": i} - ) - # Add sources a metadata - doc.metadata["source"] = f"{doc.metadata['page']}-{doc.metadata['chunk']}" - doc_chunks.append(doc) - return doc_chunks - - -@st.cache_data() -def parse_file(file: BytesIO) -> str | List[str]: - """Parses a file and returns a list of Documents.""" - if file.name.endswith(".pdf"): - return parse_pdf(file) - elif file.name.endswith(".docx"): - return parse_docx(file) - elif file.name.endswith(".txt"): - return parse_txt(file) - else: - raise ValueError("File type not supported!") - - -@st.cache_data(show_spinner=False, hash_funcs={Document: hash_func}) -def embed_docs(docs: List[Document]) -> VectorStore: - """Embeds a list of Documents and returns a FAISS index""" - - if not st.session_state.get("OPENAI_API_KEY"): - raise AuthenticationError( - "Enter your OpenAI API key in the sidebar. You can get a key at" - " https://platform.openai.com/account/api-keys." - ) - else: - # Embed the chunks - embeddings = OpenAIEmbeddings( - openai_api_key=st.session_state.get("OPENAI_API_KEY"), - ) # type: ignore - - index = FAISS.from_documents(docs, embeddings) - - return index - - -@st.cache_data(show_spinner=False, hash_funcs={Document: hash_func}) -def get_answer(docs: List[Document], query: str) -> Dict[str, Any]: - """Gets an answer to a question from a list of Documents.""" - - # Get the answer - chain = load_qa_with_sources_chain( - ChatOpenAI( - temperature=0, openai_api_key=st.session_state.get("OPENAI_API_KEY") - ), # type: ignore - chain_type="stuff", - prompt=STUFF_PROMPT, - ) - - answer = chain( - {"input_documents": docs, "question": query}, return_only_outputs=True - ) - return answer - - -@st.cache_data(show_spinner=False, hash_funcs={Document: hash_func}) -def get_sources(answer: Dict[str, Any], docs: List[Document]) -> List[Document]: - """Gets the source documents for an answer.""" - - # Get sources for the answer - source_keys = [s for s in answer["output_text"].split("SOURCES: ")[-1].split(", ")] - - source_docs = [] - for doc in docs: - if doc.metadata["source"] in source_keys: - source_docs.append(doc) - - return source_docs From 8fabbba5e88dd4a70844f7bf5cfeaf17ea947d86 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Mon, 3 Jul 2023 15:45:54 +0530 Subject: [PATCH 05/36] check input validation after submitting --- knowledge_gpt/main.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/knowledge_gpt/main.py b/knowledge_gpt/main.py index 2c2b4788..4d705fdf 100644 --- a/knowledge_gpt/main.py +++ b/knowledge_gpt/main.py @@ -56,8 +56,6 @@ show_all_chunks = st.checkbox("Show all chunks retrieved from vector search") show_full_doc = st.checkbox("Show parsed contents of the document") -if not is_valid(index, query): - st.stop() if show_full_doc: with st.expander("Document"): @@ -66,6 +64,9 @@ if submit: + if not is_valid(index, query): + st.stop() + # Output Columns answer_col, sources_col = st.columns(2) From 71490334c2d5da9cef6b902201b37577889d4928 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Mon, 3 Jul 2023 15:53:56 +0530 Subject: [PATCH 06/36] reimplement caching --- knowledge_gpt/core/cached.py | 29 +++++++++++++++++++++++++++++ knowledge_gpt/core/parsing.py | 6 +++++- knowledge_gpt/core/qa.py | 8 +++++--- knowledge_gpt/main.py | 14 +++++++++----- 4 files changed, 48 insertions(+), 9 deletions(-) create mode 100644 knowledge_gpt/core/cached.py diff --git a/knowledge_gpt/core/cached.py b/knowledge_gpt/core/cached.py new file mode 100644 index 00000000..32de10e9 --- /dev/null +++ b/knowledge_gpt/core/cached.py @@ -0,0 +1,29 @@ +"""Add caching decorators to expensive functions""" + +import streamlit as st + +from knowledge_gpt.core.parsing import to_file +from knowledge_gpt.core.chunking import chunk_file +from knowledge_gpt.core.embedding import embed_docs +from knowledge_gpt.core.qa import get_answer, get_sources +from knowledge_gpt.core.parsing import File + + +def file_hash_func(file: File) -> str: + """Get a unique hash for a file""" + return file.id + + +to_file = st.cache_data(show_spinner=False)(to_file) +chunk_file = st.cache_data(show_spinner=False, hash_funcs={File: file_hash_func})( + chunk_file +) +embed_docs = st.cache_data(show_spinner=False, hash_funcs={File: file_hash_func})( + embed_docs +) +get_answer = st.cache_data(show_spinner=False, hash_funcs={File: file_hash_func})( + get_answer +) +get_sources = st.cache_data(show_spinner=False, hash_funcs={File: file_hash_func})( + get_sources +) diff --git a/knowledge_gpt/core/parsing.py b/knowledge_gpt/core/parsing.py index c88cfadf..79735eca 100644 --- a/knowledge_gpt/core/parsing.py +++ b/knowledge_gpt/core/parsing.py @@ -6,12 +6,14 @@ from langchain.docstore.document import Document from pypdf import PdfReader from pydantic import BaseModel +from hashlib import md5 class File(BaseModel): """Represents an uploaded file comprised of Documents""" name: str + id: str # unique hash of the file metadata: dict[str, str | float | int] = {} docs: List[Document] = [] @@ -50,7 +52,9 @@ def parse_txt(file: BytesIO) -> str: def to_file(uploaded_file: BytesIO) -> File: """Parses an uploaded file and returns a File object with Documents""" docs = [] - file = File(name=uploaded_file.name) + id = md5(uploaded_file.read()).hexdigest() + uploaded_file.seek(0) + file = File(name=uploaded_file.name, id=id) if uploaded_file.name.endswith(".pdf"): texts = parse_pdf(uploaded_file) diff --git a/knowledge_gpt/core/qa.py b/knowledge_gpt/core/qa.py index f2d9bad7..7d35424e 100644 --- a/knowledge_gpt/core/qa.py +++ b/knowledge_gpt/core/qa.py @@ -9,9 +9,11 @@ def get_answer( - query: str, model: Literal["openai"], index: VectorStore, **kwargs: Any + query: str, model: Literal["openai"], _index: VectorStore, file: File, **kwargs: Any ) -> Tuple[Dict[str, Any], List[Document]]: - """Gets an answer to a question from a file.""" + """Gets an answer to a question from a file. + Even though the file argument is not used, it is needed to cache the function. + """ if model == "openai": _model = ChatOpenAI(**kwargs) # type: ignore @@ -25,7 +27,7 @@ def get_answer( prompt=STUFF_PROMPT, ) - relevant_docs = index.similarity_search(query, k=5) + relevant_docs = _index.similarity_search(query, k=5) answer = chain( {"input_documents": relevant_docs, "question": query}, return_only_outputs=True diff --git a/knowledge_gpt/main.py b/knowledge_gpt/main.py index 4d705fdf..27d49044 100644 --- a/knowledge_gpt/main.py +++ b/knowledge_gpt/main.py @@ -4,10 +4,13 @@ from knowledge_gpt.ui import wrap_doc_in_html, is_valid -from knowledge_gpt.core.parsing import to_file -from knowledge_gpt.core.chunking import chunk_file -from knowledge_gpt.core.embedding import embed_docs -from knowledge_gpt.core.qa import get_answer, get_sources +from knowledge_gpt.core.cached import ( + to_file, + embed_docs, + get_answer, + get_sources, + chunk_file, +) st.set_page_config(page_title="KnowledgeGPT", page_icon="📖", layout="wide") @@ -73,7 +76,8 @@ answer, relevant_docs = get_answer( query, model="openai", - index=index, + _index=index, + file=file, openai_api_key=openai_api_key, temperature=0, ) From bf401c9cfedb0c856c529015070e37a34c20d72a Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Tue, 4 Jul 2023 09:20:55 +0530 Subject: [PATCH 07/36] remove regex from parsing logic --- knowledge_gpt/core/parsing.py | 12 ------------ 1 file changed, 12 deletions(-) diff --git a/knowledge_gpt/core/parsing.py b/knowledge_gpt/core/parsing.py index 79735eca..773d8365 100644 --- a/knowledge_gpt/core/parsing.py +++ b/knowledge_gpt/core/parsing.py @@ -1,4 +1,3 @@ -import re from io import BytesIO from typing import List @@ -20,8 +19,6 @@ class File(BaseModel): def parse_docx(file: BytesIO) -> str: text = docx2txt.process(file) - # Remove multiple newlines - text = re.sub(r"\n\s*\n", "\n\n", text) return text @@ -30,13 +27,6 @@ def parse_pdf(file: BytesIO) -> List[str]: output = [] for page in pdf.pages: text = page.extract_text() - # Merge hyphenated words - text = re.sub(r"(\w+)-\n(\w+)", r"\1\2", text) - # Fix