mirror of
https://github.com/langbot-app/LangBot.git
synced 2025-11-25 19:37:36 +08:00
697 lines
27 KiB
Python
697 lines
27 KiB
Python
from __future__ import annotations
|
||
|
||
import typing
|
||
import json
|
||
import uuid
|
||
import re
|
||
import base64
|
||
|
||
|
||
from .. import runner
|
||
from ...core import app, entities as core_entities
|
||
from .. import entities as llm_entities
|
||
from ...utils import image
|
||
|
||
from libs.dify_service_api.v1 import client, errors
|
||
|
||
|
||
@runner.runner_class('dify-service-api')
|
||
class DifyServiceAPIRunner(runner.RequestRunner):
|
||
"""Dify Service API 对话请求器"""
|
||
|
||
dify_client: client.AsyncDifyServiceClient
|
||
|
||
def __init__(self, ap: app.Application, pipeline_config: dict):
|
||
self.ap = ap
|
||
self.pipeline_config = pipeline_config
|
||
|
||
valid_app_types = ['chat', 'agent', 'workflow']
|
||
if self.pipeline_config['ai']['dify-service-api']['app-type'] not in valid_app_types:
|
||
raise errors.DifyAPIError(
|
||
f'不支持的 Dify 应用类型: {self.pipeline_config["ai"]["dify-service-api"]["app-type"]}'
|
||
)
|
||
|
||
api_key = self.pipeline_config['ai']['dify-service-api']['api-key']
|
||
|
||
self.dify_client = client.AsyncDifyServiceClient(
|
||
api_key=api_key,
|
||
base_url=self.pipeline_config['ai']['dify-service-api']['base-url'],
|
||
)
|
||
|
||
def _try_convert_thinking(self, resp_text: str) -> str:
|
||
"""尝试转换 Dify 的思考提示"""
|
||
if not resp_text.startswith(
|
||
'<details style="color:gray;background-color: #f8f8f8;padding: 8px;border-radius: 4px;" open> <summary> Thinking... </summary>'
|
||
):
|
||
return resp_text
|
||
|
||
if self.pipeline_config['ai']['dify-service-api']['thinking-convert'] == 'original':
|
||
return resp_text
|
||
|
||
if self.pipeline_config['ai']['dify-service-api']['thinking-convert'] == 'remove':
|
||
return re.sub(
|
||
r'<details style="color:gray;background-color: #f8f8f8;padding: 8px;border-radius: 4px;" open> <summary> Thinking... </summary>.*?</details>',
|
||
'',
|
||
resp_text,
|
||
flags=re.DOTALL,
|
||
)
|
||
|
||
if self.pipeline_config['ai']['dify-service-api']['thinking-convert'] == 'plain':
|
||
pattern = r'<details style="color:gray;background-color: #f8f8f8;padding: 8px;border-radius: 4px;" open> <summary> Thinking... </summary>(.*?)</details>'
|
||
thinking_text = re.search(pattern, resp_text, flags=re.DOTALL)
|
||
content_text = re.sub(pattern, '', resp_text, flags=re.DOTALL)
|
||
return f'<think>{thinking_text.group(1)}</think>\n{content_text}'
|
||
|
||
def _process_thinking_content(
|
||
self,
|
||
content: str,
|
||
) -> tuple[str, str]:
|
||
"""处理思维链内容
|
||
|
||
Args:
|
||
content: 原始内容
|
||
Returns:
|
||
(处理后的内容, 提取的思维链内容)
|
||
"""
|
||
remove_think = self.pipeline_config['output'].get('misc', '').get('remove-think')
|
||
thinking_content = ''
|
||
# 从 content 中提取 <think> 标签内容
|
||
if content and '<think>' in content and '</think>' in content:
|
||
import re
|
||
|
||
think_pattern = r'<think>(.*?)</think>'
|
||
think_matches = re.findall(think_pattern, content, re.DOTALL)
|
||
if think_matches:
|
||
thinking_content = '\n'.join(think_matches)
|
||
# 移除 content 中的 <think> 标签
|
||
content = re.sub(think_pattern, '', content, flags=re.DOTALL).strip()
|
||
|
||
# 3. 根据 remove_think 参数决定是否保留思维链
|
||
if remove_think:
|
||
return content, ''
|
||
else:
|
||
# 如果有思维链内容，将其以 <think> 格式添加到 content 开头
|
||
if thinking_content:
|
||
content = f'<think>\n{thinking_content}\n</think>\n{content}'.strip()
|
||
return content, thinking_content
|
||
|
||
