update

app/core/runner/thread_runner.py

@@ -159,9 +159,9 @@ class ThreadRunner:
             temperature=run.temperature,
             top_p=run.top_p,
             response_format=run.response_format,
-            parallel_tool_calls=run.parallel_tool_calls,
-            audio=run.audio,
-            modalities=run.modalities,
+            # parallel_tool_calls=run.parallel_tool_calls,
+            # audio=run.audio,
+            # modalities=run.modalities,
         )
 
         # create message callback

app/models/run.py

@@ -93,9 +93,9 @@ class RunBase(BaseModel):
     usage: Optional[dict] = Field(default=None, sa_column=Column(JSON))  # 调用使用情况
     temperature: Optional[float] = Field(default=None)  # 温度
     top_p: Optional[float] = Field(default=None)  # top_p
-    parallel_tool_calls: bool = Field(default=False)  # parallel_tool_calls
-    audio: Optional[ChatCompletionAudioParam] = Field(default=None)  # audio
-    modalities: Optional[List[ChatCompletionModality]] = Field(default=None)
+    # parallel_tool_calls: bool = Field(default=False)  # parallel_tool_calls
+    # audio: Optional[ChatCompletionAudioParam] = Field(default=None)  # audio
+    # modalities: Optional[List[ChatCompletionModality]] = Field(default=None)
 
 
 class Run(RunBase, PrimaryKeyMixin, TimeStampMixin, table=True):
@@ -132,9 +132,9 @@ class RunCreate(BaseModel):
     tool_choice: Optional[str] = Field(default=None)  # 工具选择
     temperature: Optional[float] = Field(default=None)  # 温度
     top_p: Optional[float] = Field(default=None)  # top_p
-    parallel_tool_calls: bool = Field(default=False)  # parallel_tool_calls
-    audio: Optional[ChatCompletionAudioParam] = Field(default=None)  # audio
-    modalities: Optional[List[ChatCompletionModality]] = Field(default=None)
+    # parallel_tool_calls: bool = Field(default=False)  # parallel_tool_calls
+    # audio: Optional[ChatCompletionAudioParam] = Field(default=None)  # audio
+    # modalities: Optional[List[ChatCompletionModality]] = Field(default=None)
 
     @model_validator(mode="before")
     def model_validator(cls, data: Any):