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朱潮 2025-11-27 21:50:03 +08:00
parent 116f1cb471
commit 3973174c83
37 changed files with 684 additions and 387 deletions
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17
README.md
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@ -668,3 +668,20 @@ qwen-agent/
```
现在您可以开始使用 Catalog Agent 进行智能数据检索了！🚀
## 提示词工程
指南
```guideline
1) Condition: 用户意图为“执行设备控制”。 Action: 如果用户在当前交互中已回复肯定确认（例如，同意、确认、好的等），则立即调用 Iot Control-dxcore_update_device_status 工具执行设备操作。否则（用户尚未确认），则向用户发送确认询问：“即将为您[操作内容][设备名称][具体参数]，是否确认？”并等待用户回复。
3) Condition: 当用户意图为查询设备状态或信息时。 Action: 调用 Iot Control 设备相关的工具进行查询（不调用 rag_retrieve-rag_retrieve）。
4) Condition: 当用户意图为非设备相关的问题（如提问、遇到难处、咨询事实性问题、价格等）时。 Action: 优先调用 rag_retrieve-rag_retrieve 查询知识库；如果无结果，则调用 WebSearch-web_search；最后综合两个工具的内容进行回复。
```
术语表
```terms
1) Name: term_name1, Description: desc, Synonyms: syn1, syn2
2) Name: term_name2, Description: desc, Synonyms: syn1, syn2
```

6
agent/config_cache.py
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@ -7,7 +7,9 @@ import asyncio
import os
import json
from typing import Dict, Tuple, Optional, Any
from utils.logger import logger
import logging
logger = logging.getLogger('app')
class ConfigFileCache:
@ -97,4 +99,4 @@ class ConfigFileCache:
# 全局缓存实例
config_cache = ConfigFileCache()
config_cache = ConfigFileCache()

4
agent/custom_mcp_manager.py
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@ -24,7 +24,9 @@ from typing import Dict, Optional, Union
from dotenv import load_dotenv
from qwen_agent.log import logger
import logging
logger = logging.getLogger('app')
from qwen_agent.tools.base import BaseTool

4
agent/file_loaded_agent_manager.py
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@ -21,7 +21,9 @@ import asyncio
from typing import Dict, List, Optional
from qwen_agent.agents import Assistant
from qwen_agent.log import logger
import logging
logger = logging.getLogger('app')
from agent.modified_assistant import init_modified_agent_service_with_files, update_agent_llm
from agent.prompt_loader import load_system_prompt_async, load_mcp_settings_async

4
agent/modified_assistant.py
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@ -24,9 +24,11 @@ from qwen_agent.llm.schema import ASSISTANT, FUNCTION, Message
from qwen_agent.llm.oai import TextChatAtOAI
from qwen_agent.tools import BaseTool
from agent.custom_mcp_manager import CustomMCPManager
import logging
logger = logging.getLogger('app')
# 设置工具日志记录器
tool_logger = logging.getLogger('tool_logger')
tool_logger = logging.getLogger('app')
class ModifiedAssistant(Assistant):
"""

19
agent/prompt_loader.py
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@ -7,6 +7,9 @@ import json
import asyncio
from typing import List, Dict, Optional, Any
from datetime import datetime, timezone, timedelta
import logging
logger = logging.getLogger('app')
def safe_replace(text: str, placeholder: str, value: Any) -> str:
@ -142,9 +145,9 @@ async def load_system_prompt_async(project_dir: str, language: str = None, syste
default_prompt_file = os.path.join("prompt", f"system_prompt_{robot_type}.md")
system_prompt_default = await config_cache.get_text_file(default_prompt_file)
if system_prompt_default:
print(f"Using cached default system prompt for {robot_type} from prompt folder")
logger.info(f"Using cached default system prompt for {robot_type} from prompt folder")
except Exception as e:
print(f"Failed to load default system prompt for {robot_type}: {str(e)}")
logger.error(f"Failed to load default system prompt for {robot_type}: {str(e)}")
system_prompt_default = None
readme = ""
@ -244,11 +247,11 @@ async def load_mcp_settings_async(project_dir: str, mcp_settings: list=None, bot
default_mcp_file = os.path.join("mcp", f"mcp_settings_{robot_type}.json")
default_mcp_settings = await config_cache.get_json_file(default_mcp_file) or []
if default_mcp_settings:
print(f"Using cached default mcp_settings_{robot_type} from mcp folder")
logger.info(f"Using cached default mcp_settings_{robot_type} from mcp folder")
else:
print(f"No default mcp_settings_{robot_type} found, using empty default settings")
logger.warning(f"No default mcp_settings_{robot_type} found, using empty default settings")
except Exception as e:
print(f"Failed to load default mcp_settings_{robot_type}: {str(e)}")
logger.error(f"Failed to load default mcp_settings_{robot_type}: {str(e)}")
default_mcp_settings = []
# 遍历mcpServers工具，给每个工具增加env参数
@ -269,7 +272,7 @@ async def load_mcp_settings_async(project_dir: str, mcp_settings: list=None, bot
input_mcp_settings = mcp_settings
elif mcp_settings:
input_mcp_settings = [mcp_settings]
print(f"Warning: mcp_settings is not a list, converting to list format")
logger.warning(f"Warning: mcp_settings is not a list, converting to list format")
# 3. 合并默认设置和传入设置
merged_settings = []
@ -286,7 +289,7 @@ async def load_mcp_settings_async(project_dir: str, mcp_settings: list=None, bot
# 合并mcpServers对象，传入的设置覆盖默认设置中相同的key
default_mcp_servers.update(input_mcp_servers)
merged_settings[0]['mcpServers'] = default_mcp_servers
print(f"Merged mcpServers: default + {len(input_mcp_servers)} input servers")
logger.info(f"Merged mcpServers: default + {len(input_mcp_servers)} input servers")
# 如果没有默认设置但有传入设置，直接使用传入设置
elif input_mcp_settings:
@ -296,7 +299,7 @@ async def load_mcp_settings_async(project_dir: str, mcp_settings: list=None, bot
if not merged_settings:
merged_settings = []
elif not isinstance(merged_settings, list):
print(f"Warning: merged_settings is not a list, converting to list format")
logger.warning(f"Warning: merged_settings is not a list, converting to list format")
merged_settings = [merged_settings] if merged_settings else []
# 计算 dataset_dir 用于替换 MCP 配置中的占位符

4
agent/sharded_agent_manager.py
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@ -24,7 +24,9 @@ import threading
from collections import defaultdict
from qwen_agent.agents import Assistant
from qwen_agent.log import logger
import logging
logger = logging.getLogger('app')
from agent.modified_assistant import init_modified_agent_service_with_files, update_agent_llm
from agent.prompt_loader import load_system_prompt_async, load_mcp_settings_async

134
embedding/embedding.py
View File

@ -7,6 +7,10 @@ import requests
import asyncio
import hashlib
import json
import logging
# Configure logger
logger = logging.getLogger('app')
def encode_texts_via_api(texts, batch_size=32):
"""通过 API 接口编码文本"""
@ -35,18 +39,18 @@ def encode_texts_via_api(texts, batch_size=32):
if result_data.get("success"):
embeddings_list = result_data.get("embeddings", [])
print(f"API编码成功，处理了 {len(texts)} 个文本，embedding维度: {len(embeddings_list[0]) if embeddings_list else 0}")
logger.info(f"API编码成功，处理了 {len(texts)} 个文本，embedding维度: {len(embeddings_list[0]) if embeddings_list else 0}")
return np.array(embeddings_list)
else:
error_msg = result_data.get('error', '未知错误')
print(f"API编码失败: {error_msg}")
logger.error(f"API编码失败: {error_msg}")
raise Exception(f"API编码失败: {error_msg}")
else:
print(f"API请求失败: {response.status_code} - {response.text}")
logger.error(f"API请求失败: {response.status_code} - {response.text}")
raise Exception(f"API请求失败: {response.status_code}")
except Exception as e:
print(f"API编码异常: {e}")
logger.error(f"API编码异常: {e}")
raise
def clean_text(text):
@ -144,10 +148,10 @@ def embed_document(input_file='document.txt', output_file='embedding.pkl',
if is_meaningful_line(cleaned_text):
chunks.append(cleaned_text)
print(f"使用按行分块策略")
print(f"原始行数: {original_count}")
print(f"清理后有效句子数: {len(chunks)}")
print(f"过滤比例: {((original_count - len(chunks)) / original_count * 100):.1f}%")
logger.info(f"使用按行分块策略")
logger.info(f"原始行数: {original_count}")
logger.info(f"清理后有效句子数: {len(chunks)}")
logger.info(f"过滤比例: {((original_count - len(chunks)) / original_count * 100):.1f}%")
elif chunking_strategy == 'paragraph':
# 新的段落级分块策略
@ -166,13 +170,13 @@ def embed_document(input_file='document.txt', output_file='embedding.pkl',
# 使用段落分块
chunks = paragraph_chunking(cleaned_content, **params)
print(f"使用段落级分块策略")
print(f"文档总长度: {len(content)} 字符")
print(f"分块数量: {len(chunks)}")
logger.info(f"使用段落级分块策略")
logger.info(f"文档总长度: {len(content)} 字符")
logger.info(f"分块数量: {len(chunks)}")
if chunks:
print(f"平均chunk大小: {sum(len(chunk) for chunk in chunks) / len(chunks):.1f} 字符")
print(f"最大chunk大小: {max(len(chunk) for chunk in chunks)} 字符")
print(f"最小chunk大小: {min(len(chunk) for chunk in chunks)} 字符")
logger.debug(f"平均chunk大小: {sum(len(chunk) for chunk in chunks) / len(chunks):.1f} 字符")
logger.debug(f"最大chunk大小: {max(len(chunk) for chunk in chunks)} 字符")
logger.debug(f"最小chunk大小: {min(len(chunk) for chunk in chunks)} 字符")
elif chunking_strategy == 'smart':
# 智能分块策略，自动检测文档格式
@ -186,25 +190,25 @@ def embed_document(input_file='document.txt', output_file='embedding.pkl',
# 使用智能分块
chunks = smart_chunking(content, **params)
print(f"使用智能分块策略")
print(f"文档总长度: {len(content)} 字符")
print(f"分块数量: {len(chunks)}")
logger.info(f"使用智能分块策略")
logger.info(f"文档总长度: {len(content)} 字符")
logger.info(f"分块数量: {len(chunks)}")
if chunks:
print(f"平均chunk大小: {sum(len(chunk) for chunk in chunks) / len(chunks):.1f} 字符")
print(f"最大chunk大小: {max(len(chunk) for chunk in chunks)} 字符")
print(f"最小chunk大小: {min(len(chunk) for chunk in chunks)} 字符")
logger.debug(f"平均chunk大小: {sum(len(chunk) for chunk in chunks) / len(chunks):.1f} 字符")
logger.debug(f"最大chunk大小: {max(len(chunk) for chunk in chunks)} 字符")
logger.debug(f"最小chunk大小: {min(len(chunk) for chunk in chunks)} 字符")
else:
raise ValueError(f"不支持的分块策略: {chunking_strategy}")
if not chunks:
print("警告：没有找到有效的内容块！")
logger.warning("警告：没有找到有效的内容块！")
return None
print(f"正在处理 {len(chunks)} 个内容块...")
logger.info(f"正在处理 {len(chunks)} 个内容块...")
# 使用API接口进行编码
print("使用API接口进行编码...")
logger.info("使用API接口进行编码...")
chunk_embeddings = encode_texts_via_api(chunks, batch_size=32)
embedding_data = {
@ -218,14 +222,14 @@ def embed_document(input_file='document.txt', output_file='embedding.pkl',
with open(output_file, 'wb') as f:
pickle.dump(embedding_data, f)
print(f"已保存嵌入向量到 {output_file}")
logger.info(f"已保存嵌入向量到 {output_file}")
return embedding_data
except FileNotFoundError:
print(f"错误：找不到文件 {input_file}")
logger.error(f"错误：找不到文件 {input_file}")
return None
except Exception as e:
print(f"处理文档时出错：{e}")
logger.error(f"处理文档时出错：{e}")
return None
@ -611,21 +615,21 @@ def split_document_by_pages(input_file='document.txt', output_file='pagination.t
if page_content:
pages.append(page_content)
print(f"总共分割出 {len(pages)} 页")
logger.info(f"总共分割出 {len(pages)} 页")
# 写入序列化文件
with open(output_file, 'w', encoding='utf-8') as f:
for i, page_content in enumerate(pages, 1):
f.write(f"{page_content}\n")
print(f"已将页面内容序列化到 {output_file}")
logger.info(f"已将页面内容序列化到 {output_file}")
return pages
except FileNotFoundError:
print(f"错误：找不到文件 {input_file}")
logger.error(f"错误：找不到文件 {input_file}")
return []
except Exception as e:
print(f"分割文档时出错：{e}")
logger.error(f"分割文档时出错：{e}")
return []
def test_chunking_strategies():
@ -645,54 +649,54 @@ def test_chunking_strategies():
第五段：这是最后一个段落。它用来测试分块策略的完整性和准确性。
"""
print("=" * 60)
print("分块策略测试")
print("=" * 60)
logger.debug("=" * 60)
logger.debug("分块策略测试")
logger.debug("=" * 60)
# 测试1: 段落级分块（小chunk）
print("\n1. 段落级分块 - 小chunk (max_size=200):")
logger.debug("\n1. 段落级分块 - 小chunk (max_size=200):")
chunks_small = paragraph_chunking(test_text, max_chunk_size=200, overlap=50)
for i, chunk in enumerate(chunks_small):
print(f"Chunk {i+1} (长度: {len(chunk)}): {chunk[:50]}...")
logger.debug(f"Chunk {i+1} (长度: {len(chunk)}): {chunk[:50]}...")
