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Unverified Commit 186ea22e authored by Flora Feng's avatar Flora Feng Committed by GitHub
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[Misc][Harmony] Move Responses API only harmony utils to responses/harmony.py (#35339) 


Signed-off-by: default avatarsfeng33 <4florafeng@gmail.com>
parent 4a9c07a0
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tests/entrypoints/openai/parser/test_harmony_utils.py
View file @ 186ea22e
...@@ -2,13 +2,7 @@ ...@@ -2,13 +2,7 @@
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import pytest import pytest
from openai.types.responses import ( from openai_harmony import Message, Role
ResponseFunctionToolCall,
ResponseOutputMessage,
ResponseReasoningItem,
)
from openai.types.responses.response_output_item import McpCall
from openai_harmony import Author, Message, Role, TextContent
from tests.entrypoints.openai.utils import verify_harmony_messages from tests.entrypoints.openai.utils import verify_harmony_messages
from vllm.entrypoints.openai.parser.harmony_utils import ( from vllm.entrypoints.openai.parser.harmony_utils import (
...@@ -18,20 +12,21 @@ from vllm.entrypoints.openai.parser.harmony_utils import ( ...@@ -18,20 +12,21 @@ from vllm.entrypoints.openai.parser.harmony_utils import (
has_custom_tools, has_custom_tools,
parse_chat_input_to_harmony_message, parse_chat_input_to_harmony_message,
parse_chat_output, parse_chat_output,
parse_input_to_harmony_message, )
parse_output_message, from vllm.entrypoints.openai.responses.harmony import (
response_previous_input_to_harmony,
) )
class TestCommonParseInputToHarmonyMessage: class TestCommonParseInputToHarmonyMessage:
""" """
Tests for scenarios that are common to both Chat Completion Tests for scenarios that are common to both Chat Completion
parse_chat_input_to_harmony_message and Responsees API parse_chat_input_to_harmony_message and Responses API
parse_input_to_harmony_message functions. response_previous_input_to_harmony functions.
""" """
@pytest.fixture( @pytest.fixture(
params=[parse_chat_input_to_harmony_message, parse_input_to_harmony_message] params=[parse_chat_input_to_harmony_message, response_previous_input_to_harmony]
) )
def parse_function(self, request): def parse_function(self, request):
return request.param return request.param
...@@ -216,81 +211,6 @@ class TestCommonParseInputToHarmonyMessage: ...@@ -216,81 +211,6 @@ class TestCommonParseInputToHarmonyMessage:
assert messages[0].content[1].text == "actual text" assert messages[0].content[1].text == "actual text"
class TestParseInputToHarmonyMessage:
"""
Tests for scenarios that are specific to the Responses API
parse_input_to_harmony_message function.
"""
def test_message_with_empty_content(self):
"""Test parsing message with empty string content."""
chat_msg = {
"role": "user",
"content": "",
}
messages = parse_input_to_harmony_message(chat_msg)
assert len(messages) == 1
assert messages[0].content[0].text == ""
def test_tool_message_with_string_content(self):
"""Test parsing tool message with string content."""
chat_msg = {
"role": "tool",
"name": "get_weather",
"content": "The weather in San Francisco is sunny, 72°F",
}
messages = parse_input_to_harmony_message(chat_msg)
assert len(messages) == 1
assert messages[0].author.role == Role.TOOL
assert messages[0].author.name == "functions.get_weather"
assert (
messages[0].content[0].text == "The weather in San Francisco is sunny, 72°F"
)
assert messages[0].channel == "commentary"
def test_tool_message_with_array_content(self):
"""Test parsing tool message with array content."""
chat_msg = {
"role": "tool",
"name": "search_results",
"content": [
{"type": "text", "text": "Result 1: "},
{"type": "text", "text": "Result 2: "},
{
"type": "image",
"url": "http://example.com/img.png",
}, # Should be ignored
{"type": "text", "text": "Result 3"},
],
}
messages = parse_input_to_harmony_message(chat_msg)
assert len(messages) == 1
assert messages[0].author.role == Role.TOOL
assert messages[0].author.name == "functions.search_results"
assert messages[0].content[0].text == "Result 1: Result 2: Result 3"
def test_tool_message_with_empty_content(self):
"""Test parsing tool message with None content."""
chat_msg = {
"role": "tool",
"name": "empty_tool",
"content": None,
}
messages = parse_input_to_harmony_message(chat_msg)
assert len(messages) == 1
assert messages[0].author.role == Role.TOOL
assert messages[0].author.name == "functions.empty_tool"
assert messages[0].content[0].text == ""
class TestParseChatInputToHarmonyMessage: class TestParseChatInputToHarmonyMessage:
""" """
Tests for scenarios that are specific to the Chat Completion API Tests for scenarios that are specific to the Chat Completion API
...@@ -888,200 +808,6 @@ class TestParseChatOutput: ...@@ -888,200 +808,6 @@ class TestParseChatOutput:
assert final_content == "Let me look that up.\nThe answer is 42." assert final_content == "Let me look that up.\nThe answer is 42."
class TestParseOutputMessage:
"""Tests for parse_output_message function."""
def test_commentary_with_no_recipient_creates_message(self):
"""Test that commentary with recipient=None (preambles) creates message items.
Per Harmony format, preambles are intended to be shown to end-users,
unlike analysis channel content which is hidden reasoning.
See: https://cookbook.openai.com/articles/openai-harmony
"""
message = Message.from_role_and_content(
Role.ASSISTANT, "I will now search for the weather information."
)
message = message.with_channel("commentary")
# recipient is None by default, representing a preamble
output_items = parse_output_message(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseOutputMessage)
assert output_items[0].type == "message"
assert output_items[0].role == "assistant"
assert output_items[0].status == "completed"
assert len(output_items[0].content) == 1
assert output_items[0].content[0].type == "output_text"
assert (
output_items[0].content[0].text
== "I will now search for the weather information."
)
def test_commentary_with_function_recipient_creates_function_call(self):
"""Test commentary with recipient='functions.X' creates function calls."""
message = Message.from_role_and_content(
Role.ASSISTANT, '{"location": "San Francisco", "units": "celsius"}'
)
message = message.with_channel("commentary")
message = message.with_recipient("functions.get_weather")
output_items = parse_output_message(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseFunctionToolCall)
assert output_items[0].type == "function_call"
assert output_items[0].name == "get_weather"
assert (
output_items[0].arguments
== '{"location": "San Francisco", "units": "celsius"}'
)
assert output_items[0].call_id.startswith("call_")
assert output_items[0].id.startswith("fc_")
def test_commentary_with_python_recipient_creates_reasoning(self):
"""Test that commentary with recipient='python' creates reasoning items."""
message = Message.from_role_and_content(
Role.ASSISTANT, "import numpy as np\nprint(np.array([1, 2, 3]))"
)
message = message.with_channel("commentary")
message = message.with_recipient("python")
output_items = parse_output_message(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseReasoningItem)
assert output_items[0].type == "reasoning"
assert (
output_items[0].content[0].text
== "import numpy as np\nprint(np.array([1, 2, 3]))"
)
def test_commentary_with_browser_recipient_creates_reasoning(self):
"""Test that commentary with recipient='browser' creates reasoning items."""
message = Message.from_role_and_content(
Role.ASSISTANT, "Navigating to the specified URL"
)
message = message.with_channel("commentary")
message = message.with_recipient("browser")
output_items = parse_output_message(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseReasoningItem)
assert output_items[0].type == "reasoning"
assert output_items[0].content[0].text == "Navigating to the specified URL"
def test_commentary_with_container_recipient_creates_reasoning(self):
"""Test that commentary with recipient='container' creates reasoning items."""
message = Message.from_role_and_content(
Role.ASSISTANT, "Running command in container"
)
message = message.with_channel("commentary")
message = message.with_recipient("container")
output_items = parse_output_message(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseReasoningItem)
assert output_items[0].type == "reasoning"
assert output_items[0].content[0].text == "Running command in container"
def test_commentary_with_empty_content_and_no_recipient(self):
"""Test edge case: empty commentary with recipient=None."""
message = Message.from_role_and_content(Role.ASSISTANT, "")
message = message.with_channel("commentary")
output_items = parse_output_message(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseOutputMessage)
assert output_items[0].content[0].text == ""
def test_commentary_with_multiple_contents_and_no_recipient(self):
"""Test multiple content items in commentary with no recipient."""
contents = [
TextContent(text="Step 1: Analyze the request"),
TextContent(text="Step 2: Prepare to call functions"),
]
message = Message.from_role_and_contents(Role.ASSISTANT, contents)
message = message.with_channel("commentary")
output_items = parse_output_message(message)
# _parse_final_message returns single ResponseOutputMessage with
# multiple contents
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseOutputMessage)
assert len(output_items[0].content) == 2
assert output_items[0].content[0].text == "Step 1: Analyze the request"
assert output_items[0].content[1].text == "Step 2: Prepare to call functions"
def test_commentary_with_multiple_function_calls(self):
"""Test multiple function calls in commentary channel."""
contents = [
TextContent(text='{"location": "San Francisco"}'),
TextContent(text='{"location": "New York"}'),
]
message = Message.from_role_and_contents(Role.ASSISTANT, contents)
message = message.with_channel("commentary")
message = message.with_recipient("functions.get_weather")
output_items = parse_output_message(message)
assert len(output_items) == 2
assert all(isinstance(item, ResponseFunctionToolCall) for item in output_items)
assert output_items[0].name == "get_weather"
assert output_items[1].name == "get_weather"
assert output_items[0].arguments == '{"location": "San Francisco"}'
assert output_items[1].arguments == '{"location": "New York"}'
def test_commentary_with_unknown_recipient_creates_mcp_call(self):
"""Test that commentary with unknown recipient creates MCP call."""
message = Message.from_role_and_content(Role.ASSISTANT, '{"arg": "value"}')
message = message.with_channel("commentary")
message = message.with_recipient("custom_tool")
output_items = parse_output_message(message)
assert len(output_items) == 1
assert isinstance(output_items[0], McpCall)
assert output_items[0].type == "mcp_call"
assert output_items[0].name == "custom_tool"
assert output_items[0].server_label == "custom_tool"
def test_analysis_channel_creates_reasoning(self):
"""Test that analysis channel creates reasoning items."""
message = Message.from_role_and_content(
Role.ASSISTANT, "Analyzing the problem step by step..."
