github_readme.md

📧 AI-Driven Email Agent 🧠

A production-grade, multi-agent system built with LangGraph and FastAPI that automates email triage, context retrieval, and drafting. This project demonstrates advanced implementation of Long-term Memory, State Persistence, and Human-in-the-Loop Interrupts using LangGraph's Functional API Command pattern.

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🚀 Key Features

• Advanced Learning Implementation
  Implemented Semantic Memory, Checkpointer Persistence, and Functional Interrupts, enabling the agent to maintain state and handle user feedback reliably.

• Multi-Agent Workflow
  Specialized agents for:

  • Triage
  • Context Synthesis
  • Email Drafting

• Intelligent Triage
  Automatically classifies emails, assigns priority, and determines if a reply is required.

• Semantic Memory
  Uses langmem and PostgresStore to retrieve past interactions, allowing the agent to remember previous project details.

• Resource Management
  A dedicated Token Count Node ensures large emails (e.g., deployment logs) are summarized before processing to optimize costs.

• Human-in-the-Loop
  The graph pauses using interrupt() to allow users to:

  • Review drafts
  • Approve responses
  • Provide feedback via Command(resume=...)

• Scalable Architecture
  Built with FastAPI, Docker, and a modular structure for enterprise-grade deployment.

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🛠️ Tech Stack

• Orchestration: langgraph (Functional API), langchain
• LLM Interface: langchain-groq
• Memory & Persistence:
  • langmem
  • PostgresCheckpoint
  • PostgresStore (Neon/PostgreSQL)
• Database ORM: SQLAlchemy 2.0
• Embeddings: langchain_huggingface (DistilBERT)
• Backend: FastAPI + Uvicorn
• Configuration: pydantic-settings (.env management)
• Authentication: google-auth (Gmail API Integration)

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📂 Project Structure

app/
├── agents/             # Brains: Specialized LLM logic (Triage, Writer, Context)
├── database/           # Data: SQLAlchemy models and Connection Pooling
├── nodes/              # Workflow: Functional steps of the graph (Safety, Tokens)
├── persistance/        # Persistence: Postgres Checkpointer & Memory Store config
├── state/              # Schema: Pydantic & TypedDict state definitions
├── utils/              # Toolbox: Token counters, Embeddings, and Auth helpers
├── graph.py            # Logic: StateGraph construction and compilation
└── main.py             # Entry: FastAPI app and Controller logic