agentic-swarm 0.1.0

Plug-and-play SDK for building immortal, self-healing multi-agent AI systems

Build immortal, self-healing multi-agent AI systems

Features • Installation • Quick Start • Documentation • Contributing

---

What is Agentic Swarm?

Agentic Swarm is a production-grade SDK for building multi-agent AI systems where agents:

• Never die — Auto-heal on failure with state recovery
• Spawn children — Dynamically create sub-agents for complex subtasks
• Route intelligently — Pick the optimal LLM based on task complexity
• Remember everything — Tiered memory with vector-indexed long-term storage
• Stay secure — Audit logs, encryption, RBAC, and data isolation

Highlights

Features

Feature	Description
Immortal Agents	Auto-heal on failure with state recovery
Dynamic Spawning	Create sub-agents at runtime
7 LLM Providers	OpenAI, Anthropic, Bedrock, Gemini, Groq, Ollama, vLLM
Smart Routing	Cost/speed/quality optimized model selection
Tiered Memory	Core + Recall + Archival (vector-indexed)
Never-Forget Memory	Compress, store, search, inject memories across sessions
RAG Pipeline	Chunk → Embed → Retrieve (dense+BM25+RRF) → Rerank
Hybrid Search	Dense vectors + BM25 sparse + Reciprocal Rank Fusion
Sandbox Isolation	CPU/memory limits, data isolation per agent
Security	Audit logs, AES-256 encryption, RBAC

Installation

pip install agentic-swarm

With optional providers:

pip install agentic-swarm[openai]      # OpenAI
pip install agentic-swarm[anthropic]   # Anthropic
pip install agentic-swarm[bedrock]     # AWS Bedrock
pip install agentic-swarm[all]         # Everything

Quick Start

import asyncio
from agentic_swarm import Agent, Swarm, tool

@tool
def search_web(query: str) -> str:
    """Search the web for information."""
    return f"Results for: {query}"

agent = Agent(
    name="researcher",
    role="Research and gather information",
    tools=[search_web],
)

swarm = Swarm(agents=[agent])

async def main():
    result = await swarm.run("Find information about AI agents")
    print(result)

asyncio.run(main())

With LLM Provider

from agentic_swarm import Agent
from agentic_swarm.llm import LLMRouter, OpenAIProvider

router = LLMRouter(strategy="quality_optimized")
router.register_provider("openai", OpenAIProvider(model="gpt-4o"))

agent = Agent(
    name="assistant",
    role="Helpful AI assistant",
    llm_router=router,
)

result = await agent.run("Explain quantum computing")

Never-Forget Memory

from agentic_swarm import Agent
from agentic_swarm.vectordb import InMemoryVectorDB
from agentic_swarm.rag.embedder import Embedder

# Agent that remembers across sessions
agent = Agent(
    name="assistant",
    role="Helpful assistant",
    vectordb=InMemoryVectorDB(),
    embedder=Embedder(),
    auto_archive=True,
    auto_inject_memories=True,
)

# Store memories
await agent.remember("User prefers dark mode")

# Search memories
memories = await agent.recall("user preferences")

# Run task - automatically injects relevant memories
result = await agent.run("What are my preferences?")

Documentation

Document	Description
Getting Started	Installation and first steps
Configuration	All configurable parameters
API Reference	Complete API documentation
Examples	Code examples and tutorials
Architecture	System design

Examples

# Full SDK showcase
python examples/full_showcase.py --provider openai

# With AWS Bedrock
python examples/full_showcase.py --provider bedrock

# Demo mode (no LLM)
python examples/full_showcase.py --skip-llm

See examples/ for working examples covering all features.

Contributing

We welcome contributions! Please see our contributing guidelines.

Resource	Link
📖 README	README.md
🤝 Code of Conduct	CODE_OF_CONDUCT.md
👥 Contributing	CONTRIBUTING.md
📜 License	Apache 2.0
🔒 Security	SECURITY.md

Development Setup

git clone https://github.com/nik0811/agentic-swarm.git
cd agentic-swarm
python -m venv env && source env/bin/activate
pip install -e ".[dev,all]"
pytest tests/ -v

Roadmap

• 7 LLM Providers (OpenAI, Anthropic, Bedrock, Gemini, Groq, Ollama, vLLM)
• Tiered Memory (Core + Recall + Archival)
• RAG Pipeline with Hybrid Search
• Agent Sandbox & Data Isolation
• Never-Forget Memory
• Web UI Dashboard
• Distributed Multi-Node Swarms
• OpenTelemetry Integration

License

Apache License 2.0 — see LICENSE for details.

---

_{Built with ❤️ for the AI community}