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chore: refactor (chat)completions endpoints to use shared params struct (#3761)

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# What does this PR do?

Converts openai(_chat)_completions params to pydantic BaseModel to
reduce code duplication across all providers.

## Test Plan
CI









---
[//]: # (BEGIN SAPLING FOOTER)
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[ReviewStack](https://reviewstack.dev/llamastack/llama-stack/pull/3761).
* #3777
* __->__ #3761
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ehhuang 2025-10-10 15:46:34 -07:00 • committed by GitHub
parent 6954fe2274
commit 80d58ab519
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33 changed files with 599 additions and 890 deletions
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8
llama_stack/providers/inline/batches/reference/batches.py
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@ -22,6 +22,8 @@ from llama_stack.apis.files import Files, OpenAIFilePurpose
from llama_stack.apis.inference import (
Inference,
OpenAIAssistantMessageParam,
OpenAIChatCompletionRequest,
OpenAICompletionRequest,
OpenAIDeveloperMessageParam,
OpenAIMessageParam,
OpenAISystemMessageParam,
@ -606,7 +608,8 @@ class ReferenceBatchesImpl(Batches):
# TODO(SECURITY): review body for security issues
if request.url == "/v1/chat/completions":
request.body["messages"] = [convert_to_openai_message_param(msg) for msg in request.body["messages"]]
chat_response = await self.inference_api.openai_chat_completion(**request.body)
chat_params = OpenAIChatCompletionRequest(**request.body)
chat_response = await self.inference_api.openai_chat_completion(chat_params)
# this is for mypy, we don't allow streaming so we'll get the right type
assert hasattr(chat_response, "model_dump_json"), "Chat response must have model_dump_json method"
@ -620,7 +623,8 @@ class ReferenceBatchesImpl(Batches):
},
}
elif request.url == "/v1/completions":
completion_response = await self.inference_api.openai_completion(**request.body)
completion_params = OpenAICompletionRequest(**request.body)
completion_response = await self.inference_api.openai_completion(completion_params)
# this is for mypy, we don't allow streaming so we'll get the right type
assert hasattr(completion_response, "model_dump_json"), (