Metadata-Version: 2.1
Name: agensight
Version: 0.2.9
Summary: A Python SDK for logging and visualizing OpenAI agent interactions, with a built-in CLI and web dashboard.
Author: Pype
Requires-Python: >=3.10
Description-Content-Type: text/markdown

# Agensight

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python Version](https://img.shields.io/badge/python-3.7%2B-blue.svg)](https://www.python.org/downloads/)

Agensight is a powerful SDK for visualizing, managing, and debugging AI agents. It provides intuitive tools to monitor agent interactions, manage configurations, and improve the development workflow for AI systems.

## Features

- **Agent Visualization**: Interactive graph-based visualization of agent interactions and data flow
- **Configuration Management**: Version control for agent configurations
- **Prompt Engineering**: Edit and optimize prompts with a built-in editor
- **Web Dashboard**: Intuitive UI for monitoring and managing your agents
- **Command Line Interface**: Quickly access your agents from the terminal

## Installation

```bash
pip install agensight
```

## Quick Start

See the `examples/` folder for usage examples and scripts demonstrating Agensight features.

## Installation (Development)

Install all dependencies from the requirements file:

```bash
pip install -r requirements.txt
```

## Development & Local Setup

To work on Agensight locally, follow these steps:

### 1. Clone the Repository
```bash
git clone https://github.com/yourusername/agensight.git
cd agensight
```

### 2. Set Up Python Environment
```bash
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
```

### 3. Set Up the UI (Frontend)
```bash
cd agensight/ui
npm install
npm run dev
```
This will start the UI on [http://localhost:5173](http://localhost:5173) (or similar).

### 4. Run the Backend (FastAPI server)
```bash
cd agensight/server
uvicorn app:app --reload
```
This will start the backend server on [http://localhost:8000](http://localhost:8000).

### 5. Launch the Dashboard
```bash
python3 -m cli.main view
```

### 6. Inspecting the Database
- The backend uses SQLite (default: `agensight/tracing/traces.db`).
- To inspect the database, use the SQLite CLI:
  ```bash
  sqlite3 agensight/tracing/traces.db
  .tables
  SELECT * FROM traces LIMIT 5;
  .exit
  ```
- Or use a GUI tool like [DB Browser for SQLite](https://sqlitebrowser.org/).

### 7. Code Style & Linting
- Python: Use `black` and `flake8` for formatting and linting.
- TypeScript/JS: Use `eslint` and `prettier` in the `ui/` directory.

### 8. Contributing
- Please see the [contributing guidelines](./CONTRIBUTING.md) for more details.

## Configuration

Agensight uses a configuration file to manage agents, connections, and settings:

```json
{
  "agents": [
    {
      "name": "AnalysisAgent",
      "prompt": "You are an expert analysis agent...",
      "variables": ["input_data"],
      "modelParams": {
        "model": "gpt-4o",
        "temperature": 0.2
      }
    }
  ],
  "connections": [
    {"from": "AnalysisAgent", "to": "OutputAgent"}
  ]
}
```

## Documentation

For detailed documentation, please visit our [docs](./docs):

- [API Reference](./docs/api-reference.md)
- [Advanced Configuration](./docs/advanced-configuration.md)
- [Examples](./examples/)

## License

This project is licensed under the MIT License - see the [LICENSE](./LICENSE) file for details.

## Support

For questions, issues or feature requests, please [create an issue](https://github.com/yourusername/agensight/issues).
