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https://github.com/open-webui/open-webui.git
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Fix Kimi tool-call continuation reasoning
This commit is contained in:
Safzan Pirani
parent
f162d4de90
commit
2383e94985
3 changed files with 283 additions and 3 deletions
158
backend/open_webui/test/util/test_misc.py
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158
backend/open_webui/test/util/test_misc.py
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@ -0,0 +1,158 @@
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from open_webui.utils.misc import add_reasoning_content_to_tool_messages
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class TestAddReasoningContentToToolMessages:
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def test_adds_reasoning_content_for_kimi_tool_messages(self):
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messages = [
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{
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'role': 'assistant',
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'content': '<think>Need to search.</think>',
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'tool_calls': [
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{
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'id': 'call_123',
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'type': 'function',
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'function': {'name': 'search_web', 'arguments': '{"query":"Rakhi Kaag"}'},
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}
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],
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},
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{'role': 'tool', 'tool_call_id': 'call_123', 'content': 'Search results'},
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]
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output = [
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{
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'type': 'reasoning',
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'summary': [{'type': 'output_text', 'text': 'Need to search.'}],
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},
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{
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'type': 'function_call',
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'call_id': 'call_123',
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'name': 'search_web',
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'arguments': '{"query":"Rakhi Kaag"}',
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},
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{'type': 'function_call_output', 'call_id': 'call_123', 'output': []},
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]
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adjusted = add_reasoning_content_to_tool_messages(messages, output, 'kimi-k2.6')
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assert adjusted[0]['reasoning_content'] == 'Need to search.'
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assert adjusted[1] == messages[1]
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def test_scopes_reasoning_to_matching_assistant_message(self):
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messages = [
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{
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'role': 'assistant',
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'content': '<think>Need to search the web.</think>',
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'tool_calls': [
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{
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'id': 'call_1',
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'type': 'function',
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'function': {'name': 'search_web', 'arguments': '{"query":"Rakhi Kaag"}'},
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}
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],
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},
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{'role': 'tool', 'tool_call_id': 'call_1', 'content': 'First search results'},
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{
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'role': 'assistant',
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'content': '<think>Need to search notes.</think>',
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'tool_calls': [
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{
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'id': 'call_2',
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'type': 'function',
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'function': {'name': 'search_notes', 'arguments': '{"query":"Rakhi Kaag"}'},
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}
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],
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},
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]
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output = [
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{
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'type': 'reasoning',
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'summary': [{'type': 'output_text', 'text': 'Need to search the web.'}],
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},
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{
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'type': 'function_call',
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'call_id': 'call_1',
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'name': 'search_web',
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'arguments': '{"query":"Rakhi Kaag"}',
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},
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{'type': 'function_call_output', 'call_id': 'call_1', 'output': []},
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{
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'type': 'reasoning',
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'summary': [{'type': 'output_text', 'text': 'Need to search notes.'}],
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},
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{
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'type': 'function_call',
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'call_id': 'call_2',
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'name': 'search_notes',
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'arguments': '{"query":"Rakhi Kaag"}',
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},
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{'type': 'function_call_output', 'call_id': 'call_2', 'output': []},
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]
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adjusted = add_reasoning_content_to_tool_messages(messages, output, 'kimi-k2.6')
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assert adjusted[0]['reasoning_content'] == 'Need to search the web.'
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assert adjusted[2]['reasoning_content'] == 'Need to search notes.'
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def test_leaves_non_kimi_models_unchanged(self):
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messages = [
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{
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'role': 'assistant',
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'content': '<think>Need to search.</think>',
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'tool_calls': [
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{
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'id': 'call_123',
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'type': 'function',
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'function': {'name': 'search_web', 'arguments': '{"query":"Rakhi Kaag"}'},
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}
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],
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}
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]
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output = [
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{
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'type': 'reasoning',
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'summary': [{'type': 'output_text', 'text': 'Need to search.'}],
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},
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{
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'type': 'function_call',
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'call_id': 'call_123',
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'name': 'search_web',
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'arguments': '{"query":"Rakhi Kaag"}',
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},
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{'type': 'function_call_output', 'call_id': 'call_123', 'output': []},
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]
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adjusted = add_reasoning_content_to_tool_messages(messages, output, 'gpt-4.1')
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assert adjusted == messages
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def test_keeps_existing_reasoning_content(self):
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messages = [
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{
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'role': 'assistant',
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'content': '<think>Need to search.</think>',
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'reasoning_content': 'Existing reasoning',
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'tool_calls': [
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{
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'id': 'call_123',
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'type': 'function',
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'function': {'name': 'search_web', 'arguments': '{"query":"Rakhi Kaag"}'},
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}
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],
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}
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]
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output = [
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{
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'type': 'reasoning',
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'summary': [{'type': 'output_text', 'text': 'Need to search.'}],
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},
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{
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'type': 'function_call',
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'call_id': 'call_123',
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'name': 'search_web',
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'arguments': '{"query":"Rakhi Kaag"}',
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},
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{'type': 'function_call_output', 'call_id': 'call_123', 'output': []},
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]
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adjusted = add_reasoning_content_to_tool_messages(messages, output, 'moonshot-v1')
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assert adjusted[0]['reasoning_content'] == 'Existing reasoning'
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@ -98,6 +98,7 @@ from open_webui.utils.misc import (
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convert_logit_bias_input_to_json,
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get_content_from_message,
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convert_output_to_messages,
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add_reasoning_content_to_tool_messages,
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strip_empty_content_blocks,
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)
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from open_webui.utils.tools import (
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@ -4660,12 +4661,17 @@ async def streaming_chat_response_handler(response, ctx):
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if ENABLE_RESPONSES_API_STATEFUL and last_response_id:
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system_message = get_system_message(form_data['messages'])
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tool_messages = add_reasoning_content_to_tool_messages(
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convert_output_to_messages(output, raw=True), output, model_id
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)
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new_form_data['messages'] = (
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[system_message] if system_message else []
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) + convert_output_to_messages(output, raw=True)
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) + tool_messages
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new_form_data['previous_response_id'] = last_response_id
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else:
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tool_messages = convert_output_to_messages(output, raw=True)
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tool_messages = add_reasoning_content_to_tool_messages(
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convert_output_to_messages(output, raw=True), output, model_id
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)
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# Chat Completions providers don't support multimodal
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# tool messages. Extract images into a user message.
