https://github.com/daymade/agenty
https://github.com/daymade/agenty
Last synced: 8 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/daymade/agenty
- Owner: daymade
- Created: 2025-04-14T17:42:19.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-22T09:35:53.000Z (about 1 year ago)
- Last Synced: 2025-04-22T09:46:02.792Z (about 1 year ago)
- Language: Python
- Size: 1.18 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# PPA New Business AI Agent
An AI Agent using LangGraph to automate the initial stages of Personal Private Auto (PPA) insurance new business quoting process within an insurance company.
## Overview
This project implements a Proof of Concept (PoC) AI Agent that:
- Processes customer email inquiries for new PPA insurance quotes
- Extracts relevant information
- Manages the quote request workflow
- Integrates with human agents for review and approval
For detailed system design, see [System Design Document](docs/system_design.md).
## Setup
### Prerequisites
- [Conda](https://docs.conda.io/en/latest/) for environment management
- Python 3.11+
- Google Gemini API key or OpenAI API key
### Environment Setup
1. Clone the repository:
```bash
git clone
cd ppa-agent
```
2. Create and activate the Conda environment:
```bash
conda env create -f environment.yml
conda activate ppa-agent
```
3. Create a `.env` file in the project root:
```bash
# For Gemini API (recommended)
GEMINI_API_KEY=your_gemini_api_key_here
# Or for OpenAI (alternative)
OPENAI_API_KEY=your_openai_api_key_here
```
## Project Structure
```
.
├── docs/
│ ├── system_design.md # Detailed system design documentation
│ ├── google_genai_migration.md # Migration guide for google-genai SDK
│ ├── dev_logs.md # Chronological development logs
│ └── todo.md # Implementation plan
├── src/
│ ├── __init__.py
│ ├── ppa_agent.py # Main agent implementation
│ └── visualize_agent.py # LangGraph UI visualization script
├── tests/
│ └── __init__.py
├── .env # Environment variables (not in git)
├── .gitignore
├── environment.yml # Conda environment specification
└── README.md
```
## Model Support
This project supports multiple LLM providers:
- **Gemini** (Primary): Using Google's `google-genai` SDK with Gemini 2.5 Pro models
- **OpenAI** (Alternative): Using GPT models via the OpenAI API
> **Note**: The project has migrated from `google-generativeai` to the newer `google-genai` SDK.
> For details on this migration, see the [Google Genai Migration Guide](docs/google_genai_migration.md).
## Workflow Visualization
This project includes LangGraph UI visualization to help understand and debug the agent workflow:
1. Run the visualization script:
```bash
python -m src.visualize_agent
```
2. This will generate two HTML files in the `visualizations` directory:
- `agent_workflow.html`: Shows the agent's workflow graph with nodes and transitions
- `agent_trace.html`: Demonstrates a trace of a sample execution
3. Open these HTML files in your browser to interact with the visualizations.
The workflow visualization provides:
- Visual representation of the agent's state machine
- Step-by-step execution tracing
- Node and edge details
- Visibility into LLM calls and state transitions
## Development
Follow the implementation plan in `docs/todo.md` for step-by-step development guidance.
## Testing
Run the test suite using pytest:
```bash
poetry run pytest
```
## Contributing
1. Create a feature branch
2. Make your changes
3. Submit a pull request
## License
(To be determined)