newlines in the middle of sentences - text = re.sub(r"(? List[str]: def parse_txt(file: BytesIO) -> str: text = file.read().decode("utf-8") - # Remove multiple newlines - text = re.sub(r"\n\s*\n", "\n\n", text) return text From d7ad43b10634b211214ac9a2c94fa13972e6d045 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Tue, 4 Jul 2023 10:40:03 +0530 Subject: [PATCH 08/36] refactor parsing methods --- knowledge_gpt/core/parsing.py | 90 ++++++++++++++++++----------------- 1 file changed, 46 insertions(+), 44 deletions(-) diff --git a/knowledge_gpt/core/parsing.py b/knowledge_gpt/core/parsing.py index 773d8365..2ab9edec 100644 --- a/knowledge_gpt/core/parsing.py +++ b/knowledge_gpt/core/parsing.py @@ -1,65 +1,67 @@ from io import BytesIO -from typing import List +from typing import List, Any import docx2txt from langchain.docstore.document import Document from pypdf import PdfReader -from pydantic import BaseModel from hashlib import md5 +from dataclasses import dataclass +from abc import abstractmethod -class File(BaseModel): + +@dataclass(frozen=True) +class File: """Represents an uploaded file comprised of Documents""" name: str id: str # unique hash of the file - metadata: dict[str, str | float | int] = {} + metadata: dict[str, Any] = {} docs: List[Document] = [] - -def parse_docx(file: BytesIO) -> str: - text = docx2txt.process(file) - return text - - -def parse_pdf(file: BytesIO) -> List[str]: - pdf = PdfReader(file) - output = [] - for page in pdf.pages: - text = page.extract_text() - output.append(text) - - return output + @classmethod + @abstractmethod + def from_bytes(cls, file: BytesIO) -> "File": + """Creates a File from a BytesIO object""" -def parse_txt(file: BytesIO) -> str: - text = file.read().decode("utf-8") - return text +class DocxFile(File): + @classmethod + def from_bytes(cls, file: BytesIO) -> "DocxFile": + text = docx2txt.process(file) + doc = Document(page_content=text) + return cls(name=file.name, id=md5(file.read()).hexdigest(), docs=[doc]) -def to_file(uploaded_file: BytesIO) -> File: - """Parses an uploaded file and returns a File object with Documents""" - docs = [] - id = md5(uploaded_file.read()).hexdigest() - uploaded_file.seek(0) - file = File(name=uploaded_file.name, id=id) - - if uploaded_file.name.endswith(".pdf"): - texts = parse_pdf(uploaded_file) - for i, text in enumerate(texts): +class PdfFile(File): + @classmethod + def from_bytes(cls, file: BytesIO) -> "PdfFile": + pdf = PdfReader(file) + docs = [] + for i, page in enumerate(pdf.pages): + text = page.extract_text() doc = Document(page_content=text) doc.metadata["page"] = i + 1 docs.append(doc) - - elif uploaded_file.name.endswith(".docx"): - # No page numbers for docx - text = parse_docx(uploaded_file) - docs = [Document(page_content=text)] - - elif uploaded_file.name.endswith(".txt"): - # No page numbers for txt - text = parse_txt(uploaded_file) - docs = [Document(page_content=text)] - - file.docs = docs - return file + return cls(name=file.name, id=md5(file.read()).hexdigest(), docs=docs) + + +class TxtFile(File): + @classmethod + def from_bytes(cls, file: BytesIO) -> "TxtFile": + text = file.read().decode("utf-8") + file.seek(0) + doc = Document(page_content=text) + return cls(name=file.name, id=md5(file.read()).hexdigest(), docs=[doc]) + + +def read_file(file: BytesIO) -> File: + """Reads an uploaded file and returns a File object""" + if file.name.endswith(".docx"): + return DocxFile.from_bytes(file) + elif file.name.endswith(".pdf"): + return PdfFile.from_bytes(file) + elif file.name.endswith(".txt"): + return TxtFile.from_bytes(file) + else: + raise NotImplementedError From 39d11e735a0c4a4ab04df9d2433c78bbbc42bbdb Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Tue, 4 Jul 2023 10:49:24 +0530 Subject: [PATCH 09/36] update .gitignore --- .gitignore | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index f233bd5f..ab0e45ab 100644 --- a/.gitignore +++ b/.gitignore @@ -1,5 +1,5 @@ # Local data -data/local_data/ +resources/local_data/ # Prototyping notebooks notebooks/ From c5fc3fdeb631cb35f84719ac32df296bc6887723 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Tue, 4 Jul 2023 10:50:00 +0530 Subject: [PATCH 10/36] rename directory data to resources --- {data => resources}/employment_agreement.pdf | Bin {data => resources}/paul_graham_essay.docx | Bin {data => resources}/paul_graham_essay.pdf | Bin {data => resources}/paul_graham_essay.txt | 0 {data => resources}/questions.md | 0 5 files changed, 0 insertions(+), 0 deletions(-) rename {data => resources}/employment_agreement.pdf (100%) rename {data => resources}/paul_graham_essay.docx (100%) rename {data => resources}/paul_graham_essay.pdf (100%) rename {data => resources}/paul_graham_essay.txt (100%) rename {data => resources}/questions.md (100%) diff --git a/data/employment_agreement.pdf b/resources/employment_agreement.pdf similarity index 100% rename from data/employment_agreement.pdf rename to resources/employment_agreement.pdf diff --git a/data/paul_graham_essay.docx b/resources/paul_graham_essay.docx similarity index 100% rename from data/paul_graham_essay.docx rename to resources/paul_graham_essay.docx diff --git a/data/paul_graham_essay.pdf b/resources/paul_graham_essay.pdf similarity index 100% rename from data/paul_graham_essay.pdf rename to resources/paul_graham_essay.pdf diff --git a/data/paul_graham_essay.txt b/resources/paul_graham_essay.txt similarity index 100% rename from data/paul_graham_essay.txt rename to resources/paul_graham_essay.txt diff --git a/data/questions.md b/resources/questions.md similarity index 100% rename from data/questions.md rename to resources/questions.md From 3cf8d984db6d9af089c9486bba17fee218fe8dc7 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Tue, 4 Jul 2023 11:15:36 +0530 Subject: [PATCH 11/36] use explicit constructor instead of dataclass --- knowledge_gpt/core/parsing.py | 23 ++++++++++++++--------- 1 file changed, 14 insertions(+), 9 deletions(-) diff --git a/knowledge_gpt/core/parsing.py b/knowledge_gpt/core/parsing.py index 2ab9edec..accaa539 100644 --- a/knowledge_gpt/core/parsing.py +++ b/knowledge_gpt/core/parsing.py @@ -1,23 +1,28 @@ from io import BytesIO -from typing import List, Any +from typing import List, Any, Optional import docx2txt from langchain.docstore.document import Document from pypdf import PdfReader from hashlib import md5 -from dataclasses import dataclass -from abc import abstractmethod +from abc import abstractmethod, ABC -@dataclass(frozen=True) -class File: +class File(ABC): """Represents an uploaded file comprised of Documents""" - name: str - id: str # unique hash of the file - metadata: dict[str, Any] = {} - docs: List[Document] = [] + def __init__( + self, + name: str, + id: str, + metadata: Optional[dict[str, Any]] = None, + docs: Optional[List[Document]] = None, + ): + self.name = name + self.id = id + self.metadata = metadata or {} + self.docs = docs or [] @classmethod @abstractmethod From 77aa71858e17695dd8b8d14c9fd7dbbc6b836ecc Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Tue, 4 Jul 2023 11:35:34 +0530 Subject: [PATCH 12/36] split whitespace from pages --- knowledge_gpt/core/parsing.