128 lines
3.9 KiB
Python
128 lines
3.9 KiB
Python
"""
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配置文件 - API Keys 和模型设置
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"""
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import os
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from dotenv import load_dotenv
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load_dotenv()
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# API 配置
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ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY", "")
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", "")
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AIHUBMIX_API_KEY = os.getenv("AIHUBMIX_API_KEY", "sk-yd8Tik0nFW5emKYcBdFc433b7c8b4dC182848f76819bBe73")
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DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_API_KEY", "")
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SILICONFLOW_API_KEY = os.getenv("SILICONFLOW_API_KEY", "")
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# LLM Providers Configuration
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LLM_PROVIDERS = {
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"AIHubMix": {
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"base_url": "https://aihubmix.com/v1",
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"api_key_var": "AIHUBMIX_API_KEY",
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"default_model": "gpt-4o"
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},
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"DeepSeek": {
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"base_url": "https://api.deepseek.com",
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"api_key_var": "DEEPSEEK_API_KEY",
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"default_model": "deepseek-chat"
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},
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"SiliconFlow": {
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"base_url": "https://api.siliconflow.cn/v1",
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"api_key_var": "SILICONFLOW_API_KEY",
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"default_model": "deepseek-ai/DeepSeek-V3" # SiliconFlow often uses full path
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},
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"OpenAI": {
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"base_url": "https://api.openai.com/v1",
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"api_key_var": "OPENAI_API_KEY",
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"default_model": "gpt-4o"
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},
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"Custom": {
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"base_url": "http://localhost:8000/v1",
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"api_key_var": "CUSTOM_API_KEY",
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"default_model": "local-model"
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}
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}
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# AIHubMix 配置 (Legacy, keeping for backward compatibility if needed, but main logic will use LLM_PROVIDERS)
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AIHUBMIX_BASE_URL = "https://aihubmix.com/v1"
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# 模型配置
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DEFAULT_MODEL = "gpt-4o" # AIHubMix 支持的模型
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LLM_PROVIDER = "aihubmix" # 默认使用 AIHubMix
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# 支持的模型列表
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AVAILABLE_MODELS = {
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# OpenAI
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"gpt-4o": "GPT-4o (OpenAI)",
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"gpt-4o-mini": "GPT-4o Mini (OpenAI)",
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"gpt-4-turbo": "GPT-4 Turbo (OpenAI)",
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# Anthropic
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"claude-3-5-sonnet-20241022": "Claude 3.5 Sonnet (Anthropic)",
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"claude-3-opus-20240229": "Claude 3 Opus (Anthropic)",
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"claude-3-haiku-20240307": "Claude 3 Haiku (Anthropic)",
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# Google
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"gemini-1.5-pro": "Gemini 1.5 Pro (Google)",
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"gemini-1.5-flash": "Gemini 1.5 Flash (Google)",
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"gemini-2.0-flash-exp": "Gemini 2.0 Flash Exp (Google)",
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# DeepSeek
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"deepseek-chat": "DeepSeek V3 (DeepSeek)",
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"deepseek-reasoner": "DeepSeek R1 (DeepSeek)",
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"deepseek-coder": "DeepSeek Coder (DeepSeek)",
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"deepseek-v2.5": "DeepSeek V2.5 (DeepSeek)",
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"deepseek-coder-v2": "DeepSeek Coder V2 (DeepSeek)",
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# Meta
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"llama-3.3-70b-instruct": "Llama 3.3 70B (Meta)",
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"llama-3.1-405b-instruct": "Llama 3.1 405B (Meta)",
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# Alibaba
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"qwen-2.5-72b-instruct": "Qwen 2.5 72B (Alibaba)",
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"qwen-plus": "Qwen Plus (Alibaba)",
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"qwen-turbo": "Qwen Turbo (Alibaba)",
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# Mistral
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"mistral-large-latest": "Mistral Large (Mistral)",
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# Perplexity
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"llama-3.1-sonar-huge-128k-online": "Sonar Huge Online (Perplexity)",
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}
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# 辩论配置
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MAX_DEBATE_ROUNDS = 3 # 最大辩论轮数
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MAX_AGENTS = 6 # 最大参与 Agent 数量
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# 支持的输出语言
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SUPPORTED_LANGUAGES = ["Chinese", "English", "Japanese", "Spanish", "French", "German"]
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# 生成配置
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MAX_OUTPUT_TOKENS = 300 # 限制单次回复长度，保持精简
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# 研究模式模型角色配置
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RESEARCH_MODEL_ROLES = {
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"expert_a": {
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"name": "Expert A (Analyst)",
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"default_model": "gpt-4o",
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"description": "负责初步分析，提出核心观点和方案"
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},
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"expert_b": {
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"name": "Expert B (Critique)",
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"default_model": "gemini-1.5-pro",
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"description": "负责批判性分析，指出潜在问题和漏洞"
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},
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"expert_c": {
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"name": "Expert C (Synthesizer)",
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"default_model": "claude-3-5-sonnet-20241022",
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"description": "负责综合各方观点，生成最终决策方案"
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}
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}
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# 决策类型
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DECISION_TYPES = {
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"product": "产品方案",
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"business": "商业决策",
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"tech": "技术选型",
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"personal": "个人规划"
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}
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