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typing

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This commit is contained in:
UnCLAS-Prommer
2025-07-20 18:14:53 +08:00
parent 20142d1cdb
commit f2c901bc98
9 changed files with 47 additions and 46 deletions
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2
src/chat/heart_flow/heartflow_message_processor.py
View File

@@ -112,7 +112,7 @@ class HeartFCMessageReceiver:
# subheartflow.add_message_to_normal_chat_cache(message, interested_rate, is_mentioned)
chat_mood = mood_manager.get_mood_by_chat_id(subheartflow.chat_id) # type: ignore
chat_mood = mood_manager.get_mood_by_chat_id(subheartflow.chat_id)
asyncio.create_task(chat_mood.update_mood_by_message(message, interested_rate))
# 3. 日志记录

4
src/chat/message_receive/message.py
View File

@@ -494,10 +494,10 @@ class MessageSending(MessageProcessBase):
# ) -> "MessageSending":
# """从思考状态消息创建发送状态消息"""
# return cls(
# message_id=thinking.message_info.message_id, # type: ignore
# message_id=thinking.message_info.message_id,
# chat_stream=thinking.chat_stream,
# message_segment=message_segment,
# bot_user_info=thinking.message_info.user_info, # type: ignore
# bot_user_info=thinking.message_info.user_info,
# reply=thinking.reply,
# is_head=is_head,
# is_emoji=is_emoji,

2
src/chat/utils/statistic.py
View File

@@ -2348,7 +2348,7 @@ class AsyncStatisticOutputTask(AsyncTask):
@staticmethod
def _format_model_classified_stat(stats: Dict[str, Any]) -> str:
return StatisticOutputTask._format_model_classified_stat(stats) # type: ignore
return StatisticOutputTask._format_model_classified_stat(stats)
def _format_chat_stat(self, stats: Dict[str, Any]) -> str:
return StatisticOutputTask._format_chat_stat(self, stats) # type: ignore

4
src/chat/utils/utils.py
View File

@@ -285,7 +285,7 @@ def random_remove_punctuation(text: str) -> str:
continue
elif char == "，":
rand = random.random()
if rand < 0.25: # 5%概率删除逗号
if rand < 0.05: # 5%概率删除逗号
continue
elif rand < 0.25: # 20%概率把逗号变成空格
result += " "
@@ -628,7 +628,7 @@ def get_chat_type_and_target_info(chat_id: str) -> Tuple[bool, Optional[Dict]]:
elif chat_stream.user_info: # It's a private chat
is_group_chat = False
user_info = chat_stream.user_info
platform: str = chat_stream.platform # type: ignore
platform: str = chat_stream.platform
user_id: str = user_info.user_id # type: ignore
# Initialize target_info with basic info

2
src/chat/willing/willing_manager.py
View File

@@ -94,7 +94,7 @@ class BaseWillingManager(ABC):
def setup(self, message: dict, chat: ChatStream):
person_id = PersonInfoManager.get_person_id(chat.platform, chat.user_info.user_id) # type: ignore
self.ongoing_messages[message.get("message_id", "")] = WillingInfo( # type: ignore
self.ongoing_messages[message.get("message_id", "")] = WillingInfo(
message=message,
chat=chat,
person_info_manager=get_person_info_manager(),

30
src/common/database/database_model.py
View File

@@ -65,7 +65,7 @@ class ChatStreams(BaseModel):
# user_cardname 可能为空字符串或不存在，设置 null=True 更具灵活性。
user_cardname = TextField(null=True)
class Meta: # type: ignore
class Meta:
# 如果 BaseModel.Meta.database 已设置，则此模型将继承该数据库配置。
# 如果不使用带有数据库实例的 BaseModel，或者想覆盖它，
# 请取消注释并在下面设置数据库实例：
@@ -89,7 +89,7 @@ class LLMUsage(BaseModel):
status = TextField()
timestamp = DateTimeField(index=True) # 更改为 DateTimeField 并添加索引
class Meta: # type: ignore
class Meta:
# 如果 BaseModel.Meta.database 已设置，则此模型将继承该数据库配置。
# database = db
table_name = "llm_usage"
@@ -112,7 +112,7 @@ class Emoji(BaseModel):
usage_count = IntegerField(default=0) # 使用次数（被使用的次数）
last_used_time = FloatField(null=True) # 上次使用时间
class Meta: # type: ignore
class Meta:
# database = db # 继承自 BaseModel
table_name = "emoji"
@@ -163,7 +163,7 @@ class Messages(BaseModel):
is_picid = BooleanField(default=False)
is_command = BooleanField(default=False)
class Meta: # type: ignore
class Meta:
# database = db # 继承自 BaseModel
table_name = "messages"
@@ -187,7 +187,7 @@ class ActionRecords(BaseModel):
chat_info_stream_id = TextField()
chat_info_platform = TextField()
class Meta: # type: ignore
class Meta:
# database = db # 继承自 BaseModel
table_name = "action_records"
@@ -207,7 +207,7 @@ class Images(BaseModel):
type = TextField() # 图像类型，例如 "emoji"
vlm_processed = BooleanField(default=False) # 是否已经过VLM处理
class Meta: # type: ignore
class Meta:
table_name = "images"
@@ -221,7 +221,7 @@ class ImageDescriptions(BaseModel):
description = TextField() # 图像的描述
timestamp = FloatField() # 时间戳
class Meta: # type: ignore
class Meta:
# database = db # 继承自 BaseModel
table_name = "image_descriptions"
@@ -237,7 +237,7 @@ class OnlineTime(BaseModel):
start_timestamp = DateTimeField(default=datetime.datetime.now)
end_timestamp = DateTimeField(index=True)
class Meta: # type: ignore
class Meta:
# database = db # 继承自 BaseModel
table_name = "online_time"
@@ -264,7 +264,7 @@ class PersonInfo(BaseModel):
last_know = FloatField(null=True) # 最后一次印象总结时间
attitude = IntegerField(null=True, default=50) # 态度，0-100，从非常厌恶到十分喜欢
class Meta: # type: ignore
class Meta:
# database = db # 继承自 BaseModel
table_name = "person_info"
@@ -277,7 +277,7 @@ class Memory(BaseModel):
create_time = FloatField(null=True)
last_view_time = FloatField(null=True)
class Meta: # type: ignore
class Meta:
table_name = "memory"
@@ -290,7 +290,7 @@ class Knowledges(BaseModel):
embedding = TextField() # 知识内容的嵌入向量，存储为 JSON 字符串的浮点数列表
# 可以添加其他元数据字段，如 source, create_time 等
class Meta: # type: ignore
class Meta:
# database = db # 继承自 BaseModel
table_name = "knowledges"
@@ -307,7 +307,7 @@ class Expression(BaseModel):
chat_id = TextField(index=True)
type = TextField()
class Meta: # type: ignore
class Meta:
table_name = "expression"
@@ -331,7 +331,7 @@ class ThinkingLog(BaseModel):
# And: import datetime
created_at = DateTimeField(default=datetime.datetime.now)
class Meta: # type: ignore
class Meta:
table_name = "thinking_logs"
@@ -346,7 +346,7 @@ class GraphNodes(BaseModel):
created_time = FloatField() # 创建时间戳
last_modified = FloatField() # 最后修改时间戳
class Meta: # type: ignore
class Meta:
table_name = "graph_nodes"
@@ -362,7 +362,7 @@ class GraphEdges(BaseModel):
created_time = FloatField() # 创建时间戳
last_modified = FloatField() # 最后修改时间戳
class Meta: # type: ignore
class Meta:
table_name = "graph_edges"

