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 multi-provider model access and includes full observability through Langfuse, enabling real-time, context-aware assistance while maintaining compliance requirements for regulated industries.
Table of contents
The Architecture:The Project Structure:The Implementation:The Driver Code:Model Streamlining:Conclusion:Sort: