MoonshotAI / MoonshotAI/kimi-code
MS Foundry + Kimi Code 2.7 - 400 Unrecognized request argument supplied: prompt_cache_key
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- Dominant language
- TypeScript
- Stars
- 7.5k
- Forks
- 1.2k
- Avg merge
- 11h 53m
- Merged PRs (30d)
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Description
What version of Kimi Code is running?
0.32.0
Which open platform/subscription were you using?
.
Which model were you using?
kimi-k2.7-code
What platform is your computer?
Linux 5.15.167.4-microsoft-standard-WSL2 x86_64 x86_64
What issue are you seeing?
Kimi Code CLI sends prompt_cache_key in a request to an OpenAI-compatible endpoint, and the endpoint rejects it with HTTP 400: Unrecognized request argument supplied: prompt_cache_key.
Config (redacted)
default_model = "azure/kimi-k2.7-code"
[providers.azure-foundry]
type = "openai"
base_url = "https://<redacted>/openai/v1"
api_key = "<redacted>"
[providers.azure-foundry.custom_headers]
api-key = "<redacted>"
[models."azure/kimi-k2.7-code"]
provider = "azure-foundry"
model = "Kimi-K2.7-Code"
max_context_size = 262144
capabilities = [ "thinking", "tool_use", "image_in" ]
reasoning_key = "reasoning_content"
[thinking]
enabled = false
### What steps can reproduce the bug?
### Steps to reproduce
1. Configure provider/model as above.
2. Start a session (simple prompt like test).
3. First LLM turn fails.
### What is the expected behavior?
_No response_
### Additional information
_No response_
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by tracing how the Kimi Code CLI builds the first request for the configured OpenAI-compatible provider and where prompt_cache_key is added. Reproduce the failure with the supplied Azure Foundry configuration, then verify that the session starts successfully without sending an argument the endpoint rejects.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- typescript
- Domain
- api, cli
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 65/100