From a3bc0cb947e3ff04de9839da2ad3f0e4dda0c602 Mon Sep 17 00:00:00 2001 From: "Henry Ruiz, PhD" Date: Thu, 27 Jun 2024 08:37:18 -0500 Subject: [PATCH] Feat/rag (#26) (#27) RAG implementation: LOTR (Merger Retriever) Agentic Routing RAG Agentic Tool Use RAG --- .gitignore | 2 + README.md | 2 +- data/.DS_Store | Bin 10244 -> 6148 bytes data/titanic.csv | 892 ++++++++++++++++++ data/vis-language-model.pdf | Bin 0 -> 10338461 bytes examples/chat_wit_your_code.py | 2 + examples/chat_with_multiple_files.py | 26 + examples/chat_with_your_audios.py | 6 +- examples/chat_with_your_images.py | 4 +- examples/chat_with_your_pdf.py | 6 +- examples/chat_with_your_video.py | 4 +- examples/code_repo.py | 42 + examples/gemini_client_api.py | 3 +- examples/multimodal.py | 2 +- examples/playground_api.py | 10 +- examples/rag.py | 153 +++ examples/readme_example.py | 2 +- examples/summarization.py | 27 + pyproject.toml | 37 +- src/.DS_Store | Bin 6148 -> 6148 bytes src/geminiplayground/cli.py | 11 + src/geminiplayground/parts/__init__.py | 3 +- .../parts/audio_part/audio_part.py | 72 +- .../parts/git_repo/git_repo_part.py | 105 +-- .../parts/image_part/image_part.py | 72 +- src/geminiplayground/parts/multimodal_part.py | 95 +- .../parts/pdf_part/pdf_part.py | 80 +- .../parts/video_part/video_part.py | 102 +- src/geminiplayground/rag/__init__.py | 6 + .../rag/agentic_routing_rag.py | 160 ++++ src/geminiplayground/rag/agentic_tool_use.py | 78 ++ src/geminiplayground/rag/lotr_rag.py | 98 ++ src/geminiplayground/rag/rag.py | 68 ++ .../rag/summarization_loader.py | 39 + src/geminiplayground/utils/__init__.py | 3 + src/geminiplayground/utils/cacheable.py | 100 ++ src/geminiplayground/utils/file_utils.py | 4 +- src/geminiplayground/utils/git_utils.py | 15 + src/geminiplayground/utils/lib_utils.py | 9 +- src/geminiplayground/utils/prompts.py | 6 + src/geminiplayground/web/api.py | 9 +- src/geminiplayground/web/utils.py | 2 +- 42 files changed, 1991 insertions(+), 366 deletions(-) create mode 100644 data/titanic.csv create mode 100644 data/vis-language-model.pdf create mode 100644 examples/chat_with_multiple_files.py create mode 100644 examples/code_repo.py create mode 100644 examples/rag.py create mode 100644 examples/summarization.py create mode 100644 src/geminiplayground/rag/__init__.py create mode 100644 src/geminiplayground/rag/agentic_routing_rag.py create mode 100644 src/geminiplayground/rag/agentic_tool_use.py create mode 100644 src/geminiplayground/rag/lotr_rag.py create mode 100644 src/geminiplayground/rag/rag.py create mode 100644 src/geminiplayground/rag/summarization_loader.py create mode 100644 src/geminiplayground/utils/cacheable.py create mode 100644 src/geminiplayground/utils/prompts.py diff --git a/.gitignore b/.gitignore index 734ef97..fcfacce 100644 --- a/.gitignore +++ b/.gitignore @@ -21,6 +21,7 @@ poetry.lock lib64/ sdist/ var/ +.python-version wheels/ .cache/ share/python-wheels/ @@ -30,6 +31,7 @@ share/python-wheels/ .idea .DS_Store MANIFEST +data/vis-language-model.pdf # PyInstaller diff --git a/README.md b/README.md index f5c2df9..c67306b 100644 --- a/README.md +++ b/README.md @@ -81,7 +81,7 @@ response = gemini_client.generate_response("models/gemini-1.5-pro-latest", multi generation_config={"temperature": 0.0, "top_p": 1.0}) # Print the response for candidate in response.candidates: - for part in candidate.content.parts: + for part in candidate._search_content_type.parts: if part.text: print(part.text) ``` diff --git a/data/.DS_Store b/data/.DS_Store index 286c05dd574dadea0c8584ab831961cd81221288..8b33668c5f806bae750eb2e3466ded8af1c11872 100644 GIT binary patch literal 6148 zcmeHKK~BRk5FFDUA|a&0iK9Qjp+7KHxN++Tpacb^gj7Q94V1s|7oNfoxHIcrP$P1v zI3R&`C41KPj$@A$+Y2BpHq{)M0Vr4mgE%85-J?SX7Ca?}JV%3TJfOyg_%}?}eu6FT z@rX0*uD`}Dds=j;=rv6}U*2@>I&bUg{dr$r+m+?2=~j#{F4N1=+wtr9{@m)v-1Xhg zdS$h4u7E4x3b+EUfGWT{TdX)#^x7401zdqI1>}5)EP~0fSIkETtDFK5cPq7vX zfq+0jARrJB2nYmj1q5)gg0s(=*I09^a2;<9SG?1fQ`b!5E{t*CWIja2! zzwsR4`-B4-4df`7zAN_0PY)2dLU6Pz*Gd-*nRtFrIq8gVE=8G`Vv}}av83fBS=+Dn<#X#RK5e_P zoqkhxnc>Fxq%kW=2JaIx#K5_^$%2~+#(OWBu}s&CL@t6#pw`=M9P? 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zyfk#jyYzgf+Mb8J;rQ=Ku;^<_9ut3)x>_9kt}(f5eU~$G$1nfV7~(%TQ?ldI3y$(! zIcc|%vAPfSj0lO~Z+(I%?}apjzhk7~nY&gW9sSM-!7R_n{f!?)ns4qNuD;TS`y+F3 z4QCE|Sk~wM2yHZ1mpkzbUSNN$jG)!Ux5UEEJ)`8})f3@GT3^;e3yV$&^L{{8R&@&Eq(y+i-)_kaB3cmL<_ fKmYCT|Mzcy{>yiV1j6&z-~H1+{g?mtU%&hRz?f-j literal 0 HcmV?d00001 diff --git a/examples/chat_wit_your_code.py b/examples/chat_wit_your_code.py index 7f7e81b..5fc7cd5 100644 --- a/examples/chat_wit_your_code.py +++ b/examples/chat_wit_your_code.py @@ -3,6 +3,7 @@ from geminiplayground.core import GeminiClient from geminiplayground.parts import GitRepo from dotenv import load_dotenv, find_dotenv +from geminiplayground.catching import cache load_dotenv(find_dotenv()) @@ -12,6 +13,7 @@ def chat_wit_your_code(): Get the content parts of a github repo and generate a request. :return: """ + cache.clear() repo = GitRepo.from_url( "https://github.com/karpathy/ng-video-lecture", branch="master", diff --git a/examples/chat_with_multiple_files.py b/examples/chat_with_multiple_files.py new file mode 100644 index 0000000..04218d2 --- /dev/null +++ b/examples/chat_with_multiple_files.py @@ -0,0 +1,26 @@ +from rich import print + +from dotenv import load_dotenv, find_dotenv +from pathlib import Path + +from geminiplayground.parts import ImageFile +from geminiplayground.catching import cache + +from geminiplayground.core import GeminiClient + +load_dotenv(find_dotenv()) + +if __name__ == '__main__': + cache.clear() + + gemini_client = GeminiClient() + images = [ImageFile(image_file, gemini_client=gemini_client) for image_file in Path("./../data").glob("*.jpg")] + prompt = ["Please describe the following images:"] + images + + model_name = "models/gemini-1.5-pro-latest" + tokens_count = gemini_client.count_tokens(model_name, prompt) + print(f"Tokens count: {tokens_count}") + response = gemini_client.generate_response(model_name, prompt, stream=True) + for message_chunk in response: + if message_chunk.parts: + print(message_chunk.text, end="") diff --git a/examples/chat_with_your_audios.py b/examples/chat_with_your_audios.py index ec85b7a..09eaa16 100644 --- a/examples/chat_with_your_audios.py +++ b/examples/chat_with_your_audios.py @@ -13,15 +13,15 @@ def chat_wit_your_audios(): audio_file_path = "./../data/audio_example.mp3" gemini_client = GeminiClient() audio_file = AudioFile(audio_file_path, gemini_client=gemini_client) - # audio_file.delete() + # audio_file.clear_cache() prompt = ["Listen this audio:", audio_file, "Describe what you heard"] - model_name = "models/gemini-1.5-pro-latest" + model_name = "models/gemini-1.5-flash-latest" tokens_count = gemini_client.count_tokens(model_name, prompt) print(f"Tokens count: {tokens_count}") response = gemini_client.generate_response(model_name, prompt, stream=True) for message_chunk in response: if message_chunk.parts: - print(message_chunk.text) + print(message_chunk.text, end="") if __name__ == "__main__": diff --git a/examples/chat_with_your_images.py b/examples/chat_with_your_images.py index 4b27146..24b1943 100644 --- a/examples/chat_with_your_images.py +++ b/examples/chat_with_your_images.py @@ -17,13 +17,13 @@ def chat_wit_your_images(): image_file_path = "https://upload.wikimedia.org/wikipedia/commons/4/47/PNG_transparency_demonstration_1.png" image_file = ImageFile(image_file_path, gemini_client=gemini_client) prompt = ["what do you see in this image?", image_file] - model_name = "models/gemini-1.5-pro-latest" + model_name = "models/gemini-1.5-flash-latest" tokens_count = gemini_client.count_tokens(model_name, prompt) print(f"Tokens count: {tokens_count}") response = gemini_client.generate_response(model_name, prompt, stream=True) for message_chunk in response: if message_chunk.parts: - print(message_chunk.text) + print(message_chunk.text, end="") if __name__ == "__main__": diff --git a/examples/chat_with_your_pdf.py b/examples/chat_with_your_pdf.py index b569f31..1f431c8 100644 --- a/examples/chat_with_your_pdf.py +++ b/examples/chat_with_your_pdf.py @@ -1,8 +1,7 @@ -from rich import print - from geminiplayground.core import GeminiClient from geminiplayground.parts import PdfFile from dotenv import load_dotenv, find_dotenv +from geminiplayground.catching import cache load_dotenv(find_dotenv()) @@ -12,10 +11,11 @@ def chat_wit_your_pdf(): Get the content parts of a pdf file and generate a request. :return: """ + cache.clear() gemini_client = GeminiClient() pdf_file_path = "https://www.tnstate.edu/faculty/fyao/COMP3050/Py-tutorial.pdf" + # pdf_file_path = "./../data/vis-language-model.pdf" pdf_file = PdfFile(pdf_file_path, gemini_client=gemini_client) - prompt = ["Please create a summary of the pdf file:", pdf_file] model_name = "models/gemini-1.5-pro-latest" tokens_count = gemini_client.count_tokens(model_name, prompt) diff --git a/examples/chat_with_your_video.py b/examples/chat_with_your_video.py index adb8127..66c645d 100644 --- a/examples/chat_with_your_video.py +++ b/examples/chat_with_your_video.py @@ -13,7 +13,7 @@ def chat_wit_your_video(): :return: """ gemini_client = GeminiClient() - model_name = "models/gemini-1.5-pro-latest" + model_name = "models/gemini-1.5-flash-latest" video_file_path = "./../data/transformers-explained.mp4" video_file = VideoFile(video_file_path, gemini_client=gemini_client) @@ -30,7 +30,7 @@ def chat_wit_your_video(): response = gemini_client.generate_response(model_name, prompt, stream=True) for message_chunk in response: if message_chunk.parts: - print(message_chunk.text) + print(message_chunk.text, end="") if __name__ == "__main__": diff --git a/examples/code_repo.py b/examples/code_repo.py new file mode 100644 index 0000000..b8720d4 --- /dev/null +++ b/examples/code_repo.py @@ -0,0 +1,42 @@ +from rich import print + +from geminiplayground.core import GeminiClient +from geminiplayground.parts import GitRepo +from dotenv import load_dotenv, find_dotenv +from geminiplayground.catching import cache + +load_dotenv(find_dotenv()) + +cache.clear() + + +def chat_wit_your_code(): + """ + Get the content parts of a github repo and generate a request. + :return: + """ + repo = GitRepo.from_url( + "https://github.com/mhdawson/node-core-utils.git", + branch="main", + config={ + "content": "code-files" + }, + ) + prompt = [ + "Describe the following codebase:", + repo + ] + model = "models/gemini-1.5-flash-latest" + gemini_client = GeminiClient() + tokens_count = gemini_client.count_tokens(model, prompt) + print("Tokens count: ", tokens_count) + response = gemini_client.generate_response(model, prompt, stream=True) + + # Print the response + for message_chunk in response: + if message_chunk.parts: + print(message_chunk.text, "") + + +if __name__ == "__main__": + chat_wit_your_code() diff --git a/examples/gemini_client_api.py b/examples/gemini_client_api.py index 3511839..a958054 100644 --- a/examples/gemini_client_api.py +++ b/examples/gemini_client_api.py @@ -8,4 +8,5 @@ if __name__ == "__main__": gemini_client = GeminiClient() files = gemini_client.query_files(page_size=5) - print(files) + for file in files: + print(file) diff --git a/examples/multimodal.py b/examples/multimodal.py index e90a456..af2dc0f 100644 --- a/examples/multimodal.py +++ b/examples/multimodal.py @@ -31,6 +31,6 @@ # Print the response for candidate in response.candidates: - for part in candidate.content.parts: + for part in candidate._search_content_type.parts: if part.text: print(part.text) diff --git a/examples/playground_api.py b/examples/playground_api.py index c5d27d5..68cc8fb 100644 --- a/examples/playground_api.py +++ b/examples/playground_api.py @@ -1,7 +1,6 @@ from dotenv import load_dotenv, find_dotenv -from geminiplayground.core import GeminiPlayground, Message, ToolCall -from geminiplayground.parts import ImageFile +from geminiplayground.core import GeminiPlayground, ToolCall load_dotenv(find_dotenv()) @@ -24,13 +23,6 @@ def write_poem() -> str: chat = playground.start_chat(history=[]) - - image = ImageFile("./data/dog.jpg") - ai_message = chat.send_message(["can you describe the following image: ", image], stream=True) - for response_chunk in ai_message: - if isinstance(response_chunk, Message): - print(response_chunk.text, end="") - print() while True: user_input = input("You: ") if user_input == "exit": diff --git a/examples/rag.py b/examples/rag.py new file mode 100644 index 0000000..cbb724a --- /dev/null +++ b/examples/rag.py @@ -0,0 +1,153 @@ +from langchain_core.messages import HumanMessage +from langchain_core.tools import tool +from langchain_google_genai import GoogleGenerativeAIEmbeddings, ChatGoogleGenerativeAI +from langchain_weaviate import WeaviateVectorStore + +from geminiplayground.parts import MultimodalPart, ImageFile, AudioFile, GitRepo, PdfFile, VideoFile +from langchain_core.retrievers import BaseRetriever +from dotenv import load_dotenv, find_dotenv +from geminiplayground.rag import SummarizationLoader, AgenticToolUseRAG +from rich.console import Console +from langchain_core.vectorstores import VectorStore +import typing +from langchain_core.callbacks import CallbackManagerForRetrieverRun +from langchain_core.documents import Document +import weaviate + +# from geminiplayground.catching import cache + +console = Console() + +load_dotenv(find_dotenv()) + + +class MultiModalSummarizationRetriever(BaseRetriever): + summarization_model: str + docs: typing.List[MultimodalPart] + vectorstore: VectorStore + batch_docs_size = 50 + """List of documents to retrieve from.""" + k: int + """Number of top results to return""" + + def index_docs(self): + """ + Index all the documents. + """ + loader = SummarizationLoader(self.summarization_model, *self.docs) + docs = loader.load() + self.vectorstore.add_documents(docs, batch_size=self.batch_docs_size) + + def _get_relevant_documents( + self, query: str, *, run_manager: CallbackManagerForRetrieverRun + ) -> typing.List[Document]: + docs, scores = zip( + *self.vectorstore.similarity_search_with_score(query, k=self.k) + ) + for doc, score in zip(docs, scores): + doc.metadata["score"] = score + + return docs + + +def create_retriever_from_multimodal_data(docs_index_name: str, + docs: typing.List[MultimodalPart]): + """ + Create a retriever for a document + """ + return MultiModalSummarizationRetriever( + docs=docs, + summarization_model="models/gemini-1.5-flash-latest", + vectorstore=WeaviateVectorStore( + client=weaviate_client, + index_name=docs_index_name, + embedding=embeddings_model, + text_key="page_content" + ), + k=5 + ) + + +if __name__ == '__main__': + + weaviate_client = weaviate.connect_to_embedded() + embeddings_model = GoogleGenerativeAIEmbeddings(model="models/embedding-001", task_type="retrieval_document") + chat_model = ChatGoogleGenerativeAI(model="models/gemini-1.5-flash-latest", temperature=0.0) + + retrievers = [{ + "name": "media_files", + "description": "This Retriever combine a various media files, including a picture of my dog", + "retriever": create_retriever_from_multimodal_data("media_files", [ + ImageFile("./../data/dog.jpg"), + + ]) + }, { + "name": "code_files", + "description": "This Retriever contains code from karpathy's ng-video-lecture repo about transformers", + "retriever": create_retriever_from_multimodal_data("code_files", [ + GitRepo.from_url( + "https://github.com/karpathy/ng-video-lecture", + branch="master", + config={ + "content": "code-files" + }, + )]) + }, { + "name": "transformer_files", + "description": "This Retriever contains various media files, relating to transformers and language models", + "retriever": create_retriever_from_multimodal_data("pdf_files", [ + VideoFile("./../data/transformers-explained.mp4"), + PdfFile("./../data/vis-language-model.pdf"), + AudioFile("./../data/audio_example.mp3") + ]) + }] + + # Index all the documents in the retrievers + for retriever in retrievers: + retriever["retriever"].index_docs() + + + # rag = LOTRRAG( + # chat_model=chat_model, + # retrievers_info=retrievers, + # chat_history=[] + # ) + + # rag = AgenticRoutingRAG( + # chat_model=chat_model, + # retrievers_info=retrievers, + # chat_history=[] + # ) + + @tool + def subtract(x: float, y: float) -> float: + """Subtract 'x' from 'y'.""" + return y - x + + + @tool + def sum(x: float, y: float) -> float: + """Calculate the percentage difference between 'x' and 'y'.""" + return x + y + + + rag = AgenticToolUseRAG( + chat_model=chat_model, + retrievers_info=retrievers, + custom_tools=[subtract, sum], + chat_history=[ + HumanMessage(content="Hello, I am a Henry Ruiz") + ]) + + while True: + question = input("Question: ") + if question.lower() == "exit": + print(rag.chat_history) + weaviate_client.close() + break + result = rag.invoke(question) + rag.chat_history.extend([HumanMessage(content=question), result.answer]) + console.print(f"Answer: {result.answer}") + docs = result.docs + for doc in docs[:3]: + console.print(doc.page_content[:100], doc.metadata) diff --git a/examples/readme_example.py b/examples/readme_example.py index 8c74419..96cfa11 100644 --- a/examples/readme_example.py +++ b/examples/readme_example.py @@ -25,6 +25,6 @@ # Print the response for candidate in response.candidates: - for part in candidate.content.parts: + for part in candidate._search_content_type.parts: if part.text: print(part.text) diff --git a/examples/summarization.py b/examples/summarization.py new file mode 100644 index 0000000..f92e3b2 --- /dev/null +++ b/examples/summarization.py @@ -0,0 +1,27 @@ +from rich import print + +from geminiplayground.parts import VideoFile, GitRepo, ImageFile, AudioFile, PdfFile +from dotenv import load_dotenv, find_dotenv + +load_dotenv(find_dotenv()) + +if __name__ == '__main__': + my_content = [ + VideoFile("./../data/transformers-explained.mp4"), + ImageFile("./../data/dog.jpg"), + PdfFile("./../data/vis-language-model.pdf"), + AudioFile("./../data/audio_example.mp3"), + GitRepo.from_url( + "https://github.com/karpathy/ng-video-lecture", + branch="master", + config={ + "content": "code-files" + }, + ) + ] + video = VideoFile("./../data/transformers-explained.mp4") + for content in my_content: + response = content.summarize(model="models/gemini-1.5-flash-latest", stream=True) + for message_chunk in response: + if message_chunk.parts: + print(message_chunk.text, end="") diff --git a/pyproject.toml b/pyproject.toml index cf99376..cf32cbd 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,9 +8,8 @@ packages = [{ include = "geminiplayground", from = "src" }] [tool.poetry.dependencies] python = ">=3.10,<3.12" -google-api-python-client = "^2.123.0" +google-api-python-client = "^2.132.0" pillow = "^10.3.0" -opencv-python = "^4.9.0.80" numpy = "^1.26.4" matplotlib = "^3.8.3" requests = "^2.31.0" @@ -21,8 +20,8 @@ rich = "^13.7.1" alive-progress = "^3.1.5" pygithub = "^2.3.0" gitpython = "^3.1.42" -fastapi = "^0.110.0" -uvicorn = { extras = ["standard"], version = "^0.29.0" } +fastapi = "^0.111.0" +uvicorn = { extras = ["standard"], version = "^0.30.1" } typer = "^0.12.0" python-multipart = "^0.0.9" sqlalchemy = "^2.0.29" @@ -35,37 +34,35 @@ requests-toolbelt = "^1.0.0" joblib = "^1.3.2" diskcache = "^5.6.3" pytest = "^8.1.1" -pydantic-settings = "^2.2.1" +pydantic-settings = "^2.3.1" aiosqlite = "^0.20.0" greenlet = "^3.0.3" gunicorn = "^22.0.0" pypdf2 = "^3.0.1" pymupdf = "^1.24.4" -google-generativeai = "^0.5.4" arrow = "^1.3.0" tenacity = "^8.3.0" pandas = "^2.2.2" -validators = "0.28.1" -langchain-google-genai = "^1.0.5" - +validators = "0.28.3" +google-generativeai = "^0.5.4" +opencv-python = "^4.10.0.82" +tiktoken = "^0.7.0" +seaborn = "^0.13.2" +faiss-cpu = "^1.8.0" +yaspin = "^3.0.2" +python-slugify = "^8.0.4" [tool.poetry.group.rag] optional = true - [tool.poetry.group.rag.dependencies] -weaviate-client = "^4.6.3" -unstructured = { extras = ["all-docs"], version = "^0.14.3" } -pdfminer-six = "^20231228" -pillow-heif = "^0.16.0" -pdf2image = "^1.17.0" -poppler-utils = "^0.1.0" -pytesseract = "^0.3.10" -pikepdf = "^9.0.0" -langchain = "^0.2.1" -langchain-community = "^0.2.1" +langchain-experimental = "^0.0.60" +unstructured = { extras = ["all-docs"], version = "^0.14.5" } langchain-weaviate = "^0.0.2" +langgraph = "^0.0.65" +langchain-community = "^0.2.4" langchainhub = "^0.1.17" +langchain-google-genai = "^1.0.6" [tool.poetry.scripts] geminiplayground = "geminiplayground.cli:run" diff --git a/src/.DS_Store b/src/.DS_Store index 908caa19d1f0a8a1cb5410154fa342885192ae3d..94343f5ef1a4eb1433ce8366b8368e01a16550f2 100644 GIT binary patch delta 59 zcmZoMXffDe%gB68<=A8gMgxxhCpA0n2_AC~uF}8^f Le4E)h{_+C=lqD73 delta 59 zcmZoMXffDe%gB7RqHVGRqXEak2R%nP*p4{@Ick&VF>tF}8^f Le4E)h{_+C=nX48( diff --git a/src/geminiplayground/cli.py b/src/geminiplayground/cli.py index d988d1d..f5107b9 100644 --- a/src/geminiplayground/cli.py +++ b/src/geminiplayground/cli.py @@ -1,6 +1,7 @@ import os import typer from typing_extensions import Annotated +from geminiplayground.catching import cache cli = typer.Typer(invoke_without_command=True) @@ -77,6 +78,16 @@ def api( ) +@cli.command( + name="clear-cache" +) +def clear_cache(): + """ + Clear the cache + """ + cache.clear() + + def run(): """ Run the app diff --git a/src/geminiplayground/parts/__init__.py b/src/geminiplayground/parts/__init__.py index a287a20..b5a0ae4 100644 --- a/src/geminiplayground/parts/__init__.py +++ b/src/geminiplayground/parts/__init__.py @@ -1,5 +1,5 @@ from .git_repo import GitRepo, GitRepoBranchNotFoundException -from .multimodal_part import MultimodalPart +from .multimodal_part import MultimodalPart, MultiModalPartFile from .image_part import ImageFile from .audio_part import AudioFile from .pdf_part import PdfFile @@ -15,4 +15,5 @@ "AudioFile", "VideoFile", "MultimodalPartFactory", + "MultiModalPartFile", ] diff --git a/src/geminiplayground/parts/audio_part/audio_part.py b/src/geminiplayground/parts/audio_part/audio_part.py index 45bdb67..8b4a459 100644 --- a/src/geminiplayground/parts/audio_part/audio_part.py +++ b/src/geminiplayground/parts/audio_part/audio_part.py @@ -1,80 +1,16 @@ import logging import typing -from geminiplayground.catching import cache -from geminiplayground.core import GeminiClient -from .. import MultimodalPart -from geminiplayground.utils import FileUtils, LibUtils +from ..multimodal_part import MultiModalPartFile from pathlib import Path logger = logging.getLogger("rich") -class AudioFile(MultimodalPart): +class AudioFile(MultiModalPartFile): """ Audio file part implementation """ - def __init__(self, audio_path: typing.Union[str, Path], **kwargs): - self.path = audio_path - self.filename = FileUtils.get_file_name_from_path(audio_path) - self.gemini_client = kwargs.get("gemini_client", GeminiClient()) - - def upload(self): - """ - Upload the audio to Gemini - :return: - """ - # upload the file - with FileUtils.solve_file_path(self.path) as audio_file: - uploaded_file = self.gemini_client.upload_file(audio_file) - return uploaded_file - - @property - def file(self): - """ - Get the files - :return: - """ - if cache.get(self.filename): - logger.info(f"Getting audio file {self.filename} from cache") - cached_file = cache.get(self.filename) - return cached_file - - logger.info(f"Uploading audio file {self.filename}") - uploaded_file = self.upload() - delta_t = LibUtils.get_uploaded_file_exp_date_delta_t(uploaded_file) - cache.set(self.filename, uploaded_file, expire=delta_t) - return uploaded_file - - def force_upload(self): - """ - Force the upload of the audio - :return: - """ - self.delete() - self.upload() - - def delete(self): - """ - Delete the image from Gemini - :return: - """ - if cache.get(self.filename): - cached_file = cache.get(self.filename) - self.gemini_client.delete_file(cached_file.name) - cache.delete(self.filename) - - def clear_cache(self): - """ - Clear the cache - :return: - """ - cache.delete(self.filename) - - def content_parts(self) -> typing.List: - """ - Get the content parts for the audio - :return: - """ - return [self.file] + def __init__(self, file_path: typing.Union[str, Path], gemini_client=None, **kwargs): + super().