# 测试2: 段落级分块（大chunk）
print("\n2. 段落级分块 - 大chunk (max_size=500):")
logger.debug("\n2. 段落级分块 - 大chunk (max_size=500):")
chunks_large = paragraph_chunking(test_text, max_chunk_size=500, overlap=100)
for i, chunk in enumerate(chunks_large):
print(f"Chunk {i+1} (长度: {len(chunk)}): {chunk[:50]}...")
logger.debug(f"Chunk {i+1} (长度: {len(chunk)}): {chunk[:50]}...")
# 测试3: 段落级分块（无重叠）
print("\n3. 段落级分块 - 无重叠:")
logger.debug("\n3. 段落级分块 - 无重叠:")
chunks_no_overlap = paragraph_chunking(test_text, max_chunk_size=300, overlap=0)
for i, chunk in enumerate(chunks_no_overlap):
print(f"Chunk {i+1} (长度: {len(chunk)}): {chunk[:50]}...")
logger.debug(f"Chunk {i+1} (长度: {len(chunk)}): {chunk[:50]}...")
print(f"\n测试总结:")
print(f"- 小chunk策略: {len(chunks_small)} 个chunks")
print(f"- 大chunk策略: {len(chunks_large)} 个chunks")
print(f"- 无重叠策略: {len(chunks_no_overlap)} 个chunks")
logger.debug(f"\n测试总结:")
logger.debug(f"- 小chunk策略: {len(chunks_small)} 个chunks")
logger.debug(f"- 大chunk策略: {len(chunks_large)} 个chunks")
logger.debug(f"- 无重叠策略: {len(chunks_no_overlap)} 个chunks")
def demo_usage():
"""
演示如何使用新的分块功能
"""
print("=" * 60)
print("使用示例")
print("=" * 60)
logger.debug("=" * 60)
logger.debug("使用示例")
logger.debug("=" * 60)
print("\n1. 使用传统的按行分块:")
print("embed_document('document.txt', 'line_embedding.pkl', chunking_strategy='line')")
logger.debug("\n1. 使用传统的按行分块:")
logger.debug("embed_document('document.txt', 'line_embedding.pkl', chunking_strategy='line')")
print("\n2. 使用段落级分块（默认参数）:")
print("embed_document('document.txt', 'paragraph_embedding.pkl', chunking_strategy='paragraph')")
logger.debug("\n2. 使用段落级分块（默认参数）:")
logger.debug("embed_document('document.txt', 'paragraph_embedding.pkl', chunking_strategy='paragraph')")
print("\n3. 使用自定义参数的段落级分块:")
print("embed_document('document.txt', 'custom_embedding.pkl',")
print(" chunking_strategy='paragraph',")
print(" max_chunk_size=1500,")
print(" overlap=200,")
print(" min_chunk_size=300)")
logger.debug("\n3. 使用自定义参数的段落级分块:")
logger.debug("embed_document('document.txt', 'custom_embedding.pkl',")
logger.debug(" chunking_strategy='paragraph',")
logger.debug(" max_chunk_size=1500,")
logger.debug(" overlap=200,")
logger.debug(" min_chunk_size=300)")
@ -737,10 +741,10 @@ def cache_terms_embeddings(bot_id: str, terms_list: List[Dict[str, Any]]) -> Dic
# 验证缓存数据是否匹配当前的terms
current_hash = _generate_terms_hash(terms_list)
if cached_data.get('hash') == current_hash:
print(f"Using cached terms embeddings for {cache_key}")
logger.info(f"Using cached terms embeddings for {cache_key}")
return cached_data
except Exception as e:
print(f"Error loading cache: {e}")
logger.error(f"Error loading cache: {e}")
# 准备要编码的文本
term_texts = []
@ -793,11 +797,11 @@ def cache_terms_embeddings(bot_id: str, terms_list: List[Dict[str, Any]]) -> Dic
with open(cache_file, 'wb') as f:
pickle.dump(cache_data, f)
print(f"Cached {len(term_texts)} terms embeddings to {cache_file}")
logger.info(f"Cached {len(term_texts)} terms embeddings to {cache_file}")
return cache_data
except Exception as e:
print(f"Error generating terms embeddings: {e}")
logger.error(f"Error generating terms embeddings: {e}")
return {}
@ -826,14 +830,14 @@ def search_similar_terms(query_text: str, cached_terms_data: Dict[str, Any]) ->
term_info = cached_terms_data['term_info']
# 添加调试信息
print(f"DEBUG: Query text: '{query_text}'")
print(f"DEBUG: Query vector shape: {query_vector.shape}, norm: {np.linalg.norm(query_vector)}")
logger.debug(f"DEBUG: Query text: '{query_text}'")
logger.debug(f"DEBUG: Query vector shape: {query_vector.shape}, norm: {np.linalg.norm(query_vector)}")
# 计算cos相似度
similarities = _cosine_similarity(query_vector, term_embeddings)
print(f"DEBUG: Similarities: {similarities}")
print(f"DEBUG: Max similarity: {np.max(similarities):.3f}, Mean similarity: {np.mean(similarities):.3f}")
logger.debug(f"DEBUG: Similarities: {similarities}")
logger.debug(f"DEBUG: Max similarity: {np.max(similarities):.3f}, Mean similarity: {np.mean(similarities):.3f}")
# 获取所有terms的相似度
matches = []
@ -852,7 +856,7 @@ def search_similar_terms(query_text: str, cached_terms_data: Dict[str, Any]) ->
return matches[:5]
except Exception as e:
print(f"Error in similarity search: {e}")
logger.error(f"Error in similarity search: {e}")
return []

3
embedding/manager.py
View File

@ -18,8 +18,9 @@ import psutil
import numpy as np
from sentence_transformers import SentenceTransformer
import logging
logger = logging.getLogger(__name__)
logger = logging.getLogger('app')
class GlobalModelManager:

16
fastapi_app.py
View File

@ -10,7 +10,11 @@ from fastapi import FastAPI
from fastapi.staticfiles import StaticFiles
from fastapi.middleware.cors import CORSMiddleware
from routes.file_manager import router as file_manager_router
from utils.logger import logger
import logging
from utils.log_util.logger import init_with_fastapi
# Import route modules
from routes import chat, files, projects, system
@ -20,6 +24,10 @@ from routes.system import agent_manager, connection_pool, file_cache
app = FastAPI(title="Database Assistant API", version="1.0.0")
init_with_fastapi(app)
logger = logging.getLogger('app')
# 挂载public文件夹为静态文件服务
app.mount("/public", StaticFiles(directory="public"), name="static")
@ -47,7 +55,7 @@ app.include_router(file_manager_router)
if __name__ == "__main__":
# 启动 FastAPI 应用
print("Starting FastAPI server...")
print("File Manager API available at: http://localhost:8001/api/v1/files")
print("Web Interface available at: http://localhost:8001/public/file-manager.html")
logger.info("Starting FastAPI server...")
logger.info("File Manager API available at: http://localhost:8001/api/v1/files")
logger.info("Web Interface available at: http://localhost:8001/public/file-manager.html")
uvicorn.run(app, host="0.0.0.0", port=8001)

0
utils/logger.py → logger.py
View File

38
routes/chat.py
View File

@ -5,7 +5,9 @@ from typing import Union, Optional
from fastapi import APIRouter, HTTPException, Header
from fastapi.responses import StreamingResponse
from pydantic import BaseModel
import logging
logger = logging.getLogger('app')
from utils import (
Message, ChatRequest, ChatResponse
)
@ -79,6 +81,7 @@ async def generate_stream_response(agent, messages, thought_list, tool_response:
}
yield f"data: {json.dumps(chunk_data, ensure_ascii=False)}\n\n"
logger.info(f"开始生成Agent流式响应, model: {model}")
for response in agent.run(messages=messages):
previous_content = accumulated_content
accumulated_content = get_content_from_messages(response, tool_response=tool_response)
@ -92,6 +95,8 @@ async def generate_stream_response(agent, messages, thought_list, tool_response:
# 只有当有新内容时才发送chunk
if new_content:
if chunk_id == 0:
logger.info(f"Agent首个Token已生成, 开始流式输出")
chunk_id += 1
# 构造OpenAI格式的流式响应
chunk_data = {
@ -126,10 +131,11 @@ async def generate_stream_response(agent, messages, thought_list, tool_response:
# 发送结束标记
yield "data: [DONE]\n\n"
logger.info(f"Agent流式响应完成, 总共生成 {chunk_id} 个chunks")
except Exception as e:
import traceback
error_details = traceback.format_exc()
from utils.logger import logger
logger.error(f"Error in generate_stream_response: {str(e)}")
logger.error(f"Full traceback: {error_details}")
@ -168,7 +174,7 @@ async def create_agent_and_generate_response(
# 2. 如果有terms内容，先进行embedding（embedding需要缓存起来，这个可以tmp文件缓存，以{bot_id}_terms作为key）embedding实现情参考 @embedding/embedding.py 文件,可以在里面实现。拿到embedding后，可以进行相似性检索，检索方式先使用cos相似度，找到阈值相似性>0.7的匹配项，重新整理为terms_analysis，格式：1) Name: term_name1, Description: desc, Synonyms: syn1, syn2。
terms_analysis = ""
if terms_list:
print(f"terms_list: {terms_list}")
logger.info(f"terms_list: {terms_list}")
# 从messages中提取用户的查询文本用于相似性检索
query_text = get_user_last_message_content(messages)
# 使用embedding进行terms处理
@ -178,9 +184,9 @@ async def create_agent_and_generate_response(
if terms_analysis:
# 将terms分析结果也添加到消息中
system_prompt = system_prompt.replace("{terms}", terms_analysis)
print(f"Generated terms analysis: {terms_analysis[:200]}...") # 只打印前200个字符
logger.info(f"Generated terms analysis: {terms_analysis[:200]}...") # 只打印前200个字符
except Exception as e:
print(f"Error processing terms with embedding: {e}")
logger.error(f"Error processing terms with embedding: {e}")
terms_analysis = ""
else:
# 当terms_list为空时，删除对应的pkl缓存文件
@ -189,14 +195,14 @@ async def create_agent_and_generate_response(
cache_file = f"projects/cache/{bot_id}_terms.pkl"
if os.path.exists(cache_file):
os.remove(cache_file)
print(f"Removed empty terms cache file: {cache_file}")
logger.info(f"Removed empty terms cache file: {cache_file}")
except Exception as e:
print(f"Error removing terms cache file: {e}")
logger.error(f"Error removing terms cache file: {e}")
# 3. 如果有guideline内容，进行并发处理
guideline_analysis = ""
if guidelines_list:
print(f"guidelines_list: {guidelines_list}")
logger.info(f"guidelines_list: {guidelines_list}")
guidelines_count = len(guidelines_list)
if guidelines_count > 0:
@ -223,7 +229,7 @@ async def create_agent_and_generate_response(
batches[-2].extend(batches[-1])
batches.pop()
print(f"Processing {guidelines_count} guidelines in {len(batches)} batches with {batch_count} concurrent batches")
logger.info(f"Processing {guidelines_count} guidelines in {len(batches)} batches with {batch_count} concurrent batches")
# 准备chat_history
chat_history = format_messages_to_chat_history(messages)
@ -265,13 +271,13 @@ async def create_agent_and_generate_response(
# 处理结果：最后一个结果是agent，前面的是guideline批次结果
agent = all_results[-1] # agent创建的结果
batch_results = all_results[:-1] # guideline批次的结果
print(f"batch_results:{batch_results}")
logger.info(f"batch_results:{batch_results}")
# 合并guideline分析结果，使用JSON格式的checks数组
all_checks = []
for i, result in enumerate(batch_results):
if isinstance(result, Exception):
print(f"Guideline batch {i} failed: {result}")
logger.error(f"Guideline batch {i} failed: {result}")
continue
if result and isinstance(result, dict) and 'checks' in result:
# 如果是JSON对象且包含checks数组，只保留applies为true的checks
@ -279,13 +285,13 @@ async def create_agent_and_generate_response(
all_checks.extend(applicable_checks)
elif result and isinstance(result, str) and result.strip():
# 如果是普通文本，保留原有逻辑
print(f"Non-JSON result from batch {i}: {result}")
logger.info(f"Non-JSON result from batch {i}: {result}")
if all_checks:
# 将checks数组格式化为JSON字符串
guideline_analysis = "\n".join([item["rationale"] for item in all_checks])
# guideline_analysis = json.dumps({"checks": all_checks}, ensure_ascii=False)
print(f"Merged guideline analysis result: {guideline_analysis}")
logger.info(f"Merged guideline analysis result: {guideline_analysis}")
