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