RAG Tools

Chroma is an open-source AI-native embedding database designed for building LLM applications. It provides simple APIs to store embeddings and perform similarity search, making it ideal for RAG applications.

Haystack is an enterprise-grade framework for RAG and search applications, covering document processing, retrieval, generation, and evaluation end to end.

Ragas is a framework for evaluating RAG (Retrieval Augmented Generation) systems. It provides various evaluation metrics including faithfulness, answer relevance, context precision, helping developers optimize RAG application performance.

Graphiti is a temporal knowledge-graph engine for agent memory, helping systems continuously accumulate long-term context.

Mem0 is a long-term memory layer for AI agents, supporting cross-session memory management and personalized context retrieval.

Milvus is a high-performance open-source vector database built for AI applications. It supports storage, indexing, and similarity search of large-scale vector data, ideal for RAG, recommendation systems, and more.

Qdrant is a high-performance vector database widely used as the retrieval layer for RAG and agent memory search scenarios.

LlamaIndex is a data framework that provides the data connection layer for LLM applications, with strong RAG capabilities across diverse data sources and vector databases.

GPT Researcher is an autonomous research agent that can gather, organize, and analyze information to produce detailed research reports.

TruLens is an open-source tool for evaluating and tracking LLM apps. It provides specialized evaluation for RAG applications including context relevance, groundedness, and answer relevance.

Unstructured provides document parsing and cleaning capabilities, commonly used in RAG ingestion and preprocessing pipelines.

Weaviate is an open-source vector database that stores objects and vectors, allowing for combining vector search with structured filtering. It has built-in vectorization modules and supports multimodal data search.