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ai-eval-platform
by huangyiminghappy
Open-source evaluation platform for RAG, agents, LLM-as-judge, and blind human tests
Python
Updated Jul 20, 2026
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Overview
This open-source evaluation platform covers RAG, AI agents, multi-turn conversations, LLM-as-judge and human blind tests, runs automated and human-in-the-loop evaluations, and generates structured evaluation reports. This aligns with the Tool Use Pattern for tool integration.
Why It Matters
As agents interact and delegate, objective evaluation across dialogue, retrieval, and endpoints becomes essential for trust. This platform centralizes automated LLM-as-judge scoring with human blind-testing and report generation, helping teams move from ad-hoc checks to repeatable agent evaluation. That visibility is crucial for measuring agent track record, spotting failure modes, and comparing benchmark results with reputation signals. This aligns with the Semantic Capability Matching Pattern and Model Context Protocol (MCP) Pattern to ensure robust context handling and coordination.
Ideal For
Teams needing an end-to-end evaluation harness for RAG and multi-turn agent workflows combining automated LLM judges with human blind tests. Designed to fit within an Agent Service Mesh Pattern.
Applications
- Validate RAG pipelines by running retrieval+generation tests and tracking metrics over time
- Evaluate multi-turn agent dialogues with LLM-as-judge and produce structured reports
- Run blind human evaluations alongside automated scoring to surface real-world failures
- Test and compare endpoint/API behavior for agent integrations before deployment
Works With
openaihuggingface
Topics
agent-evaluationai-agentai-evaluationai-infrablind-testhuman-evaluationllm-as-judgellm-evaluationmulti-turn-conversationopenai-compatible+2 more
Similar Tools
agent-playgroundagent-arena
Keywords
multi-agent trustA2A evaluationagent-to-agent evaluationllm-as-judge