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Merge branch 'develop' into feature/multimodal

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# Conflicts:
#	api/app/core/agent/langchain_agent.py
This commit is contained in:
Mark
2026-02-02 20:32:21 +08:00
parent a6c5c44ed8 e919f89caf
commit e2f047d035
31 changed files with 1505 additions and 513 deletions
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21
api/app/services/app_chat_service.py
View File

@@ -182,7 +182,14 @@ class AppChatService:
self.conversation_service.save_conversation_messages(
conversation_id=conversation_id,
user_message=message,
assistant_message=result["content"]
assistant_message=result["content"],
meta_data={
"usage": result.get("usage", {
"prompt_tokens": 0,
"completion_tokens": 0,
"total_tokens": 0
})
}
)
elapsed_time = time.time() - start_time
@@ -329,6 +336,7 @@ class AppChatService:
# 流式调用 Agent（支持多模态）
full_content = ""
total_tokens = 0
async for chunk in agent.chat_stream(
message=message,
history=history,
@@ -340,9 +348,12 @@ class AppChatService:
memory_flag=memory_flag,
files=processed_files # 传递处理后的文件
):
full_content += chunk
# 发送消息块事件
yield f"event: message\ndata: {json.dumps({'content': chunk}, ensure_ascii=False)}\n\n"
if isinstance(chunk, int):
total_tokens = chunk
else:
full_content += chunk
# 发送消息块事件
yield f"event: message\ndata: {json.dumps({'content': chunk}, ensure_ascii=False)}\n\n"
elapsed_time = time.time() - start_time
@@ -359,7 +370,7 @@ class AppChatService:
content=full_content,
meta_data={
"model": api_key_obj.model_name,
"usage": {}
"usage": {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": total_tokens}
}
)

7
api/app/services/conversation_service.py
View File

@@ -298,7 +298,8 @@ class ConversationService:
self,
conversation_id: uuid.UUID,
user_message: str,
assistant_message: str
assistant_message: str,
meta_data: Optional[dict] = None
):
"""
Save a pair of user and assistant messages to the conversation.
@@ -307,6 +308,7 @@ class ConversationService:
conversation_id (uuid.UUID): Conversation UUID.
user_message (str): User's message content.
assistant_message (str): Assistant's response content.
meta_data (Optional[dict]): Optional metadata for the messages.
"""
self.add_message(
conversation_id=conversation_id,
@@ -317,7 +319,8 @@ class ConversationService:
self.add_message(
conversation_id=conversation_id,
role="assistant",
content=assistant_message
content=assistant_message,
meta_data=meta_data
)
logger.debug(

33
api/app/services/draft_run_service.py
View File

@@ -455,7 +455,14 @@ class DraftRunService:
user_message=message,
assistant_message=result["content"],
app_id=agent_config.app_id,
user_id=user_id
user_id=user_id,
meta_data={
"usage": result.get("usage", {
"prompt_tokens": 0,
"completion_tokens": 0,
"total_tokens": 0
})
}
)
response = {
@@ -670,6 +677,7 @@ class DraftRunService:
# 9. 流式调用 Agent（支持多模态）
full_content = ""
total_tokens = 0
async for chunk in agent.chat_stream(
message=message,
history=history,
@@ -681,11 +689,14 @@ class DraftRunService:
memory_flag=memory_flag,
files=processed_files # 传递处理后的文件
):
full_content += chunk
# 发送消息块事件
yield self._format_sse_event("message", {
"content": chunk
})
if isinstance(chunk, int):
total_tokens = chunk
else:
full_content += chunk
# 发送消息块事件
yield self._format_sse_event("message", {
"content": chunk
})
elapsed_time = time.time() - start_time
@@ -696,7 +707,10 @@ class DraftRunService:
user_message=message,
assistant_message=full_content,
app_id=agent_config.app_id,
user_id=user_id
user_id=user_id,
meta_data={
"usage": {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": total_tokens}
}
)
# 11. 发送结束事件
@@ -920,6 +934,7 @@ class DraftRunService:
conversation_id: str,
user_message: str,
assistant_message: str,
meta_data: dict,
app_id: Optional[uuid.UUID] = None,
user_id: Optional[str] = None
) -> None:
@@ -931,6 +946,7 @@ class DraftRunService:
assistant_message: AI 回复消息
app_id: 应用ID（未使用，保留用于兼容性）
user_id: 用户ID（未使用，保留用于兼容性）
meta_data: token消耗
"""
try:
from app.services.conversation_service import ConversationService
@@ -949,7 +965,8 @@ class DraftRunService:
conversation_service.add_message(
conversation_id=conv_uuid,
role="assistant",
content=assistant_message
content=assistant_message,
meta_data=meta_data
)
logger.debug(

