[Feature Request]: Support for Loading response_format as a Pydantic Model from Configuration Files

[sternakt]

Is your feature request related to a problem? Please describe.

Currently, when loading configurations using config_list_from_json, the response_format must be dynamically added to each configuration in the code. For example:

config_list = autogen.config_list_from_json(
    "OAI_CONFIG_LIST",
    filter_dict={
        "model": ["gpt-4o", "gpt-4o-mini"],
    },
)

for config in config_list:
    config["response_format"] = MathReasoning

While this approach works, it would be beneficial to explore whether response_format could be specified directly in the configuration file.

Describe the solution you'd like

We could support defining and generating a Pydantic model from JSON schema when response_format is provided in the configuration file.

Tools like [datamodel-code-generator](https://github.com/koxudaxi/datamodel-code-generator) exist for generating Pydantic models dynamically, we could use something like that.

Additional context

Only consideration is the feasibility of defining and generating a Pydantic model from JSON schema when response_format is provided in the configuration file. This functionality was discussed before in Pydantic, but implementing it was deferred at that time.

[ohdearquant]

@sternakt i like this, can you load validator from schema as well?

[marklysze]

Thanks @sternakt, also if there's an option for a helper function to apply response_format to an LLM config for a specific agent would be great. Particularly useful when a response format is for a specific agent and the llm config is shared amongst many agents.