8 Best UpTrain Alternatives in 2026 (Open Source)

UpTrain — UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform ro. vs generic eval tools: 20+ preconfigured evaluations with customizable prompts, few-shot examples, and scenario descriptions — all running locally for data privacy with root cause analysis on failures

These 8 open-source tools do the same job. They are ordered by how closely they match UpTrain, with live GitHub data so you can see which projects are actively maintained.

ToolGitHub starsStars / 30dLast commit
UpTrain(original)2.4k+42024-07-29
DeepEval18.5k+6762026-09-29
Ragas15.9k+4432026-02-24
phoenix11.7k+4182026-09-30
Langfuse35.2k+1,8212026-09-30
langwatch4.9k+2772026-09-30
Agenta4.8k+1312026-09-30
Opik22.3k+6092026-09-30
Promptfoo25.6k+1,1172026-09-30
  1. 1. DeepEval

    The LLM Evaluation Framework

    What sets it apart: Most comprehensive open-source LLM eval framework with 30+ research-backed metrics including agentic, RAG, multi-turn, MCP, and multimodal — vs Ragas (RAG-only) or custom eval scripts

    Best for: Teams needing comprehensive LLM/agent evaluation pipelines; CI/CD integration for LLM app quality gates; RAG pipeline evaluation and optimization

  2. 2. Ragas

    Supercharge Your LLM Application Evaluations 🚀

    What sets it apart: vs manual LLM evaluation: Purpose-built evaluation framework with both LLM-based and traditional metrics, automated test generation, and seamless integration with popular LLM frameworks

    Best for: Evaluating RAG pipeline quality with automated metrics; Generating comprehensive test datasets for LLM apps; Building continuous evaluation feedback loops

  3. 3. phoenix

    AI Observability & Evaluation

    What sets it apart: Full-stack AI observability (tracing + eval + datasets + prompt management) in one open-source platform — vs LangSmith which is closed-source and LangChain-specific

    Best for: Debugging and monitoring LLM applications in production; Systematic prompt engineering and experiment tracking

  4. 4. Langfuse

    🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23

    What sets it apart: Unlike LangSmith (LangChain-specific) or Helicone (proxy-based), Langfuse is fully open-source, framework-agnostic, and self-hostable, combining tracing, prompt management, evaluations, and datasets in a single platform built on ClickHouse for scalable production use.

    Best for: Teams operating production LLM applications who need tracing, prompt management, and evaluation in one platform; Organizations requiring self-hosted LLM observability for data privacy compliance

  5. 5. langwatch

    The platform for LLM evaluations and AI agent testing

    What sets it apart: Unified platform combining agent simulation, evaluation, observability, and prompt optimization with OpenTelemetry-native design — vs separate tools for tracing (Langfuse), eval (DeepEval), and prompt management

    Best for: Teams wanting eval + observability + prompt management in one tool; Agent simulation testing before production deployment; Organizations needing OpenTelemetry-native LLM observability

  6. 6. Agenta

    The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place.

    What sets it apart: Unified open-source LLMOps platform combining prompt playground, version control, 20+ evaluators, and OTel-native observability in one tool — vs separate tools for each

    Best for: Teams needing integrated prompt management + evaluation + observability; Product teams collaborating with SMEs on prompt engineering; Organizations wanting open-source LLMOps alternative

  7. 7. Opik

    Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

    What sets it apart: Full-lifecycle LLM platform combining tracing, evaluation, and optimization — uniquely includes Agent Optimizer and Guardrails alongside observability, unlike trace-only tools like LangSmith

    Best for: Teams needing end-to-end LLM observability from development to production; Automated LLM evaluation and quality assurance in CI/CD pipelines

  8. 8. Promptfoo

    Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and

    What sets it apart: Unlike LangSmith (production observability) or Langfuse (logging), promptfoo is the only open-source tool combining eval + red teaming + CI/CD code scanning — now backed by OpenAI while remaining fully MIT-licensed

    Best for: Teams hardening LLM apps against prompt injection and jailbreaks with automated red teaming; Engineering teams adding LLM eval regression tests to CI/CD pipelines