)
message = message.with_channel("analysis")
output_items = parse_output_message(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseReasoningItem)
assert output_items[0].type == "reasoning"
assert (
output_items[0].content[0].text == "Analyzing the problem step by step..."
)
def test_non_assistant_message_returns_empty(self):
"""Test that non-assistant messages return empty list.
Per the implementation, tool messages to assistant (e.g., search results)
are not included in final output to align with OpenAI behavior.
"""
message = Message.from_author_and_content(
Author.new(Role.TOOL, "functions.get_weather"),
"The weather is sunny, 72°F",
)
output_items = parse_output_message(message)
assert len(output_items) == 0
def test_has_custom_tools() -> None: def test_has_custom_tools() -> None:
assert not has_custom_tools(set()) assert not has_custom_tools(set())
assert not has_custom_tools({"web_search_preview", "code_interpreter", "container"}) assert not has_custom_tools({"web_search_preview", "code_interpreter", "container"})
...@@ -1091,185 +817,6 @@ def test_has_custom_tools() -> None: ...@@ -1091,185 +817,6 @@ def test_has_custom_tools() -> None:
) )
def test_parse_mcp_call_basic() -> None:
"""Test that MCP calls are parsed with correct type and server_label."""
message = Message.from_role_and_content(Role.ASSISTANT, '{"path": "/tmp"}')
message = message.with_recipient("filesystem")
message = message.with_channel("commentary")
output_items = parse_output_message(message)
assert len(output_items) == 1
assert isinstance(output_items[0], McpCall)
assert output_items[0].type == "mcp_call"
assert output_items[0].name == "filesystem"
assert output_items[0].server_label == "filesystem"
assert output_items[0].arguments == '{"path": "/tmp"}'
assert output_items[0].status == "completed"
def test_parse_mcp_call_dotted_recipient() -> None:
"""Test that dotted recipients extract the tool name correctly."""
message = Message.from_role_and_content(Role.ASSISTANT, '{"cmd": "ls"}')
message = message.with_recipient("repo_browser.list")
message = message.with_channel("commentary")
output_items = parse_output_message(message)
assert len(output_items) == 1
assert isinstance(output_items[0], McpCall)
assert output_items[0].name == "list"
assert output_items[0].server_label == "repo_browser"
def test_mcp_vs_function_call() -> None:
"""Test that function calls are not parsed as MCP calls."""
func_message = Message.from_role_and_content(Role.ASSISTANT, '{"arg": "value"}')
func_message = func_message.with_recipient("functions.my_tool")
func_message = func_message.with_channel("commentary")
func_items = parse_output_message(func_message)
assert len(func_items) == 1
assert not isinstance(func_items[0], McpCall)
assert func_items[0].type == "function_call"
def test_mcp_vs_builtin_tools() -> None:
"""Test that built-in tools (python, container) are not parsed as MCP calls."""
# Test python (built-in tool) - should be reasoning, not MCP
python_message = Message.from_role_and_content(Role.ASSISTANT, "print('hello')")
python_message = python_message.with_recipient("python")
python_message = python_message.with_channel("commentary")
python_items = parse_output_message(python_message)
assert len(python_items) == 1
assert not isinstance(python_items[0], McpCall)
assert python_items[0].type == "reasoning"
def test_parse_remaining_state_commentary_channel() -> None:
"""Test parse_remaining_state with commentary channel and various recipients."""
from unittest.mock import Mock
from vllm.entrypoints.openai.parser.harmony_utils import parse_remaining_state
# Test 1: functions.* recipient → should return function tool call
parser_func = Mock()
parser_func.current_content = '{"arg": "value"}'
parser_func.current_role = Role.ASSISTANT
parser_func.current_channel = "commentary"
parser_func.current_recipient = "functions.my_tool"
func_items = parse_remaining_state(parser_func)
assert len(func_items) == 1
assert not isinstance(func_items[0], McpCall)
assert func_items[0].type == "function_call"
assert func_items[0].name == "my_tool"
assert func_items[0].status == "in_progress"
# Test 2: MCP tool (not builtin) → should return MCP call
parser_mcp = Mock()
parser_mcp.current_content = '{"path": "/tmp"}'
parser_mcp.current_role = Role.ASSISTANT
parser_mcp.current_channel = "commentary"
parser_mcp.current_recipient = "filesystem"
mcp_items = parse_remaining_state(parser_mcp)
assert len(mcp_items) == 1
assert isinstance(mcp_items[0], McpCall)
assert mcp_items[0].type == "mcp_call"
assert mcp_items[0].name == "filesystem"
assert mcp_items[0].server_label == "filesystem"
assert mcp_items[0].status == "in_progress"
# Test 3: Built-in tool (python)
# should NOT return MCP call, returns reasoning (internal tool interaction)
parser_builtin = Mock()
parser_builtin.current_content = "print('hello')"
parser_builtin.current_role = Role.ASSISTANT
parser_builtin.current_channel = "commentary"
parser_builtin.current_recipient = "python"
builtin_items = parse_remaining_state(parser_builtin)
# Built-in tools explicitly return reasoning
assert len(builtin_items) == 1
assert not isinstance(builtin_items[0], McpCall)
assert builtin_items[0].type == "reasoning"
# Test 4: No recipient (preamble) → should return message, not reasoning
parser_preamble = Mock()
parser_preamble.current_content = "I'll search for that information now."
parser_preamble.current_role = Role.ASSISTANT
parser_preamble.current_channel = "commentary"
parser_preamble.current_recipient = None
preamble_items = parse_remaining_state(parser_preamble)
assert len(preamble_items) == 1
assert isinstance(preamble_items[0], ResponseOutputMessage)
assert preamble_items[0].type == "message"
assert preamble_items[0].content[0].text == "I'll search for that information now."
assert preamble_items[0].status == "incomplete" # streaming
def test_parse_remaining_state_analysis_channel() -> None:
"""Test parse_remaining_state with analysis channel and various recipients."""
from unittest.mock import Mock
from vllm.entrypoints.openai.parser.harmony_utils import parse_remaining_state
# Test 1: functions.* recipient → should return function tool call
parser_func = Mock()
parser_func.current_content = '{"arg": "value"}'
parser_func.current_role = Role.ASSISTANT
parser_func.current_channel = "analysis"
parser_func.current_recipient = "functions.my_tool"
func_items = parse_remaining_state(parser_func)
assert len(func_items) == 1
assert not isinstance(func_items[0], McpCall)
assert func_items[0].type == "function_call"
assert func_items[0].name == "my_tool"
assert func_items[0].status == "in_progress"
# Test 2: MCP tool (not builtin) → should return MCP call
parser_mcp = Mock()
parser_mcp.current_content = '{"query": "test"}'
parser_mcp.current_role = Role.ASSISTANT
parser_mcp.current_channel = "analysis"
parser_mcp.current_recipient = "database"
mcp_items = parse_remaining_state(parser_mcp)
assert len(mcp_items) == 1
assert isinstance(mcp_items[0], McpCall)
assert mcp_items[0].type == "mcp_call"
assert mcp_items[0].name == "database"
assert mcp_items[0].server_label == "database"
assert mcp_items[0].status == "in_progress"
# Test 3: Built-in tool (container)
# should NOT return MCP call, falls through to reasoning
parser_builtin = Mock()
parser_builtin.current_content = "docker run"
parser_builtin.current_role = Role.ASSISTANT
parser_builtin.current_channel = "analysis"
parser_builtin.current_recipient = "container"
builtin_items = parse_remaining_state(parser_builtin)
# Should fall through to reasoning logic
assert len(builtin_items) == 1
assert not isinstance(builtin_items[0], McpCall)
assert builtin_items[0].type == "reasoning"
class TestGetSystemMessage: class TestGetSystemMessage:
"""Tests for get_system_message channel configuration.""" """Tests for get_system_message channel configuration."""
