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LangChain
The framework for building LLM apps — chains, agents, RAG, and 600+ integrations.
VS
At a Glance
| Attribute | LangChain | DSPy |
|---|---|---|
| License / Pricing | Free | Open Source |
| Type | ai | ai |
| GitHub Stars | — | — |
| Rating | 4.6/5 | 4.3/5 |
| Key Features | 6 listed | 6 listed |
| Integrations | 6 listed | 5 listed |
| Categories | AI AgentsRAG Frameworks | AI Agents |
Key Features
LangChain
- LCEL (LangChain Expression Language) for composing chains
- LangGraph for stateful, multi-actor agent workflows
- 600+ integrations with LLMs, vector stores, tools
- RAG primitives: document loaders, splitters, retrievers
- Memory and conversation history management
- LangSmith for tracing, debugging, and evaluation
DSPy
- Declarative signatures instead of brittle prompt strings
- Automatic prompt optimization with teleprompters
- Built-in evaluation and metric-driven tuning
- Supports any LLM via OpenAI-compatible API
- ChainOfThought, ReAct, and MultiChainComparison modules
- Compiled programs that generalize across LLM versions
Real-World Use Cases
LangChain
Build a document Q&A bot with RAG
Load documents using LangChain document loaders (PDF, web, S3)
Build a ReAct agent with tools
Define tools (web search, calculator, database query)
DSPy
Build a reliable multi-hop QA system
Define a Signature: 'question -> answer' with context field
Integrations
LangChain
openaianthropicpineconechromalangsmithweaviate
DSPy
openaianthropicollamalangchainweaviate
🏆 Which should you choose?
Choose LangChain if…
- → you want a managed or commercial offering with enterprise support and SLAs
Choose DSPy if…
- → you need a fully open-source, self-hosted solution with no vendor lock-in