How to manage fine-tuned GPT models and prompt flow versions in Azure AI Foundry?

Hi Satish,

Thankyou for posting this on Microsoft Q&A Portal.

Multiple fine-tuned model versions could be managed in the following ways:

• When you deploy it, keep a fixed naming convention for the model. Here is a guide to deploy fine-tuned models:
  https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/fine-tuning-deploy?tabs=portal#deploy-your-fine-tuned-model
• You may also deploy different Foundry resources for different models, but this approach can lead to complexity when managing and running inferences.

For Prompt Flow updates tied to each model version, you can create a custom tool integrated with your prompt flow using the following documentation:
https://microsoft.github.io/promptflow/how-to-guides/develop-a-tool/create-and-use-tool-package.html

To ensure that only specific team members can deploy or modify production-ready models, enable managed identity for the AI Foundry resource and assign the contributor role to specific team members as shown below:

Feel free to accept this as an answer.
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Hi there

Keep separate projects for dev/test/prod.

Register fine-tuned models with clear versioning in the Model Catalog.

Tag Prompt Flows with the model version they use.

Control deployment via RBAC so only approved users can publish.

If this helps kindly accpt the answer