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/knowledge_gpt/core/parsing.py b/knowledge_gpt/core/parsing.py index accaa539..177e37bc 100644 --- a/knowledge_gpt/core/parsing.py +++ b/knowledge_gpt/core/parsing.py @@ -34,7 +34,7 @@ class DocxFile(File): @classmethod def from_bytes(cls, file: BytesIO) -> "DocxFile": text = docx2txt.process(file) - doc = Document(page_content=text) + doc = Document(page_content=text.strip()) return cls(name=file.name, id=md5(file.read()).hexdigest(), docs=[doc]) @@ -45,7 +45,7 @@ def from_bytes(cls, file: BytesIO) -> "PdfFile": docs = [] for i, page in enumerate(pdf.pages): text = page.extract_text() - doc = Document(page_content=text) + doc = Document(page_content=text.strip()) doc.metadata["page"] = i + 1 docs.append(doc) return cls(name=file.name, id=md5(file.read()).hexdigest(), docs=docs) @@ -56,7 +56,7 @@ class TxtFile(File): def from_bytes(cls, file: BytesIO) -> "TxtFile": text = file.read().decode("utf-8") file.seek(0) - doc = Document(page_content=text) + doc = Document(page_content=text.strip()) return cls(name=file.name, id=md5(file.read()).hexdigest(), docs=[doc]) From d0544e97e2e90ac1af78d510da82e73b99f017cd Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Tue, 4 Jul 2023 11:51:46 +0530 Subject: [PATCH 13/36] strip consecutive newlines from parsed text --- knowledge_gpt/core/parsing.py | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/knowledge_gpt/core/parsing.py b/knowledge_gpt/core/parsing.py index 177e37bc..eaa87f1a 100644 --- a/knowledge_gpt/core/parsing.py +++ b/knowledge_gpt/core/parsing.py @@ -1,5 +1,6 @@ from io import BytesIO from typing import List, Any, Optional +import re import docx2txt from langchain.docstore.document import Document @@ -30,10 +31,18 @@ def from_bytes(cls, file: BytesIO) -> "File": """Creates a File from a BytesIO object""" +def strip_consecutive_newlines(text: str) -> str: + """Strips consecutive newlines from a string + possibly with whitespace in between + """ + return re.sub(r"\s*\n\s*", "\n", text) + + class DocxFile(File): @classmethod def from_bytes(cls, file: BytesIO) -> "DocxFile": text = docx2txt.process(file) + text = strip_consecutive_newlines(text) doc = Document(page_content=text.strip()) return cls(name=file.name, id=md5(file.read()).hexdigest(), docs=[doc]) @@ -45,6 +54,7 @@ def from_bytes(cls, file: BytesIO) -> "PdfFile": docs = [] for i, page in enumerate(pdf.pages): text = page.extract_text() + text = strip_consecutive_newlines(text) doc = Document(page_content=text.strip()) doc.metadata["page"] = i + 1 docs.append(doc) @@ -55,6 +65,7 @@ class TxtFile(File): @classmethod def from_bytes(cls, file: BytesIO) -> "TxtFile": text = file.read().decode("utf-8") + text = strip_consecutive_newlines(text) file.seek(0) doc = Document(page_content=text.strip()) return cls(name=file.name, id=md5(file.read()).hexdigest(), docs=[doc]) From 84f5c3b0503ba9c98e324061549ac7fb2706ef61 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Tue, 4 Jul 2023 11:52:27 +0530 Subject: [PATCH 14/36] add tests for parsing functions --- resources/paul_graham_essay.docx | Bin 49207 -> 0 bytes resources/samples/test_hello.docx | Bin 0 -> 12502 bytes resources/samples/test_hello.pdf | Bin 0 -> 362861 bytes resources/samples/test_hello.txt | 1 + resources/samples/test_hello_multi.docx | Bin 0 -> 12916 bytes resources/samples/test_hello_multi.pdf | Bin 0 -> 369402 bytes tests/test_parsing.py | 127 ++++++++++++++++++++++++ 7 files changed, 128 insertions(+) delete mode 100644 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z%$%Tq$%2IO@FExWf8ud-asNv`b{=jv-hc5$!njbofWOlsWnn{R&VRs=c-+AM0S5XP zU!?AVpnu_^?7{Y5y65KR`7gdaz<=8VDGM*>zib2qfjCf`n19L)LMq|EV7xs4(kW6F zq(A?K2X!(=?v IP?E&_U(@F_+yDRo literal 0 HcmV?d00001 diff --git a/tests/test_parsing.py b/tests/test_parsing.py new file mode 100644 index 00000000..af77d1d6 --- /dev/null +++ b/tests/test_parsing.py @@ -0,0 +1,127 @@ +import pytest +from io import BytesIO + +from knowledge_gpt.core.parsing import ( + DocxFile, + PdfFile, + TxtFile, + read_file, + strip_consecutive_newlines, +) +from pathlib import Path + +TESTS_ROOT = Path(__file__).parent.resolve() +PROJECT_ROOT = TESTS_ROOT.parent.resolve() +RESOURCE_ROOT = PROJECT_ROOT / "resources" +SAMPLE_ROOT = RESOURCE_ROOT / "samples" + + +def test_docx_file(): + with open(SAMPLE_ROOT / "test_hello.docx", "rb") as f: + file = BytesIO(f.read()) + file.name = "test.docx" + docx_file = DocxFile.from_bytes(file) + + assert docx_file.name == "test.docx" + assert len(docx_file.docs) == 1 + assert docx_file.docs[0].page_content == "Hello World" + + +def test_docx_file_with_multiple_pages(): + with open(SAMPLE_ROOT / "test_hello_multi.docx", "rb") as f: + file = BytesIO(f.read()) + file.name = "test.docx" + docx_file = DocxFile.from_bytes(file) + + assert docx_file.name == "test.docx" + assert len(docx_file.docs) == 1 + assert ( + docx_file.docs[0].page_content == "Hello World 1\nHello World 2\nHello World 3" + ) + + +def test_pdf_file_with_single_page(): + with open(SAMPLE_ROOT / "test_hello.pdf", "rb") as f: + file = BytesIO(f.read()) + file.name = "test_hello.pdf" + pdf_file = PdfFile.from_bytes(file) + + assert pdf_file.name == "test_hello.pdf" + assert len(pdf_file.docs) == 1 + assert pdf_file.docs[0].page_content == "Hello World" + + +def test_pdf_file_with_multiple_pages(): + with open(SAMPLE_ROOT / "test_hello_multi.pdf", "rb") as f: + file = BytesIO(f.read()) + file.name = "test_hello_multiple.pdf" + pdf_file = PdfFile.from_bytes(file) + + assert pdf_file.name == "test_hello_multiple.pdf" + assert len(pdf_file.docs) == 3 + assert pdf_file.docs[0].page_content == "Hello World 1" + assert pdf_file.docs[1].page_content == "Hello World 2" + assert pdf_file.docs[2].page_content == "Hello World 3" + + assert pdf_file.docs[0].metadata["page"] == 1 + assert pdf_file.docs[1].metadata["page"] == 2 + assert pdf_file.docs[2].metadata["page"] == 3 + + +def test_txt_file(): + with open(SAMPLE_ROOT / "test_hello.txt", "rb") as f: + file = BytesIO(f.read()) + file.name = "test.txt" + txt_file = TxtFile.from_bytes(file) + + assert txt_file.name == "test.txt" + assert len(txt_file.docs) == 1 + assert txt_file.docs[0].page_content == "Hello World" + + +def test_read_file(): + # Test the `read_file` function with each file type + for ext, FileClass in [(".docx", DocxFile), (".pdf", PdfFile), (".txt", TxtFile)]: + with open(SAMPLE_ROOT / f"test_hello{ext}", "rb") as f: + file = BytesIO(f.read()) + file.name = f"test_hello{ext}" + file_obj = read_file(file) + + assert isinstance(file_obj, FileClass) + assert file_obj.name == f"test_hello{ext}" + assert len(file_obj.docs) == 1 + assert file_obj.docs[0].page_content == "Hello World" + + +def test_read_file_not_implemented(): + file = BytesIO(b"Hello World") + file.name = "test.unknown" + with pytest.raises(NotImplementedError): + read_file(file) + + +def test_strip_consecutive_newlines(): + # Test with multiple consecutive newlines + text = "\n\n\n" + expected = "\n" + assert strip_consecutive_newlines(text) == expected + + # Test with newlines and spaces + text = "\n \n \n" + expected = "\n" + assert strip_consecutive_newlines(text) == expected + + # Test with newlines and tabs + text = "\n\t\n\t\n" + expected = "\n" + assert strip_consecutive_newlines(text) == expected + + # Test with mixed whitespace characters + text = "\n \t\n \t \n" + expected = "\n" + assert strip_consecutive_newlines(text) == expected + + # Test with no consecutive newlines + text = "\nHello\nWorld\n" + expected = "\nHello\nWorld\n" + assert strip_consecutive_newlines(text) == expected From d756a2e17e186722157d951d8cdadbbf6f652a3e Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Tue, 4 Jul 2023 11:53:57 +0530 Subject: [PATCH 15/36] remove double newlines from text splitter --- knowledge_gpt/core/chunking.