Search results for "vector-database"
RAG pipeline security testing toolkit - 27 techniques across 6 kill chain phases, mapped to MITRE ATLAS
Data Infrastructure providing a declarative, incremental approach for multimodal AI workloads.
Memory that remembers the story not just the facts. Three layer sentence graph for AI agents -> Facts, Episodes, raw Sentences. One DB. Zero config.
Framework for benchmarking vector search engines
Advanced AI Real Estate Assistant using RAG, LLMs, and Python. Features market analysis, property valuation, and intelligent search.
AI Agent Development Platform - Supports multiple models (OpenAI/DeepSeek/Wenxin/Tongyi), knowledge base management, workflow automation, and enterprise-grade security. Built with Flask + Vue3 + LangC
Redis Vector Library (RedisVL) -- the AI-native Python client for Redis.
📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG
Python SDK for Milvus Vector Database
The Developer's Guide to AI - A Field Guide for the Working Developer
Graph RAG with pure vector search, achieving SOTA performance in multi-hop reasoning scenarios.
High-Performance Engine for Multi-Vector Search
The highest-scoring AI memory system ever benchmarked that isn't reliant on LLM reranking. And it's free & burns less tokens.
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
🧠 Enhance AI conversations with Cognio, a persistent memory server that retains context and enables meaningful semantic search across sessions.
🚀 Build and explore multi-agent AI workflows with ready-to-use projects for document serving, Q/A bots, and orchestration.
Benchmark for vector databases.
Humans and AI agents, building knowledge bases together. Self-hosted document annotation, version control, semantic search, and MCP.
🧠 Enhance LLM agents with an agentic memory system, featuring automatic note construction, dynamic memory updates, and intelligent semantic retrieval.
Syllabus-aware RAG study assistant for university students. Answers strictly from your own notes & PDFs, unit-scoped retrieval, cross-encoder reranking, and a hallucination gate — built to help studen
🔍 Implement hybrid search using Vespa and FastAPI, blending BM25 and dense semantic retrieval for efficient, accurate information retrieval.
🛒 Build a leading-edge e-commerce recommendation system using RAG architecture, Groq Llama 3, LangChain, and AstraDB, deployed on Kubernetes for scalability.
🚀 Build and scale reliable Retrieval-Augmented Generation (RAG) systems with this curated collection of tools, frameworks, and best practices.
🗓️ Simplify booking with this AI service agent that processes queries, finds local options, and offers immediate slots and notifications.
Self-hostable RAG platform - document ingestion, embedding, and vector search behind a simple REST API
🤖 Recommend TV shows by matching favorites, averaging embeddings, and finding similar titles using fuzzy search and vector similarity.
⚡ Optimize vector searches with a hyper-efficient cache that uses machine learning for faster, smarter data access and reduced costs.
📷 Transform any camera into ROS2 image topics for seamless integration with robotic systems and effective VLA model deployment.
🚀 Build an enterprise-ready RAG system to enhance technical documentation querying with LangGraph and multi-step reasoning workflows.
🤖 Build your own local Retrieval-Augmented Generation system for private, offline AI memory without ongoing costs or data privacy concerns.
📚 Learn from diverse sources with OmniLearnAI, an intelligent platform that combines documents, videos, and more, all with reliable citations.
🛠️ Simplify your tasks with MineContext, an open-source AI tool that provides context-aware support for clarity and efficiency in work and study.