Multi-Agent Bot Project

A modular, asynchronous bot designed to perform various business-critical tasks by integrating multiple external tools and services. This bot uses a collection of sub-agents to parse commands, plan tasks, execute tool calls (e.g., calendar events, phone calls, emails, browsing, contact search, and search), and then evaluate the outcomes.

Table of Contents

• Introduction
• Features
• Directory Structure
• Setup & Installation
• Usage
• Testing
• Contributing
• License
• Contact

Introduction

This project implements a multi-agent bot that can be used to manage various operational tasks such as:

• Browsing: Simulate web browsing or information gathering.
• Calendar: Schedule events and manage calendars.
• Call: Initiate phone calls via integrated telephony tools.
• Contact Search: Look up and manage contact data.
• Email: Send emails using external email APIs.
• Search: Perform searches for data or content.

The bot is built in a modular way with distinct agents responsible for:

• Meta Parsing: Converting raw input into structured instructions.
• Task Planning: Generating a detailed plan for the requested tasks.
• Action Execution: Calling external tools (integrations) to perform the tasks.
• Critiquing: Evaluating and summarizing the results of task execution.

Features

• Modular Architecture: Each function (parsing, planning, executing, evaluating) is handled by its own component.
• Tool Integration: Easily extendable to integrate with real-world services (Google Calendar, Twilio, Email APIs, etc.).
• Asynchronous Execution: Utilizes Python’s asyncio to efficiently handle I/O-bound operations.
• Command-Line Interface: Run and test the bot directly from the command line.
• Extensibility: New tasks and integrations can be added with minimal changes to the core logic.

Directory Structure

project/
├── main.py
├── pyproject.toml
├── README.md
├── Makefile
├── .gitignore
├── .pre-commit-config.yaml
├── .editorconfig
├── agent/
│   ├── __init__.py
│   ├── bot.py                # Main orchestrator that ties all agents together
│   ├── meta_parser.py        # Parses raw meta input into structured instructions
│   ├── plan_agent.py         # Generates a plan (list of tasks) from instructions
│   ├── action_agent.py       # Executes each task by calling external tools
│   └── critic_agent.py       # Evaluates the results of task execution
├── integrations/
│   ├── __init__.py
│   ├── google_calendar_integration.py   # Simulated integration for calendar tasks
│   ├── twilio_integration.py              # Simulated integration for call tasks
│   └── email_integration.py               # Simulated integration for email tasks
├── tests/                                  # Unit, integration, and e2e tests
│   ├── unit/
│   ├── integration/
│   └── e2e/
└── ...                                     # Additional directories (docs, scripts, etc.)



Below is an example `README.md` file that explains the project's purpose, features, structure, and usage:

```markdown
# Multi-Agent Bot Project

A modular, asynchronous bot designed to perform various business-critical tasks by integrating multiple external tools and services. This bot uses a collection of sub-agents to parse commands, plan tasks, execute tool calls (e.g., calendar events, phone calls, emails, browsing, contact search, and search), and then evaluate the outcomes.

## Table of Contents

- [Introduction](#introduction)
- [Features](#features)
- [Directory Structure](#directory-structure)
- [Setup & Installation](#setup--installation)
- [Usage](#usage)
- [Testing](#testing)
- [Contributing](#contributing)
- [License](#license)
- [Contact](#contact)

## Introduction

This project implements a multi-agent bot that can be used to manage various operational tasks such as:
- **Browsing**: Simulate web browsing or information gathering.
- **Calendar**: Schedule events and manage calendars.
- **Call**: Initiate phone calls via integrated telephony tools.
- **Contact Search**: Look up and manage contact data.
- **Email**: Send emails using external email APIs.
- **Search**: Perform searches for data or content.

The bot is built in a modular way with distinct agents responsible for:
- **Meta Parsing:** Converting raw input into structured instructions.
- **Task Planning:** Generating a detailed plan for the requested tasks.
- **Action Execution:** Calling external tools (integrations) to perform the tasks.
- **Critiquing:** Evaluating and summarizing the results of task execution.

## Features

- **Modular Architecture:** Each function (parsing, planning, executing, evaluating) is handled by its own component.
- **Tool Integration:** Easily extendable to integrate with real-world services (Google Calendar, Twilio, Email APIs, etc.).
- **Asynchronous Execution:** Utilizes Python’s `asyncio` to efficiently handle I/O-bound operations.
- **Command-Line Interface:** Run and test the bot directly from the command line.
- **Extensibility:** New tasks and integrations can be added with minimal changes to the core logic.

## Directory Structure

```plaintext
project/
├── main.py
├── pyproject.toml
├── README.md
├── Makefile
├── .gitignore
├── .pre-commit-config.yaml
├── .editorconfig
├── agent/
│   ├── __init__.py
│   ├── bot.py                # Main orchestrator that ties all agents together
│   ├── meta_parser.py        # Parses raw meta input into structured instructions
│   ├── plan_agent.py         # Generates a plan (list of tasks) from instructions
│   ├── action_agent.py       # Executes each task by calling external tools
│   └── critic_agent.py       # Evaluates the results of task execution
├── integrations/
│   ├── __init__.py
│   ├── google_calendar_integration.py   # Simulated integration for calendar tasks
│   ├── twilio_integration.py              # Simulated integration for call tasks
│   └── email_integration.py               # Simulated integration for email tasks
├── tests/                                  # Unit, integration, and e2e tests
│   ├── unit/
│   ├── integration/
│   └── e2e/
└── ...                                     # Additional directories (docs, scripts, etc.)

Setup & Installation

1. Clone the Repository:

   git clone https://github.com/your-username/your-repository.git
   cd your-repository

2. Create a Virtual Environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use: venv\Scripts\activate

3. Install Dependencies: If you have a requirements.txt file:

   pip install -r requirements.txt

   Alternatively, if you’re using pyproject.toml with Poetry:

   poetry install

4. Set Up Environment Variables (if needed): Create a .env file or configure your environment as required by the integrations (e.g., API keys for external services).

Usage

Run the bot using the command-line interface. By default, it will process all tasks:

python -m agent.bot

To run the bot with specific tasks (e.g., only "browsing" and "call"):

python -m agent.bot "browsing, call"

The bot will:

1. Parse the input.
2. Generate a plan (with task details such as title, last commit message, and date).
3. Execute each task by calling the corresponding integration tool.
4. Compile an evaluation report of the execution results.

Testing

The project includes unit and integration tests located in the tests/ directory.

To run the tests, simply use:

pytest tests/

Make sure you have installed pytest in your virtual environment:

pip install pytest

Contributing

Contributions are welcome! Please check our CONTRIBUTING.md file for details on our code of conduct and the process for submitting pull requests.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For questions or suggestions, please contact [your-email@example.com].

Feel free to modify the details (such as repository URLs, contact information, and dependency management instructions) to match your project's specifics.