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/knowledge_gpt/core/chunking.py b/knowledge_gpt/core/chunking.py index f12cfd0d..2993d4e5 100644 --- a/knowledge_gpt/core/chunking.py +++ b/knowledge_gpt/core/chunking.py @@ -11,7 +11,7 @@ def chunk_file(file: File, chunk_size: int, chunk_overlap: int = 0) -> File: for doc in file.docs: text_splitter = RecursiveCharacterTextSplitter( chunk_size=chunk_size, - separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""], + separators=["\n", ".", "!", "?", ",", " ", ""], chunk_overlap=chunk_overlap, ) From be1fc3fc0af399eac3134f0753c31002bf543254 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Tue, 4 Jul 2023 16:33:51 +0530 Subject: [PATCH 16/36] use token based splitter and fix chunk numbers --- knowledge_gpt/core/chunking.py | 17 +++++---- tests/test_chunking.py | 65 ++++++++++++++++++++++++++++++++++ 2 files changed, 76 insertions(+), 6 deletions(-) create mode 100644 tests/test_chunking.py diff --git a/knowledge_gpt/core/chunking.py b/knowledge_gpt/core/chunking.py index 2993d4e5..1aa13cb0 100644 --- a/knowledge_gpt/core/chunking.py +++ b/knowledge_gpt/core/chunking.py @@ -3,15 +3,20 @@ from knowledge_gpt.core.parsing import File -def chunk_file(file: File, chunk_size: int, chunk_overlap: int = 0) -> File: - """Chunks each document in a file into smaller documents""" +def chunk_file( + file: File, chunk_size: int, chunk_overlap: int = 0, model_name="gpt-3.5-turbo" +) -> File: + """Chunks each document in a file into smaller documents + according to the specified chunk size and overlap + where the size is determined by the number of token for the specified model. + """ # split each document into chunks chunked_docs = [] for doc in file.docs: - text_splitter = RecursiveCharacterTextSplitter( + text_splitter = RecursiveCharacterTextSplitter.from_tiktoken_encoder( + model_name=model_name, chunk_size=chunk_size, - separators=["\n", ".", "!", "?", ",", " ", ""], chunk_overlap=chunk_overlap, ) @@ -22,8 +27,8 @@ def chunk_file(file: File, chunk_size: int, chunk_overlap: int = 0) -> File: page_content=chunk, metadata={ "page": doc.metadata.get("page", 1), - "chunk": i, - "source": f"{doc.metadata.get('page', 1)}-{i}", + "chunk": i + 1, + "source": f"{doc.metadata.get('page', 1)}-{i + 1}", }, ) chunked_docs.append(doc) diff --git a/tests/test_chunking.py b/tests/test_chunking.py new file mode 100644 index 00000000..ad0aa657 --- /dev/null +++ b/tests/test_chunking.py @@ -0,0 +1,65 @@ +import pytest +from langchain.docstore.document import Document +from knowledge_gpt.core.parsing import File + +from knowledge_gpt.core.chunking import chunk_file + +from io import BytesIO + + +class FakeFile(File): + """A fake file for testing purposes""" + + @classmethod + def from_bytes(cls, file: BytesIO) -> "FakeFile": + return NotImplemented + + +@pytest.fixture +def single_page_file(): + doc = Document(page_content="This is a page.\nIt has stuff.") + file = FakeFile(name="test.txt", id="1", docs=[doc]) + return file + + +@pytest.fixture +def multi_page_file(): + docs = [ + Document(page_content="This is the first page", metadata={"page": 1}), + Document(page_content="This is the second page.", metadata={"page": 2}), + ] + file = FakeFile(name="test.pdf", id="2", docs=docs) + return file + + +def test_chunk_file_single_page_no_overlap(single_page_file): + chunked_file = chunk_file(single_page_file, chunk_size=6, chunk_overlap=0) + assert len(chunked_file.docs) == 2 # The document should be split into 2 chunks + + assert chunked_file.docs[1].page_content == "It has stuff." + assert chunked_file.docs[0].page_content == "This is a page." + + assert chunked_file.docs[0].metadata["chunk"] == 1 + assert chunked_file.docs[1].metadata["chunk"] == 2 + + assert chunked_file.docs[0].metadata["source"] == "1-1" + assert chunked_file.docs[1].metadata["source"] == "1-2" + + +def test_chunk_file_multi_page_no_overlap(multi_page_file): + chunked_file = chunk_file(multi_page_file, chunk_size=10, chunk_overlap=0) + assert ( + len(chunked_file.docs) == 2 + ) # Each of the two documents should be split into 2 chunks + + assert chunked_file.docs[0].page_content == "This is the first page" + assert chunked_file.docs[1].page_content == "This is the second page." + + assert chunked_file.docs[0].metadata["page"] == 1 + assert chunked_file.docs[1].metadata["page"] == 2 + + assert chunked_file.docs[0].metadata["chunk"] == 1 + assert chunked_file.docs[1].metadata["chunk"] == 1 + + assert chunked_file.docs[0].metadata["source"] == "1-1" + assert chunked_file.docs[1].metadata["source"] == "2-1" From 213e7baded479ce423c727ddebb73dc886422d68 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 11:26:53 +0530 Subject: [PATCH 17/36] extract FakeFile class to fake_file.py --- tests/core/fake_file.py | 10 ++++++++++ tests/test_chunking.py | 12 +----------- 2 files changed, 11 insertions(+), 11 deletions(-) create mode 100644 tests/core/fake_file.py diff --git a/tests/core/fake_file.py b/tests/core/fake_file.py new file mode 100644 index 00000000..30a5153c --- /dev/null +++ b/tests/core/fake_file.py @@ -0,0 +1,10 @@ +from knowledge_gpt.core.parsing import File +from io import BytesIO + + +class FakeFile(File): + """A fake file for testing purposes""" + + @classmethod + def from_bytes(cls, file: BytesIO) -> "FakeFile": + return NotImplemented diff --git a/tests/test_chunking.py b/tests/test_chunking.py index ad0aa657..5764b361 100644 --- a/tests/test_chunking.py +++ b/tests/test_chunking.py @@ -1,18 +1,8 @@ import pytest from langchain.docstore.document import Document -from knowledge_gpt.core.parsing import File from knowledge_gpt.core.chunking import chunk_file - -from io import BytesIO - - -class FakeFile(File): - """A fake file for testing purposes""" - - @classmethod - def from_bytes(cls, file: BytesIO) -> "FakeFile": - return NotImplemented +from tests.core.fake_file import FakeFile @pytest.fixture From 8be4d32a43244a704c2f6786169126fed2e141ea Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 11:33:03 +0530 Subject: [PATCH 18/36] implement `FolderIndex` to handle multiple files --- knowledge_gpt/core/embedding.py | 86 +++++++++++++++++++++++++-------- tests/test_embedding.py | 39 +++++++++++++++ 2 files changed, 105 insertions(+), 20 deletions(-) create mode 100644 tests/test_embedding.py diff --git a/knowledge_gpt/core/embedding.py b/knowledge_gpt/core/embedding.py index 39f2217c..d9751149 100644 --- a/knowledge_gpt/core/embedding.py +++ b/knowledge_gpt/core/embedding.py @@ -2,27 +2,73 @@ from knowledge_gpt.core.parsing import File from langchain.vectorstores.faiss import FAISS from langchain.embeddings import OpenAIEmbeddings -from typing import Literal, Any - - -def embed_docs( - file: File, - embeddings: Literal["openai"], - vector_store: Literal["faiss"], - **kwargs: Any -) -> VectorStore: - """Embeds a File and returns the vector store""" - if embeddings == "openai": - embedding_model = OpenAIEmbeddings(**kwargs) # type: ignore - else: - raise NotImplementedError +from langchain.embeddings.base import Embeddings +from langchain.vectorstores.base import VectorStore +from typing import List, TypeVar, Type +from langchain.docstore.document import Document + +VST = TypeVar("VST", bound="VectorStore") + + +class FolderIndex: + """Index for a collection of files (a folder)""" + + def __init__(self, files: List[File], index: VectorStore): + self.name: str = "default" + self.files = files + self.index: VectorStore = index + + @staticmethod + def _combine_files(files: List[File]) -> List[Document]: + """Combines all the documents in a list of files into a single list.""" + + all_texts = [] + for file in files: + for doc in file.docs: + doc.metadata["file_name"] = file.name + doc.metadata["file_id"] = file.id + all_texts.append(doc) + + return all_texts + + @classmethod + def from_files( + cls, files: List[File], embeddings: Embeddings, vector_store: Type[VST] + ) -> "FolderIndex": + """Creates an index from files.""" - if vector_store == "faiss": - index = FAISS.from_documents( - documents=file.docs, - embedding=embedding_model, + all_docs = cls._combine_files(files) + + index = vector_store.from_documents( + documents=all_docs, + embedding=embeddings, ) + + return cls(files=files, index=index) + + +def embed_files( + files: List[File], embedding: str, vector_store: str, **kwargs +) -> FolderIndex: + """Embeds a collection of files and stores them in a FolderIndex.""" + + supported_embeddings: dict[str, Type[Embeddings]] = { + "openai": OpenAIEmbeddings, + } + supported_vector_stores: dict[str, Type[VectorStore]] = { + "faiss": FAISS, + } + + if embedding in supported_embeddings: + _embeddings = supported_embeddings[embedding](**kwargs) + else: + raise NotImplementedError(f"Embedding {embedding} not supported.") + + if vector_store in supported_vector_stores: + _vector_store = supported_vector_stores[vector_store] else: - raise