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Connect your application through a source in Data. You keep your provider key and existing client library. No sandbox is needed to begin capturing calls.

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1. Create a source

In the ReasonBlocks dashboard, choose Data, create a data source and generate its connection key. Copy the complete HTTPS capture URL for your provider:
  • OpenAI Chat Completions: a URL ending in /capture/SOURCE_ID/openai/v1.
  • Anthropic Messages: a URL ending in /capture/SOURCE_ID/anthropic.
Use the URL actually returned by the dashboard. Keep its capture key in your application’s secret environment as REASONBLOCKS_CAPTURE_KEY. Keys expire after seven days; rotating the connection key invalidates the previous one.

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2. Let your coding agent connect the project

The setup guide covers installing the CLI, generating the helper, connecting your client and retaining a run ID across all calls in one task. A run is all the model calls in one task, labelled with one x-rb-run header.
The setup CLI and helper are published on PyPI as rbtrace==1.2.1. It labels runs automatically when the generated helper is imported. If a project already has a generated 1.1.0 connection, python -m rbtrace migrate upgrades its helper in place, keeping the source URL and backing up the original files; see Migrate an older generated connection.

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3. Verify capture

Run the local check, python -m rbtrace doctor --path . --json, in your application environment and test the actual entrypoint. When you run a real workflow, confirm that its records appear in Data. The local check verifies configuration and capture-key presence; it does not contact the service or validate credentials remotely. Model calls use your provider account and incur its normal fees. See Integrating your agent for task boundaries and coverage.

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4. Prepare training when ready

Training needs representative tasks, a resettable test copy of your tools and data, and a way to evaluate completed tasks. Your coding agent can help build that connection once the application-specific details are available. Follow Train your complete agent to prepare a plan and review the budget before authorizing paid work. Continue with Work with your coding agent to review data readiness, interpret training results and test a candidate before rollout.