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feat: support configurate openai compatible stream tool call (#3467)
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Yeuoly
GitHub
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5b3133f9fc
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8f8e9de601
@ -170,13 +170,14 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
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features = []
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function_calling_type = credentials.get('function_calling_type', 'no_call')
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if function_calling_type == 'function_call':
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if function_calling_type in ['function_call']:
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features.append(ModelFeature.TOOL_CALL)
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endpoint_url = credentials["endpoint_url"]
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# if not endpoint_url.endswith('/'):
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# endpoint_url += '/'
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# if 'https://api.openai.com/v1/' == endpoint_url:
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# features.append(ModelFeature.STREAM_TOOL_CALL)
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elif function_calling_type in ['tool_call']:
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features.append(ModelFeature.MULTI_TOOL_CALL)
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stream_function_calling = credentials.get('stream_function_calling', 'supported')
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if stream_function_calling == 'supported':
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features.append(ModelFeature.STREAM_TOOL_CALL)
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vision_support = credentials.get('vision_support', 'not_support')
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if vision_support == 'support':
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@ -386,29 +387,37 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
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def increase_tool_call(new_tool_calls: list[AssistantPromptMessage.ToolCall]):
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def get_tool_call(tool_call_id: str):
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tool_call = next(
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(tool_call for tool_call in tools_calls if tool_call.id == tool_call_id), None
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)
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if not tool_call_id:
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return tools_calls[-1]
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tool_call = next((tool_call for tool_call in tools_calls if tool_call.id == tool_call_id), None)
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if tool_call is None:
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tool_call = AssistantPromptMessage.ToolCall(
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id='',
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type='function',
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id=tool_call_id,
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type="function",
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function=AssistantPromptMessage.ToolCall.ToolCallFunction(
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name='',
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arguments=''
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name="",
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arguments=""
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)
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)
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tools_calls.append(tool_call)
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return tool_call
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for new_tool_call in new_tool_calls:
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# get tool call
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tool_call = get_tool_call(new_tool_call.id)
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tool_call = get_tool_call(new_tool_call.function.name)
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# update tool call
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tool_call.id = new_tool_call.id
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tool_call.type = new_tool_call.type
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tool_call.function.name = new_tool_call.function.name
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tool_call.function.arguments += new_tool_call.function.arguments
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if new_tool_call.id:
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tool_call.id = new_tool_call.id
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if new_tool_call.type:
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tool_call.type = new_tool_call.type
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if new_tool_call.function.name:
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tool_call.function.name = new_tool_call.function.name
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if new_tool_call.function.arguments:
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tool_call.function.arguments += new_tool_call.function.arguments
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finish_reason = 'Unknown'
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for chunk in response.iter_lines(decode_unicode=True, delimiter=delimiter):
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if chunk:
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@ -438,7 +447,17 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
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delta = choice['delta']
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delta_content = delta.get('content')
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assistant_message_tool_calls = delta.get('tool_calls', None)
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assistant_message_tool_calls = None
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if 'tool_calls' in delta and credentials.get('function_calling_type', 'no_call') == 'tool_call':
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assistant_message_tool_calls = delta.get('tool_calls', None)
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elif 'function_call' in delta and credentials.get('function_calling_type', 'no_call') == 'function_call':
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assistant_message_tool_calls = [{
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'id': 'tool_call_id',
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'type': 'function',
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'function': delta.get('function_call', {})
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}]
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# assistant_message_function_call = delta.delta.function_call
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# extract tool calls from response
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@ -449,15 +468,13 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
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if delta_content is None or delta_content == '':
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continue
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# function_call = self._extract_response_function_call(assistant_message_function_call)
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# tool_calls = [function_call] if function_call else []
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# transform assistant message to prompt message
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assistant_prompt_message = AssistantPromptMessage(
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content=delta_content,
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tool_calls=tool_calls if assistant_message_tool_calls else []
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)
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# reset tool calls
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tool_calls = []
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full_assistant_content += delta_content
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elif 'text' in choice:
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choice_text = choice.get('text', '')
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@ -470,37 +487,36 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
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else:
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continue
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# check payload indicator for completion
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if finish_reason is not None:
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yield LLMResultChunk(
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model=model,
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prompt_messages=prompt_messages,
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delta=LLMResultChunkDelta(
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index=chunk_index,
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message=AssistantPromptMessage(
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tool_calls=tools_calls,
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),
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finish_reason=finish_reason
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)
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)
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yield create_final_llm_result_chunk(
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yield LLMResultChunk(
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model=model,
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prompt_messages=prompt_messages,
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delta=LLMResultChunkDelta(
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index=chunk_index,
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message=assistant_prompt_message,
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finish_reason=finish_reason
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)
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else:
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yield LLMResultChunk(
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model=model,
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prompt_messages=prompt_messages,
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delta=LLMResultChunkDelta(
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index=chunk_index,
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message=assistant_prompt_message,
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)
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)
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)
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chunk_index += 1
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if tools_calls:
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yield LLMResultChunk(
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model=model,
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prompt_messages=prompt_messages,
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delta=LLMResultChunkDelta(
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index=chunk_index,
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message=AssistantPromptMessage(
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tool_calls=tools_calls,
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content=""
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),
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)
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)
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yield create_final_llm_result_chunk(
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index=chunk_index,
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message=AssistantPromptMessage(content=""),
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finish_reason=finish_reason
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)
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def _handle_generate_response(self, model: str, credentials: dict, response: requests.Response,
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prompt_messages: list[PromptMessage]) -> LLMResult:
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@ -757,13 +773,13 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
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if response_tool_calls:
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for response_tool_call in response_tool_calls:
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function = AssistantPromptMessage.ToolCall.ToolCallFunction(
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name=response_tool_call["function"]["name"],
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arguments=response_tool_call["function"]["arguments"]
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name=response_tool_call.get("function", {}).get("name", ""),
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arguments=response_tool_call.get("function", {}).get("arguments", "")
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)
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tool_call = AssistantPromptMessage.ToolCall(
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id=response_tool_call["id"],
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type=response_tool_call["type"],
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id=response_tool_call.get("id", ""),
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type=response_tool_call.get("type", ""),
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function=function
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)
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tool_calls.append(tool_call)
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@ -781,12 +797,12 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
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tool_call = None
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if response_function_call:
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function = AssistantPromptMessage.ToolCall.ToolCallFunction(
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name=response_function_call['name'],
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arguments=response_function_call['arguments']
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name=response_function_call.get('name', ''),
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arguments=response_function_call.get('arguments', '')
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)
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tool_call = AssistantPromptMessage.ToolCall(
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id=response_function_call['name'],
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id=response_function_call.get('id', ''),
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type="function",
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function=function
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)
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@ -86,14 +86,32 @@ model_credential_schema:
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default: no_call
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options:
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- value: function_call
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label:
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en_US: Function Call
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zh_Hans: Function Call
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- value: tool_call
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label:
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en_US: Tool Call
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zh_Hans: Tool Call
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- value: no_call
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label:
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en_US: Not Support
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zh_Hans: 不支持
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- variable: stream_function_calling
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show_on:
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- variable: __model_type
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value: llm
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label:
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en_US: Stream function calling
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type: select
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required: false
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default: not_supported
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options:
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- value: supported
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label:
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en_US: Support
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zh_Hans: 支持
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# - value: tool_call
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# label:
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# en_US: Tool Call
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# zh_Hans: Tool Call
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- value: no_call
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- value: not_supported
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label:
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en_US: Not Support
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zh_Hans: 不支持
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