Files
LangBot/src/langbot/libs/weknora_api/client.py
T
Typer_Body 0c6f71738c deerflow
2026-06-07 02:17:40 +08:00

181 lines
5.7 KiB
Python

from __future__ import annotations
import httpx
import typing
import json
from .errors import WeKnoraAPIError
class AsyncWeKnoraClient:
"""WeKnora API 客户端"""
api_key: str
base_url: str
def __init__(
self,
api_key: str,
base_url: str = 'http://localhost:80/api/v1',
) -> None:
self.api_key = api_key
self.base_url = base_url
async def create_session(
self,
title: str = '',
description: str = '',
timeout: float = 30.0,
) -> str:
"""创建会话,返回 session_id"""
async with httpx.AsyncClient(
base_url=self.base_url,
trust_env=True,
timeout=timeout,
) as client:
payload: dict[str, typing.Any] = {}
if title:
payload['title'] = title
if description:
payload['description'] = description
response = await client.post(
'/sessions',
headers={
'X-API-Key': self.api_key,
'Content-Type': 'application/json',
},
json=payload,
)
if response.status_code not in (200, 201):
raise WeKnoraAPIError(f'{response.status_code} {response.text}')
data = response.json()
return data['data']['id']
async def agent_chat(
self,
session_id: str,
query: str,
user: str,
agent_id: str = '',
knowledge_base_ids: list[str] | None = None,
web_search_enabled: bool = False,
timeout: float = 120.0,
) -> typing.AsyncGenerator[dict[str, typing.Any], None]:
"""
Agent 智能对话(SSE 流式)
响应事件类型:
- agent_query: Agent 开始处理
- thinking: 思考过程
- tool_call: 工具调用
- tool_result: 工具结果
- references: 知识库引用
- answer: 回答内容
- reflection: 反思
- session_title: 会话标题
- error: 错误
"""
if knowledge_base_ids is None:
knowledge_base_ids = []
async with httpx.AsyncClient(
base_url=self.base_url,
trust_env=True,
timeout=timeout,
) as client:
payload: dict[str, typing.Any] = {
'query': query,
'agent_enabled': True,
'channel': 'im',
}
if agent_id:
payload['agent_id'] = agent_id
if knowledge_base_ids:
payload['knowledge_base_ids'] = knowledge_base_ids
if web_search_enabled:
payload['web_search_enabled'] = True
async with client.stream(
'POST',
f'/agent-chat/{session_id}',
headers={
'X-API-Key': self.api_key,
'Content-Type': 'application/json',
},
json=payload,
) as r:
async for chunk in r.aiter_lines():
if r.status_code != 200:
raise WeKnoraAPIError(f'{r.status_code} {chunk}')
if chunk.strip() == '':
continue
if chunk.startswith('data:'):
try:
data = json.loads(chunk[5:].strip())
except json.JSONDecodeError:
continue
yield data
# 收到 error 事件后主动结束流,避免上层未 raise 时持续等待
if data.get('response_type') == 'error':
return
async def knowledge_chat(
self,
session_id: str,
query: str,
user: str,
agent_id: str = 'builtin-quick-answer',
knowledge_base_ids: list[str] | None = None,
timeout: float = 120.0,
) -> typing.AsyncGenerator[dict[str, typing.Any], None]:
"""
知识库 RAG 问答(SSE 流式)
响应事件类型:
- references: 知识库引用
- answer: 回答内容
"""
if knowledge_base_ids is None:
knowledge_base_ids = []
async with httpx.AsyncClient(
base_url=self.base_url,
trust_env=True,
timeout=timeout,
) as client:
payload: dict[str, typing.Any] = {
'query': query,
'channel': 'im',
}
if agent_id:
payload['agent_id'] = agent_id
if knowledge_base_ids:
payload['knowledge_base_ids'] = knowledge_base_ids
async with client.stream(
'POST',
f'/knowledge-chat/{session_id}',
headers={
'X-API-Key': self.api_key,
'Content-Type': 'application/json',
},
json=payload,
) as r:
async for chunk in r.aiter_lines():
if r.status_code != 200:
raise WeKnoraAPIError(f'{r.status_code} {chunk}')
if chunk.strip() == '':
continue
if chunk.startswith('data:'):
try:
data = json.loads(chunk[5:].strip())
except json.JSONDecodeError:
continue
yield data
# 收到 error 事件后主动结束流,避免上层未 raise 时持续等待
if data.get('response_type') == 'error':
return