Langchain Alternatives

Free and open-source alternatives to Langchain

• CrewAIopen source
• Llamaindexopen source
• OpenAI Agents SDKopen source
• Agnoopen source
• Chonkieopen source
• DSPyopen source
• Mastraopen source
• Pydantic AIopen source
• Flowiseopen source

Langchain alternatives in detail

1. CrewAI

   open sourceMITSDK

   CrewAI orchestrates multiple agents as a 'crew' with roles, goals, and tasks — a high-level, fast-to-start abstraction for collaborative multi-agent work. It also offers Flows for event-driven, more deterministic control when you need it. Standalone and independent of LangChain.

2. Llamaindex

   open sourceMITmacOS, Windows, LinuxSDK

   LlamaIndex (MIT, ~50k stars) is the data-first framework: connectors and ingestion pipelines, indexes and query engines for RAG, agents over documents, and event-driven Workflows for orchestration. The company's 2026 center of gravity is document processing — LlamaParse's agentic OCR for 50+ file types and the LlamaCloud parse/extract/index platform.

   Read: LangChain vs LlamaIndex in 2026: Agents or Data?

3. OpenAI Agents SDK

   open sourceMITSDK

   OpenAI's open-source Agents SDK is a small, unopinionated framework for building agents: a core agent loop plus handoffs (delegation between agents), guardrails (input/output validation), sessions (memory), and built-in tracing. The production-grade successor to Swarm; works with non-OpenAI models too.

4. Agno

   open sourceApache-2.0SDK

   Agno (formerly Phidata) is a Python framework for building multi-agent systems with memory, knowledge, and tools. You compose Agents, Teams, and Workflows over 20+ model providers, and can run them in production with the AgentOS runtime. The core library is open source under Apache-2.0.

5. Chonkie

   open sourceMITSDK

   Chonkie is a lightweight open-source library that turns documents into retrieval-ready chunks, with token, sentence, recursive, semantic, and code-aware chunkers behind one small API. Chunking quality sets the ceiling on RAG quality, and Chonkie makes good strategies easy to swap.

6. DSPy

   open sourceMITLinux, macOS, WindowsSDK

   DSPy (from Stanford NLP) lets you build LLM pipelines as Python code rather than brittle prompt strings. You declare each step as a typed signature, compose modules like ChainOfThought and ReAct, then run an optimizer (BootstrapFewShot, MIPROv2, GEPA) that searches instructions and few-shot demonstrations against your metric and data. Change models and you recompile, not rewrite.

7. Mastra

   open sourceApache-2.0 (core; ee/ commercial)SDK

   Mastra is an open-source TypeScript framework for building AI agents, workflows, RAG, and tool-calling, from the team behind Gatsby. It targets JavaScript/TypeScript engineers who want typed agents, graph-based workflows, memory, and observability in one stack instead of dropping to Python.

   Read: Mastra vs LangChain (2026): TypeScript Agent Frameworks Compared

8. Pydantic AI

   open sourceMITmacOS, Windows, LinuxSDK

   Pydantic AI (MIT, ~18k stars, v1 GA September 2025) brings the Pydantic team's type discipline to agents: outputs validated against your models so errors move from runtime to write-time, type-safe dependency injection for tools, the broadest model-agnostic provider list, durable execution via Temporal/DBOS/Prefect/Restate, and MCP/A2A interop.

9. Dify

   freemiumDify Open Source License (Apache-2.0 + conditions)WebPlatform

   Dify (~145k stars) is the visual answer to LLM app building: a workflow canvas for chatflows and agents, a built-in RAG pipeline from ingestion to retrieval, agent nodes with 50+ tools, hundreds of models via any provider, a prompt IDE, and LLMOps — self-hosted with one docker compose or cloud freemium. License caveat: it's a modified Apache-2.0 with conditions.

   Read: n8n vs Dify: Which AI Workflow Platform? (2026)

10. Flowise

    open sourceApache-2.0 (Community Edition; /enterprise dir is commercial)WebPlatform

    Flowise is an open-source, low-code platform for building LLM apps and AI agents on a drag-and-drop canvas. You wire nodes into chains, agents, and RAG flows, then self-host the Apache-2.0 core or run Flowise Cloud. Built flows expose an API and embed widget, so prototypes ship as real product surfaces.