readme updated

Author: fatemenajafi135

README.md

@@ -1,17 +1,80 @@
 # GraphRAG
 An implementation of GraphRAG using graphrag-sdk, falkordb, langchain, ...
 
+## Project Overview
+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.
 
-## Running Manually
+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.
 
-- DB:
-```shell
-docker pull falkordb/falkordb:edge
-docker run -p 6379:6379 -p 3000:3000 -it --rm -v ./knowledgebase:/knowledgebase falkordb/falkordb:edge
-```
+## Features
+- **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.
+  
+## How to Run the Service
 
-- FASTAPI
-```shell
-fastapi run app.py
-```
- 
+### Prerequisites
+- Python 3.11
+- Docker and Docker Compose installed
+- FastAPI and other Python dependencies
+
+### Setup Instructions
+
+1. **Clone the repository**:
+   ```bash
+   git clone https://github.com/fatemenajafi135/GraphRAG.git
+   cd GraphRAG
+    ```
+
+2. Build and run the Docker containers: The project uses Docker Compose to set up the necessary services.
+    ```shell
+    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.
+
+3. Access the FastAPI documentation: Once the services are running, you can access the FastAPI documentation at:
+    ```shell
+    http://localhost:8000/docs
+    ```
+
+4. 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.
+
+5. 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.
+
+## Technologies Used AND WHY
+
+- **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.