[gpt-oss] Add Tool/ConversationContext classes and harmony_utils (#22340)

Signed-off-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>
Co-authored-by: LiuXiaoxuanPKU <lilyliupku@gmail.com>
Co-authored-by: simon-mo <xmo@berkeley.edu>
Co-authored-by: Chen Zhang <zhangch99@outlook.com>
Co-authored-by: Hongxia Yang <62075498+hongxiayang@users.noreply.github.com>
Co-authored-by: Minseok Lee <47620120+minseokl@users.noreply.github.com>
Co-authored-by: Yongye Zhu <zyy1102000@gmail.com>
This commit is contained in:
Woosuk Kwon
2025-08-06 01:08:49 -07:00
committed by GitHub
parent fa00c5d75b
commit 178d03fbd6
3 changed files with 375 additions and 0 deletions

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# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import datetime
from typing import Literal, Optional
from openai.types.responses.tool import Tool
from openai_harmony import (Conversation, DeveloperContent,
HarmonyEncodingName, Message, ReasoningEffort,
Role, StreamableParser, SystemContent, TextContent,
ToolDescription, load_harmony_encoding)
REASONING_EFFORT = {
"high": ReasoningEffort.HIGH,
"medium": ReasoningEffort.MEDIUM,
"low": ReasoningEffort.LOW,
}
_harmony_encoding = None
def get_encoding():
global _harmony_encoding
if _harmony_encoding is None:
_harmony_encoding = load_harmony_encoding(
HarmonyEncodingName.HARMONY_GPT_OSS)
return _harmony_encoding
def get_system_message(
model_identity: Optional[str] = None,
reasoning_effort: Optional[Literal["high", "medium", "low"]] = None,
start_date: Optional[str] = None,
browser_description: Optional[str] = None,
python_description: Optional[str] = None,
) -> Message:
sys_msg_content = SystemContent.new()
if model_identity is not None:
sys_msg_content = sys_msg_content.with_model_identity(model_identity)
if reasoning_effort is not None:
sys_msg_content = sys_msg_content.with_reasoning_effort(
REASONING_EFFORT[reasoning_effort])
if start_date is None:
# NOTE(woosuk): This brings non-determinism in vLLM. Be careful.
start_date = datetime.datetime.now().strftime("%Y-%m-%d")
sys_msg_content = sys_msg_content.with_conversation_start_date(start_date)
if browser_description is not None:
sys_msg_content = sys_msg_content.with_tools(browser_description)
if python_description is not None:
sys_msg_content = sys_msg_content.with_tools(python_description)
sys_msg = Message.from_role_and_content(Role.SYSTEM, sys_msg_content)
return sys_msg
def get_developer_message(instructions: Optional[str] = None,
tools: Optional[list[Tool]] = None) -> Message:
dev_msg_content = DeveloperContent.new()
if instructions is not None:
dev_msg_content = dev_msg_content.with_instructions(instructions)
if tools is not None:
function_tools = []
for tool in tools:
if tool.type in ("web_search_preview", "code_interpreter"):
# These are built-in tools that are added to the system message.
pass
elif tool.type == "function":
function_tools.append(tool)
else:
raise ValueError(f"tool type {tool.type} not supported")
if function_tools:
function_tool_descriptions = [
ToolDescription.new(
name=tool.name,
description=tool.description,
parameters=tool.parameters,
) for tool in function_tools
]
dev_msg_content = dev_msg_content.with_function_tools(
function_tool_descriptions)
dev_msg = Message.from_role_and_content(Role.DEVELOPER, dev_msg_content)
return dev_msg
def get_user_message(content: str) -> Message:
return Message.from_role_and_content(Role.USER, content)
def parse_chat_input(chat_msg) -> Message:
role = chat_msg["role"]
content = chat_msg["content"]
if isinstance(content, str):
contents = [TextContent(text=content)]
else:
# TODO: Support refusal.
contents = [TextContent(text=c["text"]) for c in content]
msg = Message.from_role_and_contents(role, contents)
return msg
def render_for_completion(messages: list[Message]) -> list[int]:
conversation = Conversation.from_messages(messages)
token_ids = get_encoding().render_conversation_for_completion(
conversation, Role.ASSISTANT)
return token_ids
def get_stop_tokens_for_assistant_actions() -> list[int]:
return get_encoding().stop_tokens_for_assistant_actions()
def get_streamable_parser_for_assistant() -> StreamableParser:
return StreamableParser(get_encoding(), role=Role.ASSISTANT)