633 lines
24 KiB
Python
633 lines
24 KiB
Python
import tomli
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import sys
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from pathlib import Path
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from typing import Dict, Any, List, Tuple
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def load_toml_file(file_path: str) -> Dict[str, Any]:
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"""加载TOML文件"""
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try:
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with open(file_path, "rb") as f:
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return tomli.load(f)
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except Exception as e:
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print(f"错误: 无法加载配置文件 {file_path}: {str(e)} 请检查文件是否存在或者他妈的有没有东西没写值")
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sys.exit(1)
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def load_env_file(file_path: str) -> Dict[str, str]:
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"""加载.env文件中的环境变量"""
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env_vars = {}
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try:
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with open(file_path, 'r', encoding='utf-8') as f:
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for line in f:
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line = line.strip()
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if not line or line.startswith('#'):
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continue
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if '=' in line:
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key, value = line.split('=', 1)
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key = key.strip()
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value = value.strip()
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# 处理注释
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if '#' in value:
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value = value.split('#', 1)[0].strip()
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# 处理引号
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if (value.startswith('"') and value.endswith('"')) or \
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(value.startswith("'") and value.endswith("'")):
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value = value[1:-1]
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env_vars[key] = value
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return env_vars
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except Exception as e:
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print(f"警告: 无法加载.env文件 {file_path}: {str(e)}")
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return {}
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def check_required_sections(config: Dict[str, Any]) -> List[str]:
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"""检查必要的配置段是否存在"""
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required_sections = [
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"inner", "bot", "personality", "message", "emoji",
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"cq_code", "response", "willing", "memory", "mood",
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"groups", "model"
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]
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missing_sections = []
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for section in required_sections:
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if section not in config:
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missing_sections.append(section)
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return missing_sections
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def check_probability_sum(config: Dict[str, Any]) -> List[Tuple[str, float]]:
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"""检查概率总和是否为1"""
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errors = []
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# 检查人格概率
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if "personality" in config:
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personality = config["personality"]
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prob_sum = sum([
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personality.get("personality_1_probability", 0),
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personality.get("personality_2_probability", 0),
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personality.get("personality_3_probability", 0)
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])
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if abs(prob_sum - 1.0) > 0.001: # 允许有小数点精度误差
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errors.append(("人格概率总和", prob_sum))
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# 检查响应模型概率
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if "response" in config:
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response = config["response"]
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model_prob_sum = sum([
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response.get("model_r1_probability", 0),
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response.get("model_v3_probability", 0),
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response.get("model_r1_distill_probability", 0)
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])
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if abs(model_prob_sum - 1.0) > 0.001:
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errors.append(("响应模型概率总和", model_prob_sum))
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return errors
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def check_probability_range(config: Dict[str, Any]) -> List[Tuple[str, float]]:
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"""检查概率值是否在0-1范围内"""
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errors = []
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# 收集所有概率值
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prob_fields = []
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# 人格概率
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if "personality" in config:
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personality = config["personality"]
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prob_fields.extend([
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("personality.personality_1_probability", personality.get("personality_1_probability")),
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("personality.personality_2_probability", personality.get("personality_2_probability")),
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("personality.personality_3_probability", personality.get("personality_3_probability"))
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])
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# 消息概率
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if "message" in config:
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message = config["message"]