__init__(file_path, gemini_client) diff --git a/src/geminiplayground/parts/git_repo/git_repo_part.py b/src/geminiplayground/parts/git_repo/git_repo_part.py index 2a3af59..c9cd34e 100644 --- a/src/geminiplayground/parts/git_repo/git_repo_part.py +++ b/src/geminiplayground/parts/git_repo/git_repo_part.py @@ -12,6 +12,7 @@ LibUtils, ) from ..multimodal_part import MultimodalPart +from langchain_core.documents import Document import codecs logger = logging.getLogger("rich") @@ -26,36 +27,22 @@ class GitRepo(MultimodalPart): Git Repo Part implementation """ - def __init__(self, repo_folder: typing.Union[str, Path], **kwargs): + def __init__(self, repo_folder: typing.Union[str, Path], gemini_client: GeminiClient = None, **kwargs): # set the output directory for the repos - try: - repo_folder = Path(repo_folder).resolve(strict=True) - logger.info(f"Checking if {repo_folder} is a git repository") - - assert repo_folder.exists(), f"{repo_folder} does not exist" - assert GitUtils.folder_contains_git_repo( - repo_folder - ), f"{repo_folder} is not a git repository" - - self.repo_folder = repo_folder - self.repo = git.Repo(repo_folder) - self.gemini_client = kwargs.get("gemini_client", GeminiClient()) - - self.config = kwargs.setdefault("config", {"content": "code-files"}) - self.content = self.config.get("content", "code-files") - - logger.info(f"Repo folder: {self.repo_folder}") - logger.info(f"Content: {self.content}") - logger.info(f"Config: {self.config}") - - valid_contents = {"code-files", "issues"} - if self.content not in valid_contents: - raise ValueError( - f"Invalid content {self.content}, should be code-files or issues" - ) - except Exception as e: - logger.error(e) - raise e + super().__init__(gemini_client) + self._repo_folder = GitUtils.validate_repo_folder(repo_folder) + self._repo = git.Repo(repo_folder) + self._search_settings = kwargs.get("config", {"content": "code-files"}) + self._search_content_type = self._search_settings["content"] + + valid_search_options = {"code-files", "issues"} + if self._search_content_type not in valid_search_options: + raise ValueError( + f"Invalid content {self._search_content_type}, should be code-files or issues" + ) + + logger.info(f"Repo folder: {self._repo_folder}") + logger.info(f"Content: {self._search_content_type}") @classmethod def from_folder(cls, folder: typing.Union[str, Path], **kwargs): @@ -109,7 +96,6 @@ def from_url(cls, repo_url: str, branch: str = "main", **kwargs): logger.error(e) raise e config = kwargs.setdefault("config", {"content": "code-files"}) - print(repo_folder, config) return cls(repo_folder, config=config) def __get_parts_from_code_files(self): @@ -117,24 +103,29 @@ def __get_parts_from_code_files(self): Get the code parts from the repo :return: """ - file_extensions = self.config.get("file_extensions", None) - exclude_dirs = self.config.get("exclude_dirs", None) + file_extensions = self._search_settings.get("file_extensions", None) + exclude_dirs = self._search_settings.get("exclude_dirs", None) code_files = GitUtils.get_code_files_in_dir( - self.repo_folder, file_extensions, exclude_dirs + self._repo_folder, file_extensions, exclude_dirs ) parts = [] for file in code_files: with codecs.open(file, "r", encoding="utf-8", errors="ignore") as f: code_content = f.read() - parts.append( - f""" - file: {file} - ```python - {code_content} - ``` - """ + doc = Document( + page_content=f""" + file: {file} + ```python + {code_content} + ``` + """, + metadata={ + "file_path": str(file), + "category": "Code", + }, ) + parts.append(doc) return parts def __get_parts_from_repos_issues(self): @@ -142,9 +133,9 @@ def __get_parts_from_repos_issues(self): Get the issues from the repo :return: """ - issues_state = self.config.get("issues_state", "open") + issues_state = self._search_settings.get("issues_state", "open") - remotes = self.repo.remotes + remotes = self._repo.remotes assert len(remotes) > 0, "No remotes found" remote = remotes[0] url = remote.url @@ -154,12 +145,17 @@ def __get_parts_from_repos_issues(self): issues = remote_repo.get_issues(state=issues_state) parts = [] for issue in issues: - parts.append( - f""" - issue: {issue.title} - {issue.body} - """ + doc = Document( + page_content=f""" + issue: {issue.title} + {issue.body} + """, + metadata={ + "issue": issue.title, + "category": "Issue", + }, ) + parts.append(doc) return parts def content_parts(self): @@ -167,12 +163,9 @@ def content_parts(self): Get the content parts for the repo :return: """ - try: - functions_map = { - "code-files": self.__get_parts_from_code_files, - "issues": self.__get_parts_from_repos_issues, - } - return functions_map[self.content]() - except Exception as e: - logger.error(e) - raise e + functions_map = { + "code-files": self.__get_parts_from_code_files, + "issues": self.__get_parts_from_repos_issues, + } + parts = functions_map[self._search_content_type]() + return parts diff --git a/src/geminiplayground/parts/image_part/image_part.py b/src/geminiplayground/parts/image_part/image_part.py index c18353f..8c6244e 100644 --- a/src/geminiplayground/parts/image_part/image_part.py +++ b/src/geminiplayground/parts/image_part/image_part.py @@ -1,80 +1,16 @@ import logging import typing -from geminiplayground.catching import cache -from geminiplayground.core import GeminiClient -from .. import MultimodalPart -from geminiplayground.utils import FileUtils, LibUtils from pathlib import Path +from ..multimodal_part import MultiModalPartFile logger = logging.getLogger("rich") -class ImageFile(MultimodalPart): +class ImageFile(MultiModalPartFile): """ Audio file part implementation """ - def __init__(self, audio_path: typing.Union[str, Path], **kwargs): - self.path = audio_path - self.filename = FileUtils.get_file_name_from_path(audio_path) - self.gemini_client = kwargs.get("gemini_client", GeminiClient()) - - def upload(self): - """ - Upload the audio to Gemini - :return: - """ - # upload the file - with FileUtils.solve_file_path(self.path) as audio_file: - uploaded_file = self.gemini_client.upload_file(audio_file) - return uploaded_file - - @property - def file(self): - """ - Get the files - :return: - """ - if cache.get(self.filename): - logger.info(f"Getting image file {self.filename} from cache") - cached_file = cache.get(self.filename) - return cached_file - - logger.info(f"Uploading image file {self.filename}") - uploaded_file = self.upload() - delta_t = LibUtils.get_uploaded_file_exp_date_delta_t(uploaded_file) - cache.set(self.filename, uploaded_file, expire=delta_t) - return uploaded_file - - def force_upload(self): - """ - Force the upload of the audio - :return: - """ - self.delete() - self.upload() - - def delete(self): - """ - Delete the image from Gemini - :return: - """ - if cache.get(self.filename): - cached_file = cache.get(self.filename) - self.gemini_client.delete_file(cached_file.name) - cache.delete(self.filename) - - def clear_cache(self): - """ - Clear the cache - :return: - """ - cache.delete(self.filename) - - def content_parts(self) -> typing.List: - """ - Get the content parts for the audio - :return: - """ - return [self.file] + def __init__(self, file_path: typing.Union[str, Path], gemini_client=None, **kwargs): + super().__init__(file_path, gemini_client) diff --git a/src/geminiplayground/parts/multimodal_part.py b/src/geminiplayground/parts/multimodal_part.py index 703f5f2..def4b8e 100644 --- a/src/geminiplayground/parts/multimodal_part.py +++ b/src/geminiplayground/parts/multimodal_part.py @@ -1,4 +1,13 @@ from abc import ABC, abstractmethod +from geminiplayground.core import GeminiClient +import time +import typing +from pathlib import Path + +from geminiplayground.utils import FileUtils, LibUtils, Cacheable +from geminiplayground.utils.prompts import SUMMARIZATION_SYSTEM_INSTRUCTION +from geminiplayground.catching import cache +from yaspin import yaspin class MultimodalPart(ABC): @@ -6,21 +15,19 @@ class MultimodalPart(ABC): Abstract class for multimodal part """ - def upload(self, **kwargs): - """ - Upload the multimodal part - :param kwargs: - :return: - """ - ... + def __init__(self, gemini_client=None): + self._gemini_client = gemini_client if gemini_client else GeminiClient() - def clear_cache(self, **kwargs): + def summarize(self, model: str, **kwargs): """ - Clear the multimodal part - :param kwargs: + Summarize the multimodal part :return: """ - ... + summarization_prompt = ["Summarize the following content: "] + self.content_parts() + summarization_instructions = kwargs.get("summarization_instructions", SUMMARIZATION_SYSTEM_INSTRUCTION) + response = self._gemini_client.generate_response(model, summarization_prompt, + system_instruction=summarization_instructions, **kwargs) + return response.text @abstractmethod def content_parts(self, **kwargs): @@ -29,4 +36,68 @@ def content_parts(self, **kwargs): :param kwargs: :return: """ - raise NotImplementedError + raise NotImplementedError("Subclasses must implement the 'content_parts' method") + + +@Cacheable(cache, "_file_path") +class MultiModalPartFile(MultimodalPart): + """ + A class representing a cacheable file. + """ + + def __init__(self, file_path: typing.Union[str, Path], gemini_client=None): + super().