Completely refactor the LLM integration method to easily replace the LLM used by each module and optimize the retransmission mechanism.

This commit is contained in:
666ghj
2025-10-09 13:45:39 +08:00
parent ce74f00137
commit 154b29c0d7
73 changed files with 942 additions and 51758 deletions
+161 -171
View File
@@ -1,6 +1,6 @@
"""
配置管理模块
处理环境变量和配置参数
Configuration management module for the Insight Engine.
Handles environment variables and config file parameters.
"""
import os
@@ -8,226 +8,216 @@ from dataclasses import dataclass
from typing import Optional
def _get_value(source, key: str, default=None):
"""
Helper to fetch a configuration value with environment fallback.
"""
value = None
if isinstance(source, dict):
value = source.get(key)
else:
value = getattr(source, key, None)
if value is None:
value = os.getenv(key, default)
return value if value not in ("", None) else default
@dataclass
class Config:
"""配置类"""
# API密钥
deepseek_api_key: Optional[str] = None
openai_api_key: Optional[str] = None
kimi_api_key: Optional[str] = None
deepseek_base_url: str = "https://api.deepseek.com"
openai_base_url: Optional[str] = None
kimi_base_url: str = "https://api.moonshot.cn/v1"
# 数据库配置
"""Insight Engine configuration."""
# LLM configuration
llm_api_key: Optional[str] = None
llm_base_url: Optional[str] = None
llm_model_name: Optional[str] = None
llm_provider: Optional[str] = None # kept for backward compatibility
# Database configuration
db_host: Optional[str] = None
db_user: Optional[str] = None
db_password: Optional[str] = None
db_name: Optional[str] = None
db_port: int = 3306
db_charset: str = "utf8mb4"
# 模型配置
default_llm_provider: str = "deepseek" # deepseek、openai 或 kimi
deepseek_model: str = "deepseek-chat"
openai_model: str = "gpt-4o-mini"
kimi_model: str = "kimi-k2-0711-preview"
# 搜索配置
# Model behaviour configuration
max_reflections: int = 3
max_paragraphs: int = 6
search_timeout: int = 240
max_content_length: int = 500000 # 提高5倍以充分利用Kimi的长文本能力
# 数据库查询限制
max_content_length: int = 500000
# Search result limits
default_search_hot_content_limit: int = 100
default_search_topic_globally_limit_per_table: int = 50
default_search_topic_by_date_limit_per_table: int = 100
default_get_comments_for_topic_limit: int = 500
default_search_topic_on_platform_limit: int = 200
# Agent配置
max_reflections: int = 3
max_paragraphs: int = 6
# 结果处理限制
max_search_results_for_llm: int = 0 # 0表示不限制,传递所有搜索结果给LLM
max_high_confidence_sentiment_results: int = 0 # 0表示不限制,返回所有高置信度情感分析结果
# 输出配置
max_search_results_for_llm: int = 0
max_high_confidence_sentiment_results: int = 0
# Output configuration
output_dir: str = "reports"
save_intermediate_states: bool = True
def __post_init__(self):
if not self.llm_provider and self.llm_model_name:
# Provider is no longer used, but keep the attribute for compatibility.
self.llm_provider = self.llm_model_name
def validate(self) -> bool:
"""验证配置"""
# 检查必需的API密钥
if self.default_llm_provider == "deepseek" and not self.deepseek_api_key:
print("错误: DeepSeek API Key未设置")
"""Validate configuration."""
if not self.llm_api_key:
print("错误: Insight Engine LLM API Key 未设置 (INSIGHT_ENGINE_API_KEY)。")
return False
if self.default_llm_provider == "openai" and not self.openai_api_key:
print("错误: OpenAI API Key未设置")
if not self.llm_model_name:
print("错误: Insight Engine 模型名称未设置 (INSIGHT_ENGINE_MODEL_NAME)。")
return False
if not all([self.db_host, self.db_user, self.db_password, self.db_name]):
print("错误: 数据库连接信息不完整")
print("错误: 数据库连接信息不完整,请检查 config.py 中的 DB_* 配置。")
return False
return True
@classmethod
def from_file(cls, config_file: str) -> "Config":
"""从配置文件创建配置"""
if config_file.endswith('.py'):
# Python配置文件
"""Create configuration from file."""
