Files
LangBot/src/langbot/libs/deerflow_api/stream_utils.py
Typer_Body 07b90f12a2 ruff3
2026-06-07 02:38:05 +08:00

213 lines
6.9 KiB
Python

"""DeerFlow LangGraph 流式响应解析工具
参考 astrbot 实现的 deerflow_stream_utils。
"""
from __future__ import annotations
import typing
from collections.abc import Iterable
def extract_text(content: typing.Any) -> str:
"""从消息 content 中提取纯文本"""
if isinstance(content, str):
return content
if isinstance(content, dict):
if isinstance(content.get('text'), str):
return content['text']
if 'content' in content:
return extract_text(content.get('content'))
if 'kwargs' in content and isinstance(content['kwargs'], dict):
return extract_text(content['kwargs'].get('content'))
if isinstance(content, list):
parts: list[str] = []
for item in content:
if isinstance(item, str):
parts.append(item)
elif isinstance(item, dict):
item_type = item.get('type')
if item_type == 'text' and isinstance(item.get('text'), str):
parts.append(item['text'])
elif 'content' in item:
parts.append(extract_text(item['content']))
return '\n'.join([p for p in parts if p]).strip()
return str(content) if content is not None else ''
def extract_messages_from_values_data(data: typing.Any) -> list[typing.Any]:
"""从 values 事件中提取 messages 列表"""
candidates: list[typing.Any] = []
if isinstance(data, dict):
candidates.append(data)
if isinstance(data.get('values'), dict):
candidates.append(data['values'])
elif isinstance(data, list):
candidates.extend([x for x in data if isinstance(x, dict)])
for item in candidates:
messages = item.get('messages')
if isinstance(messages, list):
return messages
return []
def is_ai_message(message: dict[str, typing.Any]) -> bool:
"""判断是否为 AI/assistant 消息"""
role = str(message.get('role', '')).lower()
if role in {'assistant', 'ai'}:
return True
msg_type = str(message.get('type', '')).lower()
if msg_type in {'ai', 'assistant', 'aimessage', 'aimessagechunk'}:
return True
if 'ai' in msg_type and all(token not in msg_type for token in ('human', 'tool', 'system')):
return True
return False
def extract_latest_ai_text(messages: Iterable[typing.Any]) -> str:
"""获取最近一条 AI 消息的文本内容"""
if isinstance(messages, (list, tuple)):
iterable = reversed(messages)
else:
iterable = reversed(list(messages))
for msg in iterable:
if not isinstance(msg, dict):
continue
if is_ai_message(msg):
text = extract_text(msg.get('content'))
if text:
return text
return ''
def extract_latest_ai_message(messages: Iterable[typing.Any]) -> dict[str, typing.Any] | None:
"""获取最近一条 AI 消息对象"""
if isinstance(messages, (list, tuple)):
iterable = reversed(messages)
else:
iterable = reversed(list(messages))
for msg in iterable:
if not isinstance(msg, dict):
continue
if is_ai_message(msg):
return msg
return None
def is_clarification_tool_message(message: dict[str, typing.Any]) -> bool:
"""判断是否为澄清问题工具消息"""
msg_type = str(message.get('type', '')).lower()
tool_name = str(message.get('name', '')).lower()
return msg_type == 'tool' and tool_name == 'ask_clarification'
def extract_latest_clarification_text(messages: Iterable[typing.Any]) -> str:
"""提取最近的澄清问题文本"""
if isinstance(messages, (list, tuple)):
iterable = reversed(messages)
else:
iterable = reversed(list(messages))
for msg in iterable:
if not isinstance(msg, dict):
continue
if is_clarification_tool_message(msg):
text = extract_text(msg.get('content'))
if text:
return text
return ''
def get_message_id(message: typing.Any) -> str:
"""提取消息 ID"""
if not isinstance(message, dict):
return ''
msg_id = message.get('id')
return msg_id if isinstance(msg_id, str) else ''
def extract_event_message_obj(data: typing.Any) -> dict[str, typing.Any] | None:
"""从事件 data 中提取消息对象"""
msg_obj = data
if isinstance(data, (list, tuple)) and data:
msg_obj = data[0]
if isinstance(msg_obj, dict) and isinstance(msg_obj.get('data'), dict):
msg_obj = msg_obj['data']
return msg_obj if isinstance(msg_obj, dict) else None
def extract_ai_delta_from_event_data(data: typing.Any) -> str:
"""从 messages-tuple 事件中提取 AI delta 文本"""
msg_obj = extract_event_message_obj(data)
if not msg_obj:
return ''
if is_ai_message(msg_obj):
return extract_text(msg_obj.get('content'))
return ''
def extract_clarification_from_event_data(data: typing.Any) -> str:
"""从事件中提取澄清问题"""
msg_obj = extract_event_message_obj(data)
if not msg_obj:
return ''
if is_clarification_tool_message(msg_obj):
return extract_text(msg_obj.get('content'))
return ''
def _iter_custom_event_items(data: typing.Any) -> list[dict[str, typing.Any]]:
items: list[dict[str, typing.Any]] = []
if isinstance(data, dict):
return [data]
if isinstance(data, list):
for item in data:
if isinstance(item, dict):
items.append(item)
elif isinstance(item, (list, tuple)):
for nested in item:
if isinstance(nested, dict):
items.append(nested)
return items
def extract_task_failures_from_custom_event(data: typing.Any) -> list[str]:
"""从 custom 事件中提取子任务失败信息"""
failures: list[str] = []
for item in _iter_custom_event_items(data):
event_type = str(item.get('type', '')).lower()
if event_type not in {'task_failed', 'task_timed_out'}:
continue
task_id = str(item.get('task_id', '')).strip()
error_text = extract_text(item.get('error')).strip()
if task_id and error_text:
failures.append(f'{task_id}: {error_text}')
elif error_text:
failures.append(error_text)
elif task_id:
failures.append(f'{task_id}: unknown error')
else:
failures.append('unknown task failure')
return failures
def build_task_failure_summary(failures: list[str]) -> str:
"""构建任务失败摘要"""
if not failures:
return ''
deduped: list[str] = []
seen: set[str] = set()
for failure in failures:
if failure not in seen:
seen.add(failure)
deduped.append(failure)
if len(deduped) == 1:
return f'DeerFlow subtask failed: {deduped[0]}'
joined = '\n'.join([f'- {item}' for item in deduped[:5]])
return f'DeerFlow subtasks failed:\n{joined}'