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207 tools · 25 stacks

AI tools are all over the place. This is the full landscape — 207 tools across 17 categories, mapped and connected. Ready to narrow it down? Build your stack →

Team size

Budget

Use case

Stage

Cluster

Stack Layers
What are you building and how is it defined?
How do you write and ship code?
How does your AI think and act?
Which models and infrastructure power it?
How do you build, observe, and extend it?
These tools often paired with
DSPy
vs
LangChain

Choose DSPy when…

  • •You want to optimize LLM pipelines programmatically
  • •You're running experiments and tuning prompts at scale
  • •Academic or research-oriented LLM workflows fit you

Choose LangChain when…

  • •You want a broad, flexible LLM orchestration toolkit
  • •You need integrations with many tools and data sources
  • •You're prototyping or exploring LLM app patterns
Field
DSPy
LangChain
Category
Pipelines & RAG
Pipelines & RAG
Type
OSS
OSS
Free Tier
✓ Yes
✓ Yes
Plans
—
—
Stars
⭐ 18,000
⭐ 93,000
Health
●80 — Active
●85 — Active
Trajectory
— not enough data
— not enough data
Synced
2 days ago
today

DSPy

Stanford's framework for algorithmically optimizing LLM pipelines. Replaces hand-crafted prompts with declarative modules and automatic optimization.

LangChain

Most widely used framework for building LLM applications. Chains, agents, RAG pipelines, and deep integrations with 300+ tools.

DSPy Website ↗GitHub ↗
LangChain Website ↗GitHub ↗

Shared Connections (1)

LiteLLM

Only DSPy (1)

LangChain

Only LangChain (28)

OpenHandsCrewAIAutoGenLangGraphSemantic KernelLangSmithLlamaIndexQdrant
See full comparison in Explore →