API: Add tool_choice support and fix tool_calls spec compliance

extensions/openai/completions.py

@@ -218,6 +218,10 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p
     if 'tools' in body and body['tools'] is not None and isinstance(body['tools'], list) and len(body['tools']) > 0:
         tools = validateTools(body['tools'])  # raises InvalidRequestError if validation fails
 
+    tool_choice = body.get('tool_choice', None)
+    if tool_choice == "none":
+        tools = None  # Disable tool detection entirely
+
     messages = body['messages']
     for m in messages:
         if 'role' not in m:
@@ -367,6 +371,12 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p
     end_last_tool_call = 0
     supported_tools = [x["function"]["name"] for x in tools] if tools is not None else None
 
+    # Filter supported_tools when tool_choice specifies a particular function
+    if supported_tools and isinstance(tool_choice, dict):
+        specified_func = tool_choice.get("function", {}).get("name")
+        if specified_func and specified_func in supported_tools:
+            supported_tools = [specified_func]
+
     for a in generator:
         answer = a['internal'][-1][1]
 
@@ -375,11 +385,17 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p
             if len(tool_call) > 0:
                 for tc in tool_call:
                     tc["id"] = getToolCallId()
-                    tc["index"] = len(tool_calls)
+                    if stream:
+                        tc["index"] = len(tool_calls)
                     tc["function"]["arguments"] = json.dumps(tc["function"]["arguments"])
                     tool_calls.append(tc)
                 end_last_tool_call = len(answer)
 
+        # Stop generation before streaming content if tool_calls were detected,
+        # so that raw tool markup is not sent as content deltas.
+        if len(tool_calls) > 0:
+            break
+
         if stream:
             len_seen = len(seen_content)
             new_content = answer[len_seen:]
@@ -394,10 +410,6 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p
             seen_content = answer
             yield chunk
 
-        # stop generation if tool_calls were generated previously
-        if len(tool_calls) > 0:
-            break
-
     token_count = shared.model.last_prompt_token_count if hasattr(shared.model, 'last_prompt_token_count') else 0
     completion_token_count = len(encode(answer)[0])
     stop_reason = "stop"
@@ -441,7 +453,7 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p
             resp_list: [{
                 "index": 0,
                 "finish_reason": stop_reason,
-                "message": {"role": "assistant", "refusal": None, "content": answer, **({"tool_calls": tool_calls} if tool_calls else {})},
+                "message": {"role": "assistant", "refusal": None, "content": None if tool_calls else answer, **({"tool_calls": tool_calls} if tool_calls else {})},
                 "logprobs": None,
             }],
             "usage": {

extensions/openai/typing.py

@@ -150,6 +150,7 @@ class ChatCompletionRequestParams(BaseModel):
     function_call: str | dict | None = Field(default=None, description="Unused parameter.")
     functions: List[dict] | None = Field(default=None, description="Unused parameter.")
     tools: List[dict] | None = Field(default=None, description="Tools signatures passed via MCP.")
+    tool_choice: str | dict | None = Field(default=None, description="Controls tool use: 'auto', 'none', 'required', or {\"type\": \"function\", \"function\": {\"name\": \"...\"}}.")
     logit_bias: dict | None = None
     max_tokens: int | None = None
     n: int | None = Field(default=1, description="Unused parameter.")