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prob_fields.append(("message.emoji_chance", message.get("emoji_chance")))
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# 响应模型概率
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if "response" in config:
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response = config["response"]
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prob_fields.extend([
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("response.model_r1_probability", response.get("model_r1_probability")),
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("response.model_v3_probability", response.get("model_v3_probability")),
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("response.model_r1_distill_probability", response.get("model_r1_distill_probability"))
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])
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# 情绪衰减率
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if "mood" in config:
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mood = config["mood"]
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prob_fields.append(("mood.mood_decay_rate", mood.get("mood_decay_rate")))
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# 中文错别字概率
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if "chinese_typo" in config and config["chinese_typo"].get("enable", False):
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typo = config["chinese_typo"]
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prob_fields.extend([
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("chinese_typo.error_rate", typo.get("error_rate")),
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("chinese_typo.tone_error_rate", typo.get("tone_error_rate")),
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("chinese_typo.word_replace_rate", typo.get("word_replace_rate"))
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])
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# 检查所有概率值是否在0-1范围内
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for field_name, value in prob_fields:
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if value is not None and (value < 0 or value > 1):
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errors.append((field_name, value))
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return errors
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def check_model_configurations(config: Dict[str, Any], env_vars: Dict[str, str]) -> List[str]:
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"""检查模型配置是否完整，并验证provider是否正确"""
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errors = []
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if "model" not in config:
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return ["缺少[model]部分"]
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required_models = [
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"llm_reasoning", "llm_reasoning_minor", "llm_normal",
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"llm_normal_minor", "llm_emotion_judge", "llm_topic_judge",
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"llm_summary_by_topic", "vlm", "embedding"
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]
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# 从环境变量中提取有效的API提供商
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valid_providers = set()
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for key in env_vars:
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if key.endswith('_BASE_URL'):
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provider_name = key.replace('_BASE_URL', '')
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valid_providers.add(provider_name)
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# 将provider名称标准化以便比较
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provider_mapping = {
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"SILICONFLOW": ["SILICONFLOW", "SILICON_FLOW", "SILICON-FLOW"],
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"CHAT_ANY_WHERE": ["CHAT_ANY_WHERE", "CHAT-ANY-WHERE", "CHATANYWHERE"],
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"DEEP_SEEK": ["DEEP_SEEK", "DEEP-SEEK", "DEEPSEEK"]
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}
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# 创建反向映射表，用于检查错误拼写
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reverse_mapping = {}
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for standard, variants in provider_mapping.items():
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for variant in variants:
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reverse_mapping[variant.upper()] = standard
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for model_name in required_models:
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# 检查model下是否有对应子部分
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if model_name not in config["model"]:
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errors.append(f"缺少[model.{model_name}]配置")
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else:
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model_config = config["model"][model_name]
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if "name" not in model_config:
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errors.append(f"[model.{model_name}]缺少name属性")
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if "provider" not in model_config:
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errors.append(f"[model.{model_name}]缺少provider属性")
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else:
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provider = model_config["provider"].upper()
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# 检查拼写错误
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for known_provider, _correct_provider in reverse_mapping.items():
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# 使用模糊匹配检测拼写错误
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if (provider != known_provider and
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_similar_strings(provider, known_provider) and
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provider not in reverse_mapping):
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errors.append(
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f"[model.{model_name}]的provider '{model_config['provider']}' "
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f"可能拼写错误，应为 '{known_provider}'"
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)
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break
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return errors
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def _similar_strings(s1: str, s2: str) -> bool:
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"""简单检查两个字符串是否相似（用于检测拼写错误）"""
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# 如果两个字符串长度相差过大，则认为不相似
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if abs(len(s1) - len(s2)) > 2:
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return False
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# 计算相同字符的数量
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common_chars = sum(1 for c1, c2 in zip(s1, s2) if c1 == c2)
