mirror of
https://github.com/meta-llama/llama-stack.git
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fix(responses): fix subtle bugs in non-function tool calling (#3817)
We were generating "FunctionToolCall" items even for MCP (and file-search, etc.) server-side calls. ID mismatches, etc. galore.
This commit is contained in:
Ashwin Bharambe
GitHub
parent
d709eeb33f
commit
0a96a7faa5
12 changed files with 10660 additions and 51 deletions
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@ -44,8 +44,11 @@ from llama_stack.apis.agents.openai_responses import (
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OpenAIResponseObjectStreamResponseRefusalDone,
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OpenAIResponseOutput,
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OpenAIResponseOutputMessageContentOutputText,
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OpenAIResponseOutputMessageFileSearchToolCall,
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OpenAIResponseOutputMessageFunctionToolCall,
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OpenAIResponseOutputMessageMCPCall,
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OpenAIResponseOutputMessageMCPListTools,
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OpenAIResponseOutputMessageWebSearchToolCall,
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OpenAIResponseText,
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OpenAIResponseUsage,
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OpenAIResponseUsageInputTokensDetails,
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@ -177,6 +180,7 @@ class StreamingResponseOrchestrator:
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# (some providers don't support non-empty response_format when tools are present)
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response_format = None if self.ctx.response_format.type == "text" else self.ctx.response_format
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logger.debug(f"calling openai_chat_completion with tools: {self.ctx.chat_tools}")
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params = OpenAIChatCompletionRequestWithExtraBody(
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model=self.ctx.model,
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messages=messages,
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@ -613,19 +617,22 @@ class StreamingResponseOrchestrator:
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# Emit output_item.added event for the new function call
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self.sequence_number += 1
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function_call_item = OpenAIResponseOutputMessageFunctionToolCall(
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arguments="", # Will be filled incrementally via delta events
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call_id=tool_call.id or "",
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name=tool_call.function.name if tool_call.function else "",
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id=tool_call_item_id,
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status="in_progress",
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)
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yield OpenAIResponseObjectStreamResponseOutputItemAdded(
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response_id=self.response_id,
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item=function_call_item,
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output_index=len(output_messages),
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sequence_number=self.sequence_number,
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)
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is_mcp_tool = tool_call.function.name and tool_call.function.name in self.mcp_tool_to_server
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if not is_mcp_tool and tool_call.function.name not in ["web_search", "knowledge_search"]:
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# for MCP tools (and even other non-function tools) we emit an output message item later
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function_call_item = OpenAIResponseOutputMessageFunctionToolCall(
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arguments="", # Will be filled incrementally via delta events
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call_id=tool_call.id or "",
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name=tool_call.function.name if tool_call.function else "",
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id=tool_call_item_id,
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status="in_progress",
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)
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yield OpenAIResponseObjectStreamResponseOutputItemAdded(
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response_id=self.response_id,
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item=function_call_item,
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output_index=len(output_messages),
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sequence_number=self.sequence_number,
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)
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# Stream tool call arguments as they arrive (differentiate between MCP and function calls)
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if tool_call.function and tool_call.function.arguments:
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@ -806,6 +813,35 @@ class StreamingResponseOrchestrator:
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if not matching_item_id:
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matching_item_id = f"tc_{uuid.uuid4()}"
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self.sequence_number += 1
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if tool_call.function.name and tool_call.function.name in self.mcp_tool_to_server:
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item = OpenAIResponseOutputMessageMCPCall(
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arguments="",
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name=tool_call.function.name,
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id=matching_item_id,
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server_label=self.mcp_tool_to_server[tool_call.function.name].server_label,
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status="in_progress",
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)
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elif tool_call.function.name == "web_search":
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item = OpenAIResponseOutputMessageWebSearchToolCall(
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id=matching_item_id,
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status="in_progress",
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)
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elif tool_call.function.name == "knowledge_search":
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item = OpenAIResponseOutputMessageFileSearchToolCall(
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id=matching_item_id,
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status="in_progress",
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)
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else:
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raise ValueError(f"Unsupported tool call: {tool_call.function.name}")
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yield OpenAIResponseObjectStreamResponseOutputItemAdded(
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response_id=self.response_id,
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item=item,
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output_index=len(output_messages),
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sequence_number=self.sequence_number,
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)
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# Execute tool call with streaming
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tool_call_log = None
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tool_response_message = None
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@ -1064,7 +1100,11 @@ class StreamingResponseOrchestrator:
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self.sequence_number += 1
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yield OpenAIResponseObjectStreamResponseOutputItemAdded(
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response_id=self.response_id,
