RAG Frameworks
RAG FrameworksRetrieval-augmented generation frameworks, vector databases, and data tooling for knowledge-connected LLM apps.
Use caseNeeds verification
Tool · Needs verification
Haystack
Open-source framework for building production-style search, RAG, and NLP pipelines.
ToolNeeds verificationOpen sourceSelf-hostedFreemiumGitHub linked
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Tool fit
Primary repository
Mapped use cases
Related repositories
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
RepositoryAuto enrichedMDXApache-2.0Active signal
Related skills
Data Ingestion
DataLoading, cleaning, chunking, and normalizing documents or structured data.
Role: Recommended
SkillNeeds verificationDataRequired
Evaluation
QualityTesting LLM quality, retrieval quality, task completion, and regression behavior.
Role: Recommended
SkillNeeds verificationQualityRecommended
Connecting LLMs to external knowledge with retrieval, ranking, and grounded responses.
Role: Recommended
SkillNeeds verificationAIRequired
Python
ProgrammingGeneral Python programming for automation, data, AI, and backend scripts.
Role: Required
SkillNeeds verificationProgrammingRequired