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# 如果相同字符比例超过80%，则认为相似
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return common_chars / max(len(s1), len(s2)) > 0.8
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def check_api_providers(config: Dict[str, Any], env_vars: Dict[str, str]) -> List[str]:
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"""检查配置文件中的API提供商是否与环境变量中的一致"""
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errors = []
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if "model" not in config:
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return ["缺少[model]部分"]
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# 从环境变量中提取有效的API提供商
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valid_providers = {}
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for key in env_vars:
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if key.endswith('_BASE_URL'):
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provider_name = key.replace('_BASE_URL', '')
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base_url = env_vars[key]
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valid_providers[provider_name] = {
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"base_url": base_url,
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"key": env_vars.get(f"{provider_name}_KEY", "")
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}
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# 检查配置文件中使用的所有提供商
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used_providers = set()
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for _model_category, model_config in config["model"].items():
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if "provider" in model_config:
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provider = model_config["provider"]
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used_providers.add(provider)
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# 检查此提供商是否在环境变量中定义
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normalized_provider = provider.replace(" ", "_").upper()
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found = False
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for env_provider in valid_providers:
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if normalized_provider == env_provider:
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found = True
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break
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# 尝试更宽松的匹配（例如SILICONFLOW可能匹配SILICON_FLOW）
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elif normalized_provider.replace("_", "") == env_provider.replace("_", ""):
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found = True
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errors.append(f"提供商 '{provider}' 在环境变量中的名称是 '{env_provider}', 建议统一命名")
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break
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if not found:
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errors.append(f"提供商 '{provider}' 在环境变量中未定义")
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# 特别检查常见的拼写错误
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for provider in used_providers:
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if provider.upper() == "SILICONFOLW":
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errors.append("提供商 'SILICONFOLW' 存在拼写错误，应为 'SILICONFLOW'")
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return errors
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def check_groups_configuration(config: Dict[str, Any]) -> List[str]:
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"""检查群组配置"""
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errors = []
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if "groups" not in config:
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return ["缺少[groups]部分"]
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groups = config["groups"]
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# 检查talk_allowed是否为列表
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if "talk_allowed" not in groups:
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errors.append("缺少groups.talk_allowed配置")
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elif not isinstance(groups["talk_allowed"], list):
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errors.append("groups.talk_allowed应该是一个列表")
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else:
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# 检查talk_allowed是否包含默认示例值123
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if 123 in groups["talk_allowed"]:
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errors.append({
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"main": "groups.talk_allowed中存在默认示例值'123'，请修改为真实的群号",
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"details": [
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f" 当前值: {groups['talk_allowed']}",
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" '123'为示例值，需要替换为真实群号"
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]
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})
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# 检查是否存在重复的群号
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talk_allowed = groups["talk_allowed"]
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duplicates = []
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seen = set()
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for gid in talk_allowed:
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if gid in seen and gid not in duplicates:
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duplicates.append(gid)
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seen.add(gid)
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if duplicates:
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errors.append({
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"main": "groups.talk_allowed中存在重复的群号",
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"details": [f" 重复的群号: {duplicates}"]
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})
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# 检查其他群组配置
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if "talk_frequency_down" in groups and not isinstance(groups["talk_frequency_down"], list):
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errors.append("groups.talk_frequency_down应该是一个列表")
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if "ban_user_id" in groups and not isinstance(groups["ban_user_id"], list):
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errors.append("groups.ban_user_id应该是一个列表")
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return errors
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def check_keywords_reaction(config: Dict[str, Any]) -> List[str]:
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"""检查关键词反应配置"""
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errors = []
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if "keywords_reaction" not in config:
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return ["缺少[keywords_reaction]部分"]
