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Try again to pass CI using different python and pre-commit versions

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Signed-off-by: Bill Murdock <bmurdock@redhat.com>
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Bill Murdock 2025-10-14 15:06:16 -04:00
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docs/docs/providers/openai_responses_limitations.mdx
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## Unresolved Issues
This document outlines known limitations and inconsistencies between Llama Stack's Responses API and OpenAI's Responses API. This comparison is based on OpenAI's API and reflects a comparison with the OpenAI APIs as of October 6, 2025.
This document outlines known limitations and inconsistencies between Llama Stack's Responses API and OpenAI's Responses API. This comparison is based on OpenAI's API and reflects a comparison with the OpenAI APIs as of October 6, 2025 (OpenAI's client version `openai==1.107`).
See the OpenAI [changelog](https://platform.openai.com/docs/changelog) for details of any new functionality that has been added since that date. Links to issues are included so readers can read about status, post comments, and/or subscribe for updates relating to any limitations that are of specific interest to them. We would also love any other feedback on any use-cases you try that do not work to help prioritize the pieces left to implement.
Please open new issues in the [meta-llama/llama-stack](https://github.com/meta-llama/llama-stack) GitHub repository with details of anything that does not work that does not already have an open issue.
@ -208,6 +208,16 @@ Sampling allows MCP tools to query the generative AI model. See the [MCP specifi
- If not, is there a reasonable way to make that work within the API as is? Or would the API need to change?
- Does this work in Llama Stack?
### Prompt Caching
**Status:** Unknown
OpenAI provides a [prompt caching](https://platform.openai.com/docs/guides/prompt-caching) mechanism in Responses that is enabled for its most recent models.
**Open Questions:**
- Does this work in Llama Stack?
- If not, is there a reasonable way to make that work for those inference providers that have this capability by passing through the provided `prompt_cache_key` to the inference provider?
- Is there a reasonable way to make that work for inference providers that don't build in this capability by doing some sort of caching at the Llama Stack layer?
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### Parallel Tool Calls