{"id":22381018,"url":"https://github.com/code-raushan/langgraph-agents","last_synced_at":"2026-02-01T01:31:26.472Z","repository":{"id":266505056,"uuid":"868082460","full_name":"code-raushan/langgraph-agents","owner":"code-raushan","description":"LangGraph based RAG system. 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Document Retrieval: Fetches relevant documents from a pre-built vector store.\n2. Model Creation: Initializes the Llama 3.2:3b model using Ollama.\n3. Document Grading: Evaluates the relevance of retrieved documents.\n4. Answer Generation: Produces an answer based on relevant documents.\n5. Answer Grading: Assesses the quality of the generated answer.\n\n## Setup\n\n1. Clone the repository\n2. Install dependencies:\n   ```\n   npm install\n   ```\n3. Set up Ollama with the Llama 3.2:3b model\n4. (Optional) Set up Groq API key if using Groq\n\n## Usage\n\n1. Start the server:\n   ```\n   npm start\n   ```\n2. Send a POST request to `http://localhost:4321/ask` with a JSON body containing the question:\n   ```json\n   {\n     \"question\": \"Your question here\"\n   }\n   ```\n\n## Configuration\n\n- The system uses Ollama by default. 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