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kr = config["keywords_reaction"]
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# 检查enable字段
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if "enable" not in kr:
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errors.append("缺少keywords_reaction.enable配置")
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# 检查规则配置
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if "rules" not in kr:
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errors.append("缺少keywords_reaction.rules配置")
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elif not isinstance(kr["rules"], list):
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errors.append("keywords_reaction.rules应该是一个列表")
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else:
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for i, rule in enumerate(kr["rules"]):
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if "enable" not in rule:
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errors.append(f"关键词规则 #{i+1} 缺少enable字段")
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if "keywords" not in rule:
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errors.append(f"关键词规则 #{i+1} 缺少keywords字段")
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elif not isinstance(rule["keywords"], list):
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errors.append(f"关键词规则 #{i+1} 的keywords应该是一个列表")
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if "reaction" not in rule:
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errors.append(f"关键词规则 #{i+1} 缺少reaction字段")
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return errors
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def check_willing_mode(config: Dict[str, Any]) -> List[str]:
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"""检查回复意愿模式配置"""
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errors = []
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if "willing" not in config:
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return ["缺少[willing]部分"]
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willing = config["willing"]
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if "willing_mode" not in willing:
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errors.append("缺少willing.willing_mode配置")
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elif willing["willing_mode"] not in ["classical", "dynamic", "custom"]:
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errors.append(f"willing.willing_mode值无效: {willing['willing_mode']}, 应为classical/dynamic/custom")
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return errors
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def check_memory_config(config: Dict[str, Any]) -> List[str]:
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"""检查记忆系统配置"""
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errors = []
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if "memory" not in config:
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return ["缺少[memory]部分"]
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memory = config["memory"]
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# 检查必要的参数
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required_fields = [
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"build_memory_interval", "memory_compress_rate",
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"forget_memory_interval", "memory_forget_time",
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"memory_forget_percentage"
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]
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for field in required_fields:
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if field not in memory:
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errors.append(f"缺少memory.{field}配置")
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# 检查参数值的有效性
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if "memory_compress_rate" in memory and (memory["memory_compress_rate"] <= 0 or memory["memory_compress_rate"] > 1):
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errors.append(f"memory.memory_compress_rate值无效: {memory['memory_compress_rate']}, 应在0-1之间")
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if ("memory_forget_percentage" in memory
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and (memory["memory_forget_percentage"] <= 0 or memory["memory_forget_percentage"] > 1)):
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errors.append(f"memory.memory_forget_percentage值无效: {memory['memory_forget_percentage']}, 应在0-1之间")
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return errors
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def check_personality_config(config: Dict[str, Any]) -> List[str]:
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"""检查人格配置"""
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errors = []
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if "personality" not in config:
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return ["缺少[personality]部分"]
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personality = config["personality"]
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# 检查prompt_personality是否存在且为数组
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if "prompt_personality" not in personality:
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errors.append("缺少personality.prompt_personality配置")
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elif not isinstance(personality["prompt_personality"], list):
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errors.append("personality.prompt_personality应该是一个数组")
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else:
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# 检查数组长度
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if len(personality["prompt_personality"]) < 1:
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errors.append(
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f"personality.prompt_personality至少需要1项，"
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f"当前长度: {len(personality['prompt_personality'])}"
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)
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else:
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# 模板默认值
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template_values = [
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"用一句话或几句话描述性格特点和其他特征",
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"用一句话或几句话描述性格特点和其他特征",
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"例如，是一个热爱国家热爱党的新时代好青年"
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]
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# 检查是否仍然使用默认模板值
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error_details = []
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for i, (current, template) in enumerate(zip(personality["prompt_personality"][:3], template_values)):
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if current == template:
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error_details.append({
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"main": f"personality.prompt_personality第{i+1}项仍使用默认模板值，请自定义",
