- Set the Orq.ai OTLP endpoint and authenticate with an API key
- Configure the OpenTelemetry SDK in an existing application
- See every LLM call, agent step, and tool use in Traces
- For framework-specific setup, see the Frameworks in Integrations
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Instrument with OpenTelemetry
Install the OpenTelemetry SDK and the OTLP HTTP exporter:The exporter accepts both
https://api.orq.ai/v2/otel and the full path https://api.orq.ai/v2/otel/v1/traces. Spans from any OpenTelemetry-instrumented code are exported automatically.4
Connect a framework
Using a framework? Instrument the framework with its own setup instead of manual span creation. Each page in Integrations shows the exact installation, environment variables, and instrumentation call:LangGraph
One
setup() call instruments the graph, tools, and every LLM step.Vercel AI SDK
Python and TypeScript SDKs with experimental OpenTelemetry telemetry.
Pydantic AI
Logfire-based instrumentation for agents, tools, and streaming.
OpenAI Agents
Automatic tracing via
OpenAIAgentsInstrumentor.Agno
OpenInference instrumentation for agents and tools.
Google ADK
Trace agent workflows, tool calls, and Gemini model interactions.
Mastra
TypeScript agents and workflows with OpenTelemetry tracing.
Claude Agent SDK
Hooks-based instrumentation for agent turns and tool use.
See all frameworks
Full list of supported frameworks and setup guides.
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Analyze traces with MCP
Install the Orq MCP server in the editor or AI assistant, then ask the coding assistant:
Orq MCP trace analysis output
Troubleshooting
Traces not appearing in the Studio
Traces not appearing in the Studio
- Confirm the OTLP endpoint is set to
https://api.orq.ai/v2/otel(or/v2/otel/v1/tracesfor exporters that require the full path) - Check that the workspace in the API key matches the AI Studio workspace being viewed
- Traces can take a few seconds to appear, wait 10 seconds and refresh
Annotate traces
Label and review spans to build high-quality evaluation datasets from real production traffic.
Set up analytics
Track cost, latency, error rates, and token usage across models and deployments over time.
Run an experiment
Use traced data as a baseline to compare prompts, models, and configurations side by side.
Build an agent
Build and deploy a native Orq.ai agent with tools, memory, and full AI Studio management.