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deepset-ai/haystack

Establishedrank #164

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.

26.8k+155 · 7d 3.3k 178est. Apache-2.0Pythonpushed 7m ago
Compare View on GitHub

Composite

68

conf 65%

Momentum

49

conf 60%

Vitality (PVI)

81

conf 67%

Community

65

conf 60%

Security & maint.

90

conf 85%

Ecosystem influence

62

conf 60%

Opportunity

59

conf 60%

Breakout · 7d

43%

conf 71%

Executive summary

haystack is currently classified as established with a composite score of 68/100. Momentum (49) and vitality (81) are aligned — growth is backed by sustained maintenance. Estimated 7-day gain of 155 stars against a 26.8k-star base. Risk is assessed as low; the interpretable model puts its probability of entering the top trend cohort within 7 days at 43%.

90-day trajectory

+665 · 30d
2026-07-272026-10-24

Score breakdown

Every input, weight and normalized value — nothing hidden. Inputs marked est. are estimated until the full ingestion pipeline lands.

Momentum

Star velocityest.25%61
Star accelerationest.15%50
Fork velocityest.10%52
Contributor growthest.10%70
Issue activity growthest.10%44
PR activity growthest.10%42
External mention velocityest.10%5
Release event impactest.5%65
Trending-rank persistenceest.5%35

Model tn-interpretable-1.0.0 · confidence 60% · coverage 100%

Project Vitality Index

Commit consistency20%100
Release cadenceest.15%92
PR responsivenessest.15%86
Issue responsivenessest.15%57
Contributor diversityest.10%83
Maintainer continuityest.10%76
Documentation qualityest.5%83
Dependency freshnessest.5%54
Security hygieneest.5%55

Model tn-interpretable-1.0.0 · confidence 67% · coverage 100%

Security & maintenance

Release recency25%100
License clarity20%92
Maintenance status25%100
Dependency stalenessest.15%45
Bus factorest.15%100

Model tn-interpretable-1.0.0 · confidence 85% · coverage 100%

Ecosystem influence

Dependent repositoriesest.30%86
Quality-weighted dependentsest.20%64
Documentation citationsest.15%46
Contributor overlapest.15%27
Registry adoptionest.10%24
Topic centralityest.10%100

Model tn-interpretable-1.0.0 · confidence 60% · coverage 92% · missing: packageRegistryAdoption