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LangChain Pinecone OpenAI Python

Agentic Knowledge System

A multi-agent system designed to orchestrate complex reasoning tasks over large document sets using RAG.

Agentic Knowledge System

This project demonstrates a robust architecture for deploying autonomous agents that can:

  1. Retrieve Information: Efficiently query vector databases for semantic search.
  2. Reason: Use chain-of-thought prompting to synthesize answers from multiple sources.
  3. Act: Execute tools to fetch real-time data or perform calculations.

Key Features

  • Multi-Agent Orchestration: Uses a supervisor agent to delegate sub-tasks to specialized worker agents.
  • Dynamic Tool Selection: Agents can choose from a suite of tools based on the user query.
  • Self-Correction: Implements a feedback loop where agents can critique and refine their own outputs.

Technology Stack

  • Framework: LangChain & LangGraph
  • Vector DB: Pinecone
  • LLM: GPT-4-turbo / Claude 3 Opus
  • Backend: FastAPI

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