async def _preprocess_user_message(self, query: core_entities.Query) -> tuple[str, list[str]]:
|
||
"""预处理用户消息，提取纯文本，并将图片上传到 Dify 服务
|
||
|
||
Returns:
|
||
tuple[str, list[str]]: 纯文本和图片的 Dify 服务图片 ID
|
||
"""
|
||
plain_text = ''
|
||
image_ids = []
|
||
|
||
if isinstance(query.user_message.content, list):
|
||
for ce in query.user_message.content:
|
||
if ce.type == 'text':
|
||
plain_text += ce.text
|
||
elif ce.type == 'image_base64':
|
||
image_b64, image_format = await image.extract_b64_and_format(ce.image_base64)
|
||
file_bytes = base64.b64decode(image_b64)
|
||
file = ('img.png', file_bytes, f'image/{image_format}')
|
||
file_upload_resp = await self.dify_client.upload_file(
|
||
file,
|
||
f'{query.session.launcher_type.value}_{query.session.launcher_id}',
|
||
)
|
||
image_id = file_upload_resp['id']
|
||
image_ids.append(image_id)
|
||
elif isinstance(query.user_message.content, str):
|
||
plain_text = query.user_message.content
|
||
|
||
return plain_text, image_ids
|
||
|
||
async def _chat_messages(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
|
||
"""调用聊天助手"""
|
||
cov_id = query.session.using_conversation.uuid or ''
|
||
query.variables['conversation_id'] = cov_id
|
||
|
||
plain_text, image_ids = await self._preprocess_user_message(query)
|
||
|
||
files = [
|
||
{
|
||
'type': 'image',
|
||
'transfer_method': 'local_file',
|
||
'upload_file_id': image_id,
|
||
}
|
||
for image_id in image_ids
|
||
]
|
||
|
||
mode = 'basic' # 标记是基础编排还是工作流编排
|
||
|
||
basic_mode_pending_chunk = ''
|
||
|
||
inputs = {}
|
||
|
||
inputs.update(query.variables)
|
||
|
||
chunk = None # 初始化chunk变量，防止在没有响应时引用错误
|
||
|
||
async for chunk in self.dify_client.chat_messages(
|
||
inputs=inputs,
|
||
query=plain_text,
|
||
user=f'{query.session.launcher_type.value}_{query.session.launcher_id}',
|
||
conversation_id=cov_id,
|
||
files=files,
|
||
timeout=120,
|
||
):
|
||
self.ap.logger.debug('dify-chat-chunk: ' + str(chunk))
|
||
|
||
if chunk['event'] == 'workflow_started':
|
||
mode = 'workflow'
|
||
|
||
if mode == 'workflow':
|
||
if chunk['event'] == 'node_finished':
|
||
if chunk['data']['node_type'] == 'answer':
|
||
content, _ = self._process_thinking_content(chunk['data']['outputs']['answer'])
|
||
|
||
yield llm_entities.Message(
|
||
role='assistant',
|
||
content=content,
|
||
)
|
||
elif mode == 'basic':
|
||
if chunk['event'] == 'message':
|
||
basic_mode_pending_chunk += chunk['answer']
|
||
elif chunk['event'] == 'message_end':
|
||
content, _ = self._process_thinking_content(basic_mode_pending_chunk)
|
||
yield llm_entities.Message(
|
||
role='assistant',
|
||
content=content,
|
||
)
|
||
basic_mode_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')
|
||
|
||
query.session.using_conversation.uuid = chunk['conversation_id']
|
||
|
||
async def _agent_chat_messages(
|
||
self, query: core_entities.Query
|
||
) -> typing.AsyncGenerator[llm_entities.Message, None]:
|
||
"""调用聊天助手"""
|
||
cov_id = query.session.using_conversation.uuid or ''
|
||
query.variables['conversation_id'] = cov_id
|
||
|
||
plain_text, image_ids = await self._preprocess_user_message(query)
|
||
|
||
files = [
|
||
{
|
||
'type': 'image',
|
||
'transfer_method': 'local_file',
|
||
'upload_file_id': image_id,
|
||
}
|
||
for image_id in image_ids
|
||
]
|
||
|
||
ignored_events = []
|
||
|
||
inputs = {}
|
||
|
||
inputs.update(query.variables)
|
||
|
||
pending_agent_message = ''
|
||
|
||
chunk = None # 初始化chunk变量，防止在没有响应时引用错误
|
||
|
||
async for chunk in self.dify_client.chat_messages(
|
||
inputs=inputs,
|
||
query=plain_text,
|
||
user=f'{query.session.launcher_type.value}_{query.session.launcher_id}',
|
||
response_mode='streaming',
|
||
conversation_id=cov_id,
|
||
files=files,
|
||
timeout=120,
|
||
):
|
||
self.ap.logger.debug('dify-agent-chunk: ' + str(chunk))
|
||
|
||
if chunk['event'] in ignored_events:
|
||
continue
|
||
|
||
if chunk['event'] == 'agent_message' or chunk['event'] == 'message':
|
||
pending_agent_message += chunk['answer']
|
||
else:
|
||
if pending_agent_message.strip() != '':
|
||
pending_agent_message = pending_agent_message.replace('</details>Action:', '</details>')
|
||
content, _ = self._process_thinking_content(pending_agent_message)
|
||
yield llm_entities.Message(
|
||
role='assistant',
|
||
content=content,
|
||
)
|
||
pending_agent_message = ''
|
||
|
||
if chunk['event'] == 'agent_thought':
|
||
if chunk['tool'] != '' and chunk['observation'] != '': # 工具调用结果，跳过
|
||
continue
|
||
|
||
if chunk['tool']:
|
||
msg = llm_entities.Message(
|
||
role='assistant',
|
||
tool_calls=[
|
||
llm_entities.ToolCall(
|
||
id=chunk['id'],
|
||
type='function',
|
||
function=llm_entities.FunctionCall(
|
||
name=chunk['tool'],
|
||
arguments=json.dumps({}),
|
||
),
|
||
)
|
||
],
|
||
)
|
||
yield msg
|
||
if chunk['event'] == 'message_file':
|
||
if chunk['type'] == 'image' and chunk['belongs_to'] == 'assistant':
|
||
base_url = self.dify_client.base_url
|
||
|
||
if base_url.endswith('/v1'):
|
||
base_url = base_url[:-3]
|
||
|
||
image_url = base_url + chunk['url']
|
||
|
||
yield llm_entities.Message(
|
||
role='assistant',
|
||
content=[llm_entities.ContentElement.from_image_url(image_url)],
|
||
)
|
||
if chunk['event'] == 'error':
|
||
raise errors.DifyAPIError('dify 服务错误: ' + chunk['message'])
|
||
|
||
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')
|
||
|
||
query.session.using_conversation.uuid = chunk['conversation_id']
|
||
|
||
async def _workflow_messages(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
|
||
"""调用工作流"""
|
||
|
||
if not query.session.using_conversation.uuid:
|
||
query.session.using_conversation.uuid = str(uuid.uuid4())
|
||
|
||
query.variables['conversation_id'] = query.session.using_conversation.uuid
|
||
|
||
plain_text, image_ids = await self._preprocess_user_message(query)
|
||
|
||
files = [
|
||
{
|
||
'type': 'image',
|
||
'transfer_method': 'local_file',
|
||
'upload_file_id': image_id,
|
||
}
|
||
for image_id in image_ids
|
||
]
|
||
|
||
ignored_events = ['text_chunk', 'workflow_started']
|
||
|
||
inputs = { # these variables are legacy variables, we need to keep them for compatibility
|
||
'langbot_user_message_text': plain_text,
|
||
'langbot_session_id': query.variables['session_id'],
|
||
'langbot_conversation_id': query.variables['conversation_id'],
|
||
'langbot_msg_create_time': query.variables['msg_create_time'],
|
||
}
|
||
|
||
inputs.update(query.variables)
|
||
|
||
async for chunk in self.dify_client.workflow_run(
|
||
inputs=inputs,
|
||
user=f'{query.session.launcher_type.value}_{query.session.launcher_id}',
|
||
files=files,
|
||
timeout=120,
|
||
):
|
||
self.ap.logger.debug('dify-workflow-chunk: ' + str(chunk))
|
||
if chunk['event'] in ignored_events:
|
||
continue
|
||
|
||
if chunk['event'] == 'node_started':
|
||
if chunk['data']['node_type'] == 'start' or chunk['data']['node_type'] == 'end':
|
||
continue
|
||
|
||
msg = llm_entities.Message(
|
||
role='assistant',
|
||
content=None,
|
||
tool_calls=[
|
||
llm_entities.ToolCall(
|
||
id=chunk['data']['node_id'],
|
||
type='function',
|
||
function=llm_entities.FunctionCall(
|
||
name=chunk['data']['title'],
|
||
arguments=json.dumps({}),
|
||
),
|
||
)
|
||
],
|
||
)
|
||
|
||
yield msg
|
||
|
||
elif chunk['event'] == 'workflow_finished':
|
||
if chunk['data']['error']:
|
||
raise errors.DifyAPIError(chunk['data']['error'])
|
||
content, _ = self._process_thinking_content(chunk['data']['outputs']['summary'])
|
||
|
||
msg = llm_entities.Message(
|
||
role='assistant',
|
||
content=content,
|
||
)
|
||
|
||
yield msg
|
||
|
||
|
||
async def _chat_messages_chunk(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.MessageChunk, None]:
|
||
"""调用聊天助手"""
|
||
cov_id = query.session.using_conversation.uuid or ''
|
||
query.variables['conversation_id'] = cov_id
|
||
|
||
plain_text, image_ids = await self._preprocess_user_message(query)
|
||
|
||
files = [
|
||
{
|
||
'type': 'image',
|
||
'transfer_method': 'local_file',
|
||
'upload_file_id': image_id,
|
||
}
|
||
for image_id in image_ids
|
||
]
|
||
|
||
mode = 'basic' # 标记是基础编排还是工作流编排
|
||
|
||
basic_mode_pending_chunk = ''
|
||
|
||
inputs = {}
|
||
|
||
inputs.update(query.variables)
|
||
message_idx = 0
|
||
|
||
chunk = None # 初始化chunk变量，防止在没有响应时引用错误
|
||
|
||
is_final = False
|
||
think_start = False
|
||
think_end = False
|
||
|
||
remove_think = self.pipeline_config['output'].get('misc', '').get('remove-think')
|
||
|
||
async for chunk in self.dify_client.chat_messages(
|
||
inputs=inputs,
|
||
query=plain_text,
|
||
user=f'{query.session.launcher_type.value}_{query.session.launcher_id}',
|
||
conversation_id=cov_id,
|
||
files=files,
|
||
timeout=120,
|
||
):
|
||
self.ap.logger.debug('dify-chat-chunk: ' + str(chunk))
|
||
|
||
# if chunk['event'] == 'workflow_started':
|
||
# mode = 'workflow'
|
||
# if mode == 'workflow':
|
||
# elif mode == 'basic':
|
||
# 因为都只是返回的 message也没有工具调用什么的，暂时不分类
|
||
if chunk['event'] == 'message':
|
||
message_idx += 1
|
||
if remove_think:
|
||
if '<think>' in chunk['answer'] and not think_start:
|
||
think_start = True
|
||
continue
|
||
if '</think>' in chunk['answer'] and not think_end:
|
||
import re
|
||
content = re.sub(r'^\n</think>', '', chunk['answer'])
|
||
basic_mode_pending_chunk += content
|
||
think_end = True
|
||
elif think_end:
|
||
basic_mode_pending_chunk += chunk['answer']
|
||
if think_start:
|
||
continue
|
||
|
||
else:
|
||
basic_mode_pending_chunk += chunk['answer']
|
||
|
||
if chunk['event'] == 'message_end':
|
||
is_final = True
|
||
|
||
if is_final or message_idx % 8 == 0:
|
||
# content, _ = self._process_thinking_content(basic_mode_pending_chunk)
|
||
yield llm_entities.MessageChunk(
|
||
role='assistant',
|
||
content=basic_mode_pending_chunk,
|
||
is_final=is_final,
|
||
)
|
||
|
||
|
||
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')
|
||
|
||
query.session.using_conversation.uuid = chunk['conversation_id']
|
||
|
||
|
||
async def _agent_chat_messages_chunk(
|
||
self, query: core_entities.Query
|
||
) -> typing.AsyncGenerator[llm_entities.MessageChunk, None]:
|
||
"""调用聊天助手"""
|
||
cov_id = query.session.using_conversation.uuid or ''
|
||
query.variables['conversation_id'] = cov_id
|
||
|
||
plain_text, image_ids = await self._preprocess_user_message(query)
|
||
|
||
files = [
|
||
{
|
||
'type': 'image',
|
||
'transfer_method': 'local_file',
|
||
'upload_file_id': image_id,
|
||
}
|
||
for image_id in image_ids
|
||
]
|
||
|
||
ignored_events = []
|
||
|
||
inputs = {}
|
||
|
||
inputs.update(query.variables)
|
||
|
||
pending_agent_message = ''
|
||
|
||
chunk = None # 初始化chunk变量，防止在没有响应时引用错误
|
||
message_idx = 0
|
||
is_final = False
|
||
think_start = False
|
||
think_end = False
|
||
|
||
remove_think = self.pipeline_config['output'].get('misc', '').get('remove-think')
|
||
|
||
async for chunk in self.dify_client.chat_messages(
|
||
inputs=inputs,
|
||
query=plain_text,
|
||
user=f'{query.session.launcher_type.value}_{query.session.launcher_id}',
|
||
response_mode='streaming',
|
||
conversation_id=cov_id,
|
||
files=files,
|
||
timeout=120,
|
||
):
|
||
self.ap.logger.debug('dify-agent-chunk: ' + str(chunk))
|
||
|
||
if chunk['event'] in ignored_events:
|
||
continue
|
||
|
||
if chunk['event'] == 'agent_message':
|
||
message_idx += 1
|
||
if remove_think:
|
||
if '<think>' in chunk['answer'] and not think_start:
|
||
think_start = True
|
||
continue
|
||
if '</think>' in chunk['answer'] and not think_end:
|
||
import re
|
||
content = re.sub(r'^\n</think>', '', chunk['answer'])
|
||
pending_agent_message += content
|
||
think_end = True
|
||
elif think_end:
|
||
pending_agent_message += chunk['answer']
|
||
if think_start:
|
||
continue
|
||
|
||
else:
|
||
pending_agent_message += chunk['answer']
|
||
elif chunk['event'] == 'message_end':
|
||
is_final = True
|
||
else:
|
||
|
||
if chunk['event'] == 'agent_thought':
|
||
if chunk['tool'] != '' and chunk['observation'] != '': # 工具调用结果，跳过
|
||
continue
|
||
message_idx += 1
|
||
if chunk['tool']:
|
||
msg = llm_entities.MessageChunk(
|
||
role='assistant',
|
||
tool_calls=[
|
||
llm_entities.ToolCall(
|
||
id=chunk['id'],
|
||
type='function',
|
||
function=llm_entities.FunctionCall(
|
||
name=chunk['tool'],
|
||
arguments=json.dumps({}),
|
||
),
|
||
)
|
||
],
|
||
)
|
||
yield msg
|
||
if chunk['event'] == 'message_file':
|
||
message_idx += 1
|
||
if chunk['type'] == 'image' and chunk['belongs_to'] == 'assistant':
|
||
base_url = self.dify_client.base_url
|
||
|
||
if base_url.endswith('/v1'):
|
||
base_url = base_url[:-3]
|
||
|
||
image_url = base_url + chunk['url']
|
||
|
||
yield llm_entities.MessageChunk(
|
||
role='assistant',
|
||
content=[llm_entities.ContentElement.from_image_url(image_url)],
|
||
is_final=is_final,
|
||
|
||
)
|
||
|
||
if chunk['event'] == 'error':
|
||
raise errors.DifyAPIError('dify 服务错误: ' + chunk['message'])
|
||
if message_idx % 8 == 0 or is_final:
|
||
yield llm_entities.MessageChunk(
|
||
role='assistant',
|
||
content=pending_agent_message,
|
||
is_final=is_final,
|
||
)
|
||
|
||
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')
|
||
|
||
query.session.using_conversation.uuid = chunk['conversation_id']
|
||
|
||
async def _workflow_messages_chunk(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.MessageChunk, None]:
|
||
"""调用工作流"""
|
||
|
||
if not query.session.using_conversation.uuid:
|
||
query.session.using_conversation.uuid = str(uuid.uuid4())
|
||
|
||
query.variables['conversation_id'] = query.session.using_conversation.uuid
|
||
|
||
plain_text, image_ids = await self._preprocess_user_message(query)
|
||
|
||
files = [
|
||
{
|
||
'type': 'image',
|
||
'transfer_method': 'local_file',
|
||
'upload_file_id': image_id,
|
||
}
|
||
for image_id in image_ids
|
||
]
|
||
|
||
ignored_events = ['workflow_started']
|
||
|
||
inputs = { # these variables are legacy variables, we need to keep them for compatibility
|
||
'langbot_user_message_text': plain_text,
|
||
'langbot_session_id': query.variables['session_id'],
|
||
'langbot_conversation_id': query.variables['conversation_id'],
|
||