......
tests/entrypoints/openai/responses/test_harmony_utils.py 0 → 100644
View file @ 186ea22e
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Unit tests for vllm.entrypoints.openai.responses.harmony."""
from openai.types.responses import (
ResponseFunctionToolCall,
ResponseOutputMessage,
ResponseReasoningItem,
)
from openai.types.responses.response_output_item import McpCall
from openai_harmony import Author, Message, Role, TextContent
from vllm.entrypoints.openai.responses.harmony import (
harmony_to_response_output,
parser_state_to_response_output,
response_previous_input_to_harmony,
)
class TestResponsePreviousInputToHarmony:
"""
Tests for scenarios that are specific to the Responses API
response_previous_input_to_harmony function.
"""
def test_message_with_empty_content(self):
"""Test parsing message with empty string content."""
chat_msg = {
"role": "user",
"content": "",
}
messages = response_previous_input_to_harmony(chat_msg)
assert len(messages) == 1
assert messages[0].content[0].text == ""
def test_tool_message_with_string_content(self):
"""Test parsing tool message with string content."""
chat_msg = {
"role": "tool",
"name": "get_weather",
"content": "The weather in San Francisco is sunny, 72°F",
}
messages = response_previous_input_to_harmony(chat_msg)
assert len(messages) == 1
assert messages[0].author.role == Role.TOOL
assert messages[0].author.name == "functions.get_weather"
assert (
messages[0].content[0].text == "The weather in San Francisco is sunny, 72°F"
)
assert messages[0].channel == "commentary"
def test_tool_message_with_array_content(self):
"""Test parsing tool message with array content."""
chat_msg = {
"role": "tool",
"name": "search_results",
"content": [
{"type": "text", "text": "Result 1: "},
{"type": "text", "text": "Result 2: "},
{
"type": "image",
"url": "http://example.com/img.png",
}, # Should be ignored
{"type": "text", "text": "Result 3"},
],
}
messages = response_previous_input_to_harmony(chat_msg)
assert len(messages) == 1
assert messages[0].author.role == Role.TOOL
assert messages[0].author.name == "functions.search_results"
assert messages[0].content[0].text == "Result 1: Result 2: Result 3"
def test_tool_message_with_empty_content(self):
"""Test parsing tool message with None content."""
chat_msg = {
"role": "tool",
"name": "empty_tool",
"content": None,
}
messages = response_previous_input_to_harmony(chat_msg)
assert len(messages) == 1
assert messages[0].author.role == Role.TOOL
assert messages[0].author.name == "functions.empty_tool"
assert messages[0].content[0].text == ""
class TestHarmonyToResponseOutput:
"""Tests for harmony_to_response_output function."""
def test_commentary_with_no_recipient_creates_message(self):
"""Test that commentary with recipient=None (preambles) creates message items.
Per Harmony format, preambles are intended to be shown to end-users,
unlike analysis channel content which is hidden reasoning.
See: https://cookbook.openai.com/articles/openai-harmony
"""
message = Message.from_role_and_content(
Role.ASSISTANT, "I will now search for the weather information."
)
message = message.with_channel("commentary")
# recipient is None by default, representing a preamble
output_items = harmony_to_response_output(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseOutputMessage)
assert output_items[0].type == "message"
assert output_items[0].role == "assistant"
assert output_items[0].status == "completed"
assert len(output_items[0].content) == 1
assert output_items[0].content[0].type == "output_text"
assert (
output_items[0].content[0].text
== "I will now search for the weather information."
)
def test_commentary_with_function_recipient_creates_function_call(self):
"""Test commentary with recipient='functions.X' creates function calls."""
message = Message.from_role_and_content(
Role.ASSISTANT, '{"location": "San Francisco", "units": "celsius"}'
)
message = message.with_channel("commentary")
message = message.with_recipient("functions.get_weather")
output_items = harmony_to_response_output(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseFunctionToolCall)
assert output_items[0].type == "function_call"
assert output_items[0].name == "get_weather"
assert (
output_items[0].arguments
== '{"location": "San Francisco", "units": "celsius"}'
)
assert output_items[0].call_id.startswith("call_")
assert output_items[0].id.startswith("fc_")
def test_commentary_with_python_recipient_creates_reasoning(self):
"""Test that commentary with recipient='python' creates reasoning items."""
message = Message.from_role_and_content(
Role.ASSISTANT, "import numpy as np\nprint(np.array([1, 2, 3]))"
)
message = message.with_channel("commentary")
message = message.with_recipient("python")
output_items = harmony_to_response_output(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseReasoningItem)
assert output_items[0].type == "reasoning"
assert (
output_items[0].content[0].text
== "import numpy as np\nprint(np.array([1, 2, 3]))"
)
def test_commentary_with_browser_recipient_creates_reasoning(self):
"""Test that commentary with recipient='browser' creates reasoning items."""
message = Message.from_role_and_content(
Role.ASSISTANT, "Navigating to the specified URL"
)
message = message.with_channel("commentary")
message = message.with_recipient("browser")
output_items = harmony_to_response_output(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseReasoningItem)
assert output_items[0].type == "reasoning"
assert output_items[0].content[0].text == "Navigating to the specified URL"
def test_commentary_with_container_recipient_creates_reasoning(self):
"""Test that commentary with recipient='container' creates reasoning items."""
message = Message.from_role_and_content(
Role.ASSISTANT, "Running command in container"
)
message = message.with_channel("commentary")
message = message.with_recipient("container")
output_items = harmony_to_response_output(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseReasoningItem)
assert output_items[0].type == "reasoning"
assert output_items[0].content[0].text == "Running command in container"
def test_commentary_with_empty_content_and_no_recipient(self):
"""Test edge case: empty commentary with recipient=None."""
message = Message.from_role_and_content(Role.ASSISTANT, "")
message = message.with_channel("commentary")
output_items = harmony_to_response_output(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseOutputMessage)
assert output_items[0].content[0].text == ""
def test_commentary_with_multiple_contents_and_no_recipient(self):
"""Test multiple content items in commentary with no recipient."""
contents = [
TextContent(text="Step 1: Analyze the request"),
TextContent(text="Step 2: Prepare to call functions"),
]
message = Message.from_role_and_contents(Role.ASSISTANT, contents)
message = message.with_channel("commentary")
output_items = harmony_to_response_output(message)
# _parse_final_message returns single ResponseOutputMessage with
# multiple contents
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseOutputMessage)
assert len(output_items[0].content) == 2
assert output_items[0].content[0].text == "Step 1: Analyze the request"
assert output_items[0].content[1].text == "Step 2: Prepare to call functions"
def test_commentary_with_multiple_function_calls(self):
"""Test multiple function calls in commentary channel."""
contents = [
TextContent(text='{"location": "San Francisco"}'),
TextContent(text='{"location": "New York"}'),
]
message = Message.from_role_and_contents(Role.ASSISTANT, contents)
message = message.with_channel("commentary")
message = message.with_recipient("functions.get_weather")
output_items = harmony_to_response_output(message)
assert len(output_items) == 2
assert all(isinstance(item, ResponseFunctionToolCall) for item in output_items)
assert output_items[0].name == "get_weather"
assert output_items[1].name == "get_weather"
assert output_items[0].arguments == '{"location": "San Francisco"}'
assert output_items[1].arguments == '{"location": "New York"}'
def test_commentary_with_unknown_recipient_creates_mcp_call(self):
"""Test that commentary with unknown recipient creates MCP call."""
message = Message.from_role_and_content(Role.ASSISTANT, '{"arg": "value"}')
message = message.with_channel("commentary")
message = message.with_recipient("custom_tool")
output_items = harmony_to_response_output(message)
assert len(output_items) == 1
assert isinstance(output_items[0], McpCall)
assert output_items[0].type == "mcp_call"
assert output_items[0].name == "custom_tool"
assert output_items[0].server_label == "custom_tool"
def test_analysis_channel_creates_reasoning(self):
"""Test that analysis channel creates reasoning items."""
message = Message.from_role_and_content(
Role.ASSISTANT, "Analyzing the problem step by step..."
)
message = message.with_channel("analysis")
output_items = harmony_to_response_output(message)
assert len(output_items) == 1
assert isinstance(output_items[0], ResponseReasoningItem)
assert output_items[0].type == "reasoning"
assert (
output_items[0].content[0].text == "Analyzing the problem step by step..."
)
def test_non_assistant_message_returns_empty(self):
"""Test that non-assistant messages return empty list.
Per the implementation, tool messages to assistant (e.g., search results)
are not included in final output to align with OpenAI behavior.
"""
message = Message.from_author_and_content(
Author.new(Role.TOOL, "functions.get_weather"),
"The weather is sunny, 72°F",
)
output_items = harmony_to_response_output(message)
assert len(output_items) == 0
def test_parse_mcp_call_basic() -> None:
"""Test that MCP calls are parsed with correct type and server_label."""
message = Message.from_role_and_content(Role.ASSISTANT, '{"path": "/tmp"}')
message = message.with_recipient("filesystem")
message = message.with_channel("commentary")
output_items = harmony_to_response_output(message)
assert len(output_items) == 1
assert isinstance(output_items[0], McpCall)
assert output_items[0].type == "mcp_call"
assert output_items[0].name == "filesystem"
assert output_items[0].server_label == "filesystem"
assert output_items[0].arguments == '{"path": "/tmp"}'
assert output_items[0].status == "completed"
def test_parse_mcp_call_dotted_recipient() -> None:
"""Test that dotted recipients extract the tool name correctly."""
message = Message.from_role_and_content(Role.ASSISTANT, '{"cmd": "ls"}')
message = message.with_recipient("repo_browser.list")
message = message.with_channel("commentary")
output_items = harmony_to_response_output(message)
assert len(output_items) == 1
assert isinstance(output_items[0], McpCall)
assert output_items[0].name == "list"
assert output_items[0].server_label == "repo_browser"
def test_mcp_vs_function_call() -> None:
"""Test that function calls are not parsed as MCP calls."""
func_message = Message.from_role_and_content(Role.ASSISTANT, '{"arg": "value"}')
func_message = func_message.with_recipient("functions.my_tool")
func_message = func_message.with_channel("commentary")
func_items = harmony_to_response_output(func_message)
assert len(func_items) == 1
assert not isinstance(func_items[0], McpCall)
assert func_items[0].type == "function_call"
def test_mcp_vs_builtin_tools() -> None:
"""Test that built-in tools (python, container) are not parsed as MCP calls."""
# Test python (built-in tool) - should be reasoning, not MCP
python_message = Message.from_role_and_content(Role.ASSISTANT, "print('hello')")
python_message = python_message.with_recipient("python")
python_message = python_message.with_channel("commentary")
python_items = harmony_to_response_output(python_message)
assert len(python_items) == 1
assert not isinstance(python_items[0], McpCall)
assert python_items[0].type == "reasoning"
def test_parser_state_to_response_output_commentary_channel() -> None:
"""Test parser_state_to_response_output with commentary
channel and various recipients."""
from unittest.mock import Mock
# Test 1: functions.* recipient -> should return function tool call
parser_func = Mock()
parser_func.current_content = '{"arg": "value"}'
parser_func.current_role = Role.ASSISTANT
parser_func.current_channel = "commentary"
parser_func.current_recipient = "functions.my_tool"
func_items = parser_state_to_response_output(parser_func)
assert len(func_items) == 1
assert not isinstance(func_items[0], McpCall)
assert func_items[0].type == "function_call"
assert func_items[0].name == "my_tool"
assert func_items[0].status == "in_progress"
# Test 2: MCP tool (not builtin) -> should return MCP call
parser_mcp = Mock()
parser_mcp.current_content = '{"path": "/tmp"}'
parser_mcp.current_role = Role.ASSISTANT
parser_mcp.current_channel = "commentary"
parser_mcp.current_recipient = "filesystem"
mcp_items = parser_state_to_response_output(parser_mcp)
assert len(mcp_items) == 1
assert isinstance(mcp_items[0], McpCall)
assert mcp_items[0].type == "mcp_call"
assert mcp_items[0].name == "filesystem"
assert mcp_items[0].server_label == "filesystem"
assert mcp_items[0].status == "in_progress"
# Test 3: Built-in tool (python)
# should NOT return MCP call, returns reasoning (internal tool interaction)
parser_builtin = Mock()
parser_builtin.current_content = "print('hello')"
parser_builtin.current_role = Role.ASSISTANT
parser_builtin.current_channel = "commentary"
parser_builtin.current_recipient = "python"
builtin_items = parser_state_to_response_output(parser_builtin)
# Built-in tools explicitly return reasoning
assert len(builtin_items) == 1
assert not isinstance(builtin_items[0], McpCall)
assert builtin_items[0].type == "reasoning"
# Test 4: No recipient (preamble) → should return message, not reasoning
parser_preamble = Mock()
parser_preamble.current_content = "I'll search for that information now."
parser_preamble.current_role = Role.ASSISTANT
parser_preamble.current_channel = "commentary"
parser_preamble.current_recipient = None
preamble_items = parser_state_to_response_output(parser_preamble)
assert len(preamble_items) == 1
assert isinstance(preamble_items[0], ResponseOutputMessage)
assert preamble_items[0].type == "message"
assert preamble_items[0].content[0].text == "I'll search for that information now."
assert preamble_items[0].status == "incomplete" # streaming
def test_parser_state_to_response_output_analysis_channel() -> None:
"""Test parser_state_to_response_output with analysis
channel and various recipients."""
from unittest.mock import Mock
# Test 1: functions.* recipient -> should return function tool call
parser_func = Mock()
parser_func.current_content = '{"arg": "value"}'
parser_func.current_role = Role.ASSISTANT
parser_func.current_channel = "analysis"
parser_func.current_recipient = "functions.my_tool"
func_items = parser_state_to_response_output(parser_func)
assert len(func_items) == 1
assert not isinstance(func_items[0], McpCall)
assert func_items[0].type == "function_call"
assert func_items[0].name == "my_tool"
assert func_items[0].status == "in_progress"
# Test 2: MCP tool (not builtin) -> should return MCP call
parser_mcp = Mock()
parser_mcp.current_content = '{"query": "test"}'
parser_mcp.current_role = Role.ASSISTANT
parser_mcp.current_channel = "analysis"
parser_mcp.current_recipient = "database"
mcp_items = parser_state_to_response_output(parser_mcp)
assert len(mcp_items) == 1
assert isinstance(mcp_items[0], McpCall)
assert mcp_items[0].type == "mcp_call"
assert mcp_items[0].name == "database"
assert mcp_items[0].server_label == "database"
assert mcp_items[0].status == "in_progress"
# Test 3: Built-in tool (container)
# should NOT return MCP call, falls through to reasoning
parser_builtin = Mock()
parser_builtin.current_content = "docker run"
parser_builtin.current_role = Role.ASSISTANT
parser_builtin.current_channel = "analysis"
parser_builtin.current_recipient = "container"
builtin_items = parser_state_to_response_output(parser_builtin)
# Should fall through to reasoning logic
assert len(builtin_items) == 1
assert not isinstance(builtin_items[0], McpCall)
assert builtin_items[0].type == "reasoning"
tests/entrypoints/openai/responses/test_mcp_tools.py
View file @ 186ea22e
...@@ -97,16 +97,16 @@ class TestMCPToolServerUnit: ...@@ -97,16 +97,16 @@ class TestMCPToolServerUnit:
assert server.get_tool_description("test_server", allowed_tools=[]) is None assert server.get_tool_description("test_server", allowed_tools=[]) is None
def test_builtin_tools_consistency(self): def test_builtin_tools_consistency(self):
"""MCP_BUILTIN_TOOLS must match _BUILTIN_TOOL_TO_MCP_SERVER_LABEL values.""" """MCP_BUILTIN_TOOLS must match BUILTIN_TOOL_TO_MCP_SERVER_LABEL values."""
from vllm.entrypoints.openai.parser.harmony_utils import ( from vllm.entrypoints.openai.parser.harmony_utils import (
_BUILTIN_TOOL_TO_MCP_SERVER_LABEL, BUILTIN_TOOL_TO_MCP_SERVER_LABEL,
MCP_BUILTIN_TOOLS, MCP_BUILTIN_TOOLS,
) )
assert set(_BUILTIN_TOOL_TO_MCP_SERVER_LABEL.values()) == MCP_BUILTIN_TOOLS, ( assert set(BUILTIN_TOOL_TO_MCP_SERVER_LABEL.values()) == MCP_BUILTIN_TOOLS, (
f"MCP_BUILTIN_TOOLS {MCP_BUILTIN_TOOLS} does not match " f"MCP_BUILTIN_TOOLS {MCP_BUILTIN_TOOLS} does not match "
f"_BUILTIN_TOOL_TO_MCP_SERVER_LABEL values " f"BUILTIN_TOOL_TO_MCP_SERVER_LABEL values "
f"{set(_BUILTIN_TOOL_TO_MCP_SERVER_LABEL.values())}" f"{set(BUILTIN_TOOL_TO_MCP_SERVER_LABEL.values())}"
) )
......
vllm/entrypoints/openai/parser/harmony_utils.py
View file @ 186ea22e
...@@ -2,27 +2,9 @@ ...@@ -2,27 +2,9 @@
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import datetime import datetime
import json
from collections.abc import Iterable, Sequence from collections.abc import Iterable, Sequence
from typing import Literal from typing import Literal
from openai.types.responses import (
ResponseFunctionToolCall,
ResponseOutputItem,
ResponseOutputMessage,
ResponseOutputText,
ResponseReasoningItem,
)
from openai.types.responses.response_function_web_search import (
ActionFind,
ActionOpenPage,
ActionSearch,
ResponseFunctionWebSearch,
)
from openai.types.responses.response_output_item import McpCall
from openai.types.responses.response_reasoning_item import (
Content as ResponseReasoningTextContent,
)
from openai.types.responses.tool import Tool from openai.types.responses.tool import Tool
from openai_harmony import ( from openai_harmony import (
Author, Author,
...@@ -38,17 +20,10 @@ from openai_harmony import ( ...@@ -38,17 +20,10 @@ from openai_harmony import (
ToolDescription, ToolDescription,
load_harmony_encoding, load_harmony_encoding,
) )
from openai_harmony import Message as OpenAIHarmonyMessage
from openai_harmony import Role as OpenAIHarmonyRole
from vllm import envs from vllm import envs
from vllm.entrypoints.openai.chat_completion.protocol import ChatCompletionToolsParam from vllm.entrypoints.openai.chat_completion.protocol import ChatCompletionToolsParam
from vllm.entrypoints.openai.responses.protocol import (
ResponseInputOutputItem,
ResponsesRequest,
)
from vllm.logger import init_logger from vllm.logger import init_logger
from vllm.utils import random_uuid
logger = init_logger(__name__) logger = init_logger(__name__)
...@@ -64,14 +39,14 @@ _harmony_encoding = None ...@@ -64,14 +39,14 @@ _harmony_encoding = None
# they are available and requested by the user. # they are available and requested by the user.
# Tool args are provided by MCP tool descriptions. Output # Tool args are provided by MCP tool descriptions. Output
# of the tools are stringified. # of the tools are stringified.
_BUILTIN_TOOL_TO_MCP_SERVER_LABEL: dict[str, str] = { BUILTIN_TOOL_TO_MCP_SERVER_LABEL: dict[str, str] = {
"python": "code_interpreter", "python": "code_interpreter",
"browser": "web_search_preview", "browser": "web_search_preview",
"container": "container", "container": "container",
} }
# Derive MCP_BUILTIN_TOOLS from the canonical mapping # Derive MCP_BUILTIN_TOOLS from the canonical mapping
MCP_BUILTIN_TOOLS: set[str] = set(_BUILTIN_TOOL_TO_MCP_SERVER_LABEL.values()) MCP_BUILTIN_TOOLS: set[str] = set(BUILTIN_TOOL_TO_MCP_SERVER_LABEL.values())
def has_custom_tools(tool_types: set[str]) -> bool: def has_custom_tools(tool_types: set[str]) -> bool:
...@@ -179,55 +154,6 @@ def get_user_message(content: str) -> Message: ...@@ -179,55 +154,6 @@ def get_user_message(content: str) -> Message:
return Message.from_role_and_content(Role.USER, content) return Message.from_role_and_content(Role.USER, content)
def parse_response_input(
response_msg: ResponseInputOutputItem,
prev_responses: list[ResponseOutputItem | ResponseReasoningItem],
) -> Message:
if not isinstance(response_msg, dict):
response_msg = response_msg.model_dump()
if "type" not in response_msg or response_msg["type"] == "message":
role = response_msg["role"]
content = response_msg["content"]
# Add prefix for developer messages.
# <|start|>developer<|message|># Instructions {instructions}<|end|>
text_prefix = "Instructions:\n" if role == "developer" else ""
if isinstance(content, str):
msg = Message.from_role_and_content(role, text_prefix + content)
else:
contents = [TextContent(text=text_prefix + c["text"]) for c in content]
msg = Message.from_role_and_contents(role, contents)
if role == "assistant":
msg = msg.with_channel("final")
elif response_msg["type"] == "function_call_output":
call_id = response_msg["call_id"]
call_response: ResponseFunctionToolCall | None = None
for prev_response in reversed(prev_responses):
if (
isinstance(prev_response, ResponseFunctionToolCall)
and prev_response.call_id == call_id
):
call_response = prev_response
break
if call_response is None:
raise ValueError(f"No call message found for {call_id}")
msg = Message.from_author_and_content(
Author.new(Role.TOOL, f"functions.{call_response.name}"),
response_msg["output"],
)
elif response_msg["type"] == "reasoning":
content = response_msg["content"]
assert len(content) == 1
msg = Message.from_role_and_content(Role.ASSISTANT, content[0]["text"])
elif response_msg["type"] == "function_call":
msg = Message.from_role_and_content(Role.ASSISTANT, response_msg["arguments"])
msg = msg.with_channel("commentary")
msg = msg.with_recipient(f"functions.{response_msg['name']}")
msg = msg.with_content_type("json")
else:
raise ValueError(f"Unknown input type: {response_msg['type']}")
return msg
def parse_chat_inputs_to_harmony_messages(chat_msgs: list) -> list[Message]: def parse_chat_inputs_to_harmony_messages(chat_msgs: list) -> list[Message]:
""" """
Parse a list of messages from request.messages in the Chat Completion API to Parse a list of messages from request.messages in the Chat Completion API to
...@@ -390,139 +316,6 @@ def parse_chat_input_to_harmony_message( ...@@ -390,139 +316,6 @@ def parse_chat_input_to_harmony_message(
return msgs return msgs
def parse_input_to_harmony_message(chat_msg) -> list[Message]:
"""Parse a message from request.previous_input_messages
into Harmony messages.
Supports both OpenAI chat format ({"role": "..."}) and
Harmony format ({"author": {"role": "..."}}).
"""
if not isinstance(chat_msg, dict):
chat_msg = chat_msg.model_dump(exclude_none=True)
if "author" in chat_msg and isinstance(chat_msg.get("author"), dict):
return [_parse_harmony_format_message(chat_msg)]
return _parse_chat_format_message(chat_msg)
def _parse_harmony_format_message(chat_msg: dict) -> Message:
"""Reconstruct a Message from Harmony-format dict,
preserving channel, recipient, and content_type."""
author_dict = chat_msg["author"]
role = author_dict.get("role")
name = author_dict.get("name")
raw_content = chat_msg.get("content", "")
if isinstance(raw_content, list):
# TODO: Support refusal and non-text content types.
contents = [TextContent(text=c.get("text", "")) for c in raw_content]
elif isinstance(raw_content, str):
contents = [TextContent(text=raw_content)]
else:
contents = [TextContent(text="")]
if name:
msg = Message.from_author_and_contents(Author.new(Role(role), name), contents)
else:
msg = Message.from_role_and_contents(Role(role), contents)
channel = chat_msg.get("channel")
if channel:
msg = msg.with_channel(channel)
recipient = chat_msg.get("recipient")
if recipient:
msg = msg.with_recipient(recipient)
content_type = chat_msg.get("content_type")
if content_type:
msg = msg.with_content_type(content_type)
return msg
def _parse_chat_format_message(chat_msg: dict) -> list[Message]:
"""Parse an OpenAI chat-format dict into Harmony messages."""
role = chat_msg.get("role")
if role is None:
raise ValueError(f"Message has no 'role' key: {chat_msg}")
# Assistant message with tool calls
tool_calls = chat_msg.get("tool_calls")
if role == "assistant" and tool_calls:
msgs: list[Message] = []
for call in tool_calls:
func = call.get("function", {})
name = func.get("name", "")
arguments = func.get("arguments", "") or ""
msg = Message.from_role_and_content(Role.ASSISTANT, arguments)
msg = msg.with_channel("commentary")
msg = msg.with_recipient(f"functions.{name}")
msg = msg.with_content_type("json")
msgs.append(msg)
return msgs
# Tool role message (tool output)
if role == "tool":
name = chat_msg.get("name", "")
if name and not name.startswith("functions."):
name = f"functions.{name}"
content = chat_msg.get("content", "") or ""
content = flatten_chat_text_content(content)
# NOTE: .with_recipient("assistant") is required on tool messages
# to match parse_chat_input_to_harmony_message behavior and ensure
# proper routing in the Harmony protocol.
msg = (
Message.from_author_and_content(Author.new(Role.TOOL, name), content)
.with_channel("commentary")
.with_recipient("assistant")
)
return [msg]
# Default: user/assistant/system messages
content = chat_msg.get("content", "")
if isinstance(content, str):
contents = [TextContent(text=content)]
else:
# TODO: Support refusal.
contents = [TextContent(text=c.get("text", "")) for c in content]
msg = Message.from_role_and_contents(role, contents)
return [msg]
def construct_harmony_previous_input_messages(
request: ResponsesRequest,
) -> list[OpenAIHarmonyMessage]:
messages: list[OpenAIHarmonyMessage] = []
if request.previous_input_messages:
for message in request.previous_input_messages:
# Handle both OpenAIHarmonyMessage objects and dictionary inputs
if isinstance(message, OpenAIHarmonyMessage):
message_role = message.author.role
# To match OpenAI, instructions, reasoning and tools are
# always taken from the most recent Responses API request
# not carried over from previous requests
if (
message_role == OpenAIHarmonyRole.SYSTEM
or message_role == OpenAIHarmonyRole.DEVELOPER
):
continue
messages.append(message)
else:
harmony_messages = parse_input_to_harmony_message(message)
for harmony_msg in harmony_messages:
message_role = harmony_msg.author.role
# To match OpenAI, instructions, reasoning and tools are
# always taken from the most recent Responses API request
# not carried over from previous requests
if (
message_role == OpenAIHarmonyRole.SYSTEM
or message_role == OpenAIHarmonyRole.DEVELOPER
):
continue
messages.append(harmony_msg)
return messages
def render_for_completion(messages: list[Message]) -> list[int]: def render_for_completion(messages: list[Message]) -> list[int]:
conversation = Conversation.from_messages(messages) conversation = Conversation.from_messages(messages)
token_ids = get_encoding().render_conversation_for_completion( token_ids = get_encoding().render_conversation_for_completion(
...@@ -531,313 +324,6 @@ def render_for_completion(messages: list[Message]) -> list[int]: ...@@ -531,313 +324,6 @@ def render_for_completion(messages: list[Message]) -> list[int]:
return token_ids return token_ids
def _parse_browser_tool_call(message: Message, recipient: str) -> ResponseOutputItem:
"""Parse browser tool calls (search, open, find) into web search items."""
if len(message.content) != 1:
raise ValueError("Invalid number of contents in browser message")
content = message.content[0]
# Parse JSON args (with retry detection)
try:
browser_call = json.loads(content.text)
except json.JSONDecodeError:
logger.warning(
"Invalid JSON in browser tool call, using error placeholder: %s",
content.text,
)
json_retry_output_message = (
f"Invalid JSON args, caught and retried: {content.text}"
)
browser_call = {
"query": json_retry_output_message,
"url": json_retry_output_message,
"pattern": json_retry_output_message,
}
# Create appropriate action based on recipient
if recipient == "browser.search":
action = ActionSearch(
query=f"cursor:{browser_call.get('query', '')}", type="search"
)
elif recipient == "browser.open":
action = ActionOpenPage(
url=f"cursor:{browser_call.get('url', '')}", type="open_page"
)
elif recipient == "browser.find":
action = ActionFind(
pattern=browser_call.get("pattern", ""),
url=f"cursor:{browser_call.get('url', '')}",
type="find",
)
else:
raise ValueError(f"Unknown browser action: {recipient}")
return ResponseFunctionWebSearch(
id=f"ws_{random_uuid()}",
action=action,
status="completed",
type="web_search_call",
)
def _parse_function_call(message: Message, recipient: str) -> list[ResponseOutputItem]:
"""Parse function calls into function tool call items."""
function_name = recipient.split(".")[-1]
output_items = []
for content in message.content:
random_id = random_uuid()
response_item = ResponseFunctionToolCall(
arguments=content.text,
call_id=f"call_{random_id}",
type="function_call",
name=function_name,
id=f"fc_{random_id}",
)
output_items.append(response_item)
return output_items
def _parse_reasoning(message: Message) -> list[ResponseOutputItem]:
"""Parse reasoning/analysis content into reasoning items."""
output_items = []
for content in message.content:
reasoning_item = ResponseReasoningItem(
id=f"rs_{random_uuid()}",
summary=[],
type="reasoning",
content=[
ResponseReasoningTextContent(text=content.text, type="reasoning_text")
],
status=None,
)
output_items.append(reasoning_item)
return output_items
def _parse_final_message(message: Message) -> ResponseOutputItem:
"""Parse final channel messages into output message items."""
contents = []
for content in message.content:
output_text = ResponseOutputText(
text=content.text,
annotations=[], # TODO
type="output_text",
logprobs=None, # TODO
)
contents.append(output_text)
return ResponseOutputMessage(
id=f"msg_{random_uuid()}",
content=contents,
role=message.author.role,
status="completed",
type="message",
)
def _parse_mcp_recipient(recipient: str) -> tuple[str, str]:
"""
Parse MCP recipient into (server_label, tool_name).
For dotted recipients like "repo_browser.list":
- server_label: "repo_browser" (namespace/server)
- tool_name: "list" (specific tool)
For simple recipients like "filesystem":
- server_label: "filesystem"
- tool_name: "filesystem"
"""
if "." in recipient:
server_label = recipient.split(".")[0]
tool_name = recipient.split(".")[-1]
else:
server_label = recipient
tool_name = recipient
return server_label, tool_name
def _parse_mcp_call(message: Message, recipient: str) -> list[ResponseOutputItem]:
"""Parse MCP calls into MCP call items."""
# Handle built-in tools that need server_label mapping
if recipient in _BUILTIN_TOOL_TO_MCP_SERVER_LABEL:
server_label = _BUILTIN_TOOL_TO_MCP_SERVER_LABEL[recipient]
tool_name = recipient
else:
server_label, tool_name = _parse_mcp_recipient(recipient)
output_items = []
for content in message.content:
response_item = McpCall(
arguments=content.text,
type="mcp_call",
name=tool_name,
server_label=server_label,
id=f"mcp_{random_uuid()}",
status="completed",
)
output_items.append(response_item)
return output_items
def _parse_message_no_recipient(
message: Message,
) -> list[ResponseOutputItem]:
"""Parse a Harmony message with no recipient based on its channel."""
if message.channel == "analysis":
return _parse_reasoning(message)
if message.channel in ("commentary", "final"):
# Per Harmony format, preambles (commentary with no recipient) and
# final channel content are both intended to be shown to end-users.
# See: https://cookbook.openai.com/articles/openai-harmony
return [_parse_final_message(message)]
raise ValueError(f"Unknown channel: {message.channel}")
def parse_output_message(message: Message) -> list[ResponseOutputItem]:
"""
Parse a Harmony message into a list of output response items.
"""
if message.author.role != "assistant":
# This is a message from a tool to the assistant (e.g., search result).
# Don't include it in the final output for now. This aligns with
# OpenAI's behavior on models like o4-mini.
return []
output_items: list[ResponseOutputItem] = []
recipient = message.recipient
if recipient is not None:
# Browser tool calls (browser.search, browser.open, browser.find)
if recipient.startswith("browser."):
output_items.append(_parse_browser_tool_call(message, recipient))
# Function calls (should only happen on commentary channel)
elif message.channel == "commentary" and recipient.startswith("functions."):
output_items.extend(_parse_function_call(message, recipient))
# Built-in MCP tools (python, browser, container)
elif recipient in _BUILTIN_TOOL_TO_MCP_SERVER_LABEL:
output_items.extend(_parse_reasoning(message))
# All other recipients are MCP calls
else:
output_items.extend(_parse_mcp_call(message, recipient))
# No recipient - handle based on channel for non-tool messages
else:
output_items.extend(_parse_message_no_recipient(message))
return output_items
def parse_remaining_state(parser: StreamableParser) -> list[ResponseOutputItem]:
if not parser.current_content:
return []
if parser.current_role != Role.ASSISTANT:
return []
current_recipient = parser.current_recipient
if current_recipient is not None and current_recipient.startswith("browser."):
return []
if current_recipient and parser.current_channel in ("commentary", "analysis"):
if current_recipient.startswith("functions."):
rid = random_uuid()
return [
ResponseFunctionToolCall(
arguments=parser.current_content,
call_id=f"call_{rid}",
type="function_call",
name=current_recipient.split(".")[-1],
id=f"fc_{rid}",
status="in_progress",
)
]
# Built-in MCP tools (python, browser, container)
elif current_recipient in _BUILTIN_TOOL_TO_MCP_SERVER_LABEL:
return [
ResponseReasoningItem(
id=f"rs_{random_uuid()}",
summary=[],
type="reasoning",
content=[
ResponseReasoningTextContent(
text=parser.current_content, type="reasoning_text"
)
],
status=None,
)
]
# All other recipients are MCP calls
else:
rid = random_uuid()
server_label, tool_name = _parse_mcp_recipient(current_recipient)
return [
McpCall(
arguments=parser.current_content,
type="mcp_call",
name=tool_name,
server_label=server_label,
id=f"mcp_{rid}",
status="in_progress",
)
]
if parser.current_channel == "commentary":
# Per Harmony format, preambles (commentary with no recipient) are
# intended to be shown to end-users, unlike analysis channel content.
output_text = ResponseOutputText(
text=parser.current_content,
annotations=[],
type="output_text",
logprobs=None,
)
return [
ResponseOutputMessage(
id=f"msg_{random_uuid()}",
content=[output_text],
role="assistant",
status="incomplete",
type="message",
)
]
if parser.current_channel == "analysis":
return [
ResponseReasoningItem(
id=f"rs_{random_uuid()}",
summary=[],
type="reasoning",
content=[
ResponseReasoningTextContent(
text=parser.current_content, type="reasoning_text"
)
],
status=None,
)
]
if parser.current_channel == "final":
output_text = ResponseOutputText(
text=parser.current_content,
annotations=[], # TODO
type="output_text",
logprobs=None, # TODO
)
text_item = ResponseOutputMessage(
id=f"msg_{random_uuid()}",
content=[output_text],
role="assistant",
# if the parser still has messages (ie if the generator got cut
# abruptly), this should be incomplete
status="incomplete",
type="message",
)
return [text_item]
return []
def get_stop_tokens_for_assistant_actions() -> list[int]: def get_stop_tokens_for_assistant_actions() -> list[int]:
return get_encoding().stop_tokens_for_assistant_actions() return get_encoding().stop_tokens_for_assistant_actions()
......
vllm/entrypoints/openai/responses/harmony.py 0 → 100644
View file @ 186ea22e
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Harmony ↔ Responses API conversion utilities.