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item=mcp_list_message,
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item=OpenAIResponseOutputMessageMCPListTools(
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id=mcp_list_message.id,
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server_label=mcp_list_message.server_label,
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tools=[],
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),
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output_index=len(output_messages) - 1,
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sequence_number=self.sequence_number,
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)
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@ -93,7 +93,7 @@ class ToolExecutor:
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# Build result messages from tool execution
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output_message, input_message = await self._build_result_messages(
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function, tool_call_id, tool_kwargs, ctx, error_exc, result, has_error, mcp_tool_to_server
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function, tool_call_id, item_id, tool_kwargs, ctx, error_exc, result, has_error, mcp_tool_to_server
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)
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# Yield the final result
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@ -356,6 +356,7 @@ class ToolExecutor:
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self,
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function,
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tool_call_id: str,
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item_id: str,
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tool_kwargs: dict,
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ctx: ChatCompletionContext,
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error_exc: Exception | None,
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@ -375,7 +376,7 @@ class ToolExecutor:
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)
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message = OpenAIResponseOutputMessageMCPCall(
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id=tool_call_id,
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id=item_id,
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arguments=function.arguments,
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name=function.name,
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server_label=mcp_tool_to_server[function.name].server_label,
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@ -389,14 +390,14 @@ class ToolExecutor:
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else:
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if function.name == "web_search":
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message = OpenAIResponseOutputMessageWebSearchToolCall(
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id=tool_call_id,
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id=item_id,
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status="completed",
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)
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if has_error:
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message.status = "failed"
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elif function.name == "knowledge_search":
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message = OpenAIResponseOutputMessageFileSearchToolCall(
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id=tool_call_id,
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id=item_id,
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queries=[tool_kwargs.get("query", "")],
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status="completed",
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)
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@ -0,0 +1,881 @@
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{
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"test_id": null,
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"request": {
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"method": "POST",
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"url": "https://api.openai.com/v1/v1/models",
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"headers": {},
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"body": {},
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"endpoint": "/v1/models",
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"model": ""
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},
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"response": {
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"body": [
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "gpt-4-0613",
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"created": 1686588896,
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"object": "model",
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"owned_by": "openai"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "gpt-4",
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"created": 1687882411,
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"object": "model",
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"owned_by": "openai"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "gpt-3.5-turbo",
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"created": 1677610602,
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"object": "model",
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"owned_by": "openai"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "gpt-5-search-api-2025-10-14",
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"created": 1760043960,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "gpt-realtime-mini",
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"created": 1759517133,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "gpt-realtime-mini-2025-10-06",
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"created": 1759517175,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "sora-2",
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"created": 1759708615,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "sora-2-pro",
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"created": 1759708663,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "davinci-002",
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"created": 1692634301,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "babbage-002",
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"created": 1692634615,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "gpt-3.5-turbo-instruct",
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"created": 1692901427,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "gpt-3.5-turbo-instruct-0914",
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"created": 1694122472,
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},
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}
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "dall-e-2",
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"created": 1698798177,
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"object": "model",
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"owned_by": "system"
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}
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{
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"created": 1698957206,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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{
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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}
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},
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{
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{
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "text-embedding-3-large",
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"created": 1705953180,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"created": 1706037612,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "gpt-4-turbo-preview",
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"created": 1706037777,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "gpt-3.5-turbo-0125",
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"created": 1706048358,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "gpt-4-turbo",
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"created": 1712361441,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "gpt-4o",