'langbot_msg_create_time': query.variables['msg_create_time'],
|
||
}
|
||
|
||
inputs.update(query.variables)
|
||
messsage_idx = 0
|
||
is_final = False
|
||
think_start = False
|
||
think_end = False
|
||
workflow_contents = ''
|
||
|
||
remove_think = self.pipeline_config['output'].get('misc', '').get('remove-think')
|
||
async for chunk in self.dify_client.workflow_run(
|
||
inputs=inputs,
|
||
user=f'{query.session.launcher_type.value}_{query.session.launcher_id}',
|
||
files=files,
|
||
timeout=120,
|
||
):
|
||
self.ap.logger.debug('dify-workflow-chunk: ' + str(chunk))
|
||
if chunk['event'] in ignored_events:
|
||
continue
|
||
if chunk['event'] == 'workflow_finished':
|
||
is_final = True
|
||
if chunk['data']['error']:
|
||
raise errors.DifyAPIError(chunk['data']['error'])
|
||
|
||
if chunk['event'] == 'text_chunk':
|
||
messsage_idx += 1
|
||
if remove_think:
|
||
if '<think>' in chunk['data']['text'] and not think_start:
|
||
think_start = True
|
||
continue
|
||
if '</think>' in chunk['data']['text'] and not think_end:
|
||
import re
|
||
content = re.sub(r'^\n</think>', '', chunk['data']['text'])
|
||
workflow_contents += content
|
||
think_end = True
|
||
elif think_end:
|
||
workflow_contents += chunk['data']['text']
|
||
if think_start:
|
||
continue
|
||
|
||
else:
|
||
workflow_contents += chunk['data']['text']
|
||
|
||
if chunk['event'] == 'node_started':
|
||
if chunk['data']['node_type'] == 'start' or chunk['data']['node_type'] == 'end':
|
||
continue
|
||
messsage_idx += 1
|
||
msg = llm_entities.MessageChunk(
|
||
role='assistant',
|
||
content=None,
|
||
tool_calls=[
|
||
llm_entities.ToolCall(
|
||
id=chunk['data']['node_id'],
|
||
type='function',
|
||
function=llm_entities.FunctionCall(
|
||
name=chunk['data']['title'],
|
||
arguments=json.dumps({}),
|
||
),
|
||
)
|
||
],
|
||
)
|
||
|
||
yield msg
|
||
|
||
|
||
if messsage_idx % 8 == 0 or is_final:
|
||
yield llm_entities.MessageChunk(
|
||
role='assistant',
|
||
content=workflow_contents,
|
||
is_final=is_final,
|
||
)
|
||
|
||
async def run(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
|
||
"""运行请求"""
|
||
if await query.adapter.is_stream_output_supported():
|
||
msg_idx = 0
|
||
if self.pipeline_config['ai']['dify-service-api']['app-type'] == 'chat':
|
||
async for msg in self._chat_messages_chunk(query):
|
||
msg_idx += 1
|
||
msg.msg_sequence = msg_idx
|
||
yield msg
|
||
elif self.pipeline_config['ai']['dify-service-api']['app-type'] == 'agent':
|
||
async for msg in self._agent_chat_messages_chunk(query):
|
||
msg_idx += 1
|
||
msg.msg_sequence = msg_idx
|
||
yield msg
|
||
elif self.pipeline_config['ai']['dify-service-api']['app-type'] == 'workflow':
|
||
async for msg in self._workflow_messages_chunk(query):
|
||
msg_idx += 1
|
||
msg.msg_sequence = msg_idx
|
||
yield msg
|
||
else:
|
||
raise errors.DifyAPIError(
|
||
f'不支持的 Dify 应用类型: {self.pipeline_config["ai"]["dify-service-api"]["app-type"]}'
|
||
)
|
||
else:
|
||
if self.pipeline_config['ai']['dify-service-api']['app-type'] == 'chat':
|
||
async for msg in self._chat_messages(query):
|
||
yield msg
|
||
elif self.pipeline_config['ai']['dify-service-api']['app-type'] == 'agent':
|
||
async for msg in self._agent_chat_messages(query):
|
||
yield msg
|
||
elif self.pipeline_config['ai']['dify-service-api']['app-type'] == 'workflow':
|
||
async for msg in self._workflow_messages(query):
|
||
yield msg
|
||
else:
|
||
raise errors.DifyAPIError(
|
||
f'不支持的 Dify 应用类型: {self.pipeline_config["ai"]["dify-service-api"]["app-type"]}'
|
||
) |