# 将分析结果添加到最后一个消息的内容中
if guideline_analysis:
@ -430,8 +436,8 @@ async def chat_completions(request: ChatRequest, authorization: Optional[str] =
except Exception as e:
import traceback
error_details = traceback.format_exc()
print(f"Error in chat_completions: {str(e)}")
print(f"Full traceback: {error_details}")
logger.error(f"Error in chat_completions: {str(e)}")
logger.error(f"Full traceback: {error_details}")
raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")
@ -526,6 +532,6 @@ async def chat_completions_v2(request: ChatRequestV2, authorization: Optional[st
except Exception as e:
import traceback
error_details = traceback.format_exc()
print(f"Error in chat_completions_v2: {str(e)}")
print(f"Full traceback: {error_details}")
logger.error(f"Error in chat_completions_v2: {str(e)}")
logger.error(f"Full traceback: {error_details}")
raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")

9
routes/file_manager.py
View File

@ -13,6 +13,9 @@ from fastapi.responses import FileResponse, StreamingResponse
import mimetypes
import json
import zipfile
import logging
logger = logging.getLogger('app')
import tempfile
import io
import math
@ -485,7 +488,7 @@ async def download_folder_as_zip(request: Dict[str, str]):
zipf.write(file_path, arcname)
except (OSError, IOError) as e:
# 跳过无法读取的文件，但记录警告
print(f"Warning: Skipping file {file_path}: {e}")
logger.warning(f"Warning: Skipping file {file_path}: {e}")
continue
zip_buffer.seek(0)
@ -586,7 +589,7 @@ async def download_multiple_items_as_zip(request: Dict[str, Any]):
try:
zipf.write(target_path, target_path.name)
except (OSError, IOError) as e:
print(f"Warning: Skipping file {target_path}: {e}")
logger.warning(f"Warning: Skipping file {target_path}: {e}")
continue
elif target_path.is_dir():
# 文件夹
@ -597,7 +600,7 @@ async def download_multiple_items_as_zip(request: Dict[str, Any]):
arcname = f"{target_path.name}/{file_path.relative_to(target_path)}"
zipf.write(file_path, arcname)
except (OSError, IOError) as e:
print(f"Warning: Skipping file {file_path}: {e}")
logger.warning(f"Warning: Skipping file {file_path}: {e}")
continue
zip_buffer.seek(0)

25
routes/files.py
View File

@ -5,6 +5,9 @@ from datetime import datetime
from typing import Optional, List
from fastapi import APIRouter, HTTPException, Header, UploadFile, File, Form
from pydantic import BaseModel
import logging
logger = logging.getLogger('app')
from utils import (
DatasetRequest, QueueTaskRequest, IncrementalTaskRequest, QueueTaskResponse,
@ -83,7 +86,7 @@ async def process_files_async_endpoint(request: QueueTaskRequest, authorization:
except HTTPException:
raise
except Exception as e:
print(f"Error submitting async file processing task: {str(e)}")
logger.error(f"Error submitting async file processing task: {str(e)}")
raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")
@ -146,7 +149,7 @@ async def process_files_incremental_endpoint(request: IncrementalTaskRequest, au
except HTTPException:
raise
except Exception as e:
print(f"Error submitting incremental file processing task: {str(e)}")
logger.error(f"Error submitting incremental file processing task: {str(e)}")
raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")
@ -260,7 +263,7 @@ async def cleanup_project_async_endpoint(dataset_id: str, remove_all: bool = Fal
"action": "remove_all" if remove_all else "cleanup_logs"
}
except Exception as e:
print(f"Error submitting cleanup task: {str(e)}")
logger.error(f"Error submitting cleanup task: {str(e)}")
raise HTTPException(status_code=500, detail=f"提交清理任务失败: {str(e)}")
@ -281,8 +284,8 @@ async def upload_file(file: UploadFile = File(...), folder: Optional[str] = Form
"""
try:
# 调试信息
print(f"Received folder parameter: {folder}")
print(f"File received: {file.filename if file else 'None'}")
logger.info(f"Received folder parameter: {folder}")
logger.info(f"File received: {file.filename if file else 'None'}")
# 确定上传文件夹
if folder:
@ -345,7 +348,7 @@ async def upload_file(file: UploadFile = File(...), folder: Optional[str] = Form
except HTTPException:
raise
except Exception as e:
print(f"Error uploading file: {str(e)}")
logger.error(f"Error uploading file: {str(e)}")
raise HTTPException(status_code=500, detail=f"文件上传失败: {str(e)}")
@ -377,7 +380,7 @@ async def get_task_status(task_id: str):
}
except Exception as e:
print(f"Error getting task status: {str(e)}")
logger.error(f"Error getting task status: {str(e)}")
raise HTTPException(status_code=500, detail=f"获取任务状态失败: {str(e)}")
@ -399,7 +402,7 @@ async def delete_task(task_id: str):
"task_id": task_id
}
except Exception as e:
print(f"Error deleting task: {str(e)}")
logger.error(f"Error deleting task: {str(e)}")
raise HTTPException(status_code=500, detail=f"删除任务记录失败: {str(e)}")
@ -428,7 +431,7 @@ async def list_tasks(status: Optional[str] = None, dataset_id: Optional[str] = N
}
except Exception as e:
print(f"Error listing tasks: {str(e)}")
logger.error(f"Error listing tasks: {str(e)}")
raise HTTPException(status_code=500, detail=f"获取任务列表失败: {str(e)}")
@ -445,7 +448,7 @@ async def get_task_statistics():
}
except Exception as e:
print(f"Error getting statistics: {str(e)}")
logger.error(f"Error getting statistics: {str(e)}")
raise HTTPException(status_code=500, detail=f"获取统计信息失败: {str(e)}")
@ -463,5 +466,5 @@ async def cleanup_tasks(older_than_days: int = 7):
}
except Exception as e:
print(f"Error cleaning up tasks: {str(e)}")
logger.error(f"Error cleaning up tasks: {str(e)}")
raise HTTPException(status_code=500, detail=f"清理任务记录失败: {str(e)}")

15
routes/projects.py
View File

@ -2,6 +2,9 @@ import os
import json
from typing import Optional
from fastapi import APIRouter, HTTPException
import logging
logger = logging.getLogger('app')
from task_queue.task_status import task_status_store
@ -45,7 +48,7 @@ async def list_all_projects():
"updated_at": os.path.getmtime(item_path)
})
except Exception as e:
print(f"Error reading robot project {item}: {str(e)}")
logger.error(f"Error reading robot project {item}: {str(e)}")
robot_projects.append({
"id": item,
"name": item,
@ -95,7 +98,7 @@ async def list_all_projects():
"updated_at": os.path.getmtime(item_path)
})
except Exception as e:
print(f"Error reading dataset {item}: {str(e)}")
logger.error(f"Error reading dataset {item}: {str(e)}")
datasets.append({
"id": item,
"name": f"数据集 - {item[:8]}...",
@ -118,7 +121,7 @@ async def list_all_projects():
}
except Exception as e:
print(f"Error listing projects: {str(e)}")
logger.error(f"Error listing projects: {str(e)}")
raise HTTPException(status_code=500, detail=f"获取项目列表失败: {str(e)}")
@ -134,7 +137,7 @@ async def list_robot_projects():
"projects": response["robot_projects"]
}
except Exception as e:
print(f"Error listing robot projects: {str(e)}")
logger.error(f"Error listing robot projects: {str(e)}")
raise HTTPException(status_code=500, detail=f"获取机器人项目列表失败: {str(e)}")
@ -150,7 +153,7 @@ async def list_datasets():
"projects": response["datasets"]
}
except Exception as e:
print(f"Error listing datasets: {str(e)}")
logger.error(f"Error listing datasets: {str(e)}")
raise HTTPException(status_code=500, detail=f"获取数据集列表失败: {str(e)}")
@ -169,5 +172,5 @@ async def get_project_tasks(dataset_id: str):
}
except Exception as e:
print(f"Error getting project tasks: {str(e)}")
logger.error(f"Error getting project tasks: {str(e)}")
raise HTTPException(status_code=500, detail=f"获取项目任务失败: {str(e)}")

25
routes/system.py
View File

@ -19,6 +19,9 @@ except ImportError:
from utils.fastapi_utils import get_content_from_messages
from embedding import get_model_manager
from pydantic import BaseModel
import logging
logger = logging.getLogger('app')
router = APIRouter()
@ -38,7 +41,7 @@ class EncodeResponse(BaseModel):
# 系统优化设置初始化
print("正在初始化系统优化...")
logger.info("正在初始化系统优化...")
system_optimizer = setup_system_optimizations()
# 全局助手管理器配置（使用优化后的配置）
@ -66,10 +69,10 @@ file_cache = init_global_file_cache(
ttl=int(os.getenv("FILE_CACHE_TTL", "300"))
)
print("系统优化初始化完成")
print(f"- 分片Agent管理器: {shard_count} 个分片，最多缓存 {max_cached_agents} 个agent")
print(f"- 连接池: 每主机100连接，总计500连接")
print(f"- 文件缓存: 1000个文件，TTL 300秒")
logger.info("系统优化初始化完成")
logger.info(f"- 分片Agent管理器: {shard_count} 个分片，最多缓存 {max_cached_agents} 个agent")
logger.info(f"- 连接池: 每主机100连接，总计500连接")
logger.info(f"- 文件缓存: 1000个文件，TTL 300秒")
@router.get("/api/health")
@ -128,7 +131,7 @@ async def get_performance_stats():
}
except Exception as e:
print(f"Error getting performance stats: {str(e)}")
logger.error(f"Error getting performance stats: {str(e)}")
raise HTTPException(status_code=500, detail=f"获取性能统计失败: {str(e)}")
@ -146,7 +149,7 @@ async def optimize_system(profile: str = "balanced"):
}
except Exception as e:
print(f"Error applying optimization profile: {str(e)}")
logger.error(f"Error applying optimization profile: {str(e)}")
raise HTTPException(status_code=500, detail=f"应用优化配置失败: {str(e)}")
@ -175,7 +178,7 @@ async def clear_system_cache(cache_type: Optional[str] = None):
}
except Exception as e:
print(f"Error clearing cache: {str(e)}")
logger.error(f"Error clearing cache: {str(e)}")
raise HTTPException(status_code=500, detail=f"清理缓存失败: {str(e)}")
@ -197,7 +200,7 @@ async def get_system_config():
}
except Exception as e:
print(f"Error getting system config: {str(e)}")
logger.error(f"Error getting system config: {str(e)}")
raise HTTPException(status_code=500, detail=f"获取系统配置失败: {str(e)}")
@ -260,7 +263,7 @@ async def encode_texts(request: EncodeRequest):
)
except Exception as e:
from utils.logger import logger
logger.error(f"文本编码 API 错误: {e}")
return EncodeResponse(
success=False,
@ -269,4 +272,4 @@ async def encode_texts(request: EncodeRequest):
processing_time=0.0,
total_texts=len(request.texts) if request else 0,
error=f"编码失败: {str(e)}"
)
)

6
task_queue/config.py
View File

@ -4,9 +4,13 @@ Queue configuration using SqliteHuey for asynchronous file processing.
"""
import os
import logging
from huey import SqliteHuey
from datetime import timedelta
# 配置日志
logger = logging.getLogger('app')
# 确保projects/queue_data目录存在
queue_data_dir = os.path.join(os.path.dirname(__file__), '..', 'projects', 'queue_data')
os.makedirs(queue_data_dir, exist_ok=True)
@ -24,4 +28,4 @@ huey.store_errors = True # 存储错误信息
huey.max_retries = 3 # 最大重试次数
huey.retry_delay = timedelta(seconds=60) # 重试延迟
print(f"SqliteHuey队列已初始化，数据库路径: {os.path.join(queue_data_dir, 'huey.db')}")
logger.info(f"SqliteHuey队列已初始化，数据库路径: {os.path.join(queue_data_dir, 'huey.db')}")

28
task_queue/manager.py
View File

@ -6,11 +6,15 @@ Queue manager for handling file processing queues.
import os
import json
import time
import logging
from typing import Dict, List, Optional, Any
from huey import Huey
from huey.api import Task
from datetime import datetime, timedelta
# 配置日志
logger = logging.getLogger('app')
from .config import huey
from .tasks import process_file_async, process_multiple_files_async, process_zip_file_async, cleanup_processed_files
@ -20,7 +24,7 @@ class QueueManager:
def __init__(self):
self.huey = huey
print(f"队列管理器已初始化，使用数据库: {os.path.join(os.path.dirname(__file__), '..', 'projects', 'queue_data', 'huey.db')}")
logger.info(f"队列管理器已初始化，使用数据库: {os.path.join(os.path.dirname(__file__), '..', 'projects', 'queue_data', 'huey.db')}")
def enqueue_file(
self,
@ -49,7 +53,7 @@ class QueueManager:
else:
task = process_file_async(project_id, file_path, original_filename)
print(f"文件已加入队列: {file_path}, 任务ID: {task.id}")
logger.info(f"文件已加入队列: {file_path}, 任务ID: {task.id}")
return task.id
def enqueue_multiple_files(
@ -79,7 +83,7 @@ class QueueManager:
else:
task = process_multiple_files_async(project_id, file_paths, original_filenames)
print(f"批量文件已加入队列: {len(file_paths)} 个文件, 任务ID: {task.id}")
logger.info(f"批量文件已加入队列: {len(file_paths)} 个文件, 任务ID: {task.id}")
return [task.id]
def enqueue_zip_file(
@ -109,7 +113,7 @@ class QueueManager:
else:
task = process_zip_file_async(project_id, zip_path, extract_to)
print(f"zip文件已加入队列: {zip_path}, 任务ID: {task.id}")
logger.info(f"zip文件已加入队列: {zip_path}, 任务ID: {task.id}")
return task.id
def get_task_status(self, task_id: str) -> Dict[str, Any]:
@ -201,7 +205,7 @@ class QueueManager:
stats["pending_tasks"] = len(pending_tasks)
stats["total_tasks"] += len(pending_tasks)
except Exception as e:
print(f"获取pending任务失败: {e}")
logger.error(f"获取pending任务失败: {e}")
# 尝试获取定时任务数量
try:
@ -209,7 +213,7 @@ class QueueManager:
stats["scheduled_tasks"] = len(scheduled_tasks)
stats["total_tasks"] += len(scheduled_tasks)
except Exception as e:
print(f"获取scheduled任务失败: {e}")
logger.error(f"获取scheduled任务失败: {e}")
return stats
@ -237,7 +241,7 @@ class QueueManager:
else:
return False
except Exception as e:
print(f"取消任务失败: {str(e)}")
logger.error(f"取消任务失败: {str(e)}")
return False
def cleanup_old_tasks(self, older_than_days: int = 7) -> Dict[str, Any]:
@ -292,7 +296,7 @@ class QueueManager:
else:
task = cleanup_processed_files(project_id, older_than_days)
print(f"清理任务已加入队列: 项目 {project_id}, 任务ID: {task.id}")
logger.info(f"清理任务已加入队列: 项目 {project_id}, 任务ID: {task.id}")
return task.id
def list_pending_tasks(self, limit: int = 50) -> List[Dict[str, Any]]:
@ -318,7 +322,7 @@ class QueueManager:
"status": "pending",
})
except Exception as e:
print(f"获取pending任务失败: {e}")
logger.error(f"获取pending任务失败: {e}")
# 获取scheduled任务
try:
@ -330,12 +334,12 @@ class QueueManager:
"status": "scheduled",
})
except Exception as e:
print(f"获取scheduled任务失败: {e}")
logger.error(f"获取scheduled任务失败: {e}")
return pending_tasks
except Exception as e:
print(f"获取待处理任务失败: {str(e)}")
logger.error(f"获取待处理任务失败: {str(e)}")
return []
def get_task_result(self, task_id: str) -> Optional[Any]:
@ -354,7 +358,7 @@ class QueueManager:
return task.get()
return None
except Exception as e:
print(f"获取任务结果失败: {str(e)}")
logger.error(f"获取任务结果失败: {str(e)}")
return None

85
task_queue/optimized_consumer.py
View File

@ -9,10 +9,14 @@ import time
import signal
import argparse
import multiprocessing
import logging
from pathlib import Path
from concurrent.futures import ThreadPoolExecutor
import threading
# 配置日志
logger = logging.getLogger('app')
# 添加项目根目录到Python路径
project_root = Path(__file__).parent.parent
sys.path.insert(0, str(project_root))
@ -50,7 +54,7 @@ class OptimizedQueueConsumer:
def _signal_handler(self, signum, frame):
"""信号处理器，用于优雅关闭"""
print(f"\n收到信号 {signum}，正在关闭队列消费者...")
logger.info(f"\n收到信号 {signum}，正在关闭队列消费者...")
self.running = False
if self.consumer:
self.consumer.stop()
@ -80,9 +84,9 @@ class OptimizedQueueConsumer:
if hasattr(huey, 'always_eager'):
huey.always_eager = False
print(f"队列消费者优化设置完成:")
print(f"- 工作类型: {self.worker_type}")
print(f"- 工作线程数: {self.workers}")
logger.info(f"队列消费者优化设置完成:")
logger.info(f"- 工作类型: {self.worker_type}")
logger.info(f"- 工作线程数: {self.workers}")
def monitor_performance(self):
"""性能监控线程"""
@ -93,27 +97,26 @@ class OptimizedQueueConsumer:
elapsed = time.time() - self.start_time
rate = self.performance_stats['tasks_processed'] / max(1, elapsed)
print(f"\n[性能统计]")
print(f"- 运行时间: {elapsed:.1f}秒")
print(f"- 已处理任务: {self.performance_stats['tasks_processed']}")
print(f"- 失败任务: {self.performance_stats['tasks_failed']}")
print(f"- 平均处理速率: {rate:.2f} 任务/秒")
logger.info(f"\n[性能统计]")
logger.info(f"- 运行时间: {elapsed:.1f}秒")
logger.info(f"- 已处理任务: {self.performance_stats['tasks_processed']}")
logger.info(f"- 失败任务: {self.performance_stats['tasks_failed']}")
logger.info(f"- 平均处理速率: {rate:.2f} 任务/秒")
if self.performance_stats['avg_processing_time'] > 0:
print(f"- 平均处理时间: {self.performance_stats['avg_processing_time']:.2f}秒")
logger.info(f"- 平均处理时间: {self.performance_stats['avg_processing_time']:.2f}秒")
def start(self):
"""启动队列消费者"""
print("=" * 60)
print("优化的队列消费者启动")
print("=" * 60)
logger.info("=" * 60)
logger.info("优化的队列消费者启动")
logger.info("=" * 60)
# 设置优化
self.setup_optimizations()
print(f"数据库: {os.path.join(os.path.dirname(__file__), '..', 'projects', 'queue_data', 'huey.db')}")
print("按 Ctrl+C 停止消费者")
print()
logger.info(f"数据库: {os.path.join(os.path.dirname(__file__), '..', 'projects', 'queue_data', 'huey.db')}")
logger.info("按 Ctrl+C 停止消费者")
self.running = True
self.start_time = time.time()
@ -134,15 +137,15 @@ class OptimizedQueueConsumer:
periodic=True, # 启用定期任务
)
print("队列消费者已启动，等待任务...")
logger.info("队列消费者已启动，等待任务...")
# 启动消费者
self.consumer.run()
except KeyboardInterrupt:
print("\n收到键盘中断信号")
logger.info("\n收到键盘中断信号")
except Exception as e:
print(f"队列消费者运行错误: {e}")
logger.error(f"队列消费者运行错误: {e}")
import traceback
traceback.print_exc()
finally:
@ -150,27 +153,27 @@ class OptimizedQueueConsumer:
def shutdown(self):
"""关闭队列消费者"""
print("\n正在关闭队列消费者...")
logger.info("\n正在关闭队列消费者...")
self.running = False
if self.consumer:
try:
self.consumer.stop()
print("队列消费者已停止")
logger.info("队列消费者已停止")
except Exception as e:
print(f"停止队列消费者时出错: {e}")
logger.error(f"停止队列消费者时出错: {e}")
# 输出最终统计
if self.start_time:
elapsed = time.time() - self.start_time
print(f"\n[最终统计]")
print(f"- 总运行时间: {elapsed:.1f}秒")
print(f"- 总处理任务: {self.performance_stats['tasks_processed']}")
print(f"- 总失败任务: {self.performance_stats['tasks_failed']}")
logger.info(f"\n[最终统计]")
logger.info(f"- 总运行时间: {elapsed:.1f}秒")
logger.info(f"- 总处理任务: {self.performance_stats['tasks_processed']}")
logger.info(f"- 总失败任务: {self.performance_stats['tasks_failed']}")
if self.performance_stats['tasks_processed'] > 0:
rate = self.performance_stats['tasks_processed'] / elapsed
print(f"- 平均处理速率: {rate:.2f} 任务/秒")
logger.info(f"- 平均处理速率: {rate:.2f} 任务/秒")
def calculate_optimal_workers():
@ -191,25 +194,25 @@ def check_queue_status():
try:
stats = queue_manager.get_queue_stats()
print("\n[队列状态]")
logger.info("\n[队列状态]")
if isinstance(stats, dict):
if 'total_tasks' in stats:
print(f"- 总任务数: {stats['total_tasks']}")
logger.info(f"- 总任务数: {stats['total_tasks']}")
if 'pending_tasks' in stats:
print(f"- 待处理任务: {stats['pending_tasks']}")
logger.info(f"- 待处理任务: {stats['pending_tasks']}")
if 'scheduled_tasks' in stats:
print(f"- 定时任务: {stats['scheduled_tasks']}")
logger.info(f"- 定时任务: {stats['scheduled_tasks']}")
# 检查数据库文件
db_path = os.path.join(os.path.dirname(__file__), '..', 'projects', 'queue_data', 'huey.db')
if os.path.exists(db_path):
size = os.path.getsize(db_path)
print(f"- 数据库大小: {size} 字节")
logger.info(f"- 数据库大小: {size} 字节")
else:
print("- 数据库文件: 不存在")
logger.info("- 数据库文件: 不存在")
except Exception as e:
print(f"获取队列状态失败: {e}")
logger.error(f"获取队列状态失败: {e}")
def main():
@ -248,11 +251,11 @@ def main():
os.environ['PYTHONOPTIMIZE'] = '1'
if args.workers > 2:
args.workers = 2
print(f"低内存模式: 调整工作线程数为 {args.workers}")
logger.info(f"低内存模式: 调整工作线程数为 {args.workers}")
elif args.profile == "high_performance":
if args.workers < 4:
args.workers = 4
print(f"高性能模式: 调整工作线程数为 {args.workers}")
logger.info(f"高性能模式: 调整工作线程数为 {args.workers}")
# 检查队列状态
if args.check_status:
@ -263,12 +266,12 @@ def main():
try:
import psutil
memory = psutil.virtual_memory()
print(f"[系统信息]")
print(f"- CPU核心数: {multiprocessing.cpu_count()}")
print(f"- 可用内存: {memory.available / (1024**3):.1f}GB")
print(f"- 内存使用率: {memory.percent:.1f}%")
logger.info(f"[系统信息]")
logger.info(f"- CPU核心数: {multiprocessing.cpu_count()}")
logger.info(f"- 可用内存: {memory.available / (1024**3):.1f}GB")
logger.info(f"- 内存使用率: {memory.percent:.1f}%")
except ImportError:
print("[提示] 安装 psutil 可显示系统信息: pip install psutil")
logger.info("[提示] 安装 psutil 可显示系统信息: pip install psutil")
# 创建并启动队列消费者
consumer = OptimizedQueueConsumer(

36
task_queue/tasks.py
View File

@ -7,10 +7,14 @@ import os
import json
import time
import shutil
import logging
from pathlib import Path
from typing import Dict, List, Optional, Any
from huey import crontab
# 配置日志
logger = logging.getLogger('app')
from .config import huey
from utils.file_utils import (
extract_zip_file,
@ -42,7 +46,7 @@ def process_file_async(
处理结果字典
"""
try:
print(f"开始处理文件: {file_path}")
logger.info(f"开始处理文件: {file_path}")
# 确保项目目录存在
project_dir = os.path.join("projects", project_id)
@ -55,7 +59,7 @@ def process_file_async(
# 检查文件是否已处理
processed_log = load_processed_files_log(project_id)
if file_hash in processed_log:
print(f"文件已处理，跳过: {file_path}")
logger.info(f"文件已处理，跳过: {file_path}")
return {
"status": "skipped",
"message": "文件已处理",
@ -84,12 +88,12 @@ def process_file_async(
result["file_hash"] = file_hash
result["project_id"] = project_id
print(f"文件处理完成: {file_path}, 状态: {result['status']}")
logger.info(f"文件处理完成: {file_path}, 状态: {result['status']}")
return result
except Exception as e:
error_msg = f"处理文件时发生错误: {str(e)}"
print(error_msg)
logger.error(error_msg)
return {
"status": "error",
"message": error_msg,
@ -116,7 +120,7 @@ def process_multiple_files_async(
处理结果列表
"""
try:
print(f"开始批量处理 {len(file_paths)} 个文件")
logger.info(f"开始批量处理 {len(file_paths)} 个文件")
results = []
for i, file_path in enumerate(file_paths):
@ -126,12 +130,12 @@ def process_multiple_files_async(
result = process_file_async(project_id, file_path, original_filename)
results.append(result)
print(f"批量文件处理任务已提交，共 {len(results)} 个文件")
logger.info(f"批量文件处理任务已提交，共 {len(results)} 个文件")
return results
except Exception as e:
error_msg = f"批量处理文件时发生错误: {str(e)}"
print(error_msg)
logger.error(error_msg)
return [{
"status": "error",
"message": error_msg,
@ -157,7 +161,7 @@ def process_zip_file_async(
处理结果字典
"""
try:
print(f"开始处理zip文件: {zip_path}")
logger.info(f"开始处理zip文件: {zip_path}")
# 设置解压目录
if extract_to is None:
@ -191,7 +195,7 @@ def process_zip_file_async(
except Exception as e:
error_msg = f"处理zip文件时发生错误: {str(e)}"
print(error_msg)
logger.error(error_msg)
return {
"status": "error",
"message": error_msg,
@ -216,7 +220,7 @@ def cleanup_processed_files(
清理结果字典
"""
try:
print(f"开始清理项目 {project_id} 中 {older_than_days} 天前的文件")
logger.info(f"开始清理项目 {project_id} 中 {older_than_days} 天前的文件")
project_dir = os.path.join("projects", project_id)
if not os.path.exists(project_dir):
@ -240,9 +244,9 @@ def cleanup_processed_files(
try:
os.remove(file_path)
cleaned_files.append(file_path)
print(f"已删除旧文件: {file_path}")
logger.info(f"已删除旧文件: {file_path}")
except Exception as e:
print(f"删除文件失败 {file_path}: {str(e)}")
logger.error(f"删除文件失败 {file_path}: {str(e)}")
# 清理空目录
for root, dirs, files in os.walk(project_dir, topdown=False):
@ -251,9 +255,9 @@ def cleanup_processed_files(
try:
if not os.listdir(dir_path):
os.rmdir(dir_path)
print(f"已删除空目录: {dir_path}")
logger.info(f"已删除空目录: {dir_path}")
except Exception as e:
print(f"删除目录失败 {dir_path}: {str(e)}")
logger.error(f"删除目录失败 {dir_path}: {str(e)}")
return {
"status": "success",
@ -265,7 +269,7 @@ def cleanup_processed_files(
except Exception as e:
error_msg = f"清理文件时发生错误: {str(e)}"
print(error_msg)
logger.error(error_msg)
return {
"status": "error",
"message": error_msg,
@ -351,6 +355,6 @@ def _process_single_file(
@huey.periodic_task(crontab(hour=2, minute=0))
def daily_cleanup():
"""每日清理任务"""
print("执行每日清理任务")
logger.info("执行每日清理任务")
# 这里可以添加清理逻辑
return {"status": "completed", "message": "每日清理任务完成"}

4
utils/agent_pool.py
View File

@ -2,7 +2,7 @@ import asyncio
from typing import List, Optional
import logging
logger = logging.getLogger(__name__)
logger = logging.getLogger('app')
class AgentPool:
@ -175,4 +175,4 @@ async def release_agent_to_pool(agent):
if _global_agent_pool is None:
raise RuntimeError("全局助手实例池未初始化")
await _global_agent_pool.release_agent(agent)
await _global_agent_pool.release_agent(agent)

12
utils/async_file_ops.py
View File

@ -8,6 +8,7 @@ import json
import asyncio
import aiofiles
import aiofiles.os
import logging
from typing import Dict, List, Optional, Any
from pathlib import Path
import weakref
@ -15,6 +16,9 @@ import threading
import time
from concurrent.futures import ThreadPoolExecutor
# Configure logger
logger = logging.getLogger('app')
class AsyncFileCache:
"""异步文件缓存管理器"""
@ -70,7 +74,7 @@ class AsyncFileCache:
return content
except Exception as e:
print(f"Error reading file {abs_path}: {e}")
logger.error(f"Error reading file {abs_path}: {e}")
return ""
def _read_text_file(self, file_path: str, encoding: str) -> str:
@ -90,7 +94,7 @@ class AsyncFileCache:
try:
return json.loads(content)
except json.JSONDecodeError as e:
print(f"Error parsing JSON from {file_path}: {e}")
logger.error(f"Error parsing JSON from {file_path}: {e}")
return {}
async def write_file(self, file_path: str, content: str, encoding: str = 'utf-8'):
@ -244,7 +248,7 @@ class ParallelFileReader:
content = await task
results[file_path] = content
except Exception as e:
print(f"Error reading {file_path}: {e}")
logger.error(f"Error reading {file_path}: {e}")
results[file_path] = ""
return results
@ -269,7 +273,7 @@ class ParallelFileReader:
try:
results[file_path] = json.loads(content)
except json.JSONDecodeError as e:
print(f"Error parsing JSON from {file_path}: {e}")
logger.error(f"Error parsing JSON from {file_path}: {e}")
results[file_path] = {}
else:
results[file_path] = {}

28
utils/data_merger.py
View File

@ -5,15 +5,19 @@ Data merging functions for combining processed file results.
import os
import pickle
import logging
from typing import Dict, List, Optional, Tuple
import json
# Configure logger
logger = logging.getLogger('app')
# Try to import numpy, but handle if missing
try:
import numpy as np
NUMPY_SUPPORT = True
except ImportError:
print("NumPy not available, some embedding features may be limited")
logger.warning("NumPy not available, some embedding features may be limited")
NUMPY_SUPPORT = False
@ -66,7 +70,7 @@ def merge_documents_by_group(unique_id: str, group_name: str) -> Dict:
result["source_files"].append(filename_stem)
except Exception as e:
print(f"Error reading document file {document_path}: {str(e)}")
logger.error(f"Error reading document file {document_path}: {str(e)}")
continue
if merged_content:
@ -83,7 +87,7 @@ def merge_documents_by_group(unique_id: str, group_name: str) -> Dict:
except Exception as e:
result["error"] = f"Document merging failed: {str(e)}"
print(f"Error merging documents for group {group_name}: {str(e)}")
logger.error(f"Error merging documents for group {group_name}: {str(e)}")
return result
@ -136,7 +140,7 @@ def merge_paginations_by_group(unique_id: str, group_name: str) -> Dict:
result["source_files"].append(filename_stem)
except Exception as e:
print(f"Error reading pagination file {pagination_path}: {str(e)}")
logger.error(f"Error reading pagination file {pagination_path}: {str(e)}")
continue
if merged_lines:
@ -153,7 +157,7 @@ def merge_paginations_by_group(unique_id: str, group_name: str) -> Dict:
except Exception as e:
result["error"] = f"Pagination merging failed: {str(e)}"
print(f"Error merging paginations for group {group_name}: {str(e)}")
logger.error(f"Error merging paginations for group {group_name}: {str(e)}")
return result
@ -236,7 +240,7 @@ def merge_embeddings_by_group(unique_id: str, group_name: str) -> Dict:
result["source_files"].append(filename_stem)
except Exception as e:
print(f"Error loading embedding file {embedding_path}: {str(e)}")
logger.error(f"Error loading embedding file {embedding_path}: {str(e)}")
continue
if all_chunks and all_embeddings:
@ -259,7 +263,7 @@ def merge_embeddings_by_group(unique_id: str, group_name: str) -> Dict:
np_embeddings.append(emb)
else:
# 如果无法转换，跳过这个文件
print(f"Warning: Cannot convert embedding to numpy from file {filename_stem}")
logger.warning(f"Warning: Cannot convert embedding to numpy from file {filename_stem}")
continue
if np_embeddings:
@ -283,7 +287,7 @@ def merge_embeddings_by_group(unique_id: str, group_name: str) -> Dict:
elif isinstance(emb, np.ndarray):
np_embeddings.append(emb)
else:
print(f"Warning: Cannot convert embedding to numpy from file {filename_stem}")
logger.warning(f"Warning: Cannot convert embedding to numpy from file {filename_stem}")
continue
if np_embeddings:
@ -297,7 +301,7 @@ def merge_embeddings_by_group(unique_id: str, group_name: str) -> Dict:
return result
except Exception as e:
result["error"] = f"Failed to merge embedding tensors: {str(e)}"
print(f"Error merging embedding tensors: {str(e)}")
logger.error(f"Error merging embedding tensors: {str(e)}")
return result
# Create merged embedding data structure
@ -327,7 +331,7 @@ def merge_embeddings_by_group(unique_id: str, group_name: str) -> Dict:
except Exception as e:
result["error"] = f"Embedding merging failed: {str(e)}"
print(f"Error merging embeddings for group {group_name}: {str(e)}")
logger.error(f"Error merging embeddings for group {group_name}: {str(e)}")
return result
@ -425,11 +429,11 @@ def cleanup_dataset_group(unique_id: str, group_name: str) -> bool:
if os.path.exists(dataset_group_dir):
import shutil
shutil.rmtree(dataset_group_dir)
print(f"Cleaned up dataset group: {group_name}")
logger.info(f"Cleaned up dataset group: {group_name}")
return True
else:
return True # Nothing to clean up
except Exception as e:
print(f"Error cleaning up dataset group {group_name}: {str(e)}")
logger.error(f"Error cleaning up dataset group {group_name}: {str(e)}")
return False

42
utils/dataset_manager.py
View File

@ -6,8 +6,12 @@ New implementation with per-file processing and group merging.
import os
import json
import logging
from typing import Dict, List
# Configure logger
logger = logging.getLogger('app')
# Import new modules
from utils.file_manager import (
ensure_directories, sync_files_to_group, cleanup_orphaned_files,
@ -37,13 +41,13 @@ async def download_dataset_files(unique_id: str, files: Dict[str, List[str]], in
if not files:
return {}
print(f"Starting {'incremental' if incremental_mode else 'full'} file processing for project: {unique_id}")
logger.info(f"Starting {'incremental' if incremental_mode else 'full'} file processing for project: {unique_id}")
# Ensure project directories exist
ensure_directories(unique_id)
# Step 1: Sync files to group directories
print("Step 1: Syncing files to group directories...")
logger.info("Step 1: Syncing files to group directories...")
synced_files, failed_files = sync_files_to_group(unique_id, files, incremental_mode)
# Step 2: Detect changes and cleanup orphaned files (only in non-incremental mode)
@ -52,14 +56,14 @@ async def download_dataset_files(unique_id: str, files: Dict[str, List[str]], in
# Only cleanup orphaned files in non-incremental mode or when files are explicitly removed
if not incremental_mode and any(changes["removed"].values()):
print("Step 2: Cleaning up orphaned files...")
logger.info("Step 2: Cleaning up orphaned files...")
removed_files = cleanup_orphaned_files(unique_id, changes)
print(f"Removed orphaned files: {removed_files}")
logger.info(f"Removed orphaned files: {removed_files}")
elif incremental_mode:
print("Step 2: Skipping cleanup in incremental mode to preserve existing files")
logger.info("Step 2: Skipping cleanup in incremental mode to preserve existing files")
# Step 3: Process individual files
print("Step 3: Processing individual files...")
logger.info("Step 3: Processing individual files...")
processed_files_by_group = {}
processing_results = {}
@ -75,12 +79,12 @@ async def download_dataset_files(unique_id: str, files: Dict[str, List[str]], in
# Skip if file doesn't exist (might be remote file that failed to download)
if not os.path.exists(local_path) and not file_path.startswith(('http://', 'https://')):
print(f"Skipping non-existent file: {filename}")
logger.warning(f"Skipping non-existent file: {filename}")
continue
# Check if already processed
if check_file_already_processed(unique_id, group_name, filename):
print(f"Skipping already processed file: {filename}")
logger.info(f"Skipping already processed file: {filename}")
processed_files_by_group[group_name].append(filename)
processing_results[group_name].append({
"filename": filename,
@ -89,18 +93,18 @@ async def download_dataset_files(unique_id: str, files: Dict[str, List[str]], in
continue
# Process the file
print(f"Processing file: {filename} (group: {group_name})")
logger.info(f"Processing file: {filename} (group: {group_name})")
result = await process_single_file(unique_id, group_name, filename, file_path, local_path)
processing_results[group_name].append(result)
if result["success"]:
processed_files_by_group[group_name].append(filename)
print(f" Successfully processed {filename}")
logger.info(f" Successfully processed {filename}")
else:
print(f" Failed to process {filename}: {result['error']}")
logger.error(f" Failed to process {filename}: {result['error']}")
# Step 4: Merge results by group
print("Step 4: Merging results by group...")
logger.info("Step 4: Merging results by group...")
merge_results = {}
for group_name in processed_files_by_group.keys():
@ -108,20 +112,20 @@ async def download_dataset_files(unique_id: str, files: Dict[str, List[str]], in
group_files = get_group_files_list(unique_id, group_name)
if group_files:
print(f"Merging group: {group_name} with {len(group_files)} files")
logger.info(f"Merging group: {group_name} with {len(group_files)} files")
merge_result = merge_all_data_by_group(unique_id, group_name)
merge_results[group_name] = merge_result
if merge_result["success"]:
print(f" Successfully merged group {group_name}")
logger.info(f" Successfully merged group {group_name}")
else:
print(f" Failed to merge group {group_name}: {merge_result['errors']}")
logger.error(f" Failed to merge group {group_name}: {merge_result['errors']}")
# Step 5: Save processing log
print("Step 5: Saving processing log...")
logger.info("Step 5: Saving processing log...")
await save_processing_log(unique_id, files, synced_files, processing_results, merge_results)
print(f"File processing completed for project: {unique_id}")
logger.info(f"File processing completed for project: {unique_id}")
return processed_files_by_group
@ -156,9 +160,9 @@ async def save_processing_log(
try:
with open(log_file_path, 'w', encoding='utf-8') as f:
json.dump(log_data, f, ensure_ascii=False, indent=2)
print(f"Processing log saved to: {log_file_path}")
logger.info(f"Processing log saved to: {log_file_path}")
except Exception as e:
print(f"Error saving processing log: {str(e)}")
logger.error(f"Error saving processing log: {str(e)}")
def generate_dataset_structure(unique_id: str) -> str:

14
utils/excel_csv_processor.py
View File

@ -5,8 +5,12 @@ Excel and CSV file processor for converting data to document.txt and pagination.