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"details": [
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f" 当前值: '{current}'",
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f" 请不要使用模板值: '{template}'"
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]
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})
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# 将错误添加到errors列表
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for error in error_details:
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errors.append(error)
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return errors
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def check_bot_config(config: Dict[str, Any]) -> List[str]:
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"""检查机器人基础配置"""
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errors = []
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infos = []
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if "bot" not in config:
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return ["缺少[bot]部分"]
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bot = config["bot"]
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# 检查QQ号是否为默认值或测试值
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if "qq" not in bot:
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errors.append("缺少bot.qq配置")
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elif bot["qq"] == 1 or bot["qq"] == 123:
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errors.append(f"QQ号 '{bot['qq']}' 似乎是默认值或测试值，请设置为真实的QQ号")
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else:
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infos.append(f"当前QQ号: {bot['qq']}")
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# 检查昵称是否设置
|
||
if "nickname" not in bot or not bot["nickname"]:
|
||
errors.append("缺少bot.nickname配置或昵称为空")
|
||
elif bot["nickname"]:
|
||
infos.append(f"当前昵称: {bot['nickname']}")
|
||
|
||
# 检查别名是否为列表
|
||
if "alias_names" in bot and not isinstance(bot["alias_names"], list):
|
||
errors.append("bot.alias_names应该是一个列表")
|
||
|
||
return errors, infos
|
||
|
||
def format_results(all_errors):
|
||
"""格式化检查结果"""
|
||
sections_errors, prob_sum_errors, prob_range_errors, model_errors, api_errors, groups_errors, kr_errors, willing_errors, memory_errors, personality_errors, bot_results = all_errors # noqa: E501, F821
|
||
bot_errors, bot_infos = bot_results
|
||
|
||
if not any([
|
||
sections_errors, prob_sum_errors,
|
||
prob_range_errors, model_errors, api_errors, groups_errors,
|
||
kr_errors, willing_errors, memory_errors, personality_errors, bot_errors]):
|
||
result = "✅ 配置文件检查通过，未发现问题。"
|
||
|
||
# 添加机器人信息
|
||
if bot_infos:
|
||
result += "\n\n【机器人信息】"
|
||
for info in bot_infos:
|
||
result += f"\n - {info}"
|
||
|
||
return result
|
||
|
||
output = []
|
||
output.append("❌ 配置文件检查发现以下问题:")
|
||
|
||
if sections_errors:
|
||
output.append("\n【缺失的配置段】")
|
||
for section in sections_errors:
|
||
output.append(f" - {section}")
|
||
|
||
if prob_sum_errors:
|
||
output.append("\n【概率总和错误】(应为1.0)")
|
||
for name, value in prob_sum_errors:
|
||
output.append(f" - {name}: {value:.4f}")
|
||
|
||
if prob_range_errors:
|
||
output.append("\n【概率值范围错误】(应在0-1之间)")
|
||
for name, value in prob_range_errors:
|
||
output.append(f" - {name}: {value}")
|
||
|
||
if model_errors:
|
||
output.append("\n【模型配置错误】")
|
||
for error in model_errors:
|
||
output.append(f" - {error}")
|
||
|
||
if api_errors:
|
||
output.append("\n【API提供商错误】")
|
||
for error in api_errors:
|
||
output.append(f" - {error}")
|
||
|
||
if groups_errors:
|
||
output.append("\n【群组配置错误】")
|
||
for error in groups_errors:
|
||
if isinstance(error, dict):
|
||
output.append(f" - {error['main']}")
|
||
for detail in error['details']:
|
||
output.append(f"{detail}")
|
||
else:
|
||
output.append(f" - {error}")
|
||
|
||
if kr_errors:
|
||
output.append("\n【关键词反应配置错误】")
|
||
for error in kr_errors:
|
||
output.append(f" - {error}")
|
||
|
||
if willing_errors:
|
||
output.append("\n【回复意愿配置错误】")
|
||
for error in willing_errors:
|
||
output.append(f" - {error}")
|
||
|
||
if memory_errors:
|
||
output.append("\n【记忆系统配置错误】")
|
||
for error in memory_errors:
|
||
output.append(f" - {error}")
|
||
|
||
if personality_errors:
|
||
output.append("\n【人格配置错误】")
|
||
for error in personality_errors:
|
||
if isinstance(error, dict):
|
||
output.append(f" - {error['main']}")
|
||
for detail in error['details']:
|
||
output.append(f"{detail}")
|
||
else:
|
||
output.append(f" - {error}")
|
||
|
||
if bot_errors:
|
||
output.append("\n【机器人基础配置错误】")
|
||
for error in bot_errors:
|
||
output.append(f" - {error}")
|
||
|
||
# 添加机器人信息，即使有错误
|
||
if bot_infos:
|
||
output.append("\n【机器人信息】")
|
||
for info in bot_infos:
|
||
output.append(f" - {info}")
|
||
|
||
return "\n".join(output)
|
||
|
||
def main():
|
||
# 获取配置文件路径
|
||
config_path = Path("config/bot_config.toml")
|
||
env_path = Path(".env")
|
||
|
||
if not config_path.exists():
|
||
print(f"错误: 找不到配置文件 {config_path}")
|
||
return
|
||
|
||
if not env_path.exists():
|
||
print(f"警告: 找不到环境变量文件 {env_path}, 将跳过API提供商检查")
|
||
env_vars = {}
|
||
else:
|
||
env_vars = load_env_file(env_path)
|
||
|
||
# 加载配置文件
|
||
config = load_toml_file(config_path)
|
||
|
||
# 运行各种检查
|
||
sections_errors = check_required_sections(config)
|
||
prob_sum_errors = check_probability_sum(config)
|
||
prob_range_errors = check_probability_range(config)
|
||
model_errors = check_model_configurations(config, env_vars)
|
||
api_errors = check_api_providers(config, env_vars)
|
||
groups_errors = check_groups_configuration(config)
|
||
kr_errors = check_keywords_reaction(config)
|
||
willing_errors = check_willing_mode(config)
|
||
memory_errors = check_memory_config(config)
|
||
personality_errors = check_personality_config(config)
|
||
bot_results = check_bot_config(config)
|
||
|
||
# 格式化并打印结果
|
||
all_errors = (
|
||
sections_errors, prob_sum_errors,
|
||
prob_range_errors, model_errors, api_errors, groups_errors,
|
||
kr_errors, willing_errors, memory_errors, personality_errors, bot_results)
|
||
result = format_results(all_errors)
|
||
print("📋 机器人配置检查结果:")
|
||
print(result)
|
||
|
||
# 综合评估
|
||
total_errors = 0
|
||
|
||
# 解包bot_results
|
||
bot_errors, _ = bot_results
|
||
|
||
# 计算普通错误列表的长度
|
||
for errors in [
|
||
sections_errors, model_errors, api_errors,
|
||
groups_errors, kr_errors, willing_errors, memory_errors, bot_errors]:
|
||
total_errors += len(errors)
|
||
|
||
# 计算元组列表的长度（概率相关错误）
|
||
total_errors += len(prob_sum_errors)
|
||
total_errors += len(prob_range_errors)
|
||
|
||
# 特殊处理personality_errors和groups_errors
|
||
for errors_list in [personality_errors, groups_errors]:
|
||
for error in errors_list:
|
||
if isinstance(error, dict):
|
||
# 每个字典表示一个错误，而不是每行都算一个
|
||
total_errors += 1
|
||
else:
|
||
total_errors += 1
|
||
|
||
if total_errors > 0:
|
||
print(f"\n总计发现 {total_errors} 个配置问题。")
|
||
print("\n建议：")
|
||
print("1. 修复所有错误后再运行机器人")
|
||
print("2. 特别注意拼写错误，例如不！要！写！错！别！字！！！！！")
|
||
print("3. 确保所有API提供商名称与环境变量中一致")
|
||
print("4. 检查概率值设置，确保总和为1")
|
||
else:
|
||
print("\n您的配置文件完全正确！机器人可以正常运行。")
|
||
|
||
if __name__ == "__main__":
|
||
main()
|
||
input("\n按任意键退出...") |