17
api/app/services/memory_reflection_service.py
View File

@@ -286,7 +286,7 @@ class MemoryReflectionService:
# 检查是否需要执行反思
should_execute = False
hours_diff = 0
if current_reflection_time is None:
# 首次执行反思
should_execute = True
@@ -298,11 +298,11 @@ class MemoryReflectionService:
reflection_time = datetime.fromisoformat(current_reflection_time)
else:
reflection_time = current_reflection_time
current_time = datetime.now()
time_diff = current_time - reflection_time
hours_diff = int(time_diff.total_seconds() / 3600)
# 检查是否达到反思周期
if hours_diff >= iteration_period:
should_execute = True
@@ -312,7 +312,7 @@ class MemoryReflectionService:
except (ValueError, TypeError) as e:
api_logger.warning(f"解析反思时间失败: {e}，将执行反思")
should_execute = True
if should_execute:
api_logger.info(f"与上次的反思时间间隔为: {hours_diff} 小时")
# 3. 执行反思引擎
@@ -345,7 +345,7 @@ class MemoryReflectionService:
"next_reflection_in_hours": iteration_period - hours_diff
}
except Exception as e:
config_id = config_data.get("config_id", "unknown")
api_logger.error(f"启动反思失败，config_id: {config_id}, end_user_id: {end_user_id}, 错误: {str(e)}")
@@ -356,7 +356,7 @@ class MemoryReflectionService:
"end_user_id": end_user_id,
"config_data": config_data
}
def _create_reflection_config_from_data(self, config_data: Dict[str, Any]) -> ReflectionConfig:
"""Create reflective configuration objects from configuration data"""
@@ -364,12 +364,12 @@ class MemoryReflectionService:
if reflexion_range_value is None or reflexion_range_value == "":
reflexion_range_value = "partial"
reflexion_range = ReflectionRange(reflexion_range_value)
baseline_value = config_data.get("baseline")
if baseline_value is None or baseline_value == "":
baseline_value = "TIME"
baseline = ReflectionBaseline(baseline_value)
# iteration_period =
iteration_period = config_data.get("iteration_period", 24)
if isinstance(iteration_period, str):
@@ -377,7 +377,6 @@ class MemoryReflectionService:
iteration_period = int(iteration_period)
except (ValueError, TypeError):
iteration_period = 24 # 默认24小时
return ReflectionConfig(
enabled=config_data.get("enable_self_reflexion", False),
iteration_period=str(iteration_period), # ReflectionConfig期望字符串

21
api/app/services/shared_chat_service.py
View File

@@ -282,7 +282,14 @@ class SharedChatService:
self.conversation_service.save_conversation_messages(
conversation_id=conversation.id,
user_message=message,
assistant_message=result["content"]
assistant_message=result["content"],
meta_data={
"usage": result.get("usage", {
"prompt_tokens": 0,
"completion_tokens": 0,
"total_tokens": 0
})
}
)
# self.conversation_service.add_message(
# conversation_id=conversation.id,
@@ -469,6 +476,7 @@ class SharedChatService:
# 流式调用 Agent
full_content = ""
total_tokens = 0
async for chunk in agent.chat_stream(
message=message,
history=history,
@@ -479,9 +487,12 @@ class SharedChatService:
config_id=config_id,
memory_flag=memory_flag
):
full_content += chunk
# 发送消息块事件
yield f"event: message\ndata: {json.dumps({'content': chunk}, ensure_ascii=False)}\n\n"
if isinstance(chunk, int):
total_tokens = chunk
else:
full_content += chunk
# 发送消息块事件
yield f"event: message\ndata: {json.dumps({'content': chunk}, ensure_ascii=False)}\n\n"
elapsed_time = time.time() - start_time
@@ -498,7 +509,7 @@ class SharedChatService:
content=full_content,
meta_data={
"model": api_key_obj.model_name,
"usage": {}
"usage": {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": total_tokens}
}
)