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Dhaystack
Author description: 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.
Popularity
Repository stars11,29426,913Highest
7-day net stars——
Fork1,2113,384Highest
30-day trendInsufficient historyInsufficient history
Maintenance
Last push2026-07-262026-11-02
Maintenance notesNot verifiedNot verified
Repository created2024-12-242019-11-14
License & use
LicenseMIT · PermissiveApache-2.0 · Permissive
PricingPricing not verifiedPricing not verified
Basics
Browse by purposeRetrieval-augmented generation · Workflow automationRetrieval-augmented generation
TypeFrameworks & SDKsFrameworks & SDKs
SubcategoryAgent frameworksAgent frameworks
PlatformNot verifiedNot verified
Cost detailsCheck current official software, hosting, model and infrastructure pricing.Check current official software, hosting, model and infrastructure pricing.
Pricing source——
First collected2026-11-032026-11-03
MetricRepository stars, not unique users or individual-skill installsRepository stars, not unique users or individual-skill installs
LanguagePythonPython
About this projectPocket Flow: 100-line LLM framework. Let Agents build Agents!Author description: 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.
Measured at2026-11-02 19:02 UTC2026-11-02 18:58 UTC
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