__init__(gemini_client) + self._file_path = file_path + + @property + def local_path(self): + return self._file_path + + @property + def remote_file(self): + """ + Get the uploaded file from cache or upload it if not cached. + :return: The uploaded file + :raises ValueError: If the file type is not supported + """ + if self.in_cache(self._file_path): + cached_file = self.get_cache(self._file_path) + return cached_file + + return self.upload() + + def upload(self): + """ + Upload the audio to Gemini + :return: + """ + with yaspin(text=f"Uploading file {self._file_path}") as sp: + with FileUtils.solve_file_path(self._file_path) as file: + uploaded_file = self._gemini_client.upload_file(file) + while uploaded_file.state.name == "PROCESSING": + time.sleep(10) + uploaded_file = self._gemini_client.get_file(uploaded_file.name) + if uploaded_file.state.name == "FAILED": + sp.fail("❌") + raise Exception("File upload failed") + delta_t = LibUtils.get_uploaded_file_exp_date_delta_t(uploaded_file) + # this unction is injected by the Cacheable decorator + self.set_cache( + self._file_path, uploaded_file, expire=delta_t + ) + sp.ok("✅") + return uploaded_file + + def delete(self): + """ + Delete the image from Gemini + :return: + """ + if self.in_cache(self._file_path): + cached_file = self.get_cache(self._file_path) + self._gemini_client.delete_file(cached_file.name) + # this function remove any cache entry for the file + self.clear_cache() + + def content_parts(self, **kwargs): + return [self.remote_file] diff --git a/src/geminiplayground/parts/pdf_part/pdf_part.py b/src/geminiplayground/parts/pdf_part/pdf_part.py index 9a4707f..a4e5061 100644 --- a/src/geminiplayground/parts/pdf_part/pdf_part.py +++ b/src/geminiplayground/parts/pdf_part/pdf_part.py @@ -1,38 +1,88 @@ import logging import typing -from PyPDF2 import PdfReader +import pymupdf +import validators from geminiplayground.core import GeminiClient -from .. import MultimodalPart -from geminiplayground.utils import FileUtils +from .. import MultimodalPart, ImageFile +from geminiplayground.utils import FileUtils, Cacheable from pathlib import Path +from geminiplayground.catching import cache +from slugify import slugify +from langchain_core.documents import Document logger = logging.getLogger("rich") +@Cacheable(cache, "_file_path") class PdfFile(MultimodalPart): """ PDF file part implementation """ - def __init__(self, pdf_path: typing.Union[str, Path], **kwargs): - self.path = pdf_path - self.filename = FileUtils.get_file_name_from_path(pdf_path) - self.gemini_client = kwargs.get("gemini_client", GeminiClient()) + def __init__(self, file_path: typing.Union[str, Path], gemini_client: GeminiClient = None, **kwargs): + super().__init__(gemini_client) + self._file_path = file_path - def __get_pdf_parts(self) -> typing.List[str]: + @Cacheable.cache_func + def __get_pdf_parts(self) -> typing.List[typing.Any]: """ Get the content parts for the pdf :return: list of text parts """ - text_parts = [] - with FileUtils.solve_file_path(self.path) as pdf_path: - with open(pdf_path, "rb") as pdf_file: - reader = PdfReader(pdf_file) - for page in reader.pages: - text_parts.append(page.extract_text()) - return text_parts + parts = [] + with FileUtils.solve_file_path(self._file_path) as pdf_path: + pdf = pymupdf.open(pdf_path) + for page_num in range(len(pdf)): + page = pdf[page_num] + parts.append(self._extract_page_content(page)) + parts.extend(self._extract_page_images(pdf, page)) + pdf.close() + return parts + + def _extract_page_content(self, page): + """ + Extract text from a page + :param page: The page to extract text from + :return: The extracted text + """ + return Document( + page_content=page.get_text(), + metadata={ + "file_path": str(self._file_path), + "page_number": page.number, + "category": "Text", + }, + ) + + def _extract_page_images(self, pdf, page): + """ + Extract images from a page + :param page: The page to extract images from + :return: The extracted images + """ + file_path = str(self._file_path) + if validators.url(file_path): + images_folder = Path(slugify(file_path)) + else: + file_path = Path(file_path) + images_folder = file_path.parent / file_path.stem + + images_folder.mkdir(exist_ok=True, parents=True) + images = [] + for image in page.get_images(full=True): + # get the XREF of the image + xref = image[0] + pix = pymupdf.Pixmap(pdf, xref) + if pix.n - pix.alpha > 3: + pix = pymupdf.Pixmap(pymupdf.csRGB, pix) + image_path = images_folder / f"image{page.number}.png" + pix.save(image_path) + image = ImageFile(image_path) + images.append(image) + del pix + return images def content_parts(self): """ diff --git a/src/geminiplayground/parts/video_part/video_part.py b/src/geminiplayground/parts/video_part/video_part.py index f11f479..b611365 100644 --- a/src/geminiplayground/parts/video_part/video_part.py +++ b/src/geminiplayground/parts/video_part/video_part.py @@ -1,113 +1,23 @@ import json import logging -import time import typing from pydantic import BaseModel -from geminiplayground.catching import cache -from geminiplayground.core import GeminiClient -from .. import MultimodalPart -from geminiplayground.utils import FileUtils, LibUtils +from ..multimodal_part import MultiModalPartFile from pathlib import Path import google.generativeai as genai logger = logging.getLogger("rich") -class VideoFile(MultimodalPart): +class VideoFile(MultiModalPartFile): """ Audio file part implementation """ - def __init__(self, audio_path: typing.Union[str, Path], **kwargs): - self.path = audio_path - self.filename = FileUtils.get_file_name_from_path(audio_path) - self.gemini_client = kwargs.get("gemini_client", GeminiClient()) - - def upload(self): - """ - Upload the audio to Gemini - :return: - """ - # upload the file - with FileUtils.solve_file_path(self.path) as audio_file: - uploaded_file = self.gemini_client.upload_file(audio_file) - return uploaded_file - - def check_status(self): - """ - Check the status of the file - :return: - """ - remote_file_name = self.file.name - file = self.gemini_client.get_file(remote_file_name) - return file.state.name - - def wait(self): - """ - Wait until the file is ready - :return: - """ - logger.info(f"Waiting for the file {self.filename} to be ready") - remote_file_name = self.file.name - file = self.gemini_client.get_file(remote_file_name) - while file.state.name == "PROCESSING": - time.sleep(10) - file = self.gemini_client.get_file(remote_file_name) - if file.state.name == "FAILED": - raise Exception("File upload failed") - - @property - def file(self): - """ - Get the files - :return: - """ - if cache.get(self.filename): - logger.info(f"Getting image file {self.filename} from cache") - cached_file = cache.get(self.filename) - return cached_file - - logger.info(f"Uploading image file {self.filename}") - uploaded_file = self.upload() - delta_t = LibUtils.get_uploaded_file_exp_date_delta_t(uploaded_file) - cache.set(self.filename, uploaded_file, expire=delta_t) - return uploaded_file - - def force_upload(self): - """ - Force the upload of the audio - :return: - """ - self.delete() - self.upload() - - def delete(self): - """ - Delete the image from Gemini - :return: - """ - if cache.get(self.filename): - cached_file = cache.get(self.filename) - self.gemini_client.delete_file(cached_file.name) - cache.delete(self.filename) - - def clear_cache(self): - """ - Clear the cache - :return: - """ - cache.delete(self.filename) - - def content_parts(self) -> typing.List: - """ - Get the content parts for the audio - :return: - """ - if self.check_status() == "PROCESSING": - self.wait() - return [self.file] + def __init__(self, file_path: typing.Union[str, Path], gemini_client=None, **kwargs): + super().