LangChain
Most popular framework for building LLM applications
Overview
The framework that defined LLM application development — chains, agents, RAG, tool calling — in Python and JS. Since the October 2025 1.0 release, agents run on the LangGraph runtime; the core stays MIT-licensed, with commercial LangSmith observability and deployment on top.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 27 Sep 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
- 1 seat
- 5k base traces/mo included
- Pay-as-you-go beyond quota
- Community support
- 10k base traces/mo included
- Unlimited seats
- 1 free dev deployment
- Email support
- Self-hosted / hybrid options
- Custom SSO and RBAC
- Support SLA
- Architectural guidance
Use cases
What you can produce with LangChain
- The broadest integration surface of any LLM framework, and the fastest path from idea to working prototype
- A stable major line at last — LangChain 1.0 and LangGraph 1.0 (22 October 2025) commit to no breaking changes before 2.0, answering the loudest historical complaint
- Agents rebuilt around a single create_agent abstraction rather than the old chain ceremony
- A durable runtime in LangGraph — persistence, interrupts, human-in-the-loop control and resumable long-running workflows — which is the part production teams actually keep
- Observability through LangSmith: a free Developer tier at 5k traces a month, Plus at $39 per seat monthly with 10k base traces, then $2.50 per 1,000 extended traces
- ⚠️ A seat fee that lands before you log a single trace, with costs climbing faster than open-source rivals like Langfuse at scale — and the old criticism has moved rather than vanished: teams still find the classic chain abstractions more trouble than they are worth once requirements get specific, and a visible cohort has rewritten straight to provider SDKs
Still the default starting point for LLM apps, and meaningfully more stable since LangChain 1.0 and LangGraph 1.0 shipped in October 2025 — agents now run on LangGraph's durable runtime, and the team has promised no breaking changes before 2.0. The integration catalogue is unmatched, Python and JavaScript are both first-class, and LangSmith adds tracing, evals and deployment when you outgrow print statements. The over-abstraction critique still applies to the classic chain layers, and plenty of production teams eventually drop to raw SDKs or keep only LangGraph. Free and MIT-licensed with no regional restrictions; LangSmith's per-seat and per-trace pricing is where the bill eventually arrives.
What people say
Ask five production teams about LangChain and you'll get five different answers — which is itself the story. It remains the most-adopted way to start building LLM applications, and LangChain 1.0 and LangGraph 1.0, announced on 22 October 2025, answered the loudest historical complaint: version churn. Eleven months on, both are still on 1.x. The 1.0 line committed to no breaking changes before 2.0, rebuilt agents around a single create_agent abstraction, and made LangGraph — the lower-level durable runtime with built-in persistence, interrupts and human-in-the-loop control — the foundation everything runs on.
The old criticism hasn't vanished; it's moved. Developers still describe the classic chain abstractions as more trouble than they're worth once requirements get specific, and a visible cohort of teams has rewritten straight to provider SDKs. The same crowd generally treats LangGraph more kindly, because it solves real problems — state, resumability, long-running workflows — rather than wrapping API calls in ceremony.
The money side is LangSmith, now a platform of seven services spanning observability, evaluation, deployment, sandboxes, an LLM gateway and no-code agents. A free Developer tier includes 5k traces a month; Plus runs $39 per seat monthly with 10k base traces. Past that the old per-trace rate is gone: overage is metered in compute and storage units at $1.50 and $1.00 each, which makes older cost comparisons against Langfuse obsolete, and the seat fee still lands before you log a single trace. The framework itself stays MIT-licensed and free.
Verdict from the trenches: unbeatable integration breadth and the fastest path from idea to working prototype. Whether it survives into production depends on whether LangGraph's runtime earns a place in your stack — plenty of teams decided the older abstractions didn't.
The company raised $125 million at a $1.25 billion valuation in October 2025, and Deep Agents, a framework for long-running agents, now sits beside LangChain and LangGraph as a third open-source pillar.
Summary of public user & expert reviews, compiled by RECATOOLS.
Notable facts
- LangChain reached 50,000 GitHub stars within 3 months of release, making it one of the fastest-growing developer frameworks in history.
- Harrison Chase built the first version of LangChain in a weekend as an experiment and open-sourced it without expecting widespread adoption.
- LangChain's npm package is downloaded over 1 million times per week, making it one of the most-used AI libraries in the JavaScript ecosystem.
Frequently asked questions
About this listing
This entry was compiled from publicly available data including LangChain's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with LangChain unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
For the latest details, please refer to LangChain directly →
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