LangGraph template for a simple ReAct agent, with MCP tools support and robust test suites.
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Updated
Sep 28, 2025 - Python
LangGraph template for a simple ReAct agent, with MCP tools support and robust test suites.
agentevals is a framework-agnostic evaluations solution based on OpenTelemetry traces
Evaluation kit for testing stateful agents
🤖 Build intelligent agents with the Letta Code SDK, enabling persistent memory and learning for enhanced multi-turn conversations.
Offline LLM evaluation suite on LangSmith: RAG and tool-using agent evals, end-state checks, prompt-injection guard, judge calibration and multi-model comparison (LangGraph, openevals, agentevals, AWS Bedrock)
Adversarial customer-support RAG agent with guardrails, DeepEval evals and Langfuse tracing, tested on a trap-seeded knowledge base
Walk-forward / out-of-sample validation for agent evals — detect eval-set overfitting the way quants detect backtest overfitting. Zero dependencies.
Evaluate a LangGraph agent with the LangSmith SDK, 100% offline: evaluate() with correctness, trajectory matching, a local LLM-as-judge critic, pairwise A/B and a CI regression gate.
Is TypeSafe AI's Jev calibrated? Reliability diagram, ECE and saturation split on 240 hand-labelled agent tool calls.
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