hack/tools/scripts/llm-key-hunter/results/_cache/content/allowan_ustc-107-let-ai-think-of-one.json

{"repo": "allowan/ustc-107-let-ai-think-of-one", "files": {"model/config.py": {"3eb328ca3752de646cdad990844d607863ec51bc": {"t": 1785745980.947577, "n": 2418, "h": "32daa0cfb336e0e5", "c": "import json\nimport os\nfrom pathlib import Path\nfrom langchain.chat_models import init_chat_model\n\n_SETTINGS_PATH = Path(__file__).resolve().parent.parent / \"settings.json\"\n\n\ndef read_json() -> dict:\n    \"\"\"读取 settings.json 中的 env 配置（文件不存在时返回空字典）。\"\"\"\n    try:\n        with open(_SETTINGS_PATH, encoding=\"utf-8\") as f:\n            data = json.load(f)\n        return data.get(\"env\", {})\n    except (FileNotFoundError, json.JSONDecodeError):\n        return {}\n\n\ndef init_chat():\n    \"\"\"初始化聊天模型。环境变量优先，settings.json 作为 fallback。\"\"\"\n    file_env = read_json()\n\n    api_key = os.environ.get(\"LLM_API_KEY\") or file_env.get(\"api_key\", \"\")\n    base_url = os.environ.get(\"LLM_BASE_URL\") or file_env.get(\"base_url\", \"https://api.deepseek.com\")\n    model_id = os.environ.get(\"LLM_MODEL\") or file_env.get(\"model\", \"deepseek-v4-flash\")\n\n    if not api_key:\n        raise RuntimeError(\n            \"未配置 LLM API Key。请在环境变量 LLM_API_KEY 中设置，\"\n            \"或复制 settings.example.json 为 settings.json 并填入 api_key。\"\n        )\n\n    return init_chat_model(\n        model=model_id,\n        model_provider=\"openai\",\n        base_url=base_url,\n        api_key=api_key,\n    )\n\ndef change_model(group: str, model: str):\n    \"\"\"更改模型选项：根据 group 与 model 索引更新 env 并重新初始化模型\"\"\"\n    settings_path = Path(__file__).resolve().parent.parent / \"settings.json\"\n    with open(settings_path, encoding=\"utf-8\") as f:\n        data = json.load(f)\n\n    groups = data.get(\"groups\", [])\n    # 按 group_name 定位分组\n    target_group = next(\n        (g for g in groups if g.get(\"group_name\") == group), None\n    )\n    if target_group is None:\n        raise ValueError(f\"未找到分组: {group}\")\n\n    # 在该分组的 models 中按 show_id 定位模型（回退匹配 request_id）\n    models = target_group.get(\"models\", [])\n    target_model = next(\n        (m for m in models if m.get(\"show_id\") == model or m.get(\"request_id\") == model),\n        None,\n    )\n    if target_model is None:\n        raise ValueError(f\"在分组 '{group}' 中未找到模型: {model}\")\n\n    # 用分组与模型信息更新 env\n    env = data.setdefault(\"env\", {})\n    env[\"api_key\"] = target_group.get(\"api_key\", \"\")\n    env[\"base_url\"] = target_group.get(\"base_url\", \"\")\n    env[\"api_type\"] = target_group.get(\"api_type\", \"chat-completions\")\n    env[\"model\"] = target_model.get(\"request_id\", \"\")\n\n    # 写回 settings.json\n    with open(settings_path, \"w\", encoding=\"utf-8\") as f:\n        json.dump(data, f, ensure_ascii=False, indent=4)\n\n    # 应用初始化\n    return init_chat()\n"}, "c61c5a71849378aff8b2ccc53c899e8abafd70e1": {"t": 1785758488.7981951, "n": 2418, "h": "32daa0cfb336e0e5", "c": "import json\nimport os\nfrom pathlib import Path\nfrom langchain.chat_models import init_chat_model\n\n_SETTINGS_PATH = Path(__file__).resolve().parent.parent / \"settings.json\"\n\n\ndef read_json() -> dict:\n    \"\"\"读取 settings.json 中的 env 配置（文件不存在时返回空字典）。\"\"\"\n    try:\n        with open(_SETTINGS_PATH, encoding=\"utf-8\") as f:\n            data = json.load(f)\n        return data.get(\"env\", {})\n    except (FileNotFoundError, json.JSONDecodeError):\n        return {}\n\n\ndef init_chat():\n    \"\"\"初始化聊天模型。环境变量优先，settings.json 作为 fallback。\"\"\"\n    file_env = read_json()\n\n    api_key = os.environ.get(\"LLM_API_KEY\") or file_env.get(\"api_key\", \"\")\n    base_url = os.environ.get(\"LLM_BASE_URL\") or file_env.get(\"base_url\", \"https://api.deepseek.com\")\n    model_id = os.environ.get(\"LLM_MODEL\") or file_env.get(\"model\", \"deepseek-v4-flash\")\n\n    if not api_key:\n        raise RuntimeError(\n            \"未配置 LLM API Key。请在环境变量 LLM_API_KEY 中设置，\"\n            \"或复制 settings.example.json 为 settings.json 并填入 api_key。