mirror of
https://github.com/langbot-app/LangBot.git
synced 2026-06-13 01:06:03 +00:00
deerflow
This commit is contained in:
Typer_Body
5
src/langbot/libs/deerflow_api/__init__.py
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5
src/langbot/libs/deerflow_api/__init__.py
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from .client import AsyncDeerFlowClient
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from .errors import DeerFlowAPIError
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from . import stream_utils
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__all__ = ['AsyncDeerFlowClient', 'DeerFlowAPIError', 'stream_utils']
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203
src/langbot/libs/deerflow_api/client.py
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203
src/langbot/libs/deerflow_api/client.py
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"""DeerFlow LangGraph HTTP API 客户端
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参考 astrbot 的 deerflow_api_client 实现，使用 httpx 适配 LangBot 风格。
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"""
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from __future__ import annotations
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import codecs
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import json
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import typing
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from collections.abc import AsyncGenerator
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import httpx
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from .errors import DeerFlowAPIError
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SSE_MAX_BUFFER_CHARS = 1_048_576
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def _normalize_sse_newlines(text: str) -> str:
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"""规范化 CRLF/CR 为 LF，确保 SSE 块分割稳定"""
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return text.replace('\r\n', '\n').replace('\r', '\n')
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def _parse_sse_data_lines(data_lines: list[str]) -> typing.Any:
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raw_data = '\n'.join(data_lines)
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try:
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return json.loads(raw_data)
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except json.JSONDecodeError:
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# 某些 LangGraph 兼容服务端会在单个 SSE 事件中用多个 data 行
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# 发送多段 JSON 片段（例如 tuple payload）
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parsed_lines: list[typing.Any] = []
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can_parse_all = True
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for line in data_lines:
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line = line.strip()
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if not line:
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continue
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try:
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parsed_lines.append(json.loads(line))
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except json.JSONDecodeError:
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can_parse_all = False
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break
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if can_parse_all and parsed_lines:
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return parsed_lines[0] if len(parsed_lines) == 1 else parsed_lines
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return raw_data
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def _parse_sse_block(block: str) -> dict[str, typing.Any] | None:
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if not block.strip():
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return None
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event_name = 'message'
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data_lines: list[str] = []
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for line in block.splitlines():
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if line.startswith('event:'):
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event_name = line[6:].strip()
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elif line.startswith('data:'):
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data_lines.append(line[5:].lstrip())
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if not data_lines:
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return None
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return {'event': event_name, 'data': _parse_sse_data_lines(data_lines)}
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class AsyncDeerFlowClient:
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"""DeerFlow LangGraph HTTP API 客户端"""
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api_base: str
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headers: dict[str, str]
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def __init__(
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self,
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api_base: str = 'http://127.0.0.1:2026',
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api_key: str = '',
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auth_header: str = '',
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) -> None:
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self.api_base = api_base.rstrip('/')
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self.headers: dict[str, str] = {}
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if auth_header:
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self.headers['Authorization'] = auth_header
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elif api_key:
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self.headers['Authorization'] = f'Bearer {api_key}'
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async def create_thread(self, timeout: float = 20) -> dict[str, typing.Any]:
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"""创建一个新的 LangGraph thread
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Returns:
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包含 thread_id 等信息的字典
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"""
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url = f'{self.api_base}/api/langgraph/threads'
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payload = {'metadata': {}}
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async with httpx.AsyncClient(
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trust_env=True,
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timeout=timeout,
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) as client:
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response = await client.post(
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url,
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headers=self.headers,
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json=payload,
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)
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if response.status_code not in (200, 201):
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raise DeerFlowAPIError(
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operation='create thread',
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status=response.status_code,
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body=response.text,
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url=url,
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)
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return response.json()
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async def delete_thread(self, thread_id: str, timeout: float = 20) -> None:
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"""删除指定 thread"""
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url = f'{self.api_base}/api/threads/{thread_id}'
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async with httpx.AsyncClient(
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trust_env=True,
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timeout=timeout,
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) as client:
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response = await client.delete(url, headers=self.headers)
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if response.status_code not in (200, 202, 204, 404):
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raise DeerFlowAPIError(
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operation='delete thread',
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status=response.status_code,
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body=response.text,
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url=url,
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thread_id=thread_id,
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)
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async def stream_run(
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self,
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thread_id: str,
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payload: dict[str, typing.Any],
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timeout: float = 120,
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) -> AsyncGenerator[dict[str, typing.Any], None]:
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"""运行一次 LangGraph stream 请求，逐事件 yield
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Yields:
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事件字典 {'event': event_name, 'data': parsed_data}
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"""
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url = f'{self.api_base}/api/langgraph/threads/{thread_id}/runs/stream'
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# 流式请求使用单独的 read timeout 控制
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stream_timeout = httpx.Timeout(
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connect=min(timeout, 30),
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read=timeout,
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write=timeout,
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pool=timeout,
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)
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async with httpx.AsyncClient(