45
src/llm_models/utils_model.py
View File

@@ -2,7 +2,7 @@ import asyncio
import json
import re
from datetime import datetime
from typing import Tuple, Union, Dict, Any
from typing import Tuple, Union, Dict, Any, Callable
import aiohttp
from aiohttp.client import ClientResponse
from src.common.logger import get_logger
@@ -300,7 +300,7 @@ class LLMRequest:
file_format: str = None,
payload: dict = None,
retry_policy: dict = None,
response_handler: callable = None,
response_handler: Callable = None,
user_id: str = "system",
request_type: str = None,
):
@@ -336,19 +336,17 @@ class LLMRequest:
headers["Accept"] = "text/event-stream"
async with aiohttp.ClientSession(connector=await get_tcp_connector()) as session:
post_kwargs = {"headers": headers}
#form-data数据上传方式不同
# form-data数据上传方式不同
if file_bytes:
post_kwargs["data"] = request_content["payload"]
else:
post_kwargs["json"] = request_content["payload"]
async with session.post(
request_content["api_url"], **post_kwargs
) as response:
async with session.post(request_content["api_url"], **post_kwargs) as response:
handled_result = await self._handle_response(
response, request_content, retry, response_handler, user_id, request_type, endpoint
)
return handled_result
return handled_result
except Exception as e:
handled_payload, count_delta = await self._handle_exception(e, retry, request_content)
@@ -366,11 +364,11 @@ class LLMRequest:
response: ClientResponse,
request_content: Dict[str, Any],
retry_count: int,
response_handler: callable,
response_handler: Callable,
user_id,
request_type,
endpoint,
) -> Union[Dict[str, Any], None]:
):
policy = request_content["policy"]
stream_mode = request_content["stream_mode"]
if response.status in policy["retry_codes"] or response.status in policy["abort_codes"]:
@@ -477,9 +475,7 @@ class LLMRequest:
}
return result
async def _handle_error_response(
self, response: ClientResponse, retry_count: int, policy: Dict[str, Any]
) -> Union[Dict[str, any]]:
async def _handle_error_response(self, response: ClientResponse, retry_count: int, policy: Dict[str, Any]):
if response.status in policy["retry_codes"]:
wait_time = policy["base_wait"] * (2**retry_count)
logger.warning(f"模型 {self.model_name} 错误码: {response.status}, 等待 {wait_time}秒后重试")
@@ -629,7 +625,9 @@ class LLMRequest:
)
# 安全地检查和记录请求详情
handled_payload = await _safely_record(request_content, payload)
logger.critical(f"请求头: {await self._build_headers(no_key=True)} 请求体: {str(handled_payload)[:100]}")
logger.critical(
f"请求头: {await self._build_headers(no_key=True)} 请求体: {str(handled_payload)[:100]}"
)
raise RuntimeError(
f"模型 {self.model_name} API请求失败: 状态码 {exception.status}, {exception.message}"
)
@@ -643,7 +641,9 @@ class LLMRequest:
logger.critical(f"模型 {self.model_name} 请求失败: {str(exception)}")
# 安全地检查和记录请求详情
handled_payload = await _safely_record(request_content, payload)
logger.critical(f"请求头: {await self._build_headers(no_key=True)} 请求体: {str(handled_payload)[:100]}")
logger.critical(
f"请求头: {await self._build_headers(no_key=True)} 请求体: {str(handled_payload)[:100]}"
)
raise RuntimeError(f"模型 {self.model_name} API请求失败: {str(exception)}")
async def _transform_parameters(self, params: dict) -> dict:
@@ -682,15 +682,14 @@ class LLMRequest:
logger.warning(f"暂不支持的文件类型: {file_format}")
data.add_field(
"file",io.BytesIO(file_bytes),
"file",
io.BytesIO(file_bytes),
filename=f"file.{file_format}",
content_type=f'{content_type}' # 根据实际文件类型设置
)
data.add_field(
"model", self.model_name
content_type=f"{content_type}", # 根据实际文件类型设置
)
data.add_field("model", self.model_name)
return data
async def _build_payload(self, prompt: str, image_base64: str = None, image_format: str = None) -> dict:
"""构建请求体"""
# 复制一份参数，避免直接修改 self.params
@@ -819,9 +818,11 @@ class LLMRequest:
async def generate_response_for_voice(self, voice_bytes: bytes) -> Tuple:
"""根据输入的语音文件生成模型的异步响应"""
response = await self._execute_request(endpoint="/audio/transcriptions",file_bytes=voice_bytes, file_format='wav')
response = await self._execute_request(
endpoint="/audio/transcriptions", file_bytes=voice_bytes, file_format="wav"
)
return response
async def generate_response_async(self, prompt: str, **kwargs) -> Union[str, Tuple]:
"""异步方式根据输入的提示生成模型的响应"""
# 构建请求体，不硬编码max_tokens

2
src/mood/mood_manager.py
View File

@@ -134,7 +134,7 @@ class ChatMood:
self.mood_state = response
self.last_change_time = message_time # type: ignore
self.last_change_time = message_time
async def regress_mood(self):
message_time = time.time()

2
src/tools/tool_can_use/rename_person_tool.py
View File

@@ -71,7 +71,7 @@ class RenamePersonTool(BaseTool):
user_nickname=user_nickname, # type: ignore
user_cardname=user_cardname, # type: ignore
user_avatar=user_avatar, # type: ignore
request=request_context, # type: ignore
request=request_context,
)
# 3. 处理结果