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

# 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)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
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[ReviewStack](https://reviewstack.dev/llamastack/llama-stack/pull/3761).
* #3777
* __->__ #3761

docs/openapi_generator/pyopenapi/generator.py

@@ -23,6 +23,7 @@ from llama_stack.strong_typing.inspection import (
     is_generic_list,
     is_type_optional,
     is_type_union,
+    is_unwrapped_body_param,
     unwrap_generic_list,
     unwrap_optional_type,
     unwrap_union_types,
@@ -769,24 +770,30 @@ class Generator:
             first = next(iter(op.request_params))
             request_name, request_type = first
 
-            op_name = "".join(word.capitalize() for word in op.name.split("_"))
-            request_name = f"{op_name}Request"
-            fields = [
-                (
-                    name,
-                    type_,
-                )
-                for name, type_ in op.request_params
-            ]
-            request_type = make_dataclass(
-                request_name,
-                fields,
-                namespace={
-                    "__doc__": create_docstring_for_request(
-                        request_name, fields, doc_params
+            # Special case: if there's a single parameter with Body(embed=False) that's a BaseModel,
+            # unwrap it to show the flat structure in the OpenAPI spec
+            # Example: openai_chat_completion()
+            if (len(op.request_params) == 1 and is_unwrapped_body_param(request_type)):
+                pass
+            else:
+                op_name = "".join(word.capitalize() for word in op.name.split("_"))
+                request_name = f"{op_name}Request"
+                fields = [
+                    (
+                        name,
+                        type_,
                     )
-                },
-            )
+                    for name, type_ in op.request_params
+                ]
+                request_type = make_dataclass(
+                    request_name,
+                    fields,
+                    namespace={
+                        "__doc__": create_docstring_for_request(
+                            request_name, fields, doc_params
+                        )
+                    },
+                )
 
             requestBody = RequestBody(
                 content={

docs/openapi_generator/pyopenapi/utility.py

@@ -8,10 +8,11 @@ import json
 import typing
 import inspect
 from pathlib import Path
-from typing import TextIO
-from typing import Any, List, Optional, Union, get_type_hints, get_origin, get_args
+from typing import Any, List, Optional, TextIO, Union, get_type_hints, get_origin, get_args
 
+from pydantic import BaseModel
 from llama_stack.strong_typing.schema import object_to_json, StrictJsonType
+from llama_stack.strong_typing.inspection import is_unwrapped_body_param
 from llama_stack.core.resolver import api_protocol_map
 
 from .generator import Generator
@@ -205,6 +206,14 @@ def _validate_has_return_in_docstring(method) -> str | None:
 def _validate_has_params_in_docstring(method) -> str | None:
     source = inspect.getsource(method)
     sig = inspect.signature(method)
+
+    params_list = [p for p in sig.parameters.values() if p.name != "self"]
+    if len(params_list) == 1:
+        param = params_list[0]
+        param_type = param.annotation
+        if is_unwrapped_body_param(param_type):
+            return
+
     # Only check if the method has more than one parameter
     if len(sig.parameters) > 1 and ":param" not in source:
         return "does not have a ':param' in its docstring"