A technical implementation guide for building memory-efficient AI agents specialized for medical and legal domains. The architecture separates short-term conversational state in MongoDB from long-term semantic knowledge in Qdrant vector database, orchestrated through the Agno framework. The system uses LiteLLM for
Table of contents
The Architecture:The Project Structure:The Implementation:The Driver Code:Model Streamlining:Conclusion:Sort: