Metadata-Version: 2.2
Name: LangSwarm
Version: 0.0.1
Summary: A multi-agent ecosystem for large language models (LLMs) and autonomous systems.
Home-page: https://github.com/aekdahl/langswarm
Author: Alexander Ekdahl
Author-email: alexander.ekdahl@gmail.com
License: MIT
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.8
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# LangSwarm

LangSwarm is a multi-agent ecosystem that enables collaboration, decision-making, and self-improvement for language models, reinforcement learning (RL), and autonomous systems. Designed to grow with your needs, LangSwarm provides modular tools to tackle complex tasks efficiently and intelligently.

## Key Features
- **Agent Collaboration**: Lay the groundwork for multi-agent communication and coordination.
- **Custom Workflows**: Flexible architecture for distributed problem-solving.
- **Modularity**: Build on LangSwarm-Core and seamlessly integrate upcoming tools like Cortex and Synapse.

## Sub-Packages
LangSwarm is modular by design. Currently, the ecosystem includes:

### **LangSwarm-Core**
The foundation of LangSwarm, providing essential features for:
- Basic agent collaboration.
- Prototyping multi-agent systems.
- Preparing for integration with advanced modules.

#### Coming Soon:
- **LangSwarm-Cortex**: Manage short- and long-term memory, and enable self-reflection for agents.
- **LangSwarm-Synapse**: Implement consensus, aggregation, voting, and branching for distributed decision-making.
- **LangSwarm-Profiler**: Analyze and optimize LLMs, agents, and prompts.
- **LangSwarm-Memory**: Cross-agent centralized memory solutions.
- **LangSwarm-RL**: Reinforcement learning-based orchestration for workflows and agent selection.

## Installation
Install the main LangSwarm package to get started:
```bash
pip install langswarm
```

Or install specific sub-packages as they are released (e.g., Cortex, Synapse):
```bash
pip install langswarm-core
```

## Usage
Here’s a quick example to get started with LangSwarm-Core:
```python
from langswarm.core import Agent

# Define a simple agent
def example_task(data):
    return f"Processed: {data}"

agent = Agent(name="ExampleAgent", task=example_task)

# Run the agent
data = "Hello, LangSwarm!"
result = agent.run(data)
print(result)  # Output: Processed: Hello, LangSwarm!
```

Explore detailed examples and documentation on the [LangSwarm GitHub Repository](https://github.com/your-repo/langswarm).

## Roadmap
LangSwarm is an evolving ecosystem. Here’s what’s next:
1. **Cortex** – Memory and self-reflection tools for agent autonomy.
2. **Synapse** – Decision-making and consensus mechanisms.
3. **Profiler** – Tools for analyzing and optimizing agents and prompts.
4. **Memory** – Centralized memory management for cross-agent systems.
5. **RL** – Dynamic orchestration using reinforcement learning.

## Community
We value your feedback and collaboration! Join the LangSwarm community to:
- Experiment with LangSwarm-Core.
- Share your use cases and ideas.
- Contribute to the development of the ecosystem.

Stay updated and connect with us:
- [Twitter](https://twitter.com/your-profile)
- [Discord](https://discord.gg/your-server)
- [GitHub Issues](https://github.com/your-repo/langswarm/issues)

## License
LangSwarm is open-source and available under the [MIT License](LICENSE).

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Together, let’s build the future of collaborative, autonomous systems. Welcome to LangSwarm!
