f0ce0f7884
- Expand sitemap from 2 to 13 URLs (all docs pages) - Update JSON-LD featureList with Anthropic, OpenCode, TypeScript SDK - Update llms.txt with docs links, TS SDK, OpenCode plugin sections - Add READMEs for agentlens-sdk and opencode-agentlens packages - Add repository, homepage, author, bugs fields to both package.json
70 lines
4.5 KiB
Plaintext
70 lines
4.5 KiB
Plaintext
# AgentLens
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> AgentLens is an open-source agent observability platform that traces AI agent decisions, not just API calls. It captures why agents choose specific tools, routes, or strategies — providing visibility into the reasoning behind every action.
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AgentLens helps engineering teams debug, monitor, and improve AI agent applications in production. Unlike traditional LLM observability tools that only trace API calls, AgentLens captures the decision-making process: tool selection rationale, routing logic, retry strategies, and planning steps. It includes a real-time dashboard with decision tree visualization, cost analytics, and token tracking.
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## Getting Started
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- [Documentation](https://agentlens.vectry.tech/docs): Full docs covering SDKs, integrations, API reference, and self-hosting
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- [Quick Start](https://agentlens.vectry.tech/docs/getting-started): Install, initialize, and send your first trace in 5 minutes
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- [GitHub Repository](https://gitea.repi.fun/repi/agentlens): Source code and issues
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- [PyPI Package](https://pypi.org/project/vectry-agentlens/): Install with `pip install vectry-agentlens`
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- [npm Package (SDK)](https://www.npmjs.com/package/agentlens-sdk): Install with `npm install agentlens-sdk`
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- [npm Package (OpenCode Plugin)](https://www.npmjs.com/package/opencode-agentlens): Install with `npm install opencode-agentlens`
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- [Dashboard](https://agentlens.vectry.tech/dashboard): Live dashboard with real-time traces
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## Python SDK
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- [Python SDK Reference](https://agentlens.vectry.tech/docs/python-sdk): init(), @trace decorator, log_decision(), TraceContext, configuration
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- [Basic Usage](https://gitea.repi.fun/repi/agentlens/src/branch/main/examples/basic_agent.py): Minimal SDK usage with trace context and decision logging
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- [OpenAI Integration](https://gitea.repi.fun/repi/agentlens/src/branch/main/examples/openai_agent.py): Wrap OpenAI client for automatic LLM call tracing
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- [Multi-Agent Example](https://gitea.repi.fun/repi/agentlens/src/branch/main/examples/multi_agent.py): Nested multi-agent workflow tracing
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## TypeScript SDK
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- [TypeScript SDK Reference](https://agentlens.vectry.tech/docs/typescript-sdk): init(), TraceBuilder, createDecision(), BatchTransport
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- Install with `npm install agentlens-sdk`
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## OpenCode Plugin
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- [OpenCode Plugin Docs](https://agentlens.vectry.tech/docs/opencode-plugin): Capture coding agent sessions, tool calls, LLM calls, permission flows, and file edits
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- Install with `npm install opencode-agentlens`
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- Configure via AGENTLENS_API_KEY and AGENTLENS_ENDPOINT environment variables
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## Key Concepts
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- [Concepts](https://agentlens.vectry.tech/docs/concepts): Traces, Spans, Decision Points, Events explained
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- **Traces**: Top-level containers for agent execution sessions, with tags and metadata
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- **Spans**: Individual operations within a trace (LLM calls, tool calls, chain steps)
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- **Decision Points**: The core differentiator — captures what was chosen, what alternatives existed, and why
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- **Decision Types**: TOOL_SELECTION, ROUTING, RETRY, ESCALATION, MEMORY_RETRIEVAL, PLANNING, CUSTOM
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## API
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- [API Reference](https://agentlens.vectry.tech/docs/api-reference): Full REST API contract
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- POST /api/traces: Batch ingest traces from SDK (Bearer token auth)
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- GET /api/traces: List traces with pagination, search, filters, and sorting
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- GET /api/traces/:id: Get single trace with all spans, decisions, and events
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- GET /api/traces/stream: Server-Sent Events for real-time trace updates
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- GET /api/health: Health check endpoint
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## Integrations
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- [OpenAI Integration](https://agentlens.vectry.tech/docs/integrations/openai): `wrap_openai(client)` auto-instruments chat completions, streaming, and tool calls
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- [Anthropic Integration](https://agentlens.vectry.tech/docs/integrations/anthropic): `wrap_anthropic(client)` auto-instruments Claude API calls
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- [LangChain Integration](https://agentlens.vectry.tech/docs/integrations/langchain): `AgentLensCallbackHandler` captures chains, agents, tools, and LLM calls
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- **Any Python Code**: `@trace` decorator and `log_decision()` for custom instrumentation
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## Self-Hosting
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- [Self-Hosting Guide](https://agentlens.vectry.tech/docs/self-hosting): Docker, docker-compose, env vars, reverse proxy
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- Docker Compose deployment with PostgreSQL and Redis
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- Single `docker compose up -d` to run
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- Environment variables: DATABASE_URL, REDIS_URL, AGENTLENS_API_KEY
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## Optional
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- [Company Website](https://vectry.tech): Built by Vectry, an engineering-first AI consultancy
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- [CodeBoard](https://codeboard.vectry.tech): Sister product — understand any codebase in 5 minutes
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