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Fine-tuning data sources and eligibility

Alter formatted training examples with the openai_fine_tuning_training_data filter

Pixie CRM guidance. Follow the route for your workspace, check your role and enabled modules, and verify the result before moving on.

Modify the final message arrays before JSONL encoding.

Audience: CRM administrators and authorised staffPermission: DeveloperModule v1.0.0
Jump to steps
Where to goDevelopment integration → hook openai_fine_tuning_training_data
Before you start
  • Use an account with Developer and confirm the intended record or setting before making a change.
  • Follow the exact route above. If the screen or action is absent, check module activation, ownership and permissions rather than using another person’s account.
  • Use controlled test data for configuration, integration, email, AI, payment, portal or automation changes before production-wide use.

What this guide helps you do

Modify the final message arrays before JSONL encoding. The instructions reflect the supplied module’s registered menus, controller actions, views, settings and code-backed validation flow.

Follow these steps

  1. Go to Development integration → hook openai_fine_tuning_training_data.
  2. Select the exact record or option described in this guide.
  3. Complete the displayed fields or action using the rules below.
  4. Save or submit once and resolve any validation response.
  5. Check the resulting record, status, file, notification or integration effect.

Fields and options

ActionAlter formatted training examples with the openai_fine_tuning_training_data filter
Exact navigationDevelopment integration → hook openai_fine_tuning_training_data
Module version1.0.0
VerificationVerify the saved record, status, output or setting in the same workspace and review any linked activity, file or notification.

Rules and limits

  • Empty entries are removed after the filter.
  • Each retained entry is JSON-encoded with JSON_UNESCAPED_UNICODE and placed on its own line.

Check it worked

  • The supported alter formatted training examples with the openai_fine_tuning_training_data filter flow completes without bypassing permission or validation checks.
  • The resulting record, setting, status, file, delivery event or external response is visible from the relevant workspace.
  • Unexpected validation, provider or linked-record errors are investigated before retrying.

Security, privacy and operational checks

  • Restrict the API key and AI settings to authorised administrators.
  • Do not submit confidential, special-category or unnecessary personal data to the external AI provider.
  • Check generated text before using it in customer, staff, legal, financial or compliance communication.
  • Monitor provider billing and retention independently because this module has no built-in cost dashboard.

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