An implementation of GraphRAG using graphrag-sdk, falkordb, langchain, ...
This project is a robust service for managing, generating, and interacting with Knowledge Graphs (KG) using the GraphRAG-SDK, FalkorDB, and LangChain. The service provides a flexible and scalable platform for handling different file types, creating ontologies, generating KGs, extending them, and interacting with them via chat.
Key features of this project include:
- GraphRAG-SDK: Used for managing the creation and processing of Knowledge Graphs.
- FalkorDB: Stores and evolves the generated KGs in a highly efficient and scalable manner.
- LangChain: Powers the conversational chat interface, enabling interactions with the knowledge stored in the KG.
- FastAPI: The service is built as a FastAPI application to provide a fast and efficient API layer for interacting with the system.
- Dockerized with Docker Compose: The entire service is containerized for easy deployment, with CI/CD pipelines via GitHub Actions for continuous integration and delivery.
- Ontology Creation: Define and create an ontology to structure the data for the KG.
- Knowledge Graph Generation: Generate a KG based on a provided ontology and various data sources (PDF, Word, PowerPoint).
- KG Extension: Add new data and extend the existing KG.
- Chat Interface: Interact with the generated KG via a conversational chat powered by LangChain.
- File Upload: Upload files for future processing and integration.
- Python 3.11
- Docker and Docker Compose installed
- FastAPI and other Python dependencies
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Clone the repository:
git clone https://github.com/fatemenajafi135/GraphRAG.git cd GraphRAG -
Build and run the Docker containers: The project uses Docker Compose to set up the necessary services.
docker-compose up --build
This will:
- Build the FastAPI service container.
- Set up the FalkorDB container for storing the Knowledge Graph.
- Ensure that the CI/CD pipeline for GitHub Actions is ready for automatic deployment.
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Access the FastAPI documentation: Once the services are running, you can access the FastAPI documentation at:
http://localhost:8000/docs
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CI/CD Pipeline (GitHub Actions): The repository is integrated with GitHub Actions for CI/CD automation. It automatically builds, tests, and deploys containers upon any changes to the codebase. All relevant configuration files for GitHub Actions can be found in the
.github/workflows/directory. -
Available APIs The service exposes the following APIs for interacting with the Knowledge Graph:
- POST /ontology/create: Create a new ontology based on a provided sources.
- POST /kg/create: Generate a new Knowledge Graph based on the defined ontology.
- PUT /kg/extend: Extend an existing Knowledge Graph by adding new data.
- POST /kg/upload-files: upload files for future processing and integration. (URL, PDF, Word, PowerPoint).
- POST /chat: Chat interface to interact with the Knowledge Graph via LangChain.
- GraphRAG-SDK:
- Framework for generating and managing Knowledge Graphs.
- Chosen for its ability to efficiently manage the process of generating and processing complex Knowledge Graphs.
- FalkorDB:
- A scalable, production-grade graph database to store the Knowledge Graph.
- Ideal for storing graph-based data, providing fast querying and scalability.
- LangChain:
- Conversational AI chain for querying and interacting with the Knowledge Graph.
- A powerful tool for building conversational AI chains, perfect for creating chat interfaces with knowledge graphs.
- FastAPI:
- A modern web framework for creating APIs.
- Known for its high performance and easy integration with modern Python-based APIs.
- Docker & Docker Compose:
- Containerization and orchestration for the entire service.
- Ensures consistency in deployment across environments and simplifies managing dependencies.
- GitHub Actions:
- CI/CD for automated testing and deployment.