Establish a server-side API boundary
Keep the TextCortex key in the server environment and authenticate your own application’s users before making model requests. Limit the input size and parameters clients can submit.
Maintain approved model identifiers and default settings in configuration. Use separate configuration for workloads that require EU-hosted inference.
Validate before sending production traffic
Create a request set that covers normal inputs, malformed content, missing context and the model capabilities you use. Check output parsing, tools, streaming and cancellation.
Exercise application behavior for timeouts, invalid credentials, unknown models and rate limits. Keep retries bounded and avoid repeating external actions.
Introduce traffic gradually
Start with a small eligible workload. Compare success rate, latency and token usage against your acceptance criteria and previous configuration.
Record which model served each request. Keep enough information to diagnose regressions while minimizing the sensitive content retained in logs.
Expand with a release process
Adding a model is a product change when it can alter answers, cost or processing location.
- Evaluate the new model on the established request set.
- Review capabilities and regional requirements.
- Promote the configuration with an explicit rollback path.
- Monitor task outcomes after release.