if config_file.endswith(".py"):
import importlib.util
# 动态导入配置文件
spec = importlib.util.spec_from_file_location("config", config_file)
config_module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(config_module)
return cls(
deepseek_api_key=getattr(config_module, "DEEPSEEK_API_KEY", None),
openai_api_key=getattr(config_module, "OPENAI_API_KEY", None),
kimi_api_key=getattr(config_module, "KIMI_API_KEY", None),
deepseek_base_url=getattr(config_module, "DEEPSEEK_BASE_URL", "https://api.deepseek.com"),
openai_base_url=getattr(config_module, "OPENAI_BASE_URL", None),
kimi_base_url=getattr(config_module, "KIMI_BASE_URL", "https://api.moonshot.cn/v1"),
db_host=getattr(config_module, "DB_HOST", None),
db_user=getattr(config_module, "DB_USER", None),
db_password=getattr(config_module, "DB_PASSWORD", None),
db_name=getattr(config_module, "DB_NAME", None),
db_port=getattr(config_module, "DB_PORT", 3306),
db_charset=getattr(config_module, "DB_CHARSET", "utf8mb4"),
default_llm_provider=getattr(config_module, "DEFAULT_LLM_PROVIDER", "deepseek"),
deepseek_model=getattr(config_module, "DEEPSEEK_MODEL", "deepseek-chat"),
openai_model=getattr(config_module, "OPENAI_MODEL", "gpt-4o-mini"),
search_timeout=getattr(config_module, "SEARCH_TIMEOUT", 240),
max_content_length=getattr(config_module, "SEARCH_CONTENT_MAX_LENGTH", 200000),
default_search_hot_content_limit=getattr(config_module, "DEFAULT_SEARCH_HOT_CONTENT_LIMIT", 100),
default_search_topic_globally_limit_per_table=getattr(config_module, "DEFAULT_SEARCH_TOPIC_GLOBALLY_LIMIT_PER_TABLE", 50),
default_search_topic_by_date_limit_per_table=getattr(config_module, "DEFAULT_SEARCH_TOPIC_BY_DATE_LIMIT_PER_TABLE", 100),
default_get_comments_for_topic_limit=getattr(config_module, "DEFAULT_GET_COMMENTS_FOR_TOPIC_LIMIT", 500),
default_search_topic_on_platform_limit=getattr(config_module, "DEFAULT_SEARCH_TOPIC_ON_PLATFORM_LIMIT", 200),
max_reflections=getattr(config_module, "MAX_REFLECTIONS", 2),
max_paragraphs=getattr(config_module, "MAX_PARAGRAPHS", 5),
max_search_results_for_llm=getattr(config_module, "MAX_SEARCH_RESULTS_FOR_LLM", 0),
max_high_confidence_sentiment_results=getattr(config_module, "MAX_HIGH_CONFIDENCE_SENTIMENT_RESULTS", 0),
output_dir=getattr(config_module, "OUTPUT_DIR", "reports"),
save_intermediate_states=getattr(config_module, "SAVE_INTERMEDIATE_STATES", True)
)
else:
# .env格式配置文件
config_dict = {}
if os.path.exists(config_file):
with open(config_file, 'r', encoding='utf-8') as f:
for line in f:
line = line.strip()
if line and not line.startswith('#') and '=' in line:
key, value = line.split('=', 1)
config_dict[key.strip()] = value.strip()
return cls(
deepseek_api_key=config_dict.get("DEEPSEEK_API_KEY"),
openai_api_key=config_dict.get("OPENAI_API_KEY"),
kimi_api_key=config_dict.get("KIMI_API_KEY"),
deepseek_base_url=config_dict.get("DEEPSEEK_BASE_URL", "https://api.deepseek.com"),
openai_base_url=config_dict.get("OPENAI_BASE_URL"),
kimi_base_url=config_dict.get("KIMI_BASE_URL", "https://api.moonshot.cn/v1"),
db_host=config_dict.get("DB_HOST"),
db_user=config_dict.get("DB_USER"),
db_password=config_dict.get("DB_PASSWORD"),
db_name=config_dict.get("DB_NAME"),
db_port=int(config_dict.get("DB_PORT", "3306")),
db_charset=config_dict.get("DB_CHARSET", "utf8mb4"),
default_llm_provider=config_dict.get("DEFAULT_LLM_PROVIDER", "deepseek"),
deepseek_model=config_dict.get("DEEPSEEK_MODEL", "deepseek-chat"),
openai_model=config_dict.get("OPENAI_MODEL", "gpt-4o-mini"),
kimi_model=config_dict.get("KIMI_MODEL", "kimi-k2-0711-preview"),
search_timeout=int(config_dict.get("SEARCH_TIMEOUT", "240")),
