How can I use Agent Lightning for fine-tuning an agent’s system prompt using OpenAI models (gpt-4o)? Can VERL be used for this?

[rutvik-jaiswal-deeplearning]

I am trying to fine-tune an existing Agent using Lightning agent — specifically its system prompt (agent behavior).
My requirements:

• I must use OpenAI models only, such as gpt-4o base.
• I want to use VERL to optimize or update the agent’s prompt/behavior.
• I prefer a minimal, validated, single-file example (or as simple as possible).

My Questions:

1. Does Agent Lightning support fine-tuning or behavioral optimization using VERL when the underlying LLM is an OpenAI model?
2. Is VERL compatible with Agent Lightning for updating prompts or performing reward-based optimization on an OpenAI-powered agent?
3. Can you we have used verl with prompt optimization for the llm and get some a validated minimal example demonstrating how to integrate VERL + Agent Lightning + OpenAI (gpt-4o) for fine-tuning an agent system prompt?

[ultmaster]

1. Fine-tuning / behavior optimization or OpenAI model: yes. w/ VERL: no.
2. VERL is an RL framework for local model. You can't use VERL for prompt tuning, to the best of my knowledge.
3. It's not possible.

Related references:

• Azure OpenAI Fine-tuning (with SFT) with Agent-lightning: https://github.com/microsoft/agent-lightning/tree/main/examples/azure
• Introduction to VERL: https://github.com/microsoft/agent-lightning/tree/main/examples/azure
• Prompt tuning examples (naturally work with GPT models): https://github.com/microsoft/agent-lightning/tree/main/examples/apo