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    1. Home
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    AgentEvals icon

    AgentEvals

    Agent Frameworks
    Featured

    Readymade evaluators for scoring LLM agent trajectories in Python and TypeScript.

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    At a Glance

    Pricing
    Open Source

    agentevals is a package of evaluators for agent trajectories, released under the MIT License. It is free to use, copy, modify and distribute.

    Engagement

    Available On

    Web
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    Resources

    WebsiteDocsGitHubllms.txt

    Topics

    Agent FrameworksLLM EvaluationsAI Development Libraries

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    OpenEvalsInspect PetrirLLM
    Developer
    LangChain, Inc.San Francisco, CAEst. 2023$160M raised

    Listed Oct 2026

    About AgentEvals

    AgentEvals is an open-source package from LangChain that provides evaluators and utilities for judging the intermediate steps an agent takes as it runs, known as its trajectory. It is available for Python and TypeScript and is released under the MIT License. The README positions it as a conceptual starting point for agent evals, with the companion package openevals covering more general evaluation.

    What It Is

    AgentEvals is an agent evaluation library. You represent an agent's run as a list of OpenAI-style messages (or LangChain message objects) and pass it to an evaluator, which returns a keyed result with a score and, for LLM judges, a comment explaining the reasoning. Evaluators can be used with or without a reference trajectory, depending on the type.

    Evaluator Types

    Trajectory match evaluators compare an agent's tool calls with a reference trajectory in four modes: strict (same messages and tool calls in the same order), unordered (same tool calls in any order), subset, and superset. Tool-argument matching can be set to exact, ignore, subset, or superset, with per-tool overrides that accept a list of fields or a custom comparator function.

    The trajectory LLM-as-judge evaluator uses a judge model with a prebuilt accuracy prompt, with or without a reference. It accepts options such as continuous scoring, custom choices, a system prompt, and few-shot examples.

    Graph Trajectories and LangGraph

    For graph-based agents such as LangGraph, graph trajectory evaluators work on nodes visited rather than messages. Utilities extract a trajectory from a LangGraph thread, including multiple turns and interrupts. A graph trajectory LLM-as-judge evaluator and a strict-match evaluator are provided.

    Setup and Integrations

    Install with pip install agentevals or npm install agentevals @langchain/core. LLM-as-judge evaluators use LangChain chat model integrations by default, or the OpenAI client directly. Python async variants exist for all evaluators. Results can be logged to LangSmith through its pytest or Vitest/Jest integrations or its evaluate function.

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    Pricing

    OPEN SOURCE

    Open Source (MIT)

    agentevals is a package of evaluators for agent trajectories, released under the MIT License. It is free to use, copy, modify and distribute.

    • MIT License
    • Python package (pip install agentevals)
    • TypeScript package (npm install agentevals @langchain/core)
    • Agent trajectory evaluators
    • The quickstart evaluator uses OpenAI o3-mini, which requires your own OpenAI API key (external cost)

    Capabilities

    Key Features

    • Trajectory match evaluators with strict, unordered, subset, and superset modes
    • Configurable tool argument matching with per-tool overrides
    • Trajectory LLM-as-judge evaluator with optional reference trajectory
    • Graph trajectory LLM-as-judge and strict match evaluators
    • LangGraph trajectory extraction utilities
    • Python asyncio support
    • LangSmith integration via pytest, Vitest/Jest, and evaluate
    • Python and TypeScript packages

    Integrations

    LangGraph
    LangChain
    LangSmith
    OpenAI
    openevals
    pytest
    Vitest
    Jest
    API Available
    View Docs

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    Developer

    LangChain, Inc.

    LangChain is a company focused on building a comprehensive framework for developing applications with large language models (LLMs) through composable building blocks for orchestrating agentic workflows.

    Founded 2023
    San Francisco, CA
    $160M raised
    136 employees

    Used by

    Replit
    Clay
    Harvey
    Rippling
    +13 more
    Read more about LangChain, Inc.
    WebsiteGitHubX / Twitter
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