max_content_length=int(config_dict.get("SEARCH_CONTENT_MAX_LENGTH", "500000")),
default_search_hot_content_limit=int(config_dict.get("DEFAULT_SEARCH_HOT_CONTENT_LIMIT", "100")),
default_search_topic_globally_limit_per_table=int(config_dict.get("DEFAULT_SEARCH_TOPIC_GLOBALLY_LIMIT_PER_TABLE", "50")),
default_search_topic_by_date_limit_per_table=int(config_dict.get("DEFAULT_SEARCH_TOPIC_BY_DATE_LIMIT_PER_TABLE", "100")),
default_get_comments_for_topic_limit=int(config_dict.get("DEFAULT_GET_COMMENTS_FOR_TOPIC_LIMIT", "500")),
default_search_topic_on_platform_limit=int(config_dict.get("DEFAULT_SEARCH_TOPIC_ON_PLATFORM_LIMIT", "200")),
max_reflections=int(config_dict.get("MAX_REFLECTIONS", "2")),
max_paragraphs=int(config_dict.get("MAX_PARAGRAPHS", "5")),
max_search_results_for_llm=int(config_dict.get("MAX_SEARCH_RESULTS_FOR_LLM", "0")),
max_high_confidence_sentiment_results=int(config_dict.get("MAX_HIGH_CONFIDENCE_SENTIMENT_RESULTS", "0")),
output_dir=config_dict.get("OUTPUT_DIR", "reports"),
save_intermediate_states=config_dict.get("SAVE_INTERMEDIATE_STATES", "true").lower() == "true"
llm_api_key=_get_value(config_module, "INSIGHT_ENGINE_API_KEY"),
llm_base_url=_get_value(config_module, "INSIGHT_ENGINE_BASE_URL"),
llm_model_name=_get_value(config_module, "INSIGHT_ENGINE_MODEL_NAME"),
db_host=_get_value(config_module, "DB_HOST"),
db_user=_get_value(config_module, "DB_USER"),
db_password=_get_value(config_module, "DB_PASSWORD"),
db_name=_get_value(config_module, "DB_NAME"),
db_port=int(_get_value(config_module, "DB_PORT", 3306)),
db_charset=_get_value(config_module, "DB_CHARSET", "utf8mb4"),
max_reflections=int(_get_value(config_module, "MAX_REFLECTIONS", 3)),
max_paragraphs=int(_get_value(config_module, "MAX_PARAGRAPHS", 6)),
search_timeout=int(_get_value(config_module, "SEARCH_TIMEOUT", 240)),
max_content_length=int(_get_value(config_module, "SEARCH_CONTENT_MAX_LENGTH", 500000)),
default_search_hot_content_limit=int(
_get_value(config_module, "DEFAULT_SEARCH_HOT_CONTENT_LIMIT", 100)
),
default_search_topic_globally_limit_per_table=int(
_get_value(config_module, "DEFAULT_SEARCH_TOPIC_GLOBALLY_LIMIT_PER_TABLE", 50)
),
default_search_topic_by_date_limit_per_table=int(
_get_value(config_module, "DEFAULT_SEARCH_TOPIC_BY_DATE_LIMIT_PER_TABLE", 100)
),
default_get_comments_for_topic_limit=int(
_get_value(config_module, "DEFAULT_GET_COMMENTS_FOR_TOPIC_LIMIT", 500)
),
default_search_topic_on_platform_limit=int(
_get_value(config_module, "DEFAULT_SEARCH_TOPIC_ON_PLATFORM_LIMIT", 200)
),
max_search_results_for_llm=int(_get_value(config_module, "MAX_SEARCH_RESULTS_FOR_LLM", 0)),
max_high_confidence_sentiment_results=int(
_get_value(config_module, "MAX_HIGH_CONFIDENCE_SENTIMENT_RESULTS", 0)
),
output_dir=_get_value(config_module, "OUTPUT_DIR", "reports"),
save_intermediate_states=str(
_get_value(config_module, "SAVE_INTERMEDIATE_STATES", "true")
).lower()
in ("true", "1", "yes"),
)
# .env style configuration
config_dict = {}
if os.path.exists(config_file):
with open(config_file, "r", encoding="utf-8") as f:
for line in f:
line = line.strip()
if line and not line.startswith("#") and "=" in line:
key, value = line.split("=", 1)
config_dict[key.strip()] = value.strip()
return cls(
llm_api_key=_get_value(config_dict, "INSIGHT_ENGINE_API_KEY"),
llm_base_url=_get_value(config_dict, "INSIGHT_ENGINE_BASE_URL"),
llm_model_name=_get_value(config_dict, "INSIGHT_ENGINE_MODEL_NAME"),
db_host=_get_value(config_dict, "DB_HOST"),
db_user=_get_value(config_dict, "DB_USER"),
db_password=_get_value(config_dict, "DB_PASSWORD"),