NotImplementedError + raise NotImplementedError(f"Vector store {vector_store} not supported.") - return index + return FolderIndex.from_files( + files=files, embeddings=_embeddings, vector_store=_vector_store + ) diff --git a/tests/test_embedding.py b/tests/test_embedding.py new file mode 100644 index 00000000..301d567c --- /dev/null +++ b/tests/test_embedding.py @@ -0,0 +1,39 @@ +from knowledge_gpt.core.embedding import FolderIndex +from .core.fake_file import FakeFile +from langchain.docstore.document import Document +from knowledge_gpt.core.parsing import File +from typing import List + + +def test_combining_files(): + """Tests that combining files works.""" + + files: List[File] = [ + FakeFile( + name="file1", + id="1", + docs=[Document(page_content="1"), Document(page_content="2")], + ), + FakeFile( + name="file2", + id="2", + docs=[Document(page_content="3"), Document(page_content="4")], + ), + ] + + all_docs = FolderIndex._combine_files(files) + + assert len(all_docs) == 4 + assert all_docs[0].page_content == "1" + assert all_docs[1].page_content == "2" + assert all_docs[2].page_content == "3" + assert all_docs[3].page_content == "4" + + assert all_docs[0].metadata["file_name"] == "file1" + assert all_docs[0].metadata["file_id"] == "1" + assert all_docs[1].metadata["file_name"] == "file1" + assert all_docs[1].metadata["file_id"] == "1" + assert all_docs[2].metadata["file_name"] == "file2" + assert all_docs[2].metadata["file_id"] == "2" + assert all_docs[3].metadata["file_name"] == "file2" + assert all_docs[3].metadata["file_id"] == "2" From 11b9cc2c10954948982ee37b8b43c71e8bca07af Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 11:38:27 +0530 Subject: [PATCH 19/36] simplify types in `FolderIndex` --- knowledge_gpt/core/embedding.py | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/knowledge_gpt/core/embedding.py b/knowledge_gpt/core/embedding.py index d9751149..87b9fadb 100644 --- a/knowledge_gpt/core/embedding.py +++ b/knowledge_gpt/core/embedding.py @@ -3,12 +3,9 @@ from langchain.vectorstores.faiss import FAISS from langchain.embeddings import OpenAIEmbeddings from langchain.embeddings.base import Embeddings -from langchain.vectorstores.base import VectorStore -from typing import List, TypeVar, Type +from typing import List, Type from langchain.docstore.document import Document -VST = TypeVar("VST", bound="VectorStore") - class FolderIndex: """Index for a collection of files (a folder)""" @@ -33,7 +30,7 @@ def _combine_files(files: List[File]) -> List[Document]: @classmethod def from_files( - cls, files: List[File], embeddings: Embeddings, vector_store: Type[VST] + cls, files: List[File], embeddings: Embeddings, vector_store: Type[VectorStore] ) -> "FolderIndex": """Creates an index from files.""" From ce63cd62801266514bb8c28aaed2c6883fc41a1b Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 12:22:31 +0530 Subject: [PATCH 20/36] move `fake_file.py` to `test` root --- tests/{core => }/fake_file.py | 0 tests/test_chunking.py | 2 +- tests/test_embedding.py | 2 +- 3 files changed, 2 insertions(+), 2 deletions(-) rename tests/{core => }/fake_file.py (100%) diff --git a/tests/core/fake_file.py b/tests/fake_file.py similarity index 100% rename from tests/core/fake_file.py rename to tests/fake_file.py diff --git a/tests/test_chunking.py b/tests/test_chunking.py index 5764b361..fa2b85bc 100644 --- a/tests/test_chunking.py +++ b/tests/test_chunking.py @@ -2,7 +2,7 @@ from langchain.docstore.document import Document from knowledge_gpt.core.chunking import chunk_file -from tests.core.fake_file import FakeFile +from tests.fake_file import FakeFile @pytest.fixture diff --git a/tests/test_embedding.py b/tests/test_embedding.py index 301d567c..e624a003 100644 --- a/tests/test_embedding.py +++ b/tests/test_embedding.py @@ -1,5 +1,5 @@ from knowledge_gpt.core.embedding import FolderIndex -from .core.fake_file import FakeFile +from .fake_file import FakeFile from langchain.docstore.document import Document from knowledge_gpt.core.parsing import File from typing import List From 6c9736927d4132fe633a595f0eb64023ef70abe7 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 12:43:48 +0530 Subject: [PATCH 21/36] refactor qa functions --- knowledge_gpt/core/qa.py | 65 ++++++++++++++++++++++---------------- tests/fake_vector_store.py | 22 +++++++++++++ tests/test_qa.py | 42 ++++++++++++++++++++++++ tests/test_utils.py | 14 -------- 4 files changed, 102 insertions(+), 41 deletions(-) create mode 100644 tests/fake_vector_store.py create mode 100644 tests/test_qa.py delete mode 100644 tests/test_utils.py diff --git a/knowledge_gpt/core/qa.py b/knowledge_gpt/core/qa.py index 7d35424e..13b3d50a 100644 --- a/knowledge_gpt/core/qa.py +++ b/knowledge_gpt/core/qa.py @@ -1,49 +1,60 @@ -from typing import Any, Dict, List, Tuple -from knowledge_gpt.core.parsing import File +from typing import Any, Dict, List from langchain.chains.qa_with_sources import load_qa_with_sources_chain from knowledge_gpt.core.prompts import STUFF_PROMPT from langchain.docstore.document import Document -from typing import Literal from langchain.chat_models import ChatOpenAI -from langchain.vectorstores import VectorStore +from knowledge_gpt.core.embedding import FolderIndex +from pydantic import BaseModel -def get_answer( - query: str, model: Literal["openai"], _index: VectorStore, file: File, **kwargs: Any -) -> Tuple[Dict[str, Any], List[Document]]: - """Gets an answer to a question from a file. - Even though the file argument is not used, it is needed to cache the function. - """ +class AnswerWithSources(BaseModel): + answer: Dict[str, Any] + sources: List[Document] + + +def query_folder( + query: str, folder_index: FolderIndex, return_all: bool = False, **model_kwargs: Any +) -> AnswerWithSources: + """Queries a folder index for an answer. + + Args: + query (str): The query to search for. + folder_index (FolderIndex): The folder index to search. + return_all (bool): Whether to return all the documents from the embedding or + just the sources for the answer. + **model_kwargs (Any): Keyword arguments for the model. - if model == "openai": - _model = ChatOpenAI(**kwargs) # type: ignore - else: - raise NotImplementedError + Returns: + AnswerWithSources: The answer and the source documents. + """ - # Get the answer chain = load_qa_with_sources_chain( - llm=_model, + llm=ChatOpenAI(**model_kwargs), chain_type="stuff", prompt=STUFF_PROMPT, ) - relevant_docs = _index.similarity_search(query, k=5) - - answer = chain( + relevant_docs = folder_index.index.similarity_search(query, k=5) + result = chain( {"input_documents": relevant_docs, "question": query}, return_only_outputs=True ) - return answer, relevant_docs + sources = relevant_docs + + if not return_all: + sources = get_sources(result["output_text"], folder_index) + + return AnswerWithSources(answer=result, sources=sources) -def get_sources(answer: Dict[str, Any], file: File) -> List[Document]: - """Gets the source documents for an answer.""" +def get_sources(answer: str, folder_index: FolderIndex) -> List[Document]: + """Retrieves the docs that were used to answer the question the generated answer.""" - # Get sources for the answer - source_keys = [s for s in answer["output_text"].split("SOURCES: ")[-1].split(", ")] + source_keys = [s for s in answer.split("SOURCES: ")[-1].split(", ")] source_docs = [] - for doc in file.docs: - if doc.metadata["source"] in source_keys: - source_docs.append(doc) + for file in folder_index.files: + for doc in file.docs: + if doc.metadata["source"] in source_keys: + source_docs.append(doc) return source_docs diff --git a/tests/fake_vector_store.py b/tests/fake_vector_store.py new file mode 100644 index 00000000..6604513b --- /dev/null +++ b/tests/fake_vector_store.py @@ -0,0 +1,22 @@ +from langchain.vectorstores import VectorStore +from typing import Iterable, List, Any +from langchain.docstore.document import Document + + +class FakeVectorStore(VectorStore): + """Fake vector store for