{"id":22352200,"url":"https://github.com/shamspias/langchain-chat","last_synced_at":"2025-07-30T07:32:10.137Z","repository":{"id":162225365,"uuid":"625567062","full_name":"shamspias/langchain-chat","owner":"shamspias","description":"langchain-chat is an AI-driven Q\u0026A system that leverages OpenAI's GPT-4 model and FAISS for efficient document indexing. It loads and splits documents from websites or PDFs, remembers conversations, and provides accurate, context-aware answers based on the indexed data. 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The system indexes documents from websites or PDF files using FAISS (Facebook AI Similarity\nSearch) and offers a convenient interface for interacting with the data.\n\n## Features\n\n- Load and split documents from websites or PDF files\n- Index documents using FAISS for efficient similarity search\n- Utilize OpenAI's GPT-4 to generate human-like responses\n- Remember previous conversations and provide context-aware answers\n- Easy to set up and extend\n\n## Installation\n\n1. Clone the repository\n2. Create a virtual environment\n    ```bash\n    python -m venv venv\n    ```\n3. Activate the virtual environment\n    ```bash\n    source venv/Scripts/activate\n    ```\n4. Install the dependencies\n    ```bash\n    pip install -r requirements.txt\n    ```\n5. Copy the `.env.example` file to `.env` and fill in the required values\n   ```bash\n   cp .env.example .env\n   ```\n   ```bash\n   OPEN_AI_KEY = \"sk-\"\n   WEBSITE_URLS=\"https://website1, https://website2\"\n   ```\n6. Run the application\n    ```bash\n    python with_faiss.py\n    ```\n\n## Example Images\n\n![Example 1](https://github.com/shamspias/langchain-chat/blob/main/images/conversation.PNG)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshamspias%2Flangchain-chat","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fshamspias%2Flangchain-chat","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshamspias%2Flangchain-chat/lists"}