Multi-agent reasoning system with specialized thinker and grader components
Project description
Agentic Fleet
A powerful fleet of AI agents for complex reasoning and task execution, combining Tree of Thoughts reasoning with advanced agent orchestration capabilities.
Features
- Tree of Thoughts Reasoning: Multi-agent reasoning system with beam search
- CaptainAgent: Advanced agent orchestration based on the paper "CaptainAgent: Building Reliable Autonomous Agents through Iterative Prompting"
- Agent Fleet: Extensible collection of specialized agents for different tasks
- Tool Integration: Rich set of tools and capabilities for agents
- Modern Development: Built with modern Python tools (uv, PDM)
Installation
pip install agentic-fleet
Quick Start
from agentic_fleet import CaptainAgent, ReasoningAgent
from agentic_fleet.tools import CodeAnalysisTool, DataProcessingTool
# Initialize CaptainAgent with specialized tools
captain = CaptainAgent(
name="project_captain",
tools=[CodeAnalysisTool(), DataProcessingTool()],
max_iterations=5
)
# Execute a complex task
result = captain.execute_task(
"Analyze this codebase and suggest improvements",
context={"repo_path": "./my_project"}
)
# Use reasoning agent for complex problem-solving
reasoner = ReasoningAgent(
name="math_reasoner",
beam_size=3,
max_depth=5
)
solution = reasoner.solve("What is the optimal strategy for...")
Architecture
The package consists of several key components:
- CaptainAgent: Orchestrates complex tasks through iterative prompting
- ReasoningAgent: Implements Tree of Thoughts for complex reasoning
- SpecialistAgents: Task-specific agents (Coder, Analyst, etc.)
- Tools: Extensible set of capabilities for agents
- Prompts: Carefully crafted prompts for different scenarios
Development
# Install development dependencies
uv venv
source .venv/bin/activate
uv pip install -e ".[dev]"
# Run tests
pytest
# Run linting
ruff check .
black .
mypy .
Contributing
See CONTRIBUTING.md for guidelines.
License
MIT License - see LICENSE for details.
Project details
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