testing purposes.""" + + def add_texts( + self, texts: Iterable[str], metadatas: List[dict] | None = None, **kwargs: Any + ) -> List[str]: + raise NotImplementedError + + def from_texts( + self, texts: Iterable[str], metadatas: List[dict] | None = None, **kwargs: Any + ) -> List[str]: + raise NotImplementedError + + def similarity_search( + self, query: str, k: int = 4, **kwargs: Any + ) -> List[Document]: + raise NotImplementedError diff --git a/tests/test_qa.py b/tests/test_qa.py new file mode 100644 index 00000000..0b7d153e --- /dev/null +++ b/tests/test_qa.py @@ -0,0 +1,42 @@ +from langchain.docstore.document import Document +from knowledge_gpt.core.qa import get_sources +from knowledge_gpt.core.embedding import FolderIndex + +from typing import List +from .fake_file import FakeFile +from knowledge_gpt.core.parsing import File + +from .fake_vector_store import FakeVectorStore + + +def test_getting_sources_from_answer(): + """Test that we can get the sources from an answer.""" + files: List[File] = [ + FakeFile( + name="file1", + id="1", + docs=[ + Document(page_content="1", metadata={"source": "1"}), + Document(page_content="2", metadata={"source": "2"}), + ], + ), + FakeFile( + name="file2", + id="2", + docs=[ + Document(page_content="3", metadata={"source": "3"}), + Document(page_content="4", metadata={"source": "4"}), + ], + ), + ] + folder_index = FolderIndex(files=files, index=FakeVectorStore()) + + answer = "This is the answer. SOURCES: 1, 2, 3, 4" + + sources = get_sources(answer, folder_index) + + assert len(sources) == 4 + assert sources[0].metadata["source"] == "1" + assert sources[1].metadata["source"] == "2" + assert sources[2].metadata["source"] == "3" + assert sources[3].metadata["source"] == "4" diff --git a/tests/test_utils.py b/tests/test_utils.py deleted file mode 100644 index dbb4e0ee..00000000 --- a/tests/test_utils.py +++ /dev/null @@ -1,14 +0,0 @@ -from langchain.docstore.document import Document - -from knowledge_gpt.QA import get_sources - - -def test_get_sources(): - """Test getting sources from an answer""" - docs = [ - Document(page_content="This is a test document.", metadata={"source": "1-5"}), - Document(page_content="This is a test document.", metadata={"source": "2-6"}), - ] - answer = {"output_text": "This is a test answer. SOURCES: 1-5, 3-8"} - sources = get_sources(answer, docs) - assert sources == [docs[0]] From 42b85403cdd7578461645e977287e78b7aaa0728 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 12:46:51 +0530 Subject: [PATCH 22/36] change tests directory structure --- tests/integration_tests/__init__.py | 1 + tests/unit_tests/__init__.py | 1 + tests/{ => unit_tests}/fake_file.py | 0 tests/{ => unit_tests}/fake_vector_store.py | 0 tests/{ => unit_tests}/test_chunking.py | 0 tests/{ => unit_tests}/test_embedding.py | 0 tests/{ => unit_tests}/test_parsing.py | 0 tests/{ => unit_tests}/test_qa.py | 0 8 files changed, 2 insertions(+) create mode 100644 tests/integration_tests/__init__.py create mode 100644 tests/unit_tests/__init__.py rename tests/{ => unit_tests}/fake_file.py (100%) rename tests/{ => unit_tests}/fake_vector_store.py (100%) rename tests/{ => unit_tests}/test_chunking.py (100%) rename tests/{ => unit_tests}/test_embedding.py (100%) rename tests/{ => unit_tests}/test_parsing.py (100%) rename tests/{ => unit_tests}/test_qa.py (100%) diff --git a/tests/integration_tests/__init__.py b/tests/integration_tests/__init__.py new file mode 100644 index 00000000..a076291f --- /dev/null +++ b/tests/integration_tests/__init__.py @@ -0,0 +1 @@ +"""All integration tests (tests that call out to an external API).""" diff --git a/tests/unit_tests/__init__.py b/tests/unit_tests/__init__.py new file mode 100644 index 00000000..307b5085 --- /dev/null +++ b/tests/unit_tests/__init__.py @@ -0,0 +1 @@ +"""All unit tests (lightweight tests).""" diff --git a/tests/fake_file.py b/tests/unit_tests/fake_file.py similarity index 100% rename from tests/fake_file.py rename to tests/unit_tests/fake_file.py diff --git a/tests/fake_vector_store.py b/tests/unit_tests/fake_vector_store.py similarity index 100% rename from tests/fake_vector_store.py rename to tests/unit_tests/fake_vector_store.py diff --git a/tests/test_chunking.py b/tests/unit_tests/test_chunking.py similarity index 100% rename from tests/test_chunking.py rename to tests/unit_tests/test_chunking.py diff --git a/tests/test_embedding.py b/tests/unit_tests/test_embedding.py similarity index 100% rename from tests/test_embedding.py rename to tests/unit_tests/test_embedding.py diff --git a/tests/test_parsing.py b/tests/unit_tests/test_parsing.py similarity index 100% rename from tests/test_parsing.py rename to tests/unit_tests/test_parsing.py diff --git a/tests/test_qa.py b/tests/unit_tests/test_qa.py similarity index 100% rename from tests/test_qa.py rename to tests/unit_tests/test_qa.py From 634500af8c2abb894a18b208550676a3900f8aa2 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 14:53:48 +0530 Subject: [PATCH 23/36] strip sources from answer str --- knowledge_gpt/core/qa.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/knowledge_gpt/core/qa.py b/knowledge_gpt/core/qa.py index 13b3d50a..cdcef6fb 100644 --- a/knowledge_gpt/core/qa.py +++ b/knowledge_gpt/core/qa.py @@ -43,7 +43,9 @@ def query_folder( if not return_all: sources = get_sources(result["output_text"], folder_index) - return AnswerWithSources(answer=result, sources=sources) + answer = result["output_text"].split("SOURCES: ")[0] + + return AnswerWithSources(answer=answer, sources=sources) def get_sources(answer: str, folder_index: FolderIndex) -> List[Document]: From 4bee676f2c5727df66ec8d5bb348adca884e2fef Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 16:11:38 +0530 Subject: [PATCH 24/36] change answer type in `AnswerWithSources` --- knowledge_gpt/core/qa.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/knowledge_gpt/core/qa.py b/knowledge_gpt/core/qa.py index cdcef6fb..faae6a92 100644 --- a/knowledge_gpt/core/qa.py +++ b/knowledge_gpt/core/qa.py @@ -1,4 +1,4 @@ -from typing import Any, Dict, List +from typing import Any, List from langchain.chains.qa_with_sources import load_qa_with_sources_chain from knowledge_gpt.core.prompts import STUFF_PROMPT from langchain.docstore.document import Document @@ -8,7 +8,7 @@ class AnswerWithSources(BaseModel): - answer: Dict[str, Any] + answer: str sources: List[Document] From bde4ea9cfdaf280d91eab51848470892e133f76d Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 16:40:28 +0530 Subject: [PATCH 25/36] fix import --- tests/unit_tests/test_chunking.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/unit_tests/test_chunking.py b/tests/unit_tests/test_chunking.py index fa2b85bc..b34aaeee 100644 --- a/tests/unit_tests/test_chunking.py +++ b/tests/unit_tests/test_chunking.py @@ -2,7 +2,7 @@ from langchain.docstore.document import Document from knowledge_gpt.core.chunking import chunk_file -from tests.fake_file import FakeFile +from .fake_file import FakeFile @pytest.fixture From 3ad82589fafbe1175a9a8b19117b4bc1ea2beb4e Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 16:42:50 +0530 Subject: [PATCH 26/36] fix unit test paths --- tests/unit_tests/test_parsing.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/tests/unit_tests/test_parsing.py b/tests/unit_tests/test_parsing.py index af77d1d6..0ede5993 100644 --- a/tests/unit_tests/test_parsing.py +++ b/tests/unit_tests/test_parsing.py @@ -11,6 +11,8 @@ from pathlib import Path TESTS_ROOT = Path(__file__).parent.resolve() +UNIT_TESTS_ROOT = Path(__file__).parent.resolve() +TESTS_ROOT = UNIT_TESTS_ROOT.parent.resolve() PROJECT_ROOT = TESTS_ROOT.parent.resolve() RESOURCE_ROOT = PROJECT_ROOT / "resources" SAMPLE_ROOT = RESOURCE_ROOT / "samples" From 9f0d92dada251924a6fc20c71ceef1656185f05f Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 16:43:42 +0530 Subject: [PATCH 27/36] implement copy() method for file --- knowledge_gpt/core/parsing.py | 19 +++++++++++++++++ tests/unit_tests/test_parsing.py | 36 +++++++++++++++++++++++++++++++- 2 files changed, 54 insertions(+), 1 deletion(-) diff --git a/knowledge_gpt/core/parsing.py b/knowledge_gpt/core/parsing.py index eaa87f1a..d092f7ea 100644 --- a/knowledge_gpt/core/parsing.py +++ b/knowledge_gpt/core/parsing.py @@ -8,6 +8,7 @@ from hashlib import md5 from abc import abstractmethod, ABC +from copy import deepcopy class File(ABC): @@ -30,6 +31,24 @@ def __init__( def from_bytes(cls, file: BytesIO) -> "File": """Creates a File from a BytesIO object""" + def __repr__(self) -> str: + return ( + f"File(name={self.name}, id={self.id}," + " metadata={self.metadata}, docs={self.docs})" + ) + + def __str__(self) -> str: + return f"File(name={self.name}, id={self.id}, metadata={self.metadata})" + + def copy(self) -> "File": + """Create a deep copy of this File""" + return self.__class__( + name=self.name, + id=self.id, + metadata=deepcopy(self.metadata), + docs=deepcopy(self.docs), + ) + def strip_consecutive_newlines(text: str) -> str: """Strips consecutive newlines from a string diff --git a/tests/unit_tests/test_parsing.py b/tests/unit_tests/test_parsing.py index 0ede5993..5bfa505a 100644 --- a/tests/unit_tests/test_parsing.py +++ b/tests/unit_tests/test_parsing.py @@ -10,7 +10,10 @@ ) from pathlib import Path -TESTS_ROOT = Path(__file__).parent.resolve() +from .fake_file import FakeFile +from langchain.docstore.document import Document + + UNIT_TESTS_ROOT = Path(__file__).parent.resolve() TESTS_ROOT = UNIT_TESTS_ROOT.parent.resolve() PROJECT_ROOT = TESTS_ROOT.parent.resolve() @@ -102,6 +105,37 @@ def test_read_file_not_implemented(): read_file(file) +def test_file_copy(): + # Create a Document and FakeFile instance + document = Document(page_content="test content", metadata={"page": "1"}) + file = FakeFile("test_file", "1234", {"author": "test"}, [document]) + + # Create a copy of the file + file_copy = file.copy() + + # Check that the original and copy are distinct objects + assert file is not file_copy + + # Check that the copy has the same attributes as the original + assert file.name == file_copy.name + assert file.id == file_copy.id + + # Check the mutable attributes were deeply copied + assert file.metadata == file_copy.metadata + assert file.metadata is not file_copy.metadata + + # Check the documents were deeply copied + assert file.docs == file_copy.docs + assert file.docs is not file_copy.docs + + # Check individual documents are not the same objects + assert file.docs[0] is not file_copy.docs[0] + + # Check the documents have the same attributes + assert file.docs[0].page_content == file_copy.docs[0].page_content + assert file.docs[0].metadata == file_copy.docs[0].metadata + + def test_strip_consecutive_newlines(): # Test with multiple consecutive newlines text = "\n\n\n" From 4efb5acd099c2e423d8bb8e51c25e0ffd40747a4 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 16:45:01 +0530 Subject: [PATCH 28/36] return a copy in chunk_file() method --- knowledge_gpt/core/chunking.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/knowledge_gpt/core/chunking.py b/knowledge_gpt/core/chunking.py index 1aa13cb0..7739c663 100644 --- a/knowledge_gpt/core/chunking.py +++ b/knowledge_gpt/core/chunking.py @@ -33,5 +33,6 @@ def chunk_file( ) chunked_docs.append(doc) - file.docs = chunked_docs - return file + chunked_file = file.copy() + chunked_file.docs = chunked_docs + return chunked_file From 0b55992dce6965969f81d5994288c25dc7445e06 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 16:58:04 +0530 Subject: [PATCH 29/36] patch module function with cached versions --- knowledge_gpt/core/cached.py | 29 ----------------------------- knowledge_gpt/core/caching.py | 33 +++++++++++++++++++++++++++++++++ 2 files changed, 33 insertions(+), 29 deletions(-) delete mode 100644 knowledge_gpt/core/cached.py create mode 100644 knowledge_gpt/core/caching.py diff --git a/knowledge_gpt/core/cached.py b/knowledge_gpt/core/cached.py deleted file mode 100644 index 32de10e9..00000000 --- a/knowledge_gpt/core/cached.py +++ /dev/null @@ -1,29 +0,0 @@ -"""Add caching decorators to expensive functions""" - -import streamlit as st - -from knowledge_gpt.core.parsing import to_file -from knowledge_gpt.core.chunking import chunk_file -from knowledge_gpt.core.embedding import embed_docs -from knowledge_gpt.core.qa import get_answer, get_sources -from knowledge_gpt.core.parsing import File - - -def file_hash_func(file: File) -> str: - """Get a unique hash for a file""" - return file.id - - -to_file = st.cache_data(show_spinner=False)(to_file) -chunk_file = st.cache_data(show_spinner=False, hash_funcs={File: file_hash_func})( - chunk_file -) -embed_docs = st.cache_data(show_spinner=False, hash_funcs={File: file_hash_func})( - embed_docs -) -get_answer = st.cache_data(show_spinner=False, hash_funcs={File: file_hash_func})( - get_answer -) -get_sources = st.cache_data(show_spinner=False, hash_funcs={File: file_hash_func})( - get_sources -) diff --git a/knowledge_gpt/core/caching.py b/knowledge_gpt/core/caching.py new file mode 100644 index 00000000..a878ebbe --- /dev/null +++ b/knowledge_gpt/core/caching.py @@ -0,0 +1,33 @@ +import streamlit as st +from streamlit.runtime.caching.hashing import HashFuncsDict + +import knowledge_gpt.core.parsing as parsing +import knowledge_gpt.core.chunking as chunking +import knowledge_gpt.core.embedding as embedding +from knowledge_gpt.core.parsing import File + + +def file_hash_func(file: File) -> str: + """Get a unique hash for a file""" + return file.id + + +@st.cache_resource() +def bootstrap_caching(): + """Patch module functions with caching""" + + # Get all substypes of File from module + file_subtypes = [ + cls + for cls in vars(parsing).values() + if isinstance(cls, type) and issubclass(cls, File) and cls != File + ] + file_hash_funcs: HashFuncsDict = {cls: file_hash_func for cls in file_subtypes} + + parsing.read_file = st.cache_data(show_spinner=False)(parsing.read_file) + chunking.chunk_file = st.cache_data(show_spinner=False, hash_funcs=file_hash_funcs)( + chunking.chunk_file + ) + embedding.embed_files = st.cache_data( + show_spinner=False, hash_funcs=file_hash_funcs + )(embedding.embed_files) From c3c2155de5ef1ac5282ef870d93eb57a23101855 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 17:06:14 +0530 Subject: [PATCH 30/36] refactor main app to use new functions --- knowledge_gpt/main.py | 47 +++++++++++++++++++------------------------ 1 file changed, 21 insertions(+), 26 deletions(-) diff --git a/knowledge_gpt/main.py b/knowledge_gpt/main.py index 27d49044..27c52e4d 100644 --- a/knowledge_gpt/main.py +++ b/knowledge_gpt/main.py @@ -4,18 +4,19 @@ from knowledge_gpt.ui import wrap_doc_in_html, is_valid -from knowledge_gpt.core.cached import ( - to_file, - embed_docs, - get_answer, - get_sources, - chunk_file, -) +from knowledge_gpt.core.caching import bootstrap_caching +from knowledge_gpt.core.parsing import read_file +from knowledge_gpt.core.chunking import chunk_file +from knowledge_gpt.core.embedding import embed_files +from knowledge_gpt.core.qa import query_folder st.set_page_config(page_title="KnowledgeGPT", page_icon="📖", layout="wide") st.header("📖KnowledgeGPT") +# Enable caching for expensive functions +bootstrap_caching() + sidebar() openai_api_key = st.session_state.get("OPENAI_API_KEY") @@ -38,14 +39,14 @@ st.stop() -file = to_file(uploaded_file) -file = chunk_file(file, chunk_size=800, chunk_overlap=0) +file = read_file(uploaded_file) +chunked_file = chunk_file(file, chunk_size=800, chunk_overlap=0) with st.spinner("Indexing document... This may take a while⏳"): - index = embed_docs( - file=file, - embeddings="openai", + folder_index = embed_files( + files=[chunked_file], + embedding="openai", vector_store="faiss", openai_api_key=openai_api_key, ) @@ -56,7 +57,7 @@ with st.expander("Advanced Options"): - show_all_chunks = st.checkbox("Show all chunks retrieved from vector search") + return_all_chunks = st.checkbox("Show all chunks retrieved from vector search") show_full_doc = st.checkbox("Show parsed contents of the document") @@ -67,33 +68,27 @@ if submit: - if not is_valid(index, query): + if not is_valid(folder_index, query): st.stop() # Output Columns answer_col, sources_col = st.columns(2) - answer, relevant_docs = get_answer( - query, - model="openai", - _index=index, - file=file, + result = query_folder( + folder_index=folder_index, + query=query, + return_all=return_all_chunks, openai_api_key=openai_api_key, temperature=0, ) - if not show_all_chunks: - # Get the sources for the answer - sources = get_sources(answer, file) - else: - sources = relevant_docs with answer_col: st.markdown("#### Answer") - st.markdown(answer["output_text"].split("SOURCES: ")[0]) + st.markdown(result.answer) with sources_col: st.markdown("#### Sources") - for source in sources: + for source in result.sources: st.markdown(source.page_content) st.markdown(source.metadata["source"]) st.markdown("---") From db42eea6ae954c4d5a18f7a172033f831205c9ba Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 17:11:19 +0530 Subject: [PATCH 31/36] use proper chunk size The new function uses tokens for the len function instead of characters Fixes #15 and #8 --- knowledge_gpt/main.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/knowledge_gpt/main.py b/knowledge_gpt/main.py index 27c52e4d..012b855a 100644 --- a/knowledge_gpt/main.py +++ b/knowledge_gpt/main.py @@ -40,7 +40,7 @@ file = read_file(uploaded_file) -chunked_file = chunk_file(file, chunk_size=800, chunk_overlap=0) +chunked_file = chunk_file(file, chunk_size=300, chunk_overlap=0) with st.spinner("Indexing document... This may take a while⏳"): From 67a7f6368e1165d2ad4fe29350d6624ae6ecdc4d Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 17:45:31 +0530 Subject: [PATCH 32/36] handle OpenAI API key missing error --- knowledge_gpt/main.py | 4 ++++ knowledge_gpt/ui.py | 3 --- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/knowledge_gpt/main.py b/knowledge_gpt/main.py index 012b855a..6dee807e 100644 --- a/knowledge_gpt/main.py +++ b/knowledge_gpt/main.py @@ -42,6 +42,10 @@ file = read_file(uploaded_file) chunked_file = chunk_file(file, chunk_size=300, chunk_overlap=0) +if not openai_api_key: + st.error("Please enter your OpenAI API key in the sidebar!") + st.stop() + with st.spinner("Indexing document... This may take a while⏳"): folder_index = embed_files( diff --git a/knowledge_gpt/ui.py b/knowledge_gpt/ui.py index 33447474..4cdb5c99 100644 --- a/knowledge_gpt/ui.py +++ b/knowledge_gpt/ui.py @@ -13,9 +13,6 @@ def wrap_doc_in_html(docs: List[Document]) -> str: def is_valid(index, query): - if not st.session_state.get("OPENAI_API_KEY"): - st.error("Please configure your OpenAI API key!") - return False if not index: st.error("Please upload a document!") return False From 00af77f70f573fea8818297615b206a6fd41f2c9 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 17:57:54 +0530 Subject: [PATCH 33/36] show validation errors in UI --- knowledge_gpt/main.py | 15 +++++++++++---- knowledge_gpt/ui.py | 23 +++++++++++++++++++---- 2 files changed, 30 insertions(+), 8 deletions(-) diff --git a/knowledge_gpt/main.py b/knowledge_gpt/main.py index 6dee807e..b7db8a71 100644 --- a/knowledge_gpt/main.py +++ b/knowledge_gpt/main.py @@ -2,7 +2,12 @@ from knowledge_gpt.components.sidebar import sidebar -from knowledge_gpt.ui import wrap_doc_in_html, is_valid +from knowledge_gpt.ui import ( + wrap_doc_in_html, + is_query_valid, + is_file_valid, + is_open_ai_key_valid, +) from knowledge_gpt.core.caching import bootstrap_caching @@ -42,8 +47,10 @@ file = read_file(uploaded_file) chunked_file = chunk_file(file, chunk_size=300, chunk_overlap=0) -if not openai_api_key: - st.error("Please enter your OpenAI API key in the sidebar!") +if not is_file_valid(file): + st.stop() + +if not is_open_ai_key_valid(openai_api_key): st.stop() @@ -72,7 +79,7 @@ if submit: - if not is_valid(folder_index, query): + if not is_query_valid(query): st.stop() # Output Columns diff --git a/knowledge_gpt/ui.py b/knowledge_gpt/ui.py index 4cdb5c99..cd1e8067 100644 --- a/knowledge_gpt/ui.py +++ b/knowledge_gpt/ui.py @@ -1,6 +1,7 @@ from typing import List import streamlit as st from langchain.docstore.document import Document +from knowledge_gpt.core.parsing import File def wrap_doc_in_html(docs: List[Document]) -> str: @@ -12,11 +13,25 @@ def wrap_doc_in_html(docs: List[Document]) -> str: return "".join([f"

{line}

" for line in text.split("\n")]) -def is_valid(index, query): - if not index: - st.error("Please upload a document!") - return False +def is_query_valid(query: str) -> bool: if not query: st.error("Please enter a question!") return False return True + + +def is_file_valid(file: File) -> bool: + if len(file.docs) == 0 or len(file.docs[0].page_content.strip()) == 0: + st.error( + "Cannot read document! Make sure the document has" + " selectable text or is not password protected." + ) + return False + return True + + +def is_open_ai_key_valid(openai_api_key) -> bool: + if not openai_api_key: + st.error("Please enter your OpenAI API key in the sidebar!") + return False + return True From 8e8c423e519f1b0c2d0995b34824530cf96fea90 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 18:20:12 +0530 Subject: [PATCH 34/36] send request to check api key validity --- knowledge_gpt/ui.py | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/knowledge_gpt/ui.py b/knowledge_gpt/ui.py index cd1e8067..d4c156e1 100644 --- a/knowledge_gpt/ui.py +++ b/knowledge_gpt/ui.py @@ -2,6 +2,7 @@ import streamlit as st from langchain.docstore.document import Document from knowledge_gpt.core.parsing import File +import openai def wrap_doc_in_html(docs: List[Document]) -> str: @@ -30,8 +31,18 @@ def is_file_valid(file: File) -> bool: return True +@st.cache_data() def is_open_ai_key_valid(openai_api_key) -> bool: if not openai_api_key: st.error("Please enter your OpenAI API key in the sidebar!") return False + try: + openai.ChatCompletion.create( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "test"}], + api_key=openai_api_key, + ) + except Exception as e: + st.error(f"{e.__class__.__name__}: {e}") + return False return True From f94f555874d33f988b91fc717d728f5b521a9b20 Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 18:23:34 +0530 Subject: [PATCH 35/36] log errors --- knowledge_gpt/ui.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/knowledge_gpt/ui.py b/knowledge_gpt/ui.py index d4c156e1..a1b23ef7 100644 --- a/knowledge_gpt/ui.py +++ b/knowledge_gpt/ui.py @@ -3,6 +3,9 @@ from langchain.docstore.document import Document from knowledge_gpt.core.parsing import File import openai +from streamlit.logger import get_logger + +logger = get_logger(__name__) def wrap_doc_in_html(docs: List[Document]) -> str: @@ -27,6 +30,7 @@ def is_file_valid(file: File) -> bool: "Cannot read document! Make sure the document has" " selectable text or is not password protected." ) + logger.error("Cannot read document") return False return True @@ -44,5 +48,6 @@ def is_open_ai_key_valid(openai_api_key) -> bool: ) except Exception as e: st.error(f"{e.__class__.__name__}: {e}") + logger.error(f"{e.__class__.__name__}: {e}") return False return True From f82314be13555cda1a7df7946a6016866e7b41ec Mon Sep 17 00:00:00 2001 From: mmz-001 <70096033+mmz-001@users.noreply.github.com> Date: Wed, 5 Jul 2023 18:25:56 +0530 Subject: [PATCH 36/36] hide spinner when validating api key --- knowledge_gpt/ui.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/knowledge_gpt/ui.py b/knowledge_gpt/ui.py index a1b23ef7..81ba8007 100644 --- a/knowledge_gpt/ui.py +++ b/knowledge_gpt/ui.py @@ -35,7 +35,7 @@ def is_file_valid(file: File) -> bool: return True -@st.cache_data() +@st.cache_data(show_spinner=False) def is_open_ai_key_valid(openai_api_key) -> bool: if not openai_api_key: st.error("Please enter your OpenAI API key in the sidebar!")

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