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feat: add MoonshotAI provider with Kimi-K2 model support#2211

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@zachmayerzachmayer commentedJul 15, 2025•
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This PR adds a new MoonshotAI provider for Kimi models.

Related PRs:

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  • Add MoonshotAIProvider with OpenAI-compatible API
  • Implements OpenAI-style interface with custom base URL (api.moonshot.ai)
  • Supports tool definitions but disables strict tool validation (as per MoonshotAI docs)
  • Add moonshotai:kimi-k2-0711-preview as known model
  • Configure to use OpenAIModel for compatibility
  • Add comprehensive tests for provider functionality
  • Update CLI and model name tests
  • Uses MOONSHOT_API_KEY environment variable

The provider follows the same pattern as other OpenAI-compatible providers like DeepSeek and Grok.

As requested by@DouweM, I've split the original large PR into 3 focused PRs for easier review.

@zachmayerzachmayer marked this pull request as draftJuly 16, 2025 14:55
@zachmayerzachmayer marked this pull request as ready for reviewJuly 16, 2025 15:36
@zachmayerzachmayer changed the titlefeat: add o3-pro, grok-4, kimi-k2 model namesfeat: add o3-pro, grok-4, kimi-k2Jul 16, 2025
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@DouweM@Kludex I think this is ready for review. I'd be happy to split it up into several PRs if you like (or squash the commits!)

@DouweMDouweM self-assigned thisJul 16, 2025
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@zachmayer Thanks Zach! As you suggested, can you please split this up into separate PRs so the more straightforward ones can be merged more quickly? Pretty commit history is not that important, we'll end up squashing on merge anyway.

Also, from theMoonshotAIProvider, "Please note that the current version of Kimi API does not support the tool_choice=required parameter." makes me think we'll need a new field onOpenAIModelProfile to stop sending that value in this case and prevent errors. They suggest "you can emphasize the use of a certain tool in the prompt to achieve a similar effect" as a workaround, so I wonder if the default "The final response which ends this conversation" description of the output tool that we require to be called is already sufficient.

Maybe we can keep this PR for the MoonshotAIProvider as I already started talking about it :)

- Add MoonshotAIProvider with OpenAI-compatible API- Implements OpenAI-style interface with custom base URL- Supports tool definitions but not strict tool validation- Add moonshotai:kimi-k2-0711-preview as known model- Configure to use OpenAIModel for compatibility- Add comprehensive tests for provider functionality- Update CLI and model name tests
@zachmayerzachmayerforce-pushed thefeat/add-kimi-grok-o3pro-clean branch from4c4ebf7 todcd7d87CompareJuly 17, 2025 14:13
@zachmayerzachmayer changed the titlefeat: add o3-pro, grok-4, kimi-k2feat: add MoonshotAI provider with Kimi-K2 model supportJul 17, 2025
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@zachmayer Thank you! In addition to these comments, can you please add some docs?

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PR Change Summary

Added a new MoonshotAI provider to support Kimi-K2 models, enhancing compatibility with OpenAI's API.

  • Introduced MoonshotAIProvider with OpenAI-compatible API
  • Implemented support for Kimi-K2 model
  • Added comprehensive tests for provider functionality
  • Updated CLI and model name tests

Modified Files

  • docs/models/openai.md
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I added a moonshot example to the open ai docs


# As the MoonshotAI API is OpenAI-compatible, let's assume we also need OpenAIJsonSchemaTransformer,
# unless json_schema_transformer is set explicitly.
# Also, MoonshotAI does not support strict tool definitions
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Is this actually the case or was it just a misinterpretation of thetool_choice=required thing? If so, we can drop this from the comment and drop the field

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Looking at their docs:

When you set response_format to {"type": "json_object"}, you must explicitly guide the model to output JSON-formatted content in the prompt and specify the exact format of the JSON, otherwise it may result in unexpected outcomes.

My reading of this is that they don't support strict: mode. You can ask it for a json object, but you need to verybally describe the fields you want in the object.

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oh hmmm, this parameter is different thanstrict for output schemas though. Now I'm not sure.

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Ah look like they don't support thejson_schemaresponse_format, justjson_object, so we can setsupports_json_object_output toTrue (they're bothFalse by default).

I don't see anything aboutstrict on tool definitions though, so I think we can drop that.

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Can you look at the merge conflict as well please?


# As the MoonshotAI API is OpenAI-compatible, let's assume we also need OpenAIJsonSchemaTransformer,
# unless json_schema_transformer is set explicitly.
# Also, MoonshotAI does not support strict tool definitions
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Ah look like they don't support thejson_schemaresponse_format, justjson_object, so we can setsupports_json_object_output toTrue (they're bothFalse by default).

I don't see anything aboutstrict on tool definitions though, so I think we can drop that.

)
from pydantic_ai.providers import Provider

MoonshotModelName = Literal[
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For consistency with the provider class:

Suggested change
MoonshotModelName=Literal[
MoonshotAIModelName=Literal[

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