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trust_env=True,
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timeout=stream_timeout,
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) as client:
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async with client.stream(
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'POST',
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url,
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headers={
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**self.headers,
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'Accept': 'text/event-stream',
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'Content-Type': 'application/json',
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},
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json=payload,
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) as resp:
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if resp.status_code != 200:
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body = await resp.aread()
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raise DeerFlowAPIError(
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operation='runs/stream request',
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status=resp.status_code,
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body=body.decode('utf-8', errors='replace'),
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url=url,
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thread_id=thread_id,
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)
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decoder = codecs.getincrementaldecoder('utf-8')('replace')
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buffer = ''
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async for chunk in resp.aiter_bytes(8192):
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buffer += _normalize_sse_newlines(decoder.decode(chunk))
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while '\n\n' in buffer:
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block, buffer = buffer.split('\n\n', 1)
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parsed = _parse_sse_block(block)
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if parsed is not None:
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yield parsed
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if len(buffer) > SSE_MAX_BUFFER_CHARS:
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# 缓冲区过大，强制 flush
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parsed = _parse_sse_block(buffer)
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if parsed is not None:
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yield parsed
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buffer = ''
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# flush 剩余内容
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buffer += _normalize_sse_newlines(decoder.decode(b'', final=True))
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while '\n\n' in buffer:
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block, buffer = buffer.split('\n\n', 1)
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parsed = _parse_sse_block(block)
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if parsed is not None:
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yield parsed
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if buffer.strip():
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parsed = _parse_sse_block(buffer)
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if parsed is not None:
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yield parsed
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33
src/langbot/libs/deerflow_api/errors.py
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33
src/langbot/libs/deerflow_api/errors.py
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from __future__ import annotations
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class DeerFlowAPIError(Exception):
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"""DeerFlow API 请求失败"""
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def __init__(
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self,
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*,
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operation: str = '',
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status: int = 0,
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body: str = '',
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url: str = '',
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thread_id: str | None = None,
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message: str = '',
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) -> None:
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self.operation = operation
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self.status = status
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self.body = body
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self.url = url
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self.thread_id = thread_id
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if message:
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super().__init__(message)
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return
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msg = f'DeerFlow {operation} failed: status={status}, url={url}, body={body}'
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if thread_id is not None:
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msg = (
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f'DeerFlow {operation} failed: thread_id={thread_id}, '
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f'status={status}, url={url}, body={body}'
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)
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super().__init__(msg)
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213
src/langbot/libs/deerflow_api/stream_utils.py
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213
src/langbot/libs/deerflow_api/stream_utils.py
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@@ -0,0 +1,213 @@
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"""DeerFlow LangGraph 流式响应解析工具
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参考 astrbot 实现的 deerflow_stream_utils。
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"""
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from __future__ import annotations
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import typing
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from collections.abc import Iterable
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def extract_text(content: typing.Any) -> str:
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"""从消息 content 中提取纯文本"""
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if isinstance(content, str):
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return content
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if isinstance(content, dict):
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if isinstance(content.get('text'), str):
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return content['text']
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if 'content' in content:
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return extract_text(content.get('content'))
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if 'kwargs' in content and isinstance(content['kwargs'], dict):
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return extract_text(content['kwargs'].get('content'))
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if isinstance(content, list):
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parts: list[str] = []
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for item in content:
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if isinstance(item, str):
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parts.append(item)
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elif isinstance(item, dict):
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item_type = item.get('type')
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if item_type == 'text' and isinstance(item.get('text'), str):
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parts.append(item['text'])
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elif 'content' in item:
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parts.append(extract_text(item['content']))
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return '\n'.join([p for p in parts if p]).strip()
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return str(content) if content is not None else ''
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def extract_messages_from_values_data(data: typing.Any) -> list[typing.Any]:
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"""从 values 事件中提取 messages 列表"""
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candidates: list[typing.Any] = []
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if isinstance(data, dict):
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candidates.append(data)
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if isinstance(data.get('values'), dict):
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candidates.append(data['values'])
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elif isinstance(data, list):
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candidates.extend([x for x in data if isinstance(x, dict)])
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for item in candidates:
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messages = item.get('messages')
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if isinstance(messages, list):
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return messages
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return []
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def is_ai_message(message: dict[str, typing.Any]) -> bool:
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"""判断是否为 AI/assistant 消息"""
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role = str(message.get('role', '')).lower()
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if role in {'assistant', 'ai'}:
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return True
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msg_type = str(message.get('type', '')).lower()
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if msg_type in {'ai', 'assistant', 'aimessage', 'aimessagechunk'}:
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return True
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if 'ai' in msg_type and all(
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token not in msg_type for token in ('human', 'tool', 'system')
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):
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return True
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return False
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def extract_latest_ai_text(messages: Iterable[typing.Any]) -> str:
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"""获取最近一条 AI 消息的文本内容"""
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if isinstance(messages, (list, tuple)):
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iterable = reversed(messages)
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else:
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iterable = reversed(list(messages))
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for msg in iterable:
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if not isinstance(msg, dict):
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continue
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if is_ai_message(msg):
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text = extract_text(msg.get('content'))
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if text:
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return text
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return ''
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def extract_latest_ai_message(messages: Iterable[typing.Any]) -> dict[str, typing.Any] | None:
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"""获取最近一条 AI 消息对象"""
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if isinstance(messages, (list, tuple)):
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iterable = reversed(messages)
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else:
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iterable = reversed(list(messages))
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for msg in iterable:
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if not isinstance(msg, dict):
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continue
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if is_ai_message(msg):
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return msg
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return None
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def is_clarification_tool_message(message: dict[str, typing.Any]) -> bool:
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"""判断是否为澄清问题工具消息"""
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msg_type = str(message.get('type', '')).lower()
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tool_name = str(message.get('name', '')).lower()
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return msg_type == 'tool' and tool_name == 'ask_clarification'
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def extract_latest_clarification_text(messages: Iterable[typing.Any]) -> str:
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"""提取最近的澄清问题文本"""
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if isinstance(messages, (list, tuple)):
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iterable = reversed(messages)
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else:
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iterable = reversed(list(messages))
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for msg in iterable:
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if not isinstance(msg, dict):
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continue
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if is_clarification_tool_message(msg):
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text = extract_text(msg.get('content'))
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if text:
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return text
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return ''
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def get_message_id(message: typing.Any) -> str:
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"""提取消息 ID"""
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if not isinstance(message, dict):
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return ''
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msg_id = message.get('id')
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return msg_id if isinstance(msg_id, str) else ''
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def extract_event_message_obj(data: typing.Any) -> dict[str, typing.Any] | None:
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"""从事件 data 中提取消息对象"""
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msg_obj = data
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if isinstance(data, (list, tuple)) and data:
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msg_obj = data[0]
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if isinstance(msg_obj, dict) and isinstance(msg_obj.get('data'), dict):
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msg_obj = msg_obj['data']
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return msg_obj if isinstance(msg_obj, dict) else None
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def extract_ai_delta_from_event_data(data: typing.Any) -> str:
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"""从 messages-tuple 事件中提取 AI delta 文本"""
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msg_obj = extract_event_message_obj(data)
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if not msg_obj:
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return ''
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if is_ai_message(msg_obj):
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return extract_text(msg_obj.get('content'))
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return ''
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def extract_clarification_from_event_data(data: typing.Any) -> str:
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"""从事件中提取澄清问题"""
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msg_obj = extract_event_message_obj(data)
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if not msg_obj:
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return ''
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if is_clarification_tool_message(msg_obj):
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return extract_text(msg_obj.get('content'))
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return ''
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def _iter_custom_event_items(data: typing.Any) -> list[dict[str, typing.Any]]:
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items: list[dict[str, typing.Any]] = []
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if isinstance(data, dict):
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return [data]
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if isinstance(data, list):
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for item in data:
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if isinstance(item, dict):
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items.append(item)
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elif isinstance(item, (list, tuple)):
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for nested in item:
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if isinstance(nested, dict):
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items.append(nested)
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return items
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def extract_task_failures_from_custom_event(data: typing.Any) -> list[str]:
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"""从 custom 事件中提取子任务失败信息"""
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failures: list[str] = []
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for item in _iter_custom_event_items(data):
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event_type = str(item.get('type', '')).lower()
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if event_type not in {'task_failed', 'task_timed_out'}:
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continue
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task_id = str(item.get('task_id', '')).strip()
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error_text = extract_text(item.get('error')).strip()
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if task_id and error_text:
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failures.append(f'{task_id}: {error_text}')
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elif error_text:
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failures.append(error_text)
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elif task_id:
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failures.append(f'{task_id}: unknown error')
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else:
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failures.append('unknown task failure')
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return failures
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def build_task_failure_summary(failures: list[str]) -> str:
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"""构建任务失败摘要"""
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if not failures:
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return ''
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deduped: list[str] = []
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seen: set[str] = set()
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for failure in failures:
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if failure not in seen:
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seen.add(failure)
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deduped.append(failure)
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if len(deduped) == 1:
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return f'DeerFlow subtask failed: {deduped[0]}'
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joined = '\n'.join([f'- {item}' for item in deduped[:5]])
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return f'DeerFlow subtasks failed:\n{joined}'
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