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Email Assistant AI Agent using LangGraph (LangChain)

Overview

  • Developed an autonomous ReAct-style AI agent using LangGraph, enabling LLM-driven decision-making workflows with stateful graph transitions for enhanced context and control.
  • Google Colab Link

Key Highlights

  • Integrated Google Gemini (via LangChain) as the LLM backbone, leveraging built-in tool calling support.
  • Built two custom tools:
    • find email: Retrieve a user’s email from a remote SQL database using only their first name.
    • send email: Compose and send dynamic emails by inferring appropriate subject and body from the given prompt.
  • Designed the agent’s control flow using LangGraph’s StateGraph, managing tool selection, execution, and context-aware message handling.
  • Enhanced workflow reliability by combining LangChain’s structured outputs with LangGraph’s deterministic execution paths.

Tech Stack

  • Language: Python
  • Frameworks & Libraries: LangGraph, LangChain
  • AI Model: Google Gemini
  • Key Features: Function Calling, Tool Integration

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