Langchain vs Dspy

Langchain and Dspy are both popular ml inference & agents tools. This page compares their internal architecture, technology stack, data flow patterns, and system behavior — based on automated structural analysis of their source code. They share 2 technologies including pydantic, tenacity.

langchain-ai/langchain

131,015
Stars
Python
Language
10
Components
0.4
Connectivity

stanfordnlp/dspy

33,164
Stars
Python
Language
10
Components
2.1
Connectivity

Technology Stack

Shared Technologies

pydantic tenacity

Only in Langchain

python asyncio threading pip

Only in Dspy

litellm openai json_repair diskcache pytest asyncer

Architecture Layers

Langchain (5 layers)

Core Layer
Base abstractions and interfaces without third-party dependencies
Classic LangChain
Main framework package with high-level agent orchestration
Integration Partners
Third-party service integrations organized by provider
Specialized Tools
Text splitters, model profiles, and testing utilities
API Management
Deprecation handling, beta features, and backward compatibility

Dspy (5 layers)

Signatures & Types
Type-safe interfaces defining input/output contracts with custom types like Image, Audio, Tool
Adapters
Interface layer between DSPy and language models, handling format conversion and parsing
Modules
Composable building blocks like Predict, ChainOfThought, ReAct for creating AI programs
Optimizers
Algorithms for automatically improving prompts and weights through teleprompt techniques
Clients & Infrastructure
LM clients, caching, evaluation, and utility functions for the framework

Data Flow

Langchain (5 stages)

  1. Agent Planning
  2. Tool Execution
  3. Observation Processing
  4. Response Generation
  5. History Storage

Dspy (6 stages)

  1. Signature Definition
  2. Module Creation
  3. Adapter Processing
  4. LM Execution
  5. Response Parsing
  6. Optimization

System Behavior

DimensionLangchainDspy
Data Pools22
Feedback Loops23
Delays23
Control Points34

Code Patterns

Unique to Langchain

dynamic import system callback chain pattern abstract base classes deprecation management security by default

Unique to Dspy

adapter pattern type system signature-based programming composable modules optimization framework

When to Choose

Choose Langchain when you need

  • Unique tech: python, asyncio, threading
  • Simpler system dynamics
  • Loosely coupled, more modular
View full analysis →

Choose Dspy when you need

  • Unique tech: litellm, openai, json_repair
  • Richer system behavior (more feedback loops and control points)
  • Tighter integration between components
View full analysis →

Frequently Asked Questions

What are the main differences between Langchain and Dspy?

Langchain has 10 components with a connectivity ratio of 0.4, while Dspy has 10 components with a ratio of 2.1. They share 2 technologies but differ in 10 others.

Should I use Langchain or Dspy?

Choose Langchain if you need: Unique tech: python, asyncio, threading; Simpler system dynamics. Choose Dspy if you need: Unique tech: litellm, openai, json_repair; Richer system behavior (more feedback loops and control points).

How does the architecture of Langchain compare to Dspy?

Langchain is organized into 5 architecture layers with a 5-stage data pipeline. Dspy has 5 layers with a 6-stage pipeline.

What technology does Langchain use that Dspy doesn't?

Langchain uniquely uses: python, asyncio, threading, pip. Dspy uniquely uses: litellm, openai, json_repair, diskcache, pytest.

Explore the interactive analysis

See the full architecture maps, code patterns, and dependency graphs.

Langchain Dspy

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Compared on March 25, 2026 by CodeSea. Written by .