Handles two directions:
1. Response Input → Harmony Messages (input parsing)
2. Harmony Messages → Response Output Items (output parsing)
"""
import json
from openai.types.responses import (
ResponseFunctionToolCall,
ResponseOutputItem,
ResponseOutputMessage,
ResponseOutputText,
ResponseReasoningItem,
)
from openai.types.responses.response_function_web_search import (
ActionFind,
ActionOpenPage,
ActionSearch,
ResponseFunctionWebSearch,
)
from openai.types.responses.response_output_item import McpCall
from openai.types.responses.response_reasoning_item import (
Content as ResponseReasoningTextContent,
)
from openai_harmony import Author, Message, Role, StreamableParser, TextContent
from vllm.entrypoints.openai.parser.harmony_utils import (
BUILTIN_TOOL_TO_MCP_SERVER_LABEL,
flatten_chat_text_content,
)
from vllm.entrypoints.openai.responses.protocol import (
ResponseInputOutputItem,
ResponsesRequest,
)
from vllm.logger import init_logger
from vllm.utils import random_uuid
logger = init_logger(__name__)
# ---------------------------------------------------------------------------
# 1. Private helpers for input parsing
# ---------------------------------------------------------------------------
def _parse_harmony_format_message(chat_msg: dict) -> Message:
"""Reconstruct a Message from Harmony-format dict,
preserving channel, recipient, and content_type."""
author_dict = chat_msg["author"]
role = author_dict.get("role")
name = author_dict.get("name")
raw_content = chat_msg.get("content", "")
if isinstance(raw_content, list):
# TODO: Support refusal and non-text content types.
contents = [TextContent(text=c.get("text", "")) for c in raw_content]
elif isinstance(raw_content, str):
contents = [TextContent(text=raw_content)]
else:
contents = [TextContent(text="")]
if name:
msg = Message.from_author_and_contents(Author.new(Role(role), name), contents)
else:
msg = Message.from_role_and_contents(Role(role), contents)
channel = chat_msg.get("channel")
if channel:
msg = msg.with_channel(channel)
recipient = chat_msg.get("recipient")
if recipient:
msg = msg.with_recipient(recipient)
content_type = chat_msg.get("content_type")
if content_type:
msg = msg.with_content_type(content_type)
return msg
def _parse_chat_format_message(chat_msg: dict) -> list[Message]:
"""Parse an OpenAI chat-format dict into Harmony messages."""
role = chat_msg.get("role")
if role is None:
raise ValueError(f"Message has no 'role' key: {chat_msg}")
# Assistant message with tool calls
tool_calls = chat_msg.get("tool_calls")
if role == "assistant" and tool_calls:
msgs: list[Message] = []
for call in tool_calls:
func = call.get("function", {})
name = func.get("name", "")
arguments = func.get("arguments", "") or ""
msg = Message.from_role_and_content(Role.ASSISTANT, arguments)
msg = msg.with_channel("commentary")
msg = msg.with_recipient(f"functions.{name}")
msg = msg.with_content_type("json")
msgs.append(msg)
return msgs
# Tool role message (tool output)
if role == "tool":
name = chat_msg.get("name", "")
if name and not name.startswith("functions."):
name = f"functions.{name}"
content = chat_msg.get("content", "") or ""
content = flatten_chat_text_content(content)
# NOTE: .with_recipient("assistant") is required on tool messages
# to match parse_chat_input_to_harmony_message behavior and ensure
# proper routing in the Harmony protocol.
msg = (
Message.from_author_and_content(Author.new(Role.TOOL, name), content)
.with_channel("commentary")
.with_recipient("assistant")
)
return [msg]
# Default: user/assistant/system messages
content = chat_msg.get("content", "")
if isinstance(content, str):
contents = [TextContent(text=content)]
else:
# TODO: Support refusal.
contents = [TextContent(text=c.get("text", "")) for c in content]
msg = Message.from_role_and_contents(role, contents)
return [msg]
# ---------------------------------------------------------------------------
# 2. Public input parsing functions
# ---------------------------------------------------------------------------
def response_input_to_harmony(
response_msg: ResponseInputOutputItem,
prev_responses: list[ResponseOutputItem | ResponseReasoningItem],
) -> Message:
"""Convert a single ResponseInputOutputItem into a Harmony Message."""
if not isinstance(response_msg, dict):
response_msg = response_msg.model_dump()
if "type" not in response_msg or response_msg["type"] == "message":
role = response_msg["role"]
content = response_msg["content"]
# Add prefix for developer messages.
# <|start|>developer<|message|># Instructions {instructions}<|end|>
text_prefix = "Instructions:\n" if role == "developer" else ""
if isinstance(content, str):
msg = Message.from_role_and_content(role, text_prefix + content)
else:
contents = [TextContent(text=text_prefix + c["text"]) for c in content]
msg = Message.from_role_and_contents(role, contents)
if role == "assistant":
msg = msg.with_channel("final")
elif response_msg["type"] == "function_call_output":
call_id = response_msg["call_id"]
call_response: ResponseFunctionToolCall | None = None
for prev_response in reversed(prev_responses):
if (
isinstance(prev_response, ResponseFunctionToolCall)
and prev_response.call_id == call_id
):
call_response = prev_response
break
if call_response is None:
raise ValueError(f"No call message found for {call_id}")
msg = Message.from_author_and_content(
Author.new(Role.TOOL, f"functions.{call_response.name}"),
response_msg["output"],
)
elif response_msg["type"] == "reasoning":
content = response_msg["content"]
assert len(content) == 1
msg = Message.from_role_and_content(Role.ASSISTANT, content[0]["text"])
elif response_msg["type"] == "function_call":
msg = Message.from_role_and_content(Role.ASSISTANT, response_msg["arguments"])
msg = msg.with_channel("commentary")
msg = msg.with_recipient(f"functions.{response_msg['name']}")
msg = msg.with_content_type("json")
else:
raise ValueError(f"Unknown input type: {response_msg['type']}")
return msg
def response_previous_input_to_harmony(chat_msg) -> list[Message]:
"""Parse a message from request.previous_input_messages
into Harmony messages.
Supports both OpenAI chat format ({"role": "..."}) and
Harmony format ({"author": {"role": "..."}}).
"""
if not isinstance(chat_msg, dict):
chat_msg = chat_msg.model_dump(exclude_none=True)
if "author" in chat_msg and isinstance(chat_msg.get("author"), dict):
return [_parse_harmony_format_message(chat_msg)]
return _parse_chat_format_message(chat_msg)
def construct_harmony_previous_input_messages(
request: ResponsesRequest,
) -> list[Message]:
"""Build a Harmony message list from request.previous_input_messages.
Filters out system/developer messages to match OpenAI behavior where
instructions are always taken from the most recent Responses API request.
"""
messages: list[Message] = []
if request.previous_input_messages:
for message in request.previous_input_messages:
# Handle both Message objects and dictionary inputs
if isinstance(message, Message):
message_role = message.author.role
if message_role == Role.SYSTEM or message_role == Role.DEVELOPER:
continue
messages.append(message)
else:
harmony_messages = response_previous_input_to_harmony(message)
for harmony_msg in harmony_messages:
message_role = harmony_msg.author.role
if message_role == Role.SYSTEM or message_role == Role.DEVELOPER:
continue
messages.append(harmony_msg)
return messages
# ---------------------------------------------------------------------------
# 3. Private helpers for output parsing
# ---------------------------------------------------------------------------
def _parse_browser_tool_call(message: Message, recipient: str) -> ResponseOutputItem:
"""Parse browser tool calls (search, open, find) into web search items."""
if len(message.content) != 1:
raise ValueError("Invalid number of contents in browser message")
content = message.content[0]
# Parse JSON args (with retry detection)
try:
browser_call = json.loads(content.text)
except json.JSONDecodeError:
logger.warning(
"Invalid JSON in browser tool call, using error placeholder: %s",
content.text,
)
json_retry_output_message = (
f"Invalid JSON args, caught and retried: {content.text}"
)
browser_call = {
"query": json_retry_output_message,
"url": json_retry_output_message,
"pattern": json_retry_output_message,
}
# Create appropriate action based on recipient
if recipient == "browser.search":
action = ActionSearch(
query=f"cursor:{browser_call.get('query', '')}", type="search"
)
elif recipient == "browser.open":
action = ActionOpenPage(
url=f"cursor:{browser_call.get('url', '')}", type="open_page"
)
elif recipient == "browser.find":
action = ActionFind(
pattern=browser_call.get("pattern", ""),
url=f"cursor:{browser_call.get('url', '')}",
type="find",
)
else:
raise ValueError(f"Unknown browser action: {recipient}")
return ResponseFunctionWebSearch(
id=f"ws_{random_uuid()}",
action=action,
status="completed",
type="web_search_call",
)
def _parse_function_call(message: Message, recipient: str) -> list[ResponseOutputItem]:
"""Parse function calls into function tool call items."""
function_name = recipient.split(".")[-1]
output_items = []
for content in message.content:
random_id = random_uuid()
response_item = ResponseFunctionToolCall(
arguments=content.text,
call_id=f"call_{random_id}",
type="function_call",
name=function_name,
id=f"fc_{random_id}",
)
output_items.append(response_item)
return output_items
def _parse_reasoning(message: Message) -> list[ResponseOutputItem]:
"""Parse reasoning/analysis content into reasoning items."""
output_items = []
for content in message.content:
reasoning_item = ResponseReasoningItem(
id=f"rs_{random_uuid()}",
summary=[],
type="reasoning",
content=[
ResponseReasoningTextContent(text=content.text, type="reasoning_text")
],
status=None,
)
output_items.append(reasoning_item)
return output_items
def _parse_final_message(message: Message) -> ResponseOutputItem:
"""Parse final channel messages into output message items."""
contents = []
for content in message.content:
output_text = ResponseOutputText(
text=content.text,
annotations=[], # TODO
type="output_text",
logprobs=None, # TODO
)
contents.append(output_text)
return ResponseOutputMessage(
id=f"msg_{random_uuid()}",
content=contents,
role=message.author.role,
status="completed",
type="message",
)
def _parse_mcp_recipient(recipient: str) -> tuple[str, str]:
"""Parse MCP recipient into (server_label, tool_name).
