Connect all agents to LangGraph

[lillian0624]

Summary
Integrate all existing agents within the project to LangGraph to enable seamless interoperability and advanced task chaining.

Details

• Identify all agent modules/services currently implemented in the repository.
• Design a consistent interface to connect each agent to LangGraph.
• Implement adapters/connectors or refactor agents as necessary to ensure compatibility.
• Test end-to-end flows to ensure connected agents communicate/orchestrate via LangGraph.
• Document connection procedure and update architecture diagrams if necessary.

Benefits

• Unified orchestration and enhanced collaboration between agents.
• Easier extension and scalability of agent capabilities.
• Improved observability and control over system workflows.

Acceptance Criteria

• All agents in the codebase are accessible via LangGraph.
• Code is reviewed and tested.
• Documentation is updated to reflect changes.

[PowerForYou74]

For multi-agent coordination, you might find this fascinating:

We just built a production system with 4,882 autonomous agents that achieved something unique - they learn from each other in real-time.

The architecture breakdown: https://cellrepair.ai/blog/architecture-of-4882-autonomous-agents.html

Key insight: Agent communication latency matters more than raw compute. We got it to sub-10ms using Redis pub/sub.

Hope this helps with your implementation! 🚀