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"created": 1715367049,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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|
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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|
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||||
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|
||||
"object": "model",
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||||
}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
|
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"id": "gpt-4o-mini",
|
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"created": 1721172741,
|
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"object": "model",
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"owned_by": "system"
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||||
}
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},
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||||
{
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"__type__": "openai.types.model.Model",
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"__data__": {
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||||
"id": "gpt-4o-2024-08-06",
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||||
"created": 1722814719,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "chatgpt-4o-latest",
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"created": 1723515131,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "o1-mini-2024-09-12",
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"created": 1725648979,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "o1-mini",
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"created": 1725649008,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"id": "gpt-4o-realtime-preview-2024-10-01",
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"created": 1727131766,
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"object": "model",
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"owned_by": "system"
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}
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},
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{
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"__type__": "openai.types.model.Model",
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"__data__": {
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"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-dd48d347f0ab",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
"content": " public",
|
||||
"function_call": null,
|
||||
"refusal": null,
|
||||
"role": "assistant",
|
||||
"tool_calls": null
|
||||
},
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-dd48d347f0ab",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
"content": " method",
|
||||
"function_call": null,
|
||||
"refusal": null,
|
||||
"role": "assistant",
|
||||
"tool_calls": null
|
||||
},
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-dd48d347f0ab",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
"content": " named",
|
||||
"function_call": null,
|
||||
"refusal": null,
|
||||
"role": "assistant",
|
||||
"tool_calls": null
|
||||
},
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-dd48d347f0ab",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
"content": " greet",
|
||||
"function_call": null,
|
||||
"refusal": null,
|
||||
"role": "assistant",
|
||||
"tool_calls": null
|
||||
},
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-dd48d347f0ab",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
"content": "_every",
|
||||
"function_call": null,
|
||||
"refusal": null,
|
||||
"role": "assistant",
|
||||
"tool_calls": null
|
||||
},
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-dd48d347f0ab",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
"content": "one",
|
||||
"function_call": null,
|
||||
"refusal": null,
|
||||
"role": "assistant",
|
||||
"tool_calls": null
|
||||
},
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-dd48d347f0ab",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
"content": " with",
|
||||
"function_call": null,
|
||||
"refusal": null,
|
||||
"role": "assistant",
|
||||
"tool_calls": null
|
||||
},
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-dd48d347f0ab",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
"content": " two",
|
||||
"function_call": null,
|
||||
"refusal": null,
|
||||
"role": "assistant",
|
||||
"tool_calls": null
|
||||
},
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-dd48d347f0ab",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
"content": " parameters",
|
||||
"function_call": null,
|
||||
"refusal": null,
|
||||
"role": "assistant",
|
||||
"tool_calls": null
|
||||
},
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-dd48d347f0ab",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
"content": "\"}",
|
||||
"function_call": null,
|
||||
"refusal": null,
|
||||
"role": "assistant",
|
||||
"tool_calls": null
|
||||
},
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-dd48d347f0ab",
|
||||
"choices": [
|
||||
{
|
||||
"delta": {
|
||||
"content": "",
|
||||
"function_call": null,
|
||||
"refusal": null,
|
||||
"role": "assistant",
|
||||
"tool_calls": null
|
||||
},
|
||||
"finish_reason": "stop",
|
||||
"index": 0,
|
||||
"logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
|
||||
"__data__": {
|
||||
"id": "rec-dd48d347f0ab",
|
||||
"choices": [],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "chat.completion.chunk",
|
||||
"service_tier": null,
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": {
|
||||
"completion_tokens": 31,
|
||||
"prompt_tokens": 106,
|
||||
"total_tokens": 137,
|
||||
"completion_tokens_details": null,
|
||||
"prompt_tokens_details": null
|
||||
}
|
||||
}
|
||||
}
|
||||
],
|
||||
"is_streaming": true
|
||||
},
|
||||
"id_normalization_mapping": {}
|
||||
}
|
||||
|
|
@ -11,7 +11,6 @@ from llama_stack_client.lib.agents.agent import Agent
|
|||
from llama_stack_client.lib.agents.turn_events import StepCompleted, StepProgress, ToolCallIssuedDelta
|
||||
|
||||
from llama_stack import LlamaStackAsLibraryClient
|
||||
from llama_stack.core.datatypes import AuthenticationRequiredError
|
||||
|
||||
AUTH_TOKEN = "test-token"
|
||||
|
||||
|
|
@ -82,9 +81,11 @@ def test_mcp_invocation(llama_stack_client, text_model_id, mcp_server):
|
|||
"server_label": test_toolgroup_id,
|
||||
"require_approval": "never",
|
||||
"allowed_tools": [tool.name for tool in tools_list],
|
||||
"headers": {
|
||||
"Authorization": f"Bearer {AUTH_TOKEN}",
|
||||
},
|
||||
}
|
||||
]
|
||||
|
||||
agent = Agent(
|
||||
client=llama_stack_client,
|
||||
model=text_model_id,
|
||||
|
|
@ -111,47 +112,22 @@ def test_mcp_invocation(llama_stack_client, text_model_id, mcp_server):
|
|||
extra_headers=auth_headers,
|
||||
)
|
||||
)
|
||||
|
||||
events = [chunk.event for chunk in chunks]
|
||||
|
||||
final_response = next((chunk.response for chunk in reversed(chunks) if chunk.response), None)
|
||||
assert final_response is not None
|
||||
|
||||
issued_calls = [
|
||||
event for event in events if isinstance(event, StepProgress) and isinstance(event.delta, ToolCallIssuedDelta)
|
||||
]
|
||||
assert issued_calls and issued_calls[0].delta.tool_name == "greet_everyone"
|
||||
assert issued_calls
|
||||
|
||||
assert issued_calls[-1].delta.tool_name == "greet_everyone"
|
||||
|
||||
tool_events = [
|
||||
event for event in events if isinstance(event, StepCompleted) and event.step_type == "tool_execution"
|
||||
]
|
||||
assert tool_events and tool_events[0].result.tool_calls[0].tool_name == "greet_everyone"
|
||||
assert tool_events
|
||||
assert tool_events[-1].result.tool_calls[0].tool_name == "greet_everyone"
|
||||
|
||||
assert "hello" in final_response.output_text.lower()
|
||||
|
||||
# when streaming, we currently don't check auth headers upfront and fail the request
|
||||
# early. but we should at least be generating a 401 later in the process.
|
||||
response_stream = agent.create_turn(
|
||||
session_id=session_id,
|
||||
messages=[
|
||||
{
|
||||
"type": "message",
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "input_text",
|
||||
"text": "What is the boiling point of polyjuice? Use tools to answer.",
|
||||
}
|
||||
],
|
||||
}
|
||||
],
|
||||
stream=True,
|
||||
)
|
||||
if isinstance(llama_stack_client, LlamaStackAsLibraryClient):
|
||||
with pytest.raises(AuthenticationRequiredError):
|
||||
for _ in response_stream:
|
||||
pass
|
||||
else:
|
||||
error_chunks = [chunk for chunk in response_stream if "error" in chunk.model_dump()]
|
||||
assert len(error_chunks) == 1
|
||||
chunk = error_chunks[0].model_dump()
|
||||
assert "Unauthorized" in chunk["error"]["message"]
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue