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style(dashboard): uv lint

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This commit is contained in:
Wenjie Zhang 2025-10-08 21:54:10 +08:00
parent 7c866e7b2b
commit cfc9b903de
6 changed files with 37 additions and 55 deletions
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2
docs/changelog/update.md
View File

@ -19,7 +19,7 @@
- [ ] 知识图谱的上传和可视化，支持属性，标签的展示
- [ ] 集成智能体评估，首先使用命令行来实现，然后考虑放在 UI 里面展示
- [ ] 开发与生产环境隔离
- [ ] 添加统计信息
- [x] 添加统计信息
- [ ] 支持 MinerU 的解析方法
- [ ] Options 中添加网络搜索和绘制图片的选项，分别是用来调用工具

4
server/routers/auth_router.py
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@ -272,9 +272,7 @@ async def update_profile(
# 检查用户名是否已被其他用户使用
existing_user = (
db.query(User)
.filter(User.username == profile_data.username, User.id != current_user.id)
.first()
db.query(User).filter(User.username == profile_data.username, User.id != current_user.id).first()
)
if existing_user:
raise HTTPException(

4
server/routers/chat_router.py
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@ -183,11 +183,11 @@ async def chat_agent(
# 格式清洗
if finish_reason := msg_dict.get("response_metadata", {}).get("finish_reason"):
if "tool_call" in finish_reason and len(finish_reason) > len("tool_call") :
if "tool_call" in finish_reason and len(finish_reason) > len("tool_call"):
model_name = msg_dict.get("response_metadata", {}).get("model_name", "")
repeat_count = len(finish_reason) // len("tool_call")
msg_dict["response_metadata"]["finish_reason"] = "tool_call"
msg_dict["response_metadata"]["model_name"] = model_name[:len(model_name)//repeat_count]
msg_dict["response_metadata"]["model_name"] = model_name[: len(model_name) // repeat_count]
# 保存 AI 消息
ai_msg = conv_mgr.add_message(

69
server/routers/dashboard_router.py
View File

@ -421,9 +421,7 @@ async def get_knowledge_stats(
for _fid, finfo in files_meta.items():
file_ext = (finfo.get("file_type") or "").lower()
# 统一映射显示名
display_name = file_type_mapping.get(
file_ext, file_ext.upper() + "文件" if file_ext else "其他"
)
display_name = file_type_mapping.get(file_ext, file_ext.upper() + "文件" if file_ext else "其他")
files_by_type[display_name] = files_by_type.get(display_name, 0) + 1
# 估算大小（如果路径存在且是本地文件）
@ -721,33 +719,29 @@ async def get_call_timeseries_stats(
):
"""Get time series statistics for call analytics (Admin only)"""
try:
from src.storage.db.models import Conversation, Message, ToolCall, ConversationStats
from src.storage.db.models import Conversation, Message, ToolCall
# 计算时间范围（使用北京时间 UTC+8）
now = datetime.utcnow()
beijing_time = now + timedelta(hours=8) # 转换为北京时间
if time_range == "7hours":
intervals = 7
# 包含当前小时：从6小时前开始
start_time = now - timedelta(hours=intervals-1)
time_format = "%Y-%m-%d %H:00"
start_time = now - timedelta(hours=intervals - 1)
# SQLite compatible approach: 使用datetime函数转换UTC时间为北京时间
group_format = func.strftime("%Y-%m-%d %H:00", func.datetime(Message.created_at, '+8 hours'))
group_format = func.strftime("%Y-%m-%d %H:00", func.datetime(Message.created_at, "+8 hours"))
elif time_range == "7weeks":
intervals = 7
# 包含当前周：从6周前开始
start_time = now - timedelta(weeks=intervals-1)
time_format = "%Y-W%U"
start_time = now - timedelta(weeks=intervals - 1)
# SQLite compatible approach: 使用datetime函数转换UTC时间为北京时间
group_format = func.strftime("%Y-%W", func.datetime(Message.created_at, '+8 hours'))
group_format = func.strftime("%Y-%W", func.datetime(Message.created_at, "+8 hours"))
else: # 7days (default)
intervals = 7
# 包含当前天：从6天前开始
start_time = now - timedelta(days=intervals-1)
time_format = "%Y-%m-%d"
start_time = now - timedelta(days=intervals - 1)
# SQLite compatible approach: 使用datetime函数转换UTC时间为北京时间
group_format = func.strftime("%Y-%m-%d", func.datetime(Message.created_at, '+8 hours'))
group_format = func.strftime("%Y-%m-%d", func.datetime(Message.created_at, "+8 hours"))
# 根据类型查询数据
if type == "models":
@ -757,7 +751,7 @@ async def get_call_timeseries_stats(
db.query(
group_format.label("date"),
func.count(Message.id).label("count"),
func.json_extract(Message.extra_metadata, "$.response_metadata.model_name").label("category")
func.json_extract(Message.extra_metadata, "$.response_metadata.model_name").label("category"),
)
.filter(Message.role == "assistant", Message.created_at >= start_time)
.filter(Message.extra_metadata.isnot(None))
@ -768,17 +762,17 @@ async def get_call_timeseries_stats(
# 智能体调用统计（基于对话数量，按智能体分组）
# 为对话创建独立的时间格式化器
if time_range == "7hours":
conv_group_format = func.strftime("%Y-%m-%d %H:00", func.datetime(Conversation.created_at, '+8 hours'))
conv_group_format = func.strftime("%Y-%m-%d %H:00", func.datetime(Conversation.created_at, "+8 hours"))
elif time_range == "7weeks":
conv_group_format = func.strftime("%Y-%W", func.datetime(Conversation.created_at, '+8 hours'))
conv_group_format = func.strftime("%Y-%W", func.datetime(Conversation.created_at, "+8 hours"))
else: # 7days
conv_group_format = func.strftime("%Y-%m-%d", func.datetime(Conversation.created_at, '+8 hours'))
conv_group_format = func.strftime("%Y-%m-%d", func.datetime(Conversation.created_at, "+8 hours"))
query = (
db.query(
conv_group_format.label("date"),
func.count(Conversation.id).label("count"),
Conversation.agent_id.label("category")
Conversation.agent_id.label("category"),
)
.filter(Conversation.created_at >= start_time)
.group_by(conv_group_format, Conversation.agent_id)
@ -787,22 +781,20 @@ async def get_call_timeseries_stats(
elif type == "tokens":
# Token消耗统计（区分input/output tokens）
# 先查询input tokens
from sqlalchemy import text, literal
from sqlalchemy import literal
input_query = (
db.query(
group_format.label("date"),
func.sum(
func.coalesce(
func.json_extract(Message.extra_metadata, "$.usage_metadata.input_tokens"), 0
)
func.coalesce(func.json_extract(Message.extra_metadata, "$.usage_metadata.input_tokens"), 0)
).label("count"),
literal("input_tokens").label("category")
literal("input_tokens").label("category"),
)
.filter(
Message.created_at >= start_time,
Message.extra_metadata.isnot(None),
func.json_extract(Message.extra_metadata, "$.usage_metadata").isnot(None)
func.json_extract(Message.extra_metadata, "$.usage_metadata").isnot(None),
)
.group_by(group_format)
.order_by(group_format)
@ -813,16 +805,14 @@ async def get_call_timeseries_stats(
db.query(
group_format.label("date"),
func.sum(
func.coalesce(
func.json_extract(Message.extra_metadata, "$.usage_metadata.output_tokens"), 0
)
func.coalesce(func.json_extract(Message.extra_metadata, "$.usage_metadata.output_tokens"), 0)
).label("count"),
literal("output_tokens").label("category")
literal("output_tokens").label("category"),
)
.filter(
Message.created_at >= start_time,
Message.extra_metadata.isnot(None),
func.json_extract(Message.extra_metadata, "$.usage_metadata").isnot(None)
func.json_extract(Message.extra_metadata, "$.usage_metadata").isnot(None),
)
.group_by(group_format)
.order_by(group_format)
@ -836,17 +826,17 @@ async def get_call_timeseries_stats(
# 工具调用统计（按工具名称分组）
# 为工具调用创建独立的时间格式化器
if time_range == "7hours":
tool_group_format = func.strftime("%Y-%m-%d %H:00", func.datetime(ToolCall.created_at, '+8 hours'))
tool_group_format = func.strftime("%Y-%m-%d %H:00", func.datetime(ToolCall.created_at, "+8 hours"))
elif time_range == "7weeks":
tool_group_format = func.strftime("%Y-%W", func.datetime(ToolCall.created_at, '+8 hours'))
tool_group_format = func.strftime("%Y-%W", func.datetime(ToolCall.created_at, "+8 hours"))
else: # 7days
tool_group_format = func.strftime("%Y-%m-%d", func.datetime(ToolCall.created_at, '+8 hours'))
tool_group_format = func.strftime("%Y-%m-%d", func.datetime(ToolCall.created_at, "+8 hours"))
query = (
db.query(
tool_group_format.label("date"),
func.count(ToolCall.id).label("count"),
ToolCall.tool_name.label("category")
ToolCall.tool_name.label("category"),
)
.filter(ToolCall.created_at >= start_time)
.group_by(tool_group_format, ToolCall.tool_name)
@ -862,7 +852,7 @@ async def get_call_timeseries_stats(
# 首先收集所有类别
categories = set()
for result in results:
if hasattr(result, 'category') and result.category:
if hasattr(result, "category") and result.category:
categories.add(result.category)
# 如果没有类别数据，提供默认类别
@ -882,7 +872,7 @@ async def get_call_timeseries_stats(
time_data = {}
for result in results:
date_key = result.date
category = getattr(result, 'category', 'unknown')
category = getattr(result, "category", "unknown")
count = result.count
if date_key not in time_data:
@ -921,17 +911,14 @@ async def get_call_timeseries_stats(
if category not in day_data:
day_data[category] = 0
data.append({
"date": date_key,
"data": day_data,
"total": day_total
})
data.append({"date": date_key, "data": day_data, "total": day_total})
current_time += delta
# 计算统计指标
if type == "tools":
# 对于工具调用，显示所有时间的总数（与ToolStatsComponent保持一致）
from src.storage.db.models import ToolCall
total_count = db.query(func.count(ToolCall.id)).scalar() or 0
else:
# 其他类型使用时间序列数据的总和

1
src/agents/common/utils.py
View File

@ -2,6 +2,7 @@ from datetime import UTC, datetime
from langchain_core.messages import AIMessageChunk, ToolMessage
from langchain_core.runnables import RunnableConfig
from src.agents.common.base import BaseAgent

12
src/knowledge/implementations/chroma.py
View File

@ -205,15 +205,11 @@ class ChromaKB(KnowledgeBase):
total_batches = (len(chunks) + batch_size - 1) // batch_size
for i in range(0, len(chunks), batch_size):
batch_documents = documents[i:i + batch_size]
batch_metadatas = metadatas[i:i + batch_size]
batch_ids = ids[i:i + batch_size]
batch_documents = documents[i : i + batch_size]
batch_metadatas = metadatas[i : i + batch_size]
batch_ids = ids[i : i + batch_size]
collection.add(
documents=batch_documents,
metadatas=batch_metadatas,
ids=batch_ids
)
collection.add(documents=batch_documents, metadatas=batch_metadatas, ids=batch_ids)
batch_num = i // batch_size + 1
logger.info(f"Processed batch {batch_num}/{total_batches} for {filename}")