__init__(file_path, gemini_client) def extract_keyframes(self, model: str = "models/gemini-1.5-flash-latest"): """ @@ -126,8 +36,8 @@ class VideoKeyFrame(BaseModel): system_instruction = """you are a video processing system, follow the instructions and extract the key frames in the provided video, your response should include a description of max 100 characters and the timespan of each key frame""" - prompt = ["return the key frames in the following video", self.file] - raw_response = self.gemini_client.generate_response( + prompt = ["return the key frames in the following video"] + self.content_parts() + raw_response = self._gemini_client.generate_response( model, prompt, stream=False, diff --git a/src/geminiplayground/rag/__init__.py b/src/geminiplayground/rag/__init__.py new file mode 100644 index 0000000..ba0edd0 --- /dev/null +++ b/src/geminiplayground/rag/__init__.py @@ -0,0 +1,6 @@ +from .summarization_loader import SummarizationLoader +from .lotr_rag import LOTRRAG +from .agentic_routing_rag import AgenticRoutingRAG +from .agentic_tool_use import AgenticToolUseRAG + +__all__ = ["SummarizationLoader", "LOTRRAG", "AgenticRoutingRAG", "AgenticToolUseRAG"] diff --git a/src/geminiplayground/rag/agentic_routing_rag.py b/src/geminiplayground/rag/agentic_routing_rag.py new file mode 100644 index 0000000..654ddf9 --- /dev/null +++ b/src/geminiplayground/rag/agentic_routing_rag.py @@ -0,0 +1,160 @@ +"""Use a single chain to route an input to one of multiple retrieval qa chains.""" +from __future__ import annotations + +import typing +from typing import Any, Dict, List, Mapping, Optional + +from langchain_core.language_models import BaseLanguageModel, BaseChatModel +from langchain_core.messages import HumanMessage +from langchain_core.prompts import PromptTemplate +from langchain_core.retrievers import BaseRetriever + +from langchain.chains import ConversationChain +from langchain.chains.base import Chain +from langchain.chains.conversation.prompt import DEFAULT_TEMPLATE +from langchain.chains.retrieval_qa.base import BaseRetrievalQA, RetrievalQA +from langchain.chains.router.base import MultiRouteChain +from langchain.chains.router.llm_router import LLMRouterChain, RouterOutputParser +from langchain.chains.router.multi_retrieval_prompt import ( + MULTI_RETRIEVAL_ROUTER_TEMPLATE, +) + +from .rag import RAG, RAGResponse + + +class MultiRetrievalQAChain(MultiRouteChain): + """A multi-route chain that uses an LLM router chain to choose amongst retrieval + qa chains.""" + + router_chain: LLMRouterChain + """Chain for deciding a destination chain and the input to it.""" + destination_chains: Mapping[str, BaseRetrievalQA] + """Map of name to candidate chains that inputs can be routed to.""" + default_chain: Chain + """Default chain to use when router doesn't map input to one of the destinations.""" + + @property + def output_keys(self) -> List[str]: + return ["result"] + + @classmethod + def from_retrievers( + cls, + llm: BaseLanguageModel, + retriever_infos: List[Dict[str, Any]], + default_retriever: Optional[BaseRetriever] = None, + default_prompt: Optional[PromptTemplate] = None, + default_chain: Optional[Chain] = None, + *, + default_chain_llm: Optional[BaseLanguageModel] = None, + **kwargs: Any, + ) -> MultiRetrievalQAChain: + if default_prompt and not default_retriever: + raise ValueError( + "`default_retriever` must be specified if `default_prompt` is " + "provided. Received only `default_prompt`." + ) + destinations = [f"{r['name']}: {r['description']}" for r in retriever_infos] + destinations_str = "\n".join(destinations) + router_template = MULTI_RETRIEVAL_ROUTER_TEMPLATE.format( + destinations=destinations_str + ) + router_prompt = PromptTemplate( + template=router_template, + input_variables=["input"], + output_parser=RouterOutputParser(next_inputs_inner_key="query"), + ) + router_chain = LLMRouterChain.from_llm(llm, router_prompt) + destination_chains = {} + for r_info in retriever_infos: + prompt = r_info.get("prompt") + retriever = r_info["retriever"] + chain = RetrievalQA.from_llm( + llm, prompt=prompt, retriever=retriever, return_source_documents=True + ) + + name = r_info["name"] + destination_chains[name] = chain + if default_chain: + _default_chain = default_chain + elif default_retriever: + _default_chain = RetrievalQA.from_llm( + llm, prompt=default_prompt, retriever=default_retriever, return_source_documents=True + ) + else: + prompt_template = DEFAULT_TEMPLATE.replace("input", "query") + prompt = PromptTemplate( + template=prompt_template, input_variables=["history", "query"] + ) + if default_chain_llm is None: + raise NotImplementedError( + "conversation_llm must be provided if default_chain is not " + "specified. This API has been changed to avoid instantiating " + "default LLMs on behalf of users." + "You can provide a conversation LLM like so:\n" + "from langchain_openai import ChatOpenAI\n" + "llm = ChatOpenAI()" + ) + _default_chain = ConversationChain( + llm=default_chain_llm, + prompt=prompt, + input_key="query", + output_key="result", + ) + return cls( + router_chain=router_chain, + destination_chains=destination_chains, + default_chain=_default_chain, + **kwargs, + ) + + +class AgenticRoutingRAG(RAG): + """ + A RAG implementation using a ROUTER (MultiRetrievalQAChain) + """ + + def __init__( + self, + chat_model: BaseChatModel, + retrievers_info: typing.List[dict], + chat_history: typing.List[HumanMessage] = None + ): + super().__init__(chat_model, retrievers_info, chat_history) + + def invoke(self, question: str) -> RAGResponse: + """ + Invoke the RAG model. + """ + qa_chain = self.get_runnable() + result = qa_chain.invoke({"input": question, "chat_history": self._chat_history}) + + docs = result.get("source_documents", []) + answer = result.get("result", None) + + return RAGResponse( + answer=answer, + docs=docs + ) + + def get_runnable(self): + """ + Get the chain. + """ + + DEFAULT_TEMPLATE = """The following is a friendly conversation between a human and an AI. The AI is talkative + and provides lots of specific details from its context. If the AI does not know the answer to a question, + it truthfully says it does not know. + Current conversation: + {history} + Human: {input} + AI:""" + default_prompt_template = DEFAULT_TEMPLATE.replace('input', 'query') + default_prompt = PromptTemplate( + template=default_prompt_template, input_variables=['history', 'query'] + ) + default_chain = ConversationChain(llm=self._chat_model, prompt=default_prompt, input_key='query', + output_key='result') + return MultiRetrievalQAChain.from_retrievers(llm=self._chat_model, retriever_infos=self._retrievers_info, + default_chain=default_chain, + verbose=True) diff --git a/src/geminiplayground/rag/agentic_tool_use.py b/src/geminiplayground/rag/agentic_tool_use.py new file mode 100644 index 0000000..1f84322 --- /dev/null +++ b/src/geminiplayground/rag/agentic_tool_use.py @@ -0,0 +1,78 @@ +"""Use a single chain to route an input to one of multiple retrieval qa chains.""" +from __future__ import annotations + +import typing + +from langchain.agents import create_tool_calling_agent, AgentExecutor +from langchain_core.language_models import BaseChatModel +from langchain_core.messages import HumanMessage +from langchain_core.prompts import ChatPromptTemplate, PromptTemplate +from langchain_core.tools import create_retriever_tool + +from .rag import RAG, RAGResponse + + +class AgenticToolUseRAG(RAG): + """ + A RAG implementation using a ROUTER (MultiRetrievalQAChain) + """ + + def __init__( + self, + chat_model: BaseChatModel, + retrievers_info: typing.List[dict], + custom_tools: list = None, + chat_history: typing.List[HumanMessage] = None + ): + super().