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LangGraph Agents Project

This project demonstrates the use of LangGraph and LangChain to build various AI agents for document drafting, mathematical operations, and PDF processing using OpenAI models.

Features

  • Document Drafter Agent: Interactively helps users draft, update, and save documents using natural language.
  • Math Agents: Perform arithmetic operations (addition, subtraction, multiplication, division) via conversational interface.
  • PDF Agent: Loads and processes PDF files, enabling AI-powered analysis and interaction with document content.
  • Streaming and Tool Integration: Uses LangGraph's streaming and tool node capabilities for dynamic, multi-step workflows.

Project Structure

  • main.py: Entry point for running agents.
  • 5_agent_1.py, 6_agent_2.py, 7_agent_3.py, 8_agent_4.py, 8_1_agent_4.py, 9_agent_5.py: Example agent scripts.
  • 1_first-graph.ipynb, 2_second-graph.ipynb, ...: Jupyter notebooks demonstrating agent usage.
  • logging.txt: Log file for agent runs.
  • pyproject.toml, uv.lock: Dependency and environment management.

Requirements

  • Python 3.8+
  • OpenAI API key (set in .env)
  • Required packages:
    • langchain-core
    • langchain-openai
    • langgraph
    • langchain-community
    • python-dotenv
    • pypdf
    • IPython
    • openai
    • uv (for dependency management)

Installation

  1. Clone the repository.
  2. Create a virtual environment: 
    python -m venv .venv
  3. Activate the environment:
    • Windows: ./.venv/Scripts/activate
    • macOS/Linux: source .venv/bin/activate
  4. Install dependencies: 
    pip install -r requirements.txt
    Or, if using uv: 
    uv pip install -r requirements.txt
  5. Set your OpenAI API key in a .env file: 
    OPENAI_API_KEY=your-key-here

Usage

  • Run a specific agent script: 
     python 8_agent_4.py
  • Interact with the PDF agent: Ensure Stock_Market_Performance_2024.pdf is present in the project directory, then run: 
     python 9_agent_5.py
  • Jupyter Notebooks: Open and run the .ipynb files for step-by-step demonstrations.

Example

python 5_agent_1.py
# Enter your message when prompted to interact with the agent.

Troubleshooting

  • If you see an error like 'pypdf' package not found, install it: 
     pip install pypdf
  • For missing modules, ensure all dependencies are installed and your virtual environment is activated.