db_name=_get_value(config_dict, "DB_NAME"),
db_port=int(_get_value(config_dict, "DB_PORT", 3306)),
db_charset=_get_value(config_dict, "DB_CHARSET", "utf8mb4"),
max_reflections=int(_get_value(config_dict, "MAX_REFLECTIONS", 3)),
max_paragraphs=int(_get_value(config_dict, "MAX_PARAGRAPHS", 6)),
search_timeout=int(_get_value(config_dict, "SEARCH_TIMEOUT", 240)),
max_content_length=int(_get_value(config_dict, "SEARCH_CONTENT_MAX_LENGTH", 500000)),
default_search_hot_content_limit=int(
_get_value(config_dict, "DEFAULT_SEARCH_HOT_CONTENT_LIMIT", 100)
),
default_search_topic_globally_limit_per_table=int(
_get_value(config_dict, "DEFAULT_SEARCH_TOPIC_GLOBALLY_LIMIT_PER_TABLE", 50)
),
default_search_topic_by_date_limit_per_table=int(
_get_value(config_dict, "DEFAULT_SEARCH_TOPIC_BY_DATE_LIMIT_PER_TABLE", 100)
),
default_get_comments_for_topic_limit=int(
_get_value(config_dict, "DEFAULT_GET_COMMENTS_FOR_TOPIC_LIMIT", 500)
),
default_search_topic_on_platform_limit=int(
_get_value(config_dict, "DEFAULT_SEARCH_TOPIC_ON_PLATFORM_LIMIT", 200)
),
max_search_results_for_llm=int(_get_value(config_dict, "MAX_SEARCH_RESULTS_FOR_LLM", 0)),
max_high_confidence_sentiment_results=int(
_get_value(config_dict, "MAX_HIGH_CONFIDENCE_SENTIMENT_RESULTS", 0)
),
output_dir=_get_value(config_dict, "OUTPUT_DIR", "reports"),
save_intermediate_states=str(
_get_value(config_dict, "SAVE_INTERMEDIATE_STATES", "true")
).lower()
in ("true", "1", "yes"),
)
def load_config(config_file: Optional[str] = None) -> Config:
"""
加载配置
Args:
config_file: 配置文件路径,如果不指定则使用默认路径
Returns:
配置对象
Load configuration.
"""
# 确定配置文件路径
if config_file:
if not os.path.exists(config_file):
raise FileNotFoundError(f"配置文件不存在: {config_file}")
file_to_load = config_file
else:
# 尝试加载常见的配置文件
for config_path in ["config.py", "config.env", ".env"]:
if os.path.exists(config_path):
file_to_load = config_path
print(f"已找到配置文件: {config_path}")
for candidate in ("config.py", "config.env", ".env"):
if os.path.exists(candidate):
file_to_load = candidate
print(f"已找到配置文件: {candidate}")
break
else:
raise FileNotFoundError("未找到配置文件,请创建 config.py 文件")
# 创建配置对象
raise FileNotFoundError("未找到配置文件,请创建 config.py")
config = Config.from_file(file_to_load)
# 验证配置
if not config.validate():
raise ValueError("配置验失败,请检查配置文件中的API密钥")
raise ValueError("配置验失败,请检查 config.py 中的相关配置。")
return config
def print_config(config: Config):
"""打印配置信息(隐藏敏感信息)"""
print("\n=== 当前配置 ===")
print(f"LLM提供商: {config.default_llm_provider}")
print(f"DeepSeek模型: {config.deepseek_model}")
print(f"OpenAI模型: {config.openai_model}")
print(f"搜索超时: {config.search_timeout}")
print(f"最大内容长度: {config.max_content_length}")
"""Print configuration (sensitive values masked)."""
print("\n=== Insight Engine 配置 ===")
print(f"LLM 模型: {config.llm_model_name}")
print(f"LLM Base URL: {config.llm_base_url or '(默认)'}")
print(f"搜索超时: {config.search_timeout}")
print(f"最长内容长度: {config.max_content_length}")
print(f"最大反思次数: {config.max_reflections}")
print(f"最大段落数: {config.max_paragraphs}")
print(f"输出目录: {config.output_dir}")
print(f"保存中间状态: {config.save_intermediate_states}")
# 显示API密钥和数据库状态(不显示实际密钥)
print(f"DeepSeek API Key: {'已设置' if config.deepseek_api_key else '未设置'}")
print(f"OpenAI API Key: {'已设置' if config.openai_api_key else '未设置'}")
print(f"LLM API Key: {'已配置' if config.llm_api_key else '未配置'}")
print(f"数据库连接: {'已配置' if all([config.db_host, config.db_user, config.db_password, config.db_name]) else '未配置'}")
print(f"数据库主机: {config.db_host}")
print(f"数据库端口: {config.db_port}")
print(f"数据库名称: {config.db_name}")
print("==================\n")
print("========================\n")