mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-12-03 18:00:36 +00:00
reverting some formatting changes
This commit is contained in:
Omar Abdelwahab
parent
59793ac63b
commit
a23ee35b24
1 changed files with 25 additions and 63 deletions
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@ -26,7 +26,10 @@ from llama_stack.apis.agents.openai_responses import (
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OpenAIResponseOutputMessageMCPCall,
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OpenAIResponseOutputMessageWebSearchToolCall,
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)
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from llama_stack.apis.common.content_types import ImageContentItem, TextContentItem
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from llama_stack.apis.common.content_types import (
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ImageContentItem,
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TextContentItem,
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)
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from llama_stack.apis.inference import (
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OpenAIChatCompletionContentPartImageParam,
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OpenAIChatCompletionContentPartTextParam,
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@ -66,9 +69,7 @@ class ToolExecutor:
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) -> AsyncIterator[ToolExecutionResult]:
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tool_call_id = tool_call.id
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function = tool_call.function
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tool_kwargs = (
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json.loads(function.arguments) if function and function.arguments else {}
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)
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tool_kwargs = json.loads(function.arguments) if function and function.arguments else {}
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if not function or not tool_call_id or not function.name:
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yield ToolExecutionResult(sequence_number=sequence_number)
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@ -76,12 +77,7 @@ class ToolExecutor:
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# Emit progress events for tool execution start
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async for event_result in self._emit_progress_events(
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function.name,
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ctx,
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sequence_number,
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output_index,
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item_id,
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mcp_tool_to_server,
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function.name, ctx, sequence_number, output_index, item_id, mcp_tool_to_server
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):
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sequence_number = event_result.sequence_number
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yield event_result
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@ -97,10 +93,7 @@ class ToolExecutor:
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or (
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result
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and (
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(
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(error_code := getattr(result, "error_code", None))
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and error_code > 0
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)
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((error_code := getattr(result, "error_code", None)) and error_code > 0)
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or getattr(result, "error_message", None)
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)
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)
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@ -122,9 +115,7 @@ class ToolExecutor:
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final_output_message=output_message,
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final_input_message=input_message,
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citation_files=(
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metadata.get("citation_files")
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if result and (metadata := getattr(result, "metadata", None))
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else None
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metadata.get("citation_files") if result and (metadata := getattr(result, "metadata", None)) else None
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),
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)
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@ -153,10 +144,7 @@ class ToolExecutor:
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return []
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# Run all searches in parallel using gather
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search_tasks = [
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search_single_store(vid)
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for vid in response_file_search_tool.vector_store_ids
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]
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search_tasks = [search_single_store(vid) for vid in response_file_search_tool.vector_store_ids]
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all_results = await asyncio.gather(*search_tasks)
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# Flatten results
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@ -175,9 +163,7 @@ class ToolExecutor:
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chunk_text = result_item.content[0].text if result_item.content else ""
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# Get file_id from attributes if result_item.file_id is empty
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file_id = result_item.file_id or (
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result_item.attributes.get("document_id")
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if result_item.attributes
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else None
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result_item.attributes.get("document_id") if result_item.attributes else None
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)
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metadata_text = f"document_id: {file_id}, score: {result_item.score}"
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if result_item.attributes:
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@ -189,9 +175,7 @@ class ToolExecutor:
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content_items.append(TextContentItem(text=text_content))
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unique_files.add(file_id)
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content_items.append(
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TextContentItem(text="END of knowledge_search tool results.\n")
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)
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content_items.append(TextContentItem(text="END of knowledge_search tool results.\n"))
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citation_instruction = ""
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if unique_files:
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@ -226,9 +210,7 @@ class ToolExecutor:
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content=content_items, # type: ignore[arg-type]
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metadata={
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"document_ids": [r.file_id for r in search_results],
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"chunks": [
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r.content[0].text if r.content else "" for r in search_results
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],
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"chunks": [r.content[0].text if r.content else "" for r in search_results],
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"scores": [r.score for r in search_results],
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"citation_files": citation_files,
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},
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@ -339,11 +321,7 @@ class ToolExecutor:
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elif function_name == "knowledge_search":