For dotted recipients like "repo_browser.list":
- server_label: "repo_browser" (namespace/server)
- tool_name: "list" (specific tool)
For simple recipients like "filesystem":
- server_label: "filesystem"
- tool_name: "filesystem"
"""
if "." in recipient:
server_label = recipient.split(".")[0]
tool_name = recipient.split(".")[-1]
else:
server_label = recipient
tool_name = recipient
return server_label, tool_name
def _parse_mcp_call(message: Message, recipient: str) -> list[ResponseOutputItem]:
"""Parse MCP calls into MCP call items."""
# Handle built-in tools that need server_label mapping
if recipient in BUILTIN_TOOL_TO_MCP_SERVER_LABEL:
server_label = BUILTIN_TOOL_TO_MCP_SERVER_LABEL[recipient]
tool_name = recipient
else:
server_label, tool_name = _parse_mcp_recipient(recipient)
output_items = []
for content in message.content:
response_item = McpCall(
arguments=content.text,
type="mcp_call",
name=tool_name,
server_label=server_label,
id=f"mcp_{random_uuid()}",
status="completed",
)
output_items.append(response_item)
return output_items
def _parse_message_no_recipient(
message: Message,
) -> list[ResponseOutputItem]:
"""Parse a Harmony message with no recipient based on its channel."""
if message.channel == "analysis":
return _parse_reasoning(message)
if message.channel in ("commentary", "final"):
# Per Harmony format, preambles (commentary with no recipient) and
# final channel content are both intended to be shown to end-users.
# See: https://cookbook.openai.com/articles/openai-harmony
return [_parse_final_message(message)]
raise ValueError(f"Unknown channel: {message.channel}")
# ---------------------------------------------------------------------------
# 4. Public output parsing functions
# ---------------------------------------------------------------------------
def harmony_to_response_output(message: Message) -> list[ResponseOutputItem]:
"""Parse a Harmony message into a list of output response items.
This is the main dispatcher that routes based on channel and recipient.
"""
if message.author.role != "assistant":
# This is a message from a tool to the assistant (e.g., search result).
# Don't include it in the final output for now. This aligns with
# OpenAI's behavior on models like o4-mini.
return []
output_items: list[ResponseOutputItem] = []
recipient = message.recipient
if recipient is not None:
# Browser tool calls (browser.search, browser.open, browser.find)
if recipient.startswith("browser."):
output_items.append(_parse_browser_tool_call(message, recipient))
# Function calls (should only happen on commentary channel)
elif message.channel == "commentary" and recipient.startswith("functions."):
output_items.extend(_parse_function_call(message, recipient))
# Built-in MCP tools (python, browser, container)
elif recipient in BUILTIN_TOOL_TO_MCP_SERVER_LABEL:
output_items.extend(_parse_reasoning(message))
# All other recipients are MCP calls
else:
output_items.extend(_parse_mcp_call(message, recipient))
# No recipient - handle based on channel for non-tool messages
else:
output_items.extend(_parse_message_no_recipient(message))
return output_items
def parser_state_to_response_output(
parser: StreamableParser,
) -> list[ResponseOutputItem]:
"""Extract in-progress response items from incomplete parser state.
Called when the parser has buffered content that hasn't formed a
complete message yet (e.g., generation was cut short).
"""
if not parser.current_content:
return []
if parser.current_role != Role.ASSISTANT:
return []
current_recipient = parser.current_recipient
if current_recipient is not None and current_recipient.startswith("browser."):
return []
if current_recipient and parser.current_channel in ("commentary", "analysis"):
if current_recipient.startswith("functions."):
rid = random_uuid()
return [
ResponseFunctionToolCall(
arguments=parser.current_content,
call_id=f"call_{rid}",
type="function_call",
name=current_recipient.split(".")[-1],
id=f"fc_{rid}",
status="in_progress",
)
]
# Built-in MCP tools (python, browser, container)
elif current_recipient in BUILTIN_TOOL_TO_MCP_SERVER_LABEL:
return [
ResponseReasoningItem(
id=f"rs_{random_uuid()}",
summary=[],
type="reasoning",
content=[
ResponseReasoningTextContent(
text=parser.current_content, type="reasoning_text"
)
],
status=None,
)
]
# All other recipients are MCP calls
else:
rid = random_uuid()
server_label, tool_name = _parse_mcp_recipient(current_recipient)
return [
McpCall(
arguments=parser.current_content,
type="mcp_call",
name=tool_name,
server_label=server_label,
id=f"mcp_{rid}",
status="in_progress",
)
]
if parser.current_channel == "commentary":
# Per Harmony format, preambles (commentary with no recipient) are
# intended to be shown to end-users, unlike analysis channel content.
output_text = ResponseOutputText(
text=parser.current_content,
annotations=[],
type="output_text",
logprobs=None,
)
return [
ResponseOutputMessage(
id=f"msg_{random_uuid()}",
content=[output_text],
role="assistant",
status="incomplete",
type="message",
)
]
if parser.current_channel == "analysis":
return [
ResponseReasoningItem(
id=f"rs_{random_uuid()}",
summary=[],
type="reasoning",
content=[
ResponseReasoningTextContent(
text=parser.current_content, type="reasoning_text"
)
],
status=None,
)
]
if parser.current_channel == "final":
output_text = ResponseOutputText(
text=parser.current_content,
annotations=[], # TODO
type="output_text",
logprobs=None, # TODO
)
text_item = ResponseOutputMessage(
id=f"msg_{random_uuid()}",
content=[output_text],
role="assistant",
# if the parser still has messages (ie if the generator got cut
# abruptly), this should be incomplete
status="incomplete",
type="message",
)
return [text_item]
return []
vllm/entrypoints/openai/responses/serving.py
View file @ 186ea22e
...@@ -58,15 +58,11 @@ from vllm.entrypoints.openai.engine.serving import ( ...@@ -58,15 +58,11 @@ from vllm.entrypoints.openai.engine.serving import (
) )
from vllm.entrypoints.openai.models.serving import OpenAIServingModels from vllm.entrypoints.openai.models.serving import OpenAIServingModels
from vllm.entrypoints.openai.parser.harmony_utils import ( from vllm.entrypoints.openai.parser.harmony_utils import (
construct_harmony_previous_input_messages,
get_developer_message, get_developer_message,
get_stop_tokens_for_assistant_actions, get_stop_tokens_for_assistant_actions,
get_system_message, get_system_message,
get_user_message, get_user_message,
has_custom_tools, has_custom_tools,
parse_output_message,
parse_remaining_state,
parse_response_input,
render_for_completion, render_for_completion,
) )
from vllm.entrypoints.openai.responses.context import ( from vllm.entrypoints.openai.responses.context import (
...@@ -76,6 +72,12 @@ from vllm.entrypoints.openai.responses.context import ( ...@@ -76,6 +72,12 @@ from vllm.entrypoints.openai.responses.context import (
SimpleContext, SimpleContext,
StreamingHarmonyContext, StreamingHarmonyContext,
) )
from vllm.entrypoints.openai.responses.harmony import (
construct_harmony_previous_input_messages,
harmony_to_response_output,
parser_state_to_response_output,
response_input_to_harmony,
)
from vllm.entrypoints.openai.responses.protocol import ( from vllm.entrypoints.openai.responses.protocol import (
InputTokensDetails, InputTokensDetails,
OutputTokensDetails, OutputTokensDetails,
...@@ -954,9 +956,9 @@ class OpenAIServingResponses(OpenAIServing): ...@@ -954,9 +956,9 @@ class OpenAIServingResponses(OpenAIServing):
output_items: list[ResponseOutputItem] = [] output_items: list[ResponseOutputItem] = []
num_init_messages = context.num_init_messages num_init_messages = context.num_init_messages
for msg in context.messages[num_init_messages:]: for msg in context.messages[num_init_messages:]:
output_items.extend(parse_output_message(msg)) output_items.extend(harmony_to_response_output(msg))
# Handle the generation stopped in the middle (if any). # Handle the generation stopped in the middle (if any).
last_items = parse_remaining_state(context.parser) last_items = parser_state_to_response_output(context.parser)
if last_items: if last_items:
output_items.extend(last_items) output_items.extend(last_items)
return output_items return output_items
...@@ -1103,13 +1105,13 @@ class OpenAIServingResponses(OpenAIServing): ...@@ -1103,13 +1105,13 @@ class OpenAIServingResponses(OpenAIServing):
else: else:
prev_outputs = [] prev_outputs = []
for response_msg in request.input: for response_msg in request.input:
new_msg = parse_response_input(response_msg, prev_outputs) new_msg = response_input_to_harmony(response_msg, prev_outputs)
if new_msg.author.role != "system": if new_msg.author.role != "system":
messages.append(new_msg) messages.append(new_msg)
# User passes in a tool call request and its output. We need # User passes in a tool call request and its output. We need
# to add the tool call request to prev_outputs so that the # to add the tool call request to prev_outputs so that
# parse_response_input can find the tool call request when # response_input_to_harmony can find the tool call request when
# parsing the tool call output. # parsing the tool call output.
if isinstance(response_msg, ResponseFunctionToolCall): if isinstance(response_msg, ResponseFunctionToolCall):
prev_outputs.append(response_msg) prev_outputs.append(response_msg)
......
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