import os
import pandas as pd
import logging
from typing import List, Dict, Any, Tuple
# 配置日志
logger = logging.getLogger('app')
def read_excel_sheets(file_path: str) -> Dict[str, List[Dict[str, Any]]]:
"""
@ -48,16 +52,16 @@ def read_excel_sheets(file_path: str) -> Dict[str, List[Dict[str, Any]]]:
sheet_data.append(row_dict)
sheets_data[sheet_name] = sheet_data
print(f"读取 Excel sheet '{sheet_name}': {len(sheet_data)} 行数据")
logger.info(f"读取 Excel sheet '{sheet_name}': {len(sheet_data)} 行数据")
except Exception as e:
print(f"读取 Excel sheet '{sheet_name}' 失败: {str(e)}")
logger.error(f"读取 Excel sheet '{sheet_name}' 失败: {str(e)}")
continue
return sheets_data
except Exception as e:
print(f"读取 Excel 文件失败: {str(e)}")
logger.error(f"读取 Excel 文件失败: {str(e)}")
return {}
@ -105,11 +109,11 @@ def read_csv_file(file_path: str, encoding: str = 'utf-8') -> List[Dict[str, Any
if any(v.strip() for v in row_dict.values()):
csv_data.append(row_dict)
print(f"读取 CSV 文件: {len(csv_data)} 行数据")
logger.info(f"读取 CSV 文件: {len(csv_data)} 行数据")
return csv_data
except Exception as e:
print(f"读取 CSV 文件失败: {str(e)}")
logger.error(f"读取 CSV 文件失败: {str(e)}")
return []

77
utils/fastapi_utils.py
View File

@ -9,7 +9,9 @@ import aiohttp
from qwen_agent.llm.schema import ASSISTANT, FUNCTION
from qwen_agent.llm.oai import TextChatAtOAI
from fastapi import HTTPException
from utils.logger import logger
import logging
logger = logging.getLogger('app')
# 创建全局线程池执行器，用于执行同步的HTTP调用
thread_pool = ThreadPoolExecutor(max_workers=10)
@ -61,9 +63,9 @@ def get_versioned_filename(upload_dir: str, name_without_ext: str, file_extensio
file_to_delete = os.path.join(upload_dir, filename)
try:
os.remove(file_to_delete)
print(f"已删除文件: {file_to_delete}")
logger.info(f"已删除文件: {file_to_delete}")
except OSError as e:
print(f"删除文件失败 {file_to_delete}: {e}")
logger.error(f"删除文件失败 {file_to_delete}: {e}")
# 确定下一个版本号
if existing_versions:
@ -301,7 +303,7 @@ def create_project_directory(dataset_ids: Optional[List[str]], bot_id: str, robo
from utils.multi_project_manager import create_robot_project
return create_robot_project(dataset_ids, bot_id)
except Exception as e:
print(f"Error creating project directory: {e}")
logger.error(f"Error creating project directory: {e}")
return None
@ -392,7 +394,7 @@ def _sync_call_guideline_llm(llm_config, messages) -> str:
return str(response) if response else ""
except Exception as e:
print(f"Error calling guideline LLM: {e}")
logger.error(f"Error calling guideline LLM: {e}")
return ""
@ -414,7 +416,7 @@ async def call_guideline_llm(chat_history: str, guidelines_text: str, terms:str,
with open('./prompt/guideline_prompt.md', 'r', encoding='utf-8') as f:
guideline_template = f.read()
except Exception as e:
print(f"Error reading guideline prompt template: {e}")
logger.error(f"Error reading guideline prompt template: {e}")
return ""
# 替换模板中的占位符
@ -439,7 +441,7 @@ async def call_guideline_llm(chat_history: str, guidelines_text: str, terms:str,
return response
except Exception as e:
print(f"Error calling guideline LLM: {e}")
logger.error(f"Error calling guideline LLM: {e}")
return ""
@ -466,28 +468,43 @@ async def process_guideline_batch(
model_server: str
) -> str:
"""处理单个guideline批次"""
try:
# 调用LLM分析这批guidelines
batch_guidelines_text = "\n".join(guidelines_batch)
batch_analysis = await call_guideline_llm(chat_history, batch_guidelines_text, terms, model_name, api_key, model_server)
max_retries = 3
# 从响应中提取 ```json 和 ``` 包裹的内容
json_pattern = r'```json\s*\n(.*?)\n```'
json_matches = re.findall(json_pattern, batch_analysis, re.DOTALL)
if json_matches:
try:
# 解析第一个找到的JSON对象
json_data = json.loads(json_matches[0])
return json_data # 返回解析后的JSON对象
except json.JSONDecodeError as e:
print(f"Error parsing JSON from guideline analysis: {e}")
return batch_analysis # 如果JSON解析失败，返回原始文本
else:
return batch_analysis # 如果没有找到JSON格式，返回原始文本
except Exception as e:
print(f"Error processing guideline batch: {e}")
return ""
for attempt in range(max_retries):
try:
# 调用LLM分析这批guidelines
batch_guidelines_text = "\n".join(guidelines_batch)
logger.info(f"Start processed guideline batch on attempt {attempt + 1}")
batch_analysis = await call_guideline_llm(chat_history, batch_guidelines_text, terms, model_name, api_key, model_server)
# 从响应中提取 ```json 和 ``` 包裹的内容
json_pattern = r'```json\s*\n(.*?)\n```'
json_matches = re.findall(json_pattern, batch_analysis, re.DOTALL)
if json_matches:
try:
# 解析第一个找到的JSON对象
json_data = json.loads(json_matches[0])
logger.info(f"Successfully processed guideline batch on attempt {attempt + 1}")
return json_data # 返回解析后的JSON对象
except json.JSONDecodeError as e:
logger.error(f"Error parsing JSON from guideline analysis on attempt {attempt + 1}: {e}")
if attempt == max_retries - 1:
return batch_analysis # 最后一次尝试失败，返回原始文本
continue
else:
logger.warning(f"No JSON format found in guideline analysis on attempt {attempt + 1}")
if attempt == max_retries - 1:
return batch_analysis # 最后一次尝试失败，返回原始文本
continue
except Exception as e:
logger.error(f"Error processing guideline batch on attempt {attempt + 1}: {e}")
if attempt == max_retries - 1:
return "" # 最后一次尝试失败，返回空字符串
# 这里不应该到达，但为了完整性
return ""
def extract_block_from_system_prompt(system_prompt: Optional[str]) -> tuple[str, List[Dict[str, Any]], List[Dict[str, Any]]]:
@ -519,7 +536,7 @@ def extract_block_from_system_prompt(system_prompt: Optional[str]) -> tuple[str,
guidelines_list.extend(guidelines)
blocks_to_remove.append(match.group(0))
except Exception as e:
print(f"Error parsing guidelines: {e}")
logger.error(f"Error parsing guidelines: {e}")
elif block_type == 'terms':
try:
@ -527,7 +544,7 @@ def extract_block_from_system_prompt(system_prompt: Optional[str]) -> tuple[str,
terms_list.extend(terms)
blocks_to_remove.append(match.group(0))
except Exception as e:
print(f"Error parsing terms: {e}")
logger.error(f"Error parsing terms: {e}")
# 从system_prompt中移除这些已解析的块
cleaned_prompt = system_prompt

11
utils/file_manager.py
View File

@ -8,6 +8,9 @@ import json
import shutil
from typing import Dict, List, Set, Tuple
from pathlib import Path
import logging
logger = logging.getLogger('app')
def get_existing_files(unique_id: str) -> Dict[str, Set[str]]:
@ -204,11 +207,11 @@ def cleanup_orphaned_files(unique_id: str, changes: Dict) -> Dict[str, List[str]
removed_files[group_name].append(f"processed: {Path(filename).stem}")
except Exception as e:
print(f"Error cleaning up {filename}: {str(e)}")
logger.error(f"Error cleaning up {filename}: {str(e)}")
# Handle completely removed groups
for group_name in changes.get("removed_groups", set()):
print(f"Cleaning up completely removed group: {group_name}")
logger.info(f"Cleaning up completely removed group: {group_name}")
removed_files[group_name] = []
try:
@ -230,10 +233,10 @@ def cleanup_orphaned_files(unique_id: str, changes: Dict) -> Dict[str, List[str]
shutil.rmtree(dataset_group_dir)
removed_files[group_name].append("dataset group directory")
print(f"Completely removed group '{group_name}' and all its data")
logger.info(f"Completely removed group '{group_name}' and all its data")
except Exception as e:
print(f"Error cleaning up group {group_name}: {str(e)}")
logger.error(f"Error cleaning up group {group_name}: {str(e)}")
return removed_files

34
utils/file_utils.py
View File

@ -10,9 +10,13 @@ import aiohttp
import shutil
import zipfile
import tempfile
import logging
from typing import Dict, List, Optional
from pathlib import Path
# 配置日志
logger = logging.getLogger('app')
async def download_file(url: str, destination_path: str) -> bool:
"""Download file from URL asynchronously"""
@ -25,10 +29,10 @@ async def download_file(url: str, destination_path: str) -> bool:
await f.write(chunk)
return True
else:
print(f"Failed to download {url}, status code: {response.status}")
logger.error(f"Failed to download {url}, status code: {response.status}")
return False
except Exception as e:
print(f"Error downloading {url}: {str(e)}")
logger.error(f"Error downloading {url}: {str(e)}")
return False
@ -45,11 +49,11 @@ def remove_file_or_directory(path: str):
os.remove(path)
elif os.path.isdir(path):
shutil.rmtree(path)
print(f"Removed: {path}")
logger.info(f"Removed: {path}")
else:
print(f"Path does not exist: {path}")
logger.warning(f"Path does not exist: {path}")
except Exception as e:
print(f"Error removing {path}: {str(e)}")
logger.error(f"Error removing {path}: {str(e)}")
def extract_zip_file(zip_path: str, extract_dir: str) -> List[str]:
@ -65,11 +69,11 @@ def extract_zip_file(zip_path: str, extract_dir: str) -> List[str]:
if file.lower().endswith(('.txt', '.md', '.xlsx', '.xls', '.csv')):
extracted_files.append(os.path.join(root, file))
print(f"Extracted {len(extracted_files)} txt/md/xlsx/csv files from {zip_path}")
logger.info(f"Extracted {len(extracted_files)} txt/md/xlsx/csv files from {zip_path}")
return extracted_files
except Exception as e:
print(f"Error extracting zip file {zip_path}: {str(e)}")
logger.error(f"Error extracting zip file {zip_path}: {str(e)}")
return []
@ -110,7 +114,7 @@ def load_processed_files_log(unique_id: str) -> Dict[str, Dict]:
with open(log_file, 'r', encoding='utf-8') as f:
return json.load(f)
except Exception as e:
print(f"Error loading processed files log: {e}")
logger.error(f"Error loading processed files log: {e}")
return {}
@ -123,7 +127,7 @@ def save_processed_files_log(unique_id: str, processed_log: Dict[str, Dict]):
with open(log_file, 'w', encoding='utf-8') as f:
json.dump(processed_log, f, ensure_ascii=False, indent=2)
except Exception as e:
print(f"Error saving processed files log: {e}")
logger.error(f"Error saving processed files log: {e}")
def get_processing_log(unique_id: str) -> Dict:
@ -135,7 +139,7 @@ def get_processing_log(unique_id: str) -> Dict:
with open(log_file, 'r', encoding='utf-8') as f:
return json.load(f)
except Exception as e:
print(f"Error loading processing log: {e}")
logger.error(f"Error loading processing log: {e}")
return {}
@ -148,7 +152,7 @@ def save_project_status(unique_id: str, status: Dict):
with open(status_file, 'w', encoding='utf-8') as f:
json.dump(status, f, ensure_ascii=False, indent=2)
except Exception as e:
print(f"Error saving project status: {e}")
logger.error(f"Error saving project status: {e}")
def load_project_status(unique_id: str) -> Dict:
@ -160,7 +164,7 @@ def load_project_status(unique_id: str) -> Dict:
with open(status_file, 'r', encoding='utf-8') as f:
return json.load(f)
except Exception as e:
print(f"Error loading project status: {e}")
logger.error(f"Error loading project status: {e}")
return {}
@ -212,7 +216,7 @@ def update_file_processing_status(unique_id: str, group_name: str, filename: str
json.dump(file_status, f, ensure_ascii=False, indent=2)
except Exception as e:
print(f"Error updating file processing status: {e}")
logger.error(f"Error updating file processing status: {e}")
def get_file_processing_status(unique_id: str, group_name: str = None, filename: str = None) -> Dict:
@ -240,7 +244,7 @@ def get_file_processing_status(unique_id: str, group_name: str = None, filename:
return file_status
except Exception as e:
print(f"Error getting file processing status: {e}")
logger.error(f"Error getting file processing status: {e}")
return {}
@ -254,7 +258,7 @@ def calculate_directory_size(directory_path: str) -> int:
if os.path.exists(file_path):
total_size += os.path.getsize(file_path)
except Exception as e:
print(f"Error calculating directory size: {e}")
logger.error(f"Error calculating directory size: {e}")
return total_size

32
utils/log_util/context.py Normal file
View File

@ -0,0 +1,32 @@
# author: askfiy
import contextvars
class GlobalContext:
def __init__(self):
super().__setattr__('_contextvar', contextvars.ContextVar(f"{__class__.__name__}_g"))
def __getattr__(self, k: str):
ctx = self._contextvar.get()
return ctx[k]
def __setattr__(self, k: str, v):
try:
ctx = self._contextvar.get()
except LookupError:
ctx = {}
ctx.update({k: v})
self._contextvar.set(ctx)
def get_context(self):
return self._contextvar.get()
def update_context(self, ctx):
self._contextvar.set(ctx)
g = GlobalContext()

32
utils/log_util/decorator.py Normal file
View File

@ -0,0 +1,32 @@
import time
import logging
from functools import wraps
from functools import update_wrapper
from .context import g
app_logger = logging.getLogger('app')
def safe_network(func):
@wraps(func)
def wrapper(*args, **kwargs):
while True:
try:
return func(*args, **kwargs)
except Exception as exc:
app_logger.error(exc)
time.sleep(1)
return wrapper
def copy_threading_context(func):
main_thridng_g_ctx = g.get_context()
def wrapper(*args, **kwargs):
g.update_context(main_thridng_g_ctx)
return func(*args, **kwargs)
return update_wrapper(wrapper, func)

93
utils/log_util/logger.py Normal file
View File

@ -0,0 +1,93 @@
import logging
import uuid
import json
from datetime import datetime
from fastapi import Request, FastAPI
from starlette.responses import JSONResponse
from starlette.requests import HTTPConnection
from typing import Callable, Awaitable
from .context import g
def add_request_routes(app: FastAPI):
@app.middleware("http")
async def before_request(request: Request, call_next: Callable[[Request], Awaitable[JSONResponse]]):
# 先从header中获取X-Trace-Id，如果没有则生成新的
trace_id = request.headers.get('X-Trace-Id')
if not trace_id:
trace_id = "generate_" + str(uuid.uuid4())
# user_id = "未知的 user_id"
g.trace_id = trace_id
# g.user_id = user_id
response = await call_next(request)
response.headers['X-Trace-Id'] = g.trace_id
return response
class Formatter(logging.Formatter):
def formatTime(self, record, datefmt=None):
# 将时间戳转换为datetime对象
dt = datetime.fromtimestamp(record.created)
# 格式化时间戳到毫秒
if datefmt:
s = dt.strftime(datefmt)
# 去除微秒的后三位，保留毫秒部分
s = s[:-3]
else:
# 去除微秒的后三位，保留毫秒部分
s = dt.strftime("%H:%M:%S.%f")[:-3]
return s
def format(self, record):
# 处理 trace_id
if not hasattr(record, "trace_id"):
record.trace_id = getattr(g, "trace_id")
# 处理 user_id
# if not hasattr(record, "user_id"):
# record.user_id = getattr(g, "user_id")
# 格式化时间戳
record.timestamp = self.formatTime(record, self.datefmt)
return super().format(record)
# 这里注册session 上下文追踪一次就可以了
def init_logger_once(name,level):
logger = logging.getLogger(name)
logger.setLevel(level=level)
formatter = Formatter("%(timestamp)s | %(levelname)-5s | %(trace_id)s | %(name)s:%(funcName)s:%(lineno)s - %(message)s", datefmt='%Y-%m-%d %H:%M:%S.%f')
handler = logging.StreamHandler()
handler.setFormatter(formatter)
logger.addHandler(handler)
def init_with_fastapi(app,level=logging.INFO):
init_logger_once("app",level)
add_request_routes(app)
def info(message, *args, **kwargs):
app_logger = logging.getLogger('app')
app_logger.info(message, *args, **kwargs)
def debug(message, *args, **kwargs):
app_logger = logging.getLogger('app')
app_logger.debug(message, *args, **kwargs)
def warning(message, *args, **kwargs):
app_logger = logging.getLogger('app')
app_logger.warning(message, *args, **kwargs)
def error(message, *args, **kwargs):
app_logger = logging.getLogger('app')
app_logger.error(message, *args, **kwargs)
def critical(message, *args, **kwargs):
app_logger = logging.getLogger('app')
app_logger.critical(message, *args, **kwargs)

78
utils/multi_project_manager.py
View File

@ -6,10 +6,14 @@
import os
import shutil
import json
import logging
from pathlib import Path
from typing import List, Dict, Optional
from datetime import datetime
# Configure logger
logger = logging.getLogger('app')
from utils.file_utils import get_document_preview
@ -177,11 +181,11 @@ def copy_dataset_folder(source_project_id: str, target_dataset_dir: Path, folder
shutil.copytree(source_folder, target_folder)
result["success"] = True
print(f" Copied: {source_folder} -> {target_folder}")
logger.info(f" Copied: {source_folder} -> {target_folder}")
except Exception as e:
result["error"] = str(e)
print(f" Error copying {folder_name}: {str(e)}")
logger.error(f" Error copying {folder_name}: {str(e)}")
return result
@ -237,7 +241,7 @@ def generate_robot_readme(robot_id: str, dataset_ids: List[str], copy_results: L
if item_path.is_dir():
doc_dirs.append(item)
except Exception as e:
print(f"Error listing dataset directories: {str(e)}")
logger.error(f"Error listing dataset directories: {str(e)}")
if not doc_dirs:
readme_content += "No document directories found.\n"
@ -292,7 +296,7 @@ def generate_robot_readme(robot_id: str, dataset_ids: List[str], copy_results: L
with open(readme_path, 'w', encoding='utf-8') as f:
f.write(readme_content)
print(f"Generated README: {readme_path}")
logger.info(f"Generated README: {readme_path}")
return str(readme_path)
@ -314,14 +318,14 @@ def should_rebuild_robot_project(dataset_ids: List[str], bot_id: str) -> bool:
# 如果机器人项目不存在，需要创建
if not robot_dir.exists():
print(f"Robot project does not exist, need to create: {bot_id}")
return True
logger.info(f"Robot project does not exist, need to create: {bot_id}")
return True
# 检查机器人项目的配置信息
config_file = robot_dir / "robot_config.json"
if not config_file.exists():
print(f"Robot config file not found, need to rebuild: {bot_id}")
return True
logger.info(f"Robot config file not found, need to rebuild: {bot_id}")
return True
# 读取配置信息
try:
@ -329,8 +333,8 @@ def should_rebuild_robot_project(dataset_ids: List[str], bot_id: str) -> bool:
config = json.load(f)
cached_dataset_ids = set(config.get("dataset_ids", []))
except Exception as e:
print(f"Error reading robot config: {e}, need to rebuild")
return True
logger.error(f"Error reading robot config: {e}, need to rebuild")
return True
# 检查dataset_ids是否有变化
current_dataset_ids = set(dataset_ids)
@ -338,14 +342,14 @@ def should_rebuild_robot_project(dataset_ids: List[str], bot_id: str) -> bool:
# 如果有新增的dataset_id
new_ids = current_dataset_ids - cached_dataset_ids
if new_ids:
print(f"Found new dataset_ids: {new_ids}, need to rebuild")
return True
logger.info(f"Found new dataset_ids: {new_ids}, need to rebuild")
return True
# 如果有删除的dataset_id
removed_ids = cached_dataset_ids - current_dataset_ids
if removed_ids:
print(f"Removed dataset_ids: {removed_ids}, need to rebuild")
return True
logger.info(f"Removed dataset_ids: {removed_ids}, need to rebuild")
return True
# 获取机器人项目的最后修改时间
robot_mod_time = robot_dir.stat().st_mtime
@ -355,17 +359,17 @@ def should_rebuild_robot_project(dataset_ids: List[str], bot_id: str) -> bool:
log_file = Path("projects") / "data" / source_project_id / "processing_log.json"
if not log_file.exists():
print(f"Processing log file not found for project {source_project_id}, will rebuild")
return True
logger.info(f"Processing log file not found for project {source_project_id}, will rebuild")
return True
log_mod_time = log_file.stat().st_mtime
# 如果任何一个processing_log.json文件比机器人项目新，需要重建
if log_mod_time > robot_mod_time:
print(f"Processing log updated for project {source_project_id}, need to rebuild")
return True
logger.info(f"Processing log updated for project {source_project_id}, need to rebuild")
return True
print(f"Robot project {bot_id} is up to date, no rebuild needed")
logger.info(f"Robot project {bot_id} is up to date, no rebuild needed")
return False
@ -381,12 +385,12 @@ def create_robot_project(dataset_ids: List[str], bot_id: str, force_rebuild: boo
Returns:
str: 机器人项目目录路径
"""
print(f"Creating robot project: {bot_id} from sources: {dataset_ids}")
logger.info(f"Creating robot project: {bot_id} from sources: {dataset_ids}")
# 检查是否需要重建
if not force_rebuild and not should_rebuild_robot_project(dataset_ids, bot_id):
robot_dir = Path("projects") / "robot" / bot_id
print(f"Using existing robot project: {robot_dir}")
logger.info(f"Using existing robot project: {robot_dir}")
return str(robot_dir)
# 创建机器人目录结构
@ -395,8 +399,8 @@ def create_robot_project(dataset_ids: List[str], bot_id: str, force_rebuild: boo
# 清理已存在的目录（如果需要）
if robot_dir.exists():
print(f"Robot directory already exists, cleaning up: {robot_dir}")
shutil.rmtree(robot_dir)
logger.info(f"Robot directory already exists, cleaning up: {robot_dir}")
shutil.rmtree(robot_dir)
robot_dir.mkdir(parents=True, exist_ok=True)
dataset_dir.mkdir(parents=True, exist_ok=True)
@ -405,19 +409,19 @@ def create_robot_project(dataset_ids: List[str], bot_id: str, force_rebuild: boo
# 遍历每个源项目
for source_project_id in dataset_ids:
print(f"\nProcessing source project: {source_project_id}")
logger.info(f"\nProcessing source project: {source_project_id}")
source_dataset_dir = Path("projects") / "data" / source_project_id / "dataset"
if not source_dataset_dir.exists():
print(f" Warning: Dataset directory not found for project {source_project_id}")
logger.warning(f" Warning: Dataset directory not found for project {source_project_id}")
continue
# 获取所有子文件夹
folders = [f for f in source_dataset_dir.iterdir() if f.is_dir()]
if not folders:
print(f" Warning: No folders found in dataset directory for project {source_project_id}")
logger.warning(f" Warning: No folders found in dataset directory for project {source_project_id}")
continue
# 复制每个文件夹
@ -442,12 +446,12 @@ def create_robot_project(dataset_ids: List[str], bot_id: str, force_rebuild: boo
# 统计信息
successful_copies = sum(1 for r in copy_results if r["success"])
print(f"\nRobot project creation completed:")
print(f" Robot directory: {robot_dir}")
print(f" Total folders processed: {len(copy_results)}")
print(f" Successful copies: {successful_copies}")
print(f" Config saved: {config_file}")
print(f" README generated: {readme_path}")
logger.info(f"\nRobot project creation completed:")
logger.info(f" Robot directory: {robot_dir}")
logger.info(f" Total folders processed: {len(copy_results)}")
logger.info(f" Successful copies: {successful_copies}")
logger.info(f" Config saved: {config_file}")
logger.info(f" README generated: {readme_path}")
return str(robot_dir)
@ -513,14 +517,14 @@ def cleanup_robot_project(bot_id: str) -> bool:
if robot_dir.exists():
shutil.rmtree(robot_dir)
print(f"Cleaned up robot project: {bot_id}")
logger.info(f"Cleaned up robot project: {bot_id}")
return True
else:
print(f"Robot project does not exist: {bot_id}")
logger.info(f"Robot project does not exist: {bot_id}")
return True
except Exception as e:
print(f"Error cleaning up robot project {bot_id}: {str(e)}")
logger.error(f"Error cleaning up robot project {bot_id}: {str(e)}")
return False
@ -530,7 +534,7 @@ if __name__ == "__main__":
test_bot_id = "test-robot-001"
robot_dir = create_robot_project(test_dataset_ids, test_bot_id)
print(f"Created robot project at: {robot_dir}")
logger.info(f"Created robot project at: {robot_dir}")
info = get_robot_project_info(test_bot_id)
print(f"Robot project info: {json.dumps(info, indent=2, ensure_ascii=False)}")
logger.info(f"Robot project info: {json.dumps(info, indent=2, ensure_ascii=False)}")

22
utils/organize_dataset_files.py
View File

@ -1,8 +1,12 @@
#!/usr/bin/env python3
import os
import shutil
import logging
from pathlib import Path
# 配置日志
logger = logging.getLogger('app')
def is_file_already_processed(target_file: Path, pagination_file: Path, embeddings_file: Path) -> bool:
"""Check if a file has already been processed (document.txt, pagination.txt, and embeddings exist)"""
if not target_file.exists():
@ -22,22 +26,22 @@ def organize_single_project_files(unique_id: str, skip_processed=True):
project_dir = Path("projects") / "data" / unique_id
if not project_dir.exists():
print(f"Project directory not found: {project_dir}")
logger.error(f"Project directory not found: {project_dir}")
return
print(f"Organizing files for project: {unique_id} (skip_processed={skip_processed})")
logger.info(f"Organizing files for project: {unique_id} (skip_processed={skip_processed})")
files_dir = project_dir / "files"
dataset_dir = project_dir / "dataset"
# Check if files directory exists and has files
if not files_dir.exists():
print(f" No files directory found, skipping...")
logger.info(f" No files directory found, skipping...")
return
files = list(files_dir.glob("*"))
if not files:
print(f" Files directory is empty, skipping...")
logger.info(f" Files directory is empty, skipping...")
return
# Create dataset directory if it doesn't exist
@ -55,10 +59,10 @@ def organize_single_project_files(unique_id: str, skip_processed=True):
# Check if file is already processed
if skip_processed and is_file_already_processed(target_file, pagination_file, embeddings_file):
print(f" Skipping already processed file: {file_path.name}")
logger.info(f" Skipping already processed file: {file_path.name}")
continue
print(f" Copying {file_path.name} -> {target_file.relative_to(project_dir)}")
logger.info(f" Copying {file_path.name} -> {target_file.relative_to(project_dir)}")
# Create target directory
target_dir.mkdir(exist_ok=True)
@ -140,12 +144,12 @@ def organize_dataset_files():
# Check if files directory exists and has files
if not files_dir.exists():
print(f" No files directory found, skipping...")
logger.info(f" No files directory found, skipping...")
continue
files = list(files_dir.glob("*"))
if not files:
print(f" Files directory is empty, skipping...")
logger.info(f" Files directory is empty, skipping...")
continue
# Create dataset directory if it doesn't exist
@ -159,7 +163,7 @@ def organize_dataset_files():
target_dir = dataset_dir / file_name_without_ext
target_file = target_dir / "document.txt"
print(f" Copying {file_path.name} -> {target_file.relative_to(project_dir)}")
logger.info(f" Copying {file_path.name} -> {target_file.relative_to(project_dir)}")
# Create target directory
target_dir.mkdir(exist_ok=True)

18
utils/project_manager.py
View File

@ -5,9 +5,13 @@ Project management functions for handling projects, README generation, and statu
import os
import json
import logging
from typing import Dict, List, Optional
from pathlib import Path
# Configure logger
logger = logging.getLogger('app')
from utils.file_utils import get_document_preview, load_processed_files_log
@ -145,7 +149,7 @@ This project contains processed documents and their associated embeddings for se
if os.path.isdir(item_path):
doc_dirs.append(item)
except Exception as e:
print(f"Error listing dataset directories: {str(e)}")
logger.error(f"Error listing dataset directories: {str(e)}")
if not doc_dirs:
readme_content += "No document directories found.\n"
@ -198,10 +202,10 @@ def save_project_readme(unique_id: str):
os.makedirs(os.path.dirname(readme_path), exist_ok=True)
with open(readme_path, 'w', encoding='utf-8') as f:
f.write(readme_content)
print(f"Generated README.md for project {unique_id}")
logger.info(f"Generated README.md for project {unique_id}")
return readme_path
except Exception as e:
print(f"Error generating README for project {unique_id}: {str(e)}")
logger.error(f"Error generating README for project {unique_id}: {str(e)}")
return None
@ -264,13 +268,13 @@ def remove_project(unique_id: str) -> bool:
if os.path.exists(project_dir):
import shutil
shutil.rmtree(project_dir)
print(f"Removed project directory: {project_dir}")
logger.info(f"Removed project directory: {project_dir}")
return True
else:
print(f"Project directory not found: {project_dir}")
logger.warning(f"Project directory not found: {project_dir}")
return False
except Exception as e:
print(f"Error removing project {unique_id}: {str(e)}")
logger.error(f"Error removing project {unique_id}: {str(e)}")
return False
@ -284,7 +288,7 @@ def list_projects() -> List[str]:
return [item for item in os.listdir(projects_dir)
if os.path.isdir(os.path.join(projects_dir, item))]
except Exception as e:
print(f"Error listing projects: {str(e)}")
logger.error(f"Error listing projects: {str(e)}")
return []

26
utils/single_file_processor.py
View File

@ -6,9 +6,13 @@ Single file processing functions for handling individual files.
import os
import tempfile
import zipfile
import logging
from typing import Dict, List, Tuple, Optional
from pathlib import Path
# Configure logger
logger = logging.getLogger('app')
from utils.file_utils import download_file
# Try to import excel/csv processor, but handle if dependencies are missing
@ -18,7 +22,7 @@ try:
)
EXCEL_CSV_SUPPORT = True
except ImportError as e:
print(f"Excel/CSV processing not available: {e}")
logger.warning(f"Excel/CSV processing not available: {e}")
EXCEL_CSV_SUPPORT = False
# Fallback functions
@ -71,7 +75,7 @@ async def process_single_file(
# Download file if it's remote and not yet downloaded
if original_path.startswith(('http://', 'https://')):
if not os.path.exists(local_path):
print(f"Downloading {original_path} -> {local_path}")
logger.info(f"Downloading {original_path} -> {local_path}")
success = await download_file(original_path, local_path)
if not success:
result["error"] = "Failed to download file"
@ -112,11 +116,11 @@ async def process_single_file(
except Exception as e:
result["error"] = f"Embedding generation failed: {str(e)}"
print(f"Failed to generate embeddings for {filename}: {str(e)}")
logger.error(f"Failed to generate embeddings for {filename}: {str(e)}")
except Exception as e:
result["error"] = f"File processing failed: {str(e)}"
print(f"Error processing file {filename}: {str(e)}")
logger.error(f"Error processing file {filename}: {str(e)}")
return result
@ -167,14 +171,14 @@ async def extract_from_zip(zip_path: str, filename: str) -> Tuple[str, List[str]
pagination_lines.extend(file_pagination)
except Exception as e:
print(f"Error processing extracted file {file}: {str(e)}")
logger.error(f"Error processing extracted file {file}: {str(e)}")
# Clean up temporary directory
import shutil
shutil.rmtree(temp_dir)
except Exception as e:
print(f"Error extracting zip file {filename}: {str(e)}")
logger.error(f"Error extracting zip file {filename}: {str(e)}")
return "", []
return '\n\n'.join(content_parts), pagination_lines
@ -192,7 +196,7 @@ async def extract_from_excel(file_path: str, filename: str) -> Tuple[str, List[s
return "", []
except Exception as e:
print(f"Error processing Excel file {filename}: {str(e)}")
logger.error(f"Error processing Excel file {filename}: {str(e)}")
return "", []
@ -208,7 +212,7 @@ async def extract_from_csv(file_path: str, filename: str) -> Tuple[str, List[str
return "", []
except Exception as e:
print(f"Error processing CSV file {filename}: {str(e)}")
logger.error(f"Error processing CSV file {filename}: {str(e)}")
return "", []
@ -224,7 +228,7 @@ async def extract_from_text(file_path: str, filename: str) -> Tuple[str, List[st
return "", []
except Exception as e:
print(f"Error reading text file {filename}: {str(e)}")
logger.error(f"Error reading text file {filename}: {str(e)}")
return "", []
@ -248,7 +252,7 @@ def generate_pagination_from_text(document_path: str, pagination_path: str) -> L
return pagination_lines
except Exception as e:
print(f"Error generating pagination from text: {str(e)}")
logger.error(f"Error generating pagination from text: {str(e)}")
return []
@ -273,7 +277,7 @@ async def generate_embeddings_for_file(document_path: str, embedding_path: str)
return None
except Exception as e:
print(f"Error generating embeddings: {str(e)}")
logger.error(f"Error generating embeddings: {str(e)}")
return None

34
utils/system_optimizer.py
View File

@ -9,9 +9,13 @@ import multiprocessing
import threading
import time
import resource
import logging
from typing import Dict, Any, Optional
from concurrent.futures import ThreadPoolExecutor
# 配置日志
logger = logging.getLogger('app')
class SystemOptimizer:
"""系统优化器
@ -37,9 +41,9 @@ class SystemOptimizer:
new_limit = min(65536, hard) # 增加到65536或硬件限制
resource.setrlimit(resource.RLIMIT_NOFILE, (new_limit, hard))
self.original_settings['RLIMIT_NOFILE'] = (soft, hard)
print(f"文件描述符限制从 {soft} 增加到 {new_limit}")
logger.info(f"文件描述符限制从 {soft} 增加到 {new_limit}")
except (ValueError, OSError) as e:
print(f"无法设置文件描述符限制: {e}")
logger.error(f"无法设置文件描述符限制: {e}")
# 2. 优化线程栈大小
try:
@ -47,9 +51,9 @@ class SystemOptimizer:
new_stack = min(8 * 1024 * 1024, hard) # 8MB栈大小
resource.setrlimit(resource.RLIMIT_STACK, (new_stack, hard))
self.original_settings['RLIMIT_STACK'] = (soft, hard)
print(f"线程栈大小设置为 {new_stack // (1024*1024)}MB")
logger.info(f"线程栈大小设置为 {new_stack // (1024*1024)}MB")
except (ValueError, OSError) as e:
print(f"无法设置线程栈大小: {e}")
logger.error(f"无法设置线程栈大小: {e}")
# 3. 环境变量优化
env_vars = {
@ -85,10 +89,10 @@ class SystemOptimizer:
for key, value in env_vars.items():
if key not in os.environ:
os.environ[key] = value
print(f"设置环境变量: {key}={value}")
logger.info(f"设置环境变量: {key}={value}")
self.optimized = True
print("系统优化完成")
logger.info("系统优化完成")
def _backup_original_settings(self):
"""备份原始设置"""
@ -115,20 +119,20 @@ class SystemOptimizer:
if not self.original_settings:
return
print("恢复原始系统设置...")
logger.info("恢复原始系统设置...")
# 恢复资源限制
if 'RLIMIT_NOFILE' in self.original_settings:
try:
resource.setrlimit(resource.RLIMIT_NOFILE, self.original_settings['RLIMIT_NOFILE'])
print(f"恢复文件描述符限制")
logger.info(f"恢复文件描述符限制")
except:
pass
if 'RLIMIT_STACK' in self.original_settings:
try:
resource.setrlimit(resource.RLIMIT_STACK, self.original_settings['RLIMIT_STACK'])
print(f"恢复线程栈大小")
logger.info(f"恢复线程栈大小")
except:
pass
@ -137,13 +141,13 @@ class SystemOptimizer:
if key.startswith('TOKENIZERS_') or key in ['PYTHONUNBUFFERED', 'PYTHONDONTWRITEBYTECODE']:
if key in os.environ:
del os.environ[key]
print(f"移除环境变量: {key}")
logger.info(f"移除环境变量: {key}")
elif key in ['OMP_NUM_THREADS'] and value is not None:
os.environ[key] = value
print(f"恢复环境变量: {key}={value}")
logger.info(f"恢复环境变量: {key}={value}")
self.optimized = False
print("系统设置已恢复")
logger.info("系统设置已恢复")
class AsyncioOptimizer:
@ -156,9 +160,9 @@ class AsyncioOptimizer:
# 尝试使用uvloop（如果可用）
import uvloop
asyncio.set_event_loop_policy(uvloop.EventLoopPolicy())
print("使用uvloop事件循环策略")
logger.info("使用uvloop事件循环策略")
except ImportError:
print("使用默认事件循环策略")
logger.info("使用默认事件循环策略")
# 设置线程池大小
cpu_count = multiprocessing.cpu_count()
@ -166,7 +170,7 @@ class AsyncioOptimizer:
# 注意：不能在这里设置默认线程池执行器，因为还没有运行事件循环
# 这个设置会在应用启动时进行
print(f"建议线程池大小: {thread_pool_size}")
logger.info(f"建议线程池大小: {thread_pool_size}")
@staticmethod
def optimize_gunicorn_settings() -> Dict[str, Any]:

36
zip_project_handler.py
View File

@ -9,10 +9,14 @@ import hashlib
import zipfile
import requests
import tempfile
import logging
from typing import List, Optional
from urllib.parse import urlparse
from pathlib import Path
# 配置日志
logger = logging.getLogger('app')
class ZipProjectHandler:
"""ZIP项目处理器"""
@ -56,7 +60,7 @@ class ZipProjectHandler:
return True
except Exception as e:
print(f"下载文件失败: {e}")
logger.error(f"下载文件失败: {e}")
return False
def _copy_local_file(self, local_path: str, target_path: str) -> bool:
@ -66,7 +70,7 @@ class ZipProjectHandler:
shutil.copy2(local_path, target_path)
return True
except Exception as e:
print(f"复制本地文件失败: {e}")
logger.error(f"复制本地文件失败: {e}")
return False
def _extract_zip(self, zip_path: str, extract_to: str) -> bool:
@ -76,7 +80,7 @@ class ZipProjectHandler:
zip_ref.extractall(extract_to)
return True
except Exception as e:
print(f"解压ZIP文件失败: {e}")
logger.error(f"解压ZIP文件失败: {e}")
return False
def get_project_from_zip(self, zip_url: str, unique_id: Optional[str] = None) -> Optional[str]:
@ -91,7 +95,7 @@ class ZipProjectHandler:
Optional[str]: 成功时返回项目目录路径，失败时返回None
"""
if not self._is_valid_url_or_path(zip_url):
print(f"无效的URL或路径: {zip_url}")
logger.error(f"无效的URL或路径: {zip_url}")
return None
# 使用unique_id作为目录名，如果没有则使用url_hash
@ -104,7 +108,7 @@ class ZipProjectHandler:
cached_project_dir = self.projects_dir / project_dir_name
if cached_project_dir.exists() and not unique_id:
print(f"使用缓存的项目目录: {cached_project_dir}")
logger.info(f"使用缓存的项目目录: {cached_project_dir}")
return str(cached_project_dir)
# 下载或复制ZIP文件
@ -125,24 +129,24 @@ class ZipProjectHandler:
is_url = False
if is_url:
print(f"下载ZIP文件: {zip_url}")
logger.info(f"下载ZIP文件: {zip_url}")
if not self._download_file(zip_url, str(zip_path)):
return None
else:
print(f"复制本地ZIP文件: {zip_url}")
logger.info(f"复制本地ZIP文件: {zip_url}")
# 解析相对路径
local_path = Path(zip_url).resolve()
if not self._copy_local_file(str(local_path), str(zip_path)):
return None
else:
print(f"使用缓存的ZIP文件: {zip_path}")
logger.info(f"使用缓存的ZIP文件: {zip_path}")
# 解压到项目目录
print(f"解压ZIP文件到: {cached_project_dir}")
logger.info(f"解压ZIP文件到: {cached_project_dir}")
if not self._extract_zip(str(zip_path), str(cached_project_dir)):
return None
print(f"项目准备完成: {cached_project_dir}")
logger.info(f"项目准备完成: {cached_project_dir}")
return str(cached_project_dir)
def collect_document_files(self, project_dir: str) -> List[str]:
@ -159,7 +163,7 @@ class ZipProjectHandler:
project_path = Path(project_dir)
if not project_path.exists():
print(f"项目目录不存在: {project_dir}")
logger.error(f"项目目录不存在: {project_dir}")
return document_files
# 递归搜索所有 document.txt 文件
@ -167,11 +171,11 @@ class ZipProjectHandler:
if file_path.is_file():
document_files.append(str(file_path))
print(f"在项目目录 {project_dir} 中找到 {len(document_files)} 个 document.txt 文件")
logger.info(f"在项目目录 {project_dir} 中找到 {len(document_files)} 个 document.txt 文件")
for file_path in document_files[:5]: # 只打印前5个文件路径作为示例
print(f" - {file_path}")
logger.info(f" - {file_path}")
if len(document_files) > 5:
print(f" ... 还有 {len(document_files) - 5} 个文件")
logger.info(f" ... 还有 {len(document_files) - 5} 个文件")
return document_files
@ -182,9 +186,9 @@ class ZipProjectHandler:
if self.cache_dir.exists():
shutil.rmtree(self.cache_dir)
self.cache_dir.mkdir(exist_ok=True)
print("缓存清理完成")
logger.info("缓存清理完成")
except Exception as e:
print(f"清理缓存失败: {e}")
logger.error(f"清理缓存失败: {e}")
# 全局ZIP项目处理器实例