The open-source, local-first alternative to LangSmith. No cloud. No setup.
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Updated
Jul 26, 2026 - Python
The open-source, local-first alternative to LangSmith. No cloud. No setup.
Open-source LLMOps platform with prompt management, an OpenAI-compatible AI gateway, OpenTelemetry tracing, a versioned tool catalog, and LLM evaluation. Use hosted or self-host with TypeScript and Python SDKs.
A sub-millisecond, zero-allocation deterministic state proxy and Merkle DAG execution engine for multi-step AI agents. Features time-travel branching and dynamic TLS MITM packet virtualization via .NET 11 Pipelines.
I built AgentWatch to solve a problem I had: AI agents burning tokens and money behind my back. Now I can monitor everything in real-time. Feedback welcome! 🤖💸
Drop-in observability for LLM apps — quality scoring, hallucination detection, cost tracking and agent debugging
Decision-quality observability for LLM agents — scores whether each decision was good, not just how fast it ran. Tool ROI, reasoning coherence, confidence signals. Pure Node.js, zero frameworks.
Self-hosted observability and debugging platform for AI agents with traces, execution DAGs, cost analytics, latency stats, and live events.
Hand-built LLM agent observability: trace logging, token budget/sliding window, and LLM-as-judge scoring — no external SaaS. Wraps any agent function with timing, context truncation, and semantic (not string-match) answer evaluation.
🟢 No LangSmith required. DeerFlow Trace Edition — super agent harness (fork of bytedance/deer-flow) with BUILT-IN Execution Flow trace panel. Every LangGraph checkpoint, sub-agent, tool, and model node is inspectable directly inside chat UI. 100% local, zero SaaS, zero per-trace fees, zero data leaving your machine.
Official TypeScript/Node SDK for Observyze. 1-line auto-instrumentation for OpenAI, Anthropic, Gemini, Vercel AI & LangChain, with OpenTelemetry tracing, execution budgets, PII redaction & guardrails.
This repo contains detailed notes on LangSmith concepts including traces, runs, observability, and integrations with LangChain, RAG, and LangGraph.
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