RAG Server
Provides a comprehensive Retrieval-Augmented Generation (RAG) server, offering robust file management and vector memory capabilities for AI agents.
Acerca de
This robust RAG server empowers AI agents by offering advanced retrieval capabilities for various document types. It integrates comprehensive file management for adding, removing, and searching documents in formats like PDF, DOCX, TXT, MD, CSV, and JSON. A dedicated vector memory system allows agents to store and retrieve important information for future use. Leveraging Hugging Face embeddings and a local ChromaDB, it enables sophisticated semantic search, making it an ideal backend for AI applications requiring contextual awareness and dynamic knowledge retrieval. The server also includes a powerful command-line interface (CLI) for system maintenance and management.
Características Principales
- Comprehensive Document Management (PDF, DOCX, TXT, MD, CSV, JSON)
- Dedicated Vector Memory for AI Agents
- Semantic Search using Hugging Face Embeddings
- Local ChromaDB for Efficient Vector Storage
- Command-Line Interface (CLI) for System Maintenance
- 0 GitHub stars
Casos de Uso
- Building AI agents with external and persistent knowledge bases
- Enhancing AI models with contextual information from various document collections
- Creating intelligent search systems for large document archives
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