__init__(chat_model, retrievers_info, chat_history) + self._custom_tools = custom_tools or [] + + def _get_retriever_tools(self): + """ + Get the retriever tools. + """ + tools = [] + document_prompt = PromptTemplate.from_template("{page_content} \n {file_path}") + for retriever_info in self._retrievers_info: + retriever = retriever_info.get("retriever") + name = retriever_info.get("name") + description = retriever_info.get("description") + retriever_tool = create_retriever_tool( + retriever, + name=name, + description=description, + document_prompt=document_prompt + ) + tools.append(retriever_tool) + return tools + + def get_runnable(self): + """ + Get the chain. + """ + tools = self._get_retriever_tools() + self._custom_tools + + prompt = ChatPromptTemplate.from_messages( + [ + ("system", "You are a helpful assistant"), + ("placeholder", "{chat_history}"), + ("human", "{input}"), + ("placeholder", "{agent_scratchpad}"), + ] + ) + + agent = create_tool_calling_agent(self._chat_model, tools, prompt) + agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True, handle_parsing_errors=True) + return agent_executor + + def invoke(self, question: str) -> typing.Any: + """ + Invoke the RAG model. + """ + agent_executor = self.get_runnable() + print("Chat history:", self._chat_history) + result = agent_executor.invoke({"input": question, "chat_history": self._chat_history}) + return RAGResponse( + answer=result["output"], + docs=[] + ) diff --git a/src/geminiplayground/rag/lotr_rag.py b/src/geminiplayground/rag/lotr_rag.py new file mode 100644 index 0000000..5d18b65 --- /dev/null +++ b/src/geminiplayground/rag/lotr_rag.py @@ -0,0 +1,98 @@ +import logging +import typing + +from dotenv import load_dotenv, find_dotenv +from langchain.chains.combine_documents import create_stuff_documents_chain +from langchain.chains.history_aware_retriever import create_history_aware_retriever +from langchain.chains.retrieval import create_retrieval_chain +from langchain.retrievers import MergerRetriever +from langchain_core.messages import HumanMessage +from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder +from langchain_core.retrievers import BaseRetriever +from langchain_core.runnables import Runnable +from langchain_core.language_models import BaseChatModel +from .rag import RAG, RAGResponse + +logging.basicConfig(level=logging.INFO) + +load_dotenv(find_dotenv()) + + +class LOTRRAG(RAG): + """ + A RAG implementation using LOTR (Merger Retriever) + """ + + def __init__( + self, + chat_model: BaseChatModel, + retrievers_info: typing.List[dict], + chat_history: typing.List[HumanMessage] = None + ): + super().__init__(chat_model, retrievers_info, chat_history) + + def get_retriever(self) -> BaseRetriever: + """ + Get the retriever. + """ + assert len(self._retrievers_info) > 0, "At least one retriever is required." + + # Single retriever + if len(self._retrievers_info) == 1: + return self._retrievers_info[0].get("retriever") + + # LOTR (Merger Retriever) + lotr_retriever = MergerRetriever(retrievers=[ + retriever["retriever"] for retriever in self._retrievers_info + ]) + return lotr_retriever + + def invoke(self, question: str) -> RAGResponse: + """ + Invoke the RAG model. + """ + qa_chain = self.get_runnable() + result = qa_chain.invoke({"input": question, "chat_history": self._chat_history}) + return RAGResponse( + answer=result["answer"], + docs=result["context"] + ) + + def get_runnable(self) -> Runnable: + """ + Get the RAG chain. + """ + retriever = self.get_retriever() + llm = self._chat_model + contextualize_q_system_prompt = """Given a chat history and the latest user question \ + which might reference context in the chat history, formulate a standalone question \ + which can be understood without the chat history. Do NOT answer the question, \ + just reformulate it if needed and otherwise return it as is.""" + contextualize_q_prompt = ChatPromptTemplate.from_messages( + [ + ("system", contextualize_q_system_prompt), + MessagesPlaceholder("chat_history"), + ("human", "{input}"), + ] + ) + history_aware_retriever = create_history_aware_retriever( + llm, retriever, contextualize_q_prompt + ) + + qa_system_prompt = """You are an assistant for question-answering tasks. \ + Use the following pieces of retrieved context to answer the question. \ + If you don't know the answer, just say that you don't know. \ + Use three sentences maximum and keep the answer concise.\ + + {context}""" + qa_prompt = ChatPromptTemplate.from_messages( + [ + ("system", qa_system_prompt), + MessagesPlaceholder("chat_history"), + ("human", "{input}"), + ] + ) + + question_answer_chain = create_stuff_documents_chain(llm, qa_prompt) + rag_chain_with_chat_history = create_retrieval_chain(history_aware_retriever, question_answer_chain) + return rag_chain_with_chat_history diff --git a/src/geminiplayground/rag/rag.py b/src/geminiplayground/rag/rag.py new file mode 100644 index 0000000..d7ecd5c --- /dev/null +++ b/src/geminiplayground/rag/rag.py @@ -0,0 +1,68 @@ +import typing +from abc import abstractmethod, ABC + +from langchain_core.messages import HumanMessage +from langchain_core.retrievers import BaseRetriever +from langchain_core.runnables import Runnable +from pydantic import BaseModel +from rich.console import Console +from langchain_core.language_models import BaseChatModel + + +class RAGResponse(BaseModel): + answer: str + docs: list + + +class RAG(ABC): + """ + A RAG model for summarization. + """ + + def __init__( + self, + chat_model: BaseChatModel, + retrievers_info: typing.List[typing.Union[BaseRetriever, typing.Dict[str, typing.Any]]], + chat_history: typing.List[HumanMessage] = None + ): + self._chat_model = chat_model + self._retrievers_info = retrievers_info + self._chat_history = chat_history or [] + + @property + def chat_history(self): + """ + Get the chat history. + """ + return self._chat_history + + @abstractmethod + def get_runnable(self) -> Runnable: + """ + Get the RAG runnable + """ + raise NotImplementedError("This function must be implemented in the subclass.") + + @abstractmethod + def invoke(self, question: str) -> RAGResponse: + """ + Invoke the RAG model. + """ + raise NotImplementedError("This function must be implemented in the subclass.") + + def chat(self): + """ + Main function to execute the RAG workflow. + """ + + console = Console() + while True: + question = input("Question: ") + if question.lower() == "exit": + break + result = self.invoke(question) + self._chat_history.extend([HumanMessage(content=question), result.answer]) + console.print(f"Answer: {result.answer}") + docs = result.docs + for doc in docs[:3]: + console.print(doc) diff --git a/src/geminiplayground/rag/summarization_loader.py b/src/geminiplayground/rag/summarization_loader.py new file mode 100644 index 0000000..bf929c4 --- /dev/null +++ b/src/geminiplayground/rag/summarization_loader.py @@ -0,0 +1,39 @@ +from typing import Iterator + +from langchain_core.document_loaders import BaseLoader +from langchain_core.documents import Document +from geminiplayground.parts import MultiModalPartFile, MultimodalPart + + +class SummarizationLoader(BaseLoader): + + def __init__(self, model: str, *content: MultimodalPart): + self._content = content + self._model = model + + def lazy_load(self) -> Iterator[Document]: + """ + Lazy load documents. + """ + for content in self._content: + if isinstance(content, MultiModalPartFile): + yield self._create_document_from_file(content) + else: + for part in content.content_parts(): + if isinstance(part, MultiModalPartFile): + yield self._create_document_from_file(part) + elif isinstance(part, Document): + yield part + + def _create_document_from_file(self, part: MultiModalPartFile) -> Document: + """ + Create a Document object from a MultiModalPartFile. + """ + try: + file_summary = part.summarize(model=self._model, stream=False) + return Document( + page_content=file_summary, + metadata={"file_path": str(part.local_path)} + ) + except Exception as ex: + raise ValueError(f"Error summarizing file {part.local_path}: {ex}") from ex diff --git a/src/geminiplayground/utils/__init__.py b/src/geminiplayground/utils/__init__.py index db68d48..27bd5ea 100644 --- a/src/geminiplayground/utils/__init__.py +++ b/src/geminiplayground/utils/__init__.py @@ -6,6 +6,7 @@ from .lib_utils import LibUtils from .video_utils import VideoUtils from .pdf_utils import PDFUtils +from .cacheable import Cacheable __all__ = [ "GitRemoteProgress", @@ -16,4 +17,6 @@ "LibUtils", "VideoUtils", "PDFUtils", + "Cacheable", + ] diff --git a/src/geminiplayground/utils/cacheable.py b/src/geminiplayground/utils/cacheable.py new file mode 100644 index 0000000..0b47212 --- /dev/null +++ b/src/geminiplayground/utils/cacheable.py @@ -0,0 +1,100 @@ +import functools +from diskcache import Cache +import logging + +logger = logging.getLogger("rich") + + +class Cacheable: + """ + Decorator to cache make classes cacheable. + """ + + def __init__(self, cache: Cache, cache_tag_attr: str): + self._cache = cache + self._cache_tag_attr = cache_tag_attr + + @staticmethod + def cache_func(func): + """ + Decorator to cache the results of a function. + :param func: The function to be decorated + :return: The decorated function + """ + + @functools.wraps(func) + def decorator(self, *args, **kwargs): + """ + Decorator to cache the results of a function implementation. + :param self: + :param args: + :param kwargs: + :return: + """ + assert hasattr(self, "_cache_tag_attr"), ( + f"To use the `cache_func` decorator, you must make sure to decorate the class `{self.__class__.__name__}`" + f"with the Cacheable decorator as follows: @Cacheable(cache, 'tag_attr')" + ) + + cache_entry_key = ( + f"{self.__class__.__name__}_{func.__name__}_{args}_{kwargs}" + ) + cache_entry_tag = str(getattr(self, self._cache_tag_attr)) + cached_result, cached_result_tag = self._cache.get(cache_entry_key, tag=cache_entry_tag) + + if cache_entry_key in self._cache and cached_result_tag == cache_entry_tag: + logger.info(f"Loading cached results for {cache_entry_key}") + return cached_result + + logger.info( + f"No cache found for {cache_entry_key}. Computing results and saving to cache. This may take a while." + ) + result = func(self, *args, **kwargs) + self._cache.set(cache_entry_key, result, tag=cache_entry_tag) + return result + + return decorator + + def __call__(self, cls): + def clear_cache(self): + """ + Clear the cache for this file. + """ + logger.info(f"Clearing cache for {self.__class__.__name__}") + cache_tag = str(getattr(self, self._cache_tag_attr)) + self._cache.evict(tag=cache_tag) + + def set_cache(self, key, value, **kwargs): + """ + Add a value to the cache + """ + cache_tag = str(getattr(self, self._cache_tag_attr)) + self._cache.set(str(key), value, tag=cache_tag, **kwargs) + + def get_cache(self, key): + """ + Get a value from the cache + """ + return self._cache.get(str(key)) + + def del_cache(self, key): + """ + Delete a value from the cache + """ + del self._cache[str(key)] + + def in_cache(self, key): + """ + Check if a value is in the cache + """ + return str(key) in self._cache + + cls.clear_cache = clear_cache + cls.set_cache = set_cache + cls.get_cache = get_cache + cls.del_cache = del_cache + cls.in_cache = in_cache + setattr(cls, "_cache", self._cache) + setattr(cls, "_cache_tag_attr", self._cache_tag_attr) + + return cls diff --git a/src/geminiplayground/utils/file_utils.py b/src/geminiplayground/utils/file_utils.py index 9d6c967..c7dce06 100644 --- a/src/geminiplayground/utils/file_utils.py +++ b/src/geminiplayground/utils/file_utils.py @@ -45,7 +45,9 @@ def onflyTemporaryDirectory(cls, **kwargs): try: yield name finally: - cls.rm_tree(name) + cls.clear_folder(name) + if os.path.exists(name): + os.rmdir(name) @staticmethod @contextmanager diff --git a/src/geminiplayground/utils/git_utils.py b/src/geminiplayground/utils/git_utils.py index 20f6b72..e66727a 100644 --- a/src/geminiplayground/utils/git_utils.py +++ b/src/geminiplayground/utils/git_utils.py @@ -63,11 +63,26 @@ def folder_contains_git_repo(path): :return: True if the given folder is a repor or false otherwise """ try: + if not Path(path).exists(): + raise Exception(f"Path {path} does not exist") _ = git.Repo(path).git_dir return True except (git.exc.InvalidGitRepositoryError, Exception): return False + @staticmethod + def validate_repo_folder(repo_folder: typing.Union[str, Path]) -> Path: + """ + Validate the repo folder + """ + repo_folder = Path(repo_folder).resolve(strict=True) + if not repo_folder.exists(): + raise FileNotFoundError(f"{repo_folder} does not exist") + if not GitUtils.folder_contains_git_repo(repo_folder): + raise ValueError(f"{repo_folder} is not a git repository") + + return repo_folder + @staticmethod def get_repo_name_from_url(url: str) -> str: """ diff --git a/src/geminiplayground/utils/lib_utils.py b/src/geminiplayground/utils/lib_utils.py index 7f6420d..29d0c60 100644 --- a/src/geminiplayground/utils/lib_utils.py +++ b/src/geminiplayground/utils/lib_utils.py @@ -1,9 +1,11 @@ import inspect import typing +from PIL.Image import Image from google.generativeai.types import File, FunctionDeclaration from datetime import datetime, timezone from pathlib import Path +from langchain_core.documents import Document import os import re @@ -157,8 +159,11 @@ def normalize_prompt(prompt): normalized_prompt.append(part) elif isinstance(part, MultimodalPart): content_parts = part.content_parts() - normalized_prompt.extend(content_parts) - elif isinstance(part, File): + normalized_parts = LibUtils.normalize_prompt(content_parts) + normalized_prompt.extend(normalized_parts) + elif isinstance(part, Document): + normalized_prompt.append(part.page_content) + elif isinstance(part, (File, Image)): normalized_prompt.append(part) else: raise ValueError(f"Invalid prompt part: {part}") diff --git a/src/geminiplayground/utils/prompts.py b/src/geminiplayground/utils/prompts.py new file mode 100644 index 0000000..80a94ee --- /dev/null +++ b/src/geminiplayground/utils/prompts.py @@ -0,0 +1,6 @@ +SUMMARIZATION_SYSTEM_INSTRUCTION = """ + you are an assistant tasked with summarizing files, and content for retrieval. \ + These summaries will be embedded and used to retrieve the original file/content. Therefore, \ + make sure you detailed describe the content of the file and expand on the details. \ +Only describe what you see, hear or read in the file. + """ diff --git a/src/geminiplayground/web/api.py b/src/geminiplayground/web/api.py index 3d840a4..1ab0875 100644 --- a/src/geminiplayground/web/api.py +++ b/src/geminiplayground/web/api.py @@ -21,6 +21,7 @@ from sqlalchemy import select from sqlalchemy.ext.asyncio import AsyncSession from fastapi.concurrency import run_in_threadpool +from geminiplayground.parts import MultiModalPartFile from geminiplayground.core import GeminiClient, GeminiPlayground, ToolCall from geminiplayground.utils import ( GitUtils, VideoUtils, ImageUtils, PDFUtils, LibUtils, FileUtils @@ -257,8 +258,9 @@ async def upload_file(session: AsyncSession, file_path: Path, content_type: str) thumbnail_img.save(thumbnail_path) multimodal_part = MultimodalPartFactory.from_path(file_path) - multimodal_part.clear_cache() - await run_in_threadpool(multimodal_part.upload) + if isinstance(multimodal_part, MultiModalPartFile): + multimodal_part.clear_cache() + await run_in_threadpool(multimodal_part.upload) logger.info(f"Uploaded file {file_path}") part.status = EntryStatus.READY part.status_message = "" @@ -368,7 +370,8 @@ async def delete_part_handler( multimodal_part = MultimodalPartFactory.from_path( PLAYGROUND_HOME_DIR.joinpath(part_id) ) - background_tasks.add_task(delete_multimodal_part_files, multimodal_part) + if isinstance(multimodal_part, MultiModalPartFile): + background_tasks.add_task(delete_multimodal_part_files, multimodal_part) file = PLAYGROUND_HOME_DIR.joinpath(part_id) if file.exists(): file.unlink() diff --git a/src/geminiplayground/web/utils.py b/src/geminiplayground/web/utils.py index e31ba54..95688ba 100644 --- a/src/geminiplayground/web/utils.py +++ b/src/geminiplayground/web/utils.py @@ -65,7 +65,7 @@ async def process_multimodal_part(part, files_dir, repos_dir): repo_folder = repos_dir.joinpath(part_entry.name) repo = GitRepo.from_folder( repo_folder, - config={"content": "code-files", "file_extensions": [".py"]}, + config={"content": "code-files"}, ) parts.extend(repo.content_parts()) else:

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