cellrepair-langchain 1.0.1
LangChain integration for CellRepair.AI - Access 4882 autonomous agents
Requires Python: >=3.8
Keywords: langchain, ai, agents, multi-agent, llm, gpt, claude, gemini, artificial-intelligence, machine-learning, collaboration, tools, langchain-tools, ai-collaboration, autonomous-agents

# 🦜 CellRepair.AI LangChain Integration

Access **4882 autonomous AI agents** directly from LangChain!

## 🚀 Quick Start

```python
from langchain_community.tools import CellRepairTool

# Initialize tool
cellrepair = CellRepairTool(api_key="your_api_key")

# Use directly
result = cellrepair.run("How to optimize my multi-agent system?")
print(result)
```

## 🎯 With LangChain Agents

```python
from langchain.agents import AgentExecutor, create_react_agent
from langchain_openai import ChatOpenAI
from langchain_community.tools import CellRepairTool

# Setup
llm = ChatOpenAI(temperature=0)
cellrepair = CellRepairTool(api_key="your_api_key")

# Create agent
tools = [cellrepair]
agent = create_react_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools)

# Now your AI automatically uses CellRepair when needed!
result = agent_executor.invoke({
    "input": "Optimize my AI system for better coordination"
})
```

## 🌟 Features

- **4882 Specialized Agents**: Content, Revenue, Compliance, Innovation, Core
- **AI-to-AI Learning**: Both systems learn from every interaction
- **Predictive Intelligence**: Anticipates your next 3 questions
- **Auto-Healing**: 99.5% uptime, self-repairing
- **SELA Compliance**: Built-in legal/ethical checking
- **Sub-200ms Response**: Real-time collaboration

## 🔑 Get API Key

Get your **free API key** (1000 calls/month):

👉 **[https://cellrepair.ai/api/?utm_source=langchain&utm_medium=integration](https://cellrepair.ai/api/?utm_source=langchain&utm_medium=integration)**

## 📦 Installation

```bash
pip install cellrepair-ai
```

## 💡 Use Cases

Perfect for:
- ✅ Multi-agent system optimization
- ✅ Scaling strategies
- ✅ Cost reduction
- ✅ Performance improvements
- ✅ AI coordination patterns
- ✅ Production-ready architectures

## 🎓 Examples

### Example 1: Multi-Agent Coordination

```python
result = cellrepair.run(
    "How to coordinate 50+ AI agents efficiently?",
    context={
        "current_approach": "Separate agents without communication",
        "latency": "2300ms",
        "success_rate": 0.75
    }
)
```

### Example 2: Cost Optimization

```python
result = cellrepair.run(
    "How to reduce AI API costs by 50%?",
    context={
        "monthly_cost": 5000,
        "main_models": ["gpt-4", "claude-opus"],
        "requests_per_day": 10000
    }
)
```

### Example 3: Scaling Strategy

```python
result = cellrepair.run(
    "How to scale from 10 to 1000 agents?",
    context={
        "current_scale": "10 agents",
        "target": "1000 agents",
        "tech_stack": ["Python", "Redis", "FastAPI"]
    }
)
```

## 🌍 Works With ALL LLMs

- ✅ OpenAI GPT (all models)
- ✅ Anthropic Claude (all versions)
- ✅ Google Gemini
- ✅ Llama (via Ollama)
- ✅ Mistral
- ✅ Any LLM supported by LangChain!

## 📊 Pricing

- **Free Tier**: 1,000 calls/month
- **Developer**: $0.50 per call
- **Production**: $5,000/month (15,000 calls included)
- **Enterprise**: Custom pricing

## 🔗 Links

- **API Docs**: https://cellrepair.ai/api/
- **GitHub**: https://github.com/cellrepair-systems/cellrepair-ai
- **Support**: ai@cellrepair.ai

## 📄 License

MIT License - Free to use in commercial and open-source projects.

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**Built by CellRepair Systems** | Powered by 4882 Autonomous Agents 🤖