Free open source alternative app list of LangSmith :

Langfuse

Key features Open-source LLM engineering platform for AI-powered applications. Tracing and observability tools to debug and analyze LLM requests. Monitoring capabilities for production LLM-based products. Built-in evaluation features to assess and improve model performance. Prompt management to organize, version, and maintain prompts. Platforms: Linux, macOS, Windows Links Official website Source code repository Pricing Free. The entire platform is open source under the MIT license and free to self-host with no feature restrictions.

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Arize Phoenix

Key features Open-source LLM tracing and evaluation platform for AI applications. Monitor, debug, and optimize LLM workflows with built-in observability. Self-hosted deployment for full control over tracing and evaluation data. Supports experimentation with LLM tracing and evaluation using the Phoenix library. Designed for machine-learning and AI observability use cases. Platforms Windows, macOS, Linux Links Official website Source code repository Pricing Free. The free plan includes self-hosted LLM tracing, evaluation, and experimentation with the open-source Phoenix library.

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Helicone

Key features Open-source LLM observability and monitoring platform built for AI applications. Tracks LLM requests to help developers understand usage patterns and behavior. Monitors costs associated with AI application usage. Measures latency and performance for model calls. Evaluates quality metrics to assess model outputs and application reliability. Platforms: Linux Links: Official website · Source code Pricing: Free self-hosted open-source license (Apache-2.0) with full observability features; cloud managed service available with a free tier.

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Agenta

Key features Build, evaluate, and improve AI agents and LLM applications in a single collaborative platform. Manage prompts with versioning and organization tools for LLM workflows. Run evaluations to test and compare AI agent and LLM outputs. Gain observability into LLM application behavior and performance. Support LLMOps practices for teams developing with large language models. Platforms Windows, macOS, Linux Links Official website: https://agenta.ai Source code: https://github.com/Agenta-AI/agenta Pricing Free. Free and open-source self-hosted platform under Apache-2.0 license.

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Laminar

Key features Open-source, AI-powered platform designed for engineering LLM products. Comprehensive LLM tracing to monitor and debug application behavior. Evaluation tools for assessing model performance and reliability. Prompt management features to organize and version prompts. Free to self-host with the full feature set, including tracing, evaluation, and prompt management. Available on Linux, macOS, and Windows. Platforms: Linux, macOS, Windows. Links Official website: https://www.lmnr.ai Source code: https://github.com/lmnr-ai/laminar Pricing: Free — the open-source platform is free to self-host with full features, including LLM tracing, evaluation, and prompt management.

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LangWatch

Key features Simulation-based testing for AI agents and LLM applications. Evaluation tools for LLM applications. Observability for AI agents and LLM applications. Open-source platform licensed under Apache-2.0. Self-hostable via Docker. Platforms: Linux, macOS, Windows Links Official website: langwatch.ai Source code: github.com/langwatch/langwatch Pricing: Free and open-source under Apache-2.0, with self-hosting via Docker.

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langgraph

langgraph is a free, open-source software / service you can self-host or use without paying. Low-level orchestration framework for building stateful agents. Trusted by companies shaping the future of agents – including Klarna, Replit, Elastic, and more – LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents. pip install -U langgraph Tip If you're looking to quickly build agents, check out Deep Agents — a higher-level package built on LangGraph for agents that can plan, use subagents, and leverage file systems for complex tasks. For an equivalent JS/TS library, check out LangGraph.js and the JS docs . Why use LangGraph? LangGraph provides low-level supporting infrastructure for any long-running, stateful workflow or agent: Durable execution — Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off. Human-in-the-loop — Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution. Comprehensive memory — Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions. Debugging with LangSmith — Gain deep visibility into complex agent behavior with visualization tools that trace execution paths, capture state transitions, and provide detailed runtime metrics. Production-ready deployment — Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows. Tip For developing, debugging, and deploying AI agents and LLM applications, see LangSmith . LangGraph ecosystem While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents. To improve your LLM application development, pair LangGraph with: Deep Agents – Build agents that can plan, use subagents, and leverage file systems for complex tasks. LangChain – Provides integrations and composable components to streamline LLM application development. LangSmith – Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time. LangSmith Deployment – Deploy and scale agents effortlessly with a purpose-built deployment platform for long-running, stateful workflows. Discover, reuse, configure, and share agents across teams – and iterate quickly with visual prototyping in LangSmith Studio . Documentation docs.langchain.com – Comprehensive documentation, including conceptual overviews and guides reference.langchain.com/python/langgraph – API reference docs for LangGraph packages LangGraph Quickstart – Get started building with LangGraph Chat LangChain – Chat with the LangChain documentation and get answers to your questions Discussions : Visit the LangChain Forum to connect with the community and share all of your technical questions, ideas, and feedback. Additional resources Guides – Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.). LangChain Academy – Learn the basics of LangGraph in our free, structured course. Case studies – Hear how industry leaders use LangGraph to ship AI applications at scale. Contributing Guide – Learn how to contribute to LangChain projects and find good first issues. Code of Conduct – Our community guidelines and standards for participation. Acknowledgements LangGraph is inspired by Pregel and Apache Beam . The public interface draws inspiration from NetworkX . LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.

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