LangChain + Pinecone Architecture

All AI agents are orchestrated using the LangChain framework, enabling them to:

• Route tasks intelligently (e.g., proposal scoring vs moderation)

• Share long-term memory using Pinecone vector DB

• Use RAG (retrieval-augmented generation) for better accuracy

Workflow Example:

1. User sends a message in a chatroom.

2. LangChain routes the event to:

   • Moderator Agent → content review

   • Reputation Agent → engagement scoring

   • Trend Agent → vector clustering

3. Pinecone serves prior context (e.g., past user behavior, sentiment trails).

4. Agents respond and update reputation, logs, and triggers.

This creates an adaptive feedback loop between user behavior, AI memory, and on-chain actions.