Python: [Feature]: Support prompt cache breakpoints for GPT 5.6 models

[cecheta]

Description

The GPT-5.6 models support a new prompt_cache_breakpoint parameter that explicitly sets breakpoints for where prompt prefixes should be saved to the cache. This is important for the newer models, as cache writes now cost.
https://developers.openai.com/api/docs/guides/prompt-caching#prompt-cache-breakpoints

Code Sample

Perhaps something like this.

Content.from_text(
  "Text input",
  additional_properties={
    "prompt_cache_breakpoint": {
      "mode": "explicit"
    }
  }
)

Language/SDK

Python

[Mordris]

I'd like to pick this up if no one's already on it.

Before opening a PR I looked at how the OpenAI clients assemble requests, and there are a couple of design choices worth settling first.

Block-level prompt_cache_breakpoint: content parts are built in _prepare_content_for_openai, which doesn't currently carry arbitrary Content metadata onto the outgoing part, so the additional_properties={"prompt_cache_breakpoint": {...}} form from the description would be dropped today. There's already a precedent for the pattern that would make it work: detail, file_id, and filename are read from content.additional_properties and set on the part. The low-footprint option is to read prompt_cache_breakpoint the same way and attach it to the blocks each API accepts it on (text, image, audio and file parts for Chat Completions; input_text/input_image/input_file for Responses). The alternative is a first-class field on Content. Do you have a preference between the additional_properties route and a typed field?

Request-level prompt_cache_options ({"mode": "implicit" | "explicit", "ttl": "30m"}): this reads as a natural sibling to the existing prompt_cache_key / prompt_cache_retention on OpenAIChatOptions, and _prepare_options already forwards options through, so it should be a small addition.

SDK floor: the typed params landed in openai==2.45.0, and the package currently pins openai>=2.25.0,<3, so the request-level option would need the floor bumped to >=2.45.0.

I'd cover both the Responses and Chat Completions clients, add unit tests asserting the params reach the request payload, and validate against the gpt-5.6 models. Happy to build whatever shape you land on.