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response_file_search_tool = (
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next(
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(
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t
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for t in ctx.response_tools
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if isinstance(t, OpenAIResponseInputToolFileSearch)
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),
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(t for t in ctx.response_tools if isinstance(t, OpenAIResponseInputToolFileSearch)),
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None,
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)
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if ctx.response_tools
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@ -389,39 +367,33 @@ class ToolExecutor:
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mcp_failed_event = OpenAIResponseObjectStreamResponseMcpCallFailed(
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sequence_number=sequence_number,
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)
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yield ToolExecutionResult(
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stream_event=mcp_failed_event, sequence_number=sequence_number
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)
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yield ToolExecutionResult(stream_event=mcp_failed_event, sequence_number=sequence_number)
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else:
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mcp_completed_event = (
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OpenAIResponseObjectStreamResponseMcpCallCompleted(
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mcp_completed_event = OpenAIResponseObjectStreamResponseMcpCallCompleted(
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sequence_number=sequence_number,
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)
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)
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yield ToolExecutionResult(
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stream_event=mcp_completed_event, sequence_number=sequence_number
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)
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elif function_name == "web_search":
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sequence_number += 1
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web_completion_event = (
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OpenAIResponseObjectStreamResponseWebSearchCallCompleted(
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web_completion_event = OpenAIResponseObjectStreamResponseWebSearchCallCompleted(
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item_id=item_id,
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output_index=output_index,
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sequence_number=sequence_number,
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)
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)
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yield ToolExecutionResult(
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stream_event=web_completion_event, sequence_number=sequence_number
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)
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elif function_name == "knowledge_search":
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sequence_number += 1
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file_completion_event = (
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OpenAIResponseObjectStreamResponseFileSearchCallCompleted(
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file_completion_event = OpenAIResponseObjectStreamResponseFileSearchCallCompleted(
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item_id=item_id,
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output_index=output_index,
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sequence_number=sequence_number,
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)
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)
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yield ToolExecutionResult(
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stream_event=file_completion_event, sequence_number=sequence_number
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)
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@ -454,11 +426,9 @@ class ToolExecutor:
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)
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if error_exc:
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message.error = str(error_exc)
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elif (
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result
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and (error_code := getattr(result, "error_code", None))
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and error_code > 0
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) or (result and getattr(result, "error_message", None)):
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elif (result and (error_code := getattr(result, "error_code", None)) and error_code > 0) or (
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result and getattr(result, "error_message", None)
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):
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ec = getattr(result, "error_code", "unknown")
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em = getattr(result, "error_message", "")
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message.error = f"Error (code {ec}): {em}"
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@ -478,11 +448,7 @@ class ToolExecutor:
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queries=[tool_kwargs.get("query", "")],
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status="completed",
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)
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if (
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result
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and (metadata := getattr(result, "metadata", None))
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and "document_ids" in metadata
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):
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if result and (metadata := getattr(result, "metadata", None)) and "document_ids" in metadata:
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message.results = []
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for i, doc_id in enumerate(metadata["document_ids"]):
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text = metadata["chunks"][i] if "chunks" in metadata else None
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@ -518,9 +484,7 @@ class ToolExecutor:
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url_value = f"data:image;base64,{item.image.data}"
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else:
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url_value = str(item.image.url) if item.image.url else ""
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part = OpenAIChatCompletionContentPartImageParam(
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image_url=OpenAIImageURL(url=url_value)
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)
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part = OpenAIChatCompletionContentPartImageParam(image_url=OpenAIImageURL(url=url_value))
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else:
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raise ValueError(f"Unknown result content type: {type(item)}")
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content_list.append(part)
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@ -532,8 +496,6 @@ class ToolExecutor:
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input_message = OpenAIToolMessageParam(content=msg_content, tool_call_id=tool_call_id) # type: ignore[arg-type]
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else:
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text = str(error_exc) if error_exc else "Tool execution failed"
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input_message = OpenAIToolMessageParam(
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content=text, tool_call_id=tool_call_id
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)
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input_message = OpenAIToolMessageParam(content=text, tool_call_id=tool_call_id)
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return message, input_message
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