Adk Rag
Createdkhoi03
Implements a Retrieval-Augmented Generation (RAG) system leveraging Google's Agent Development Kit (ADK) and Qdrant vector database for enhanced LLM responses.
About
Adk Rag combines Google's Agent Development Kit (ADK) with Qdrant vector database via an MCP server to build a powerful Retrieval-Augmented Generation (RAG) system. This system enhances Large Language Model (LLM) responses by retrieving relevant context from a vector database before generating answers, leading to more informed and accurate outputs. It uses semantic search powered by Qdrant and provides comprehensive monitoring and logging for system performance.
Key Features
- 2 GitHub stars
- Utilizes MCP Server for Qdrant vector database interaction
- Enhances LLM responses with retrieved information
- Leverages Google's Agent Development Kit for LLM capabilities
- Comprehensive monitoring and logging
- Semantic search powered by Qdrant vector database
Use Cases
- Knowledge Retrieval
- Context-aware Chatbots
- Document Q&A