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Code Issues Packages Projects Releases Wiki Activity

feat:support dify message streaming output (#1437)

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* fix:lark adapter listeners init problem

* feat:support dify streaming mode

* feat:remove some log

* fix(bot form): field desc missing

* fix: not compatible with chatflow

---------

Co-authored-by: wangzejie <wangzejie@meicai.cn>
Co-authored-by: Junyan Qin <rockchinq@gmail.com>
This commit is contained in:
zejiewang
2025-05-18 12:03:01 +08:00
committed by Junyan Qin
parent 14411a8af6
commit 3c6e858c35
5 changed files with 180 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
pkg/platform/botmgr.py
View File

@@ -120,8 +120,10 @@ class RuntimeBot:
if isinstance(e, asyncio.CancelledError):
self.task_context.set_current_action('Exited.')
return
traceback_str = traceback.format_exc()
self.task_context.set_current_action('Exited with error.')
await self.logger.error(f'平台适配器运行出错:\n{e}\n{traceback.format_exc()}')
await self.logger.error(f'平台适配器运行出错:\n{e}\n{traceback_str}')
self.task_wrapper = self.ap.task_mgr.create_task(
exception_wrapper(),

108
pkg/platform/sources/lark.py
View File

@@ -9,6 +9,7 @@ import re
import base64
import uuid
import json
import time
import datetime
import hashlib
from Crypto.Cipher import AES
@@ -320,6 +321,10 @@ class LarkEventConverter(adapter.EventConverter):
)
CARD_ID_CACHE_SIZE = 500
CARD_ID_CACHE_MAX_LIFETIME = 20 * 60 # 20分钟
class LarkAdapter(adapter.MessagePlatformAdapter):
bot: lark_oapi.ws.Client
api_client: lark_oapi.Client
@@ -338,6 +343,8 @@ class LarkAdapter(adapter.MessagePlatformAdapter):
config: dict
quart_app: quart.Quart
ap: app.Application
message_id_to_card_id: typing.Dict[str, typing.Tuple[str, int]]
def __init__(self, config: dict, ap: app.Application, logger: EventLogger):
self.config = config
@@ -345,6 +352,7 @@ class LarkAdapter(adapter.MessagePlatformAdapter):
self.logger = logger
self.quart_app = quart.Quart(__name__)
self.listeners = {}
self.message_id_to_card_id = {}
@self.quart_app.route('/lark/callback', methods=['POST'])
async def lark_callback():
@@ -390,6 +398,19 @@ class LarkAdapter(adapter.MessagePlatformAdapter):
return {'code': 500, 'message': 'error'}
async def on_message(event: lark_oapi.im.v1.P2ImMessageReceiveV1):
if self.config['enable-card-reply'] and event.event.message.message_id not in self.message_id_to_card_id:
self.ap.logger.debug('卡片回复模式开启')
# 开启卡片回复模式. 这里可以实现飞书一发消息，马上创建卡片进行回复"思考中..."
reply_message_id = await self.create_message_card(event.event.message.message_id)
self.message_id_to_card_id[event.event.message.message_id] = (reply_message_id, time.time())
if len(self.message_id_to_card_id) > CARD_ID_CACHE_SIZE:
self.message_id_to_card_id = {
k: v
for k, v in self.message_id_to_card_id.items()
if v[1] > time.time() - CARD_ID_CACHE_MAX_LIFETIME
}
lb_event = await self.event_converter.target2yiri(event, self.api_client)
await self.listeners[type(lb_event)](lb_event, self)
@@ -409,11 +430,93 @@ class LarkAdapter(adapter.MessagePlatformAdapter):
async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
pass
async def create_message_card(self, message_id: str) -> str:
"""
创建卡片消息。
使用卡片消息是因为普通消息更新次数有限制，而大模型流式返回结果可能很多而超过限制，而飞书卡片没有这个限制
"""
# TODO 目前只支持卡片模板方式，且卡片变量一定是content，未来这块要做成可配置
# 发消息马上就会回复显示初始化的content信息，即思考中
content = {
'type': 'template',
'data': {'template_id': self.config['card_template_id'], 'template_variable': {'content': 'Thinking...'}},
}
request: ReplyMessageRequest = (
ReplyMessageRequest.builder()
.message_id(message_id)
.request_body(
ReplyMessageRequestBody.builder().content(json.dumps(content)).msg_type('interactive').build()
)
.build()
)
# 发起请求
response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request)
# 处理失败返回
if not response.success():
raise Exception(
f'client.im.v1.message.reply failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
)
return response.data.message_id
async def reply_message(
self,
message_source: platform_events.MessageEvent,
message: platform_message.MessageChain,
quote_origin: bool = False,
):
if self.config['enable-card-reply']:
await self.reply_card_message(message_source, message, quote_origin)
else:
await self.reply_normal_message(message_source, message, quote_origin)
async def reply_card_message(
self,
message_source: platform_events.MessageEvent,
message: platform_message.MessageChain,
quote_origin: bool = False,
):
"""
回复消息变成更新卡片消息
"""
lark_message = await self.message_converter.yiri2target(message, self.api_client)
text_message = ''
for ele in lark_message[0]:
if ele['tag'] == 'text':
text_message += ele['text']
elif ele['tag'] == 'md':
text_message += ele['text']
content = {
'type': 'template',
'data': {'template_id': self.config['card_template_id'], 'template_variable': {'content': text_message}},
}
request: PatchMessageRequest = (
PatchMessageRequest.builder()
.message_id(self.message_id_to_card_id[message_source.message_chain.message_id][0])
.request_body(PatchMessageRequestBody.builder().content(json.dumps(content)).build())
.build()
)
# 发起请求
response: PatchMessageResponse = self.api_client.im.v1.message.patch(request)
# 处理失败返回
if not response.success():
raise Exception(
f'client.im.v1.message.patch failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
)
return
async def reply_normal_message(
self,
message_source: platform_events.MessageEvent,
message: platform_message.MessageChain,
quote_origin: bool = False,
):
# 不再需要了，因为message_id已经被包含到message_chain中
# lark_event = await self.event_converter.yiri2target(message_source)
@@ -492,4 +595,9 @@ class LarkAdapter(adapter.MessagePlatformAdapter):
)
async def kill(self) -> bool:
# 需要断开连接，不然旧的连接会继续运行，导致飞书消息来时会随机选择一个连接
# 断开时lark.ws.Client的_receive_message_loop会打印error日志: receive message loop exit。然后进行重连，
# 所以要设置_auto_reconnect=False,让其不重连。
self.bot._auto_reconnect = False
await self.bot._disconnect()
return False

17
pkg/platform/sources/lark.yaml
View File

@@ -65,6 +65,23 @@ spec:
type: string
required: true
default: ""
- name: enable-card-reply
label:
en_US: Enable Card Reply Mode
zh_Hans: 启用飞书卡片回复模式
description:
en_US: If enabled, the bot will use the card of lark reply mode
zh_Hans: 如果启用，将使用飞书卡片方式来回复内容
type: boolean
required: true
default: false
- name: card_template_id
label:
en_US: card template id
zh_Hans: 卡片模板ID
type: string
required: true
default: "填写你的卡片template_id"
execution:
python:
path: ./lark.py

41
pkg/provider/runners/difysvapi.py
View File

@@ -108,7 +108,13 @@ class DifyServiceAPIRunner(runner.RequestRunner):
mode = 'basic' # 标记是基础编排还是工作流编排
basic_mode_pending_chunk = ''
stream_output_pending_chunk = ''
batch_pending_max_size = self.pipeline_config['ai']['dify-service-api'].get(
'output-batch-size', 0
) # 积累一定量的消息更新消息一次
batch_pending_index = 0
inputs = {}
@@ -126,6 +132,13 @@ class DifyServiceAPIRunner(runner.RequestRunner):
):
self.ap.logger.debug('dify-chat-chunk: ' + str(chunk))
# 查询异常情况
if chunk['event'] == 'error':
yield llm_entities.Message(
role='assistant',
content=f"查询异常: [{chunk['code']}]. {chunk['message']}.\n请重试，如果还报错，请用 <font color='red'>**!reset**</font> 命令重置对话再尝试。",
)
if chunk['event'] == 'workflow_started':
mode = 'workflow'
@@ -136,15 +149,35 @@ class DifyServiceAPIRunner(runner.RequestRunner):
role='assistant',
content=self._try_convert_thinking(chunk['data']['outputs']['answer']),
)
elif chunk['event'] == 'message':
stream_output_pending_chunk += chunk['answer']
if self.pipeline_config['ai']['dify-service-api'].get('enable-streaming', False):
# 消息数超过量就输出，从而达到streaming的效果
batch_pending_index += 1
if batch_pending_index >= batch_pending_max_size:
yield llm_entities.Message(
role='assistant',
content=self._try_convert_thinking(stream_output_pending_chunk),
)
batch_pending_index = 0
elif mode == 'basic':
if chunk['event'] == 'message':
basic_mode_pending_chunk += chunk['answer']
stream_output_pending_chunk += chunk['answer']
if self.pipeline_config['ai']['dify-service-api'].get('enable-streaming', False):
# 消息数超过量就输出，从而达到streaming的效果
batch_pending_index += 1
if batch_pending_index >= batch_pending_max_size:
yield llm_entities.Message(
role='assistant',
content=self._try_convert_thinking(stream_output_pending_chunk),
)
batch_pending_index = 0
elif chunk['event'] == 'message_end':
yield llm_entities.Message(
role='assistant',
content=self._try_convert_thinking(basic_mode_pending_chunk),
content=self._try_convert_thinking(stream_output_pending_chunk),
)
basic_mode_pending_chunk = ''
stream_output_pending_chunk = ''
if chunk is None:
raise errors.DifyAPIError('Dify API 没有返回任何响应，请检查网络连接和API配置')

15
templates/metadata/pipeline/ai.yaml
View File

@@ -128,6 +128,21 @@ stages:
label:
en_US: Remove
zh_Hans: 移除
- name: enable-streaming
label:
en_US: enable streaming mode
zh_Hans: 开启流式输出
type: boolean
required: true
default: false
- name: output-batch-size
label:
en_US: output batch size
zh_Hans: 输出批次大小(积累多少条消息后一起输出)
type: integer
required: true
default: 10
- name: dashscope-app-api
label:
en_US: Aliyun Dashscope App API