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@ -4875,13 +4881,16 @@ async def streaming_chat_response_handler(response, ctx):
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)
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try:
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tool_messages = add_reasoning_content_to_tool_messages(
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convert_output_to_messages(output, raw=True), output, model_id
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)
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new_form_data = {
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**form_data,
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'model': model_id,
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'stream': True,
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'messages': [
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*form_data['messages'],
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*convert_output_to_messages(output, raw=True),
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*tool_messages,
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],
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}
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@ -129,6 +129,119 @@ def get_content_from_message(message: dict) -> Optional[str]:
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return None
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def model_requires_reasoning_content_for_tool_calls(model_id: Optional[str]) -> bool:
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"""
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Some OpenAI-compatible thinking models require assistant tool-call messages
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to preserve top-level reasoning_content on continuation turns.
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"""
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if not model_id:
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return False
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model_name = model_id.lower()
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return 'kimi' in model_name or 'moonshot' in model_name
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def _extract_reasoning_content_from_item(item: dict) -> str:
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reasoning_parts = []
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source_list = item.get('summary', []) or item.get('content', [])
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for part in source_list:
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text = part.get('text', '')
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if text:
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reasoning_parts.append(text)
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return ''.join(reasoning_parts).strip()
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def get_assistant_reasoning_content_from_output(output: list[dict]) -> list[str]:
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"""
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Mirror convert_output_to_messages() assistant-message boundaries so
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reasoning_content can be reattached to the matching assistant tool-call
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message instead of being applied globally.
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"""
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assistant_reasoning = []
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pending_reasoning = []
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pending_tool_calls = []
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pending_content = []
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def flush_pending():
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nonlocal pending_reasoning, pending_tool_calls, pending_content
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if pending_content or pending_tool_calls:
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assistant_reasoning.append(''.join(pending_reasoning).strip())
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pending_reasoning = []
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pending_tool_calls = []
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pending_content = []
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for item in output:
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item_type = item.get('type', '')
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if item_type == 'message':
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content_parts = item.get('content', [])
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text = ''
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for part in content_parts:
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if part.get('type') == 'output_text':
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text += part.get('text', '')
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if text:
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pending_content.append(text)
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elif item_type == 'function_call':
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pending_tool_calls.append(item)
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elif item_type == 'function_call_output':
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flush_pending()
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elif item_type == 'reasoning':
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reasoning_text = _extract_reasoning_content_from_item(item)
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if reasoning_text:
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pending_reasoning.append(reasoning_text)
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elif item_type == 'open_webui:code_interpreter':
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if item.get('code') or item.get('output'):
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pending_content.append('code_interpreter')
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elif item_type.startswith('open_webui:'):
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pass
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flush_pending()
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return assistant_reasoning
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def add_reasoning_content_to_tool_messages(
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messages: list[dict], output: list[dict], model_id: Optional[str]
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) -> list[dict]:
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"""
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Re-add top-level reasoning_content to assistant tool-call messages for
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providers that require it during the post-tool continuation request.
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"""
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if not model_requires_reasoning_content_for_tool_calls(model_id):
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return messages
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assistant_reasoning = get_assistant_reasoning_content_from_output(output)
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if not any(assistant_reasoning):
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return messages
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adjusted_messages = []
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assistant_index = 0
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for message in messages:
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reasoning_content = None
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if message.get('role') == 'assistant':
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if assistant_index < len(assistant_reasoning):
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reasoning_content = assistant_reasoning[assistant_index]
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assistant_index += 1
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if (
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message.get('role') == 'assistant'
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and message.get('tool_calls')
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and reasoning_content
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and not message.get('reasoning_content')
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):
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message = {**message, 'reasoning_content': reasoning_content}
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adjusted_messages.append(message)
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return adjusted_messages
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def convert_output_to_messages(output: list, raw: bool = False) -> list[dict]:
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"""
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Convert OR-aligned output items to OpenAI Chat Completion-format messages.
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