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fix:修复了因为迭代数据只推入resq_messages和resq_message_chain导致缓存到内存中的数据和写入log中的数据量庞大，以及有思考的think处理

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feat:增加带有深度思考模型的think的去think操作
feat:dify中聊天机器人，chatflow对流式的支持
This commit is contained in:
Dong_master
2025-07-13 22:41:39 +08:00
parent 301509b1db
commit 0be08d8882
4 changed files with 113 additions and 41 deletions
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pkg/provider/runners/difysvapi.py
+53 -20
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@@ -95,6 +95,11 @@ class DifyServiceAPIRunner(runner.RequestRunner):
cov_id = query.session.using_conversation.uuid or ''
query.variables['conversation_id'] = cov_id
try:
is_stream = query.adapter.is_stream
except AttributeError:
is_stream = False
plain_text, image_ids = await self._preprocess_user_message(query)
files = [
@@ -144,40 +149,54 @@ class DifyServiceAPIRunner(runner.RequestRunner):
if mode == 'workflow':
if chunk['event'] == 'node_finished':
if chunk['data']['node_type'] == 'answer':
yield llm_entities.Message(
role='assistant',
content=self._try_convert_thinking(chunk['data']['outputs']['answer']),
)
if not is_stream:
if chunk['data']['node_type'] == 'answer':
yield llm_entities.Message(
role='assistant',
content=self._try_convert_thinking(chunk['data']['outputs']['answer']),
)
else:
if chunk['data']['node_type'] == 'answer':
yield llm_entities.MessageChunk(
role='assistant',
content=self._try_convert_thinking(chunk['data']['outputs']['answer']),
is_final=True,
)
elif chunk['event'] == 'message':
stream_output_pending_chunk += chunk['answer']
if self.pipeline_config['ai']['dify-service-api'].get('enable-streaming', False):
if is_stream:
# 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(
yield llm_entities.MessageChunk(
role='assistant',
content=self._try_convert_thinking(stream_output_pending_chunk),
)
batch_pending_index = 0
elif mode == 'basic':
if 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:
if chunk['event'] == 'message' or chunk['event'] == 'message_end':
if chunk['event'] == 'message_end':
is_final = True
if is_stream and batch_pending_index % batch_pending_max_size == 0:
# 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.MessageChunk(
role='assistant',
content=self._try_convert_thinking(stream_output_pending_chunk),
is_final=is_final,
)
# batch_pending_index = 0
elif not is_stream:
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(stream_output_pending_chunk),
)
stream_output_pending_chunk = ''
stream_output_pending_chunk = ''
else:
stream_output_pending_chunk += chunk['answer']
is_final = False
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')
@@ -191,6 +210,13 @@ class DifyServiceAPIRunner(runner.RequestRunner):
cov_id = query.session.using_conversation.uuid or ''
query.variables['conversation_id'] = cov_id
try:
is_stream = query.adapter.is_stream
except AttributeError:
is_stream = False
batch_pending_index = 0
plain_text, image_ids = await self._preprocess_user_message(query)
files = [
@@ -285,6 +311,13 @@ class DifyServiceAPIRunner(runner.RequestRunner):
query.variables['conversation_id'] = query.session.using_conversation.uuid
try:
is_stream = query.adapter.is_stream
except AttributeError:
is_stream = False
batch_pending_index = 0
plain_text, image_ids = await self._preprocess_user_message(query)
files = [