\"\n        )\n\n    return init_chat_model(\n        model=model_id,\n        model_provider=\"openai\",\n        base_url=base_url,\n        api_key=api_key,\n    )\n\ndef change_model(group: str, model: str):\n    \"\"\"更改模型选项：根据 group 与 model 索引更新 env 并重新初始化模型\"\"\"\n    settings_path = Path(__file__).resolve().parent.parent / \"settings.json\"\n    with open(settings_path, encoding=\"utf-8\") as f:\n        data = json.load(f)\n\n    groups = data.get(\"groups\", [])\n    # 按 group_name 定位分组\n    target_group = next(\n        (g for g in groups if g.get(\"group_name\") == group), None\n    )\n    if target_group is None:\n        raise ValueError(f\"未找到分组: {group}\")\n\n    # 在该分组的 models 中按 show_id 定位模型（回退匹配 request_id）\n    models = target_group.get(\"models\", [])\n    target_model = next(\n        (m for m in models if m.get(\"show_id\") == model or m.get(\"request_id\") == model),\n        None,\n    )\n    if target_model is None:\n        raise ValueError(f\"在分组 '{group}' 中未找到模型: {model}\")\n\n    # 用分组与模型信息更新 env\n    env = data.setdefault(\"env\", {})\n    env[\"api_key\"] = target_group.get(\"api_key\", \"\")\n    env[\"base_url\"] = target_group.get(\"base_url\", \"\")\n    env[\"api_type\"] = target_group.get(\"api_type\", \"chat-completions\")\n    env[\"model\"] = target_model.get(\"request_id\", \"\")\n\n    # 写回 settings.json\n    with open(settings_path, \"w\", encoding=\"utf-8\") as f:\n        json.dump(data, f, ensure_ascii=False, indent=4)\n\n    # 应用初始化\n    return init_chat()\n"}, "a95c52d80d0cde6f25e1c79ea4f5f6bd98cf4756": {"t": 1785758491.374085, "n": 1853, "h": "74dc484b1b4e2806", "c": "import json\nfrom pathlib import Path\nfrom langchain.chat_models import init_chat_model\n\n\ndef read_json() -> dict:\n    \"\"\"读取 ../settings.json 中的 env 配置\"\"\"\n    settings_path = Path(__file__).resolve().parent.parent / \"settings.json\"\n    with open(settings_path, encoding=\"utf-8\") as f:\n        data = json.load(f)\n    return data.get(\"env\", {})\n\ndef init_chat():\n    \"\"\"完成对模型的初始化\"\"\"\n    env = read_json()\n    model = init_chat_model(\n        model=env[\"model\"],\n        model_provider=\"openai\",\n        base_url=env[\"base_url\"],\n        api_key=env[\"api_key\"],\n    )\n    return model\n\ndef change_model(group: str, model: str):\n    \"\"\"更改模型选项：根据 group 与 model 索引更新 env 并重新初始化模型\"\"\"\n    settings_path = Path(__file__).resolve().parent.parent / \"settings.json\"\n    with open(settings_path, encoding=\"utf-8\") as f:\n        data = json.load(f)\n\n    groups = data.get(\"groups\", [])\n    # 按 group_name 定位分组\n    target_group = next(\n        (g for g in groups if g.get(\"group_name\") == group), None\n    )\n    if target_group is None:\n        raise ValueError(f\"未找到分组: {group}\")\n\n    # 在该分组的 models 中按 show_id 定位模型（回退匹配 request_id）\n    models = target_group.get(\"models\", [])\n    target_model = next(\n        (m for m in models if m.get(\"show_id\") == model or m.get(\"request_id\") == model),\n        None,\n    )\n    if target_model is None:\n        raise ValueError(f\"在分组 '{group}' 中未找到模型: {model}\")\n\n    # 用分组与模型信息更新 env\n    env = data.setdefault(\"env\", {})\n    env[\"api_key\"] = target_group.get(\"api_key\", \"\")\n    env[\"base_url\"] = target_group.get(\"base_url\", \"\")\n    env[\"api_type\"] = target_group.get(\"api_type\", \"chat-completions\")\n    env[\"model\"] = target_model.get(\"request_id\", \"\")\n\n    # 写回 settings.json\n    with open(settings_path, \"w\", encoding=\"utf-8\") as f:\n        json.dump(data, f, ensure_ascii=False, indent=4)\n\n    # 应用初始化\n    return init_chat()\n"}, "1786ababffad1f5155254158ec5d20a2738ab984": {"t": 1785758492.5764182, "n": 1872, "h": "ed61621b28c622fd", "c": "import json\nimport os\nfrom pathlib import Path\nfrom langchain.chat_models import init_chat_model\n\n\ndef read_json() -> dict:\n    \"\"\"读取 ../settings.json 中的 env 配置\"\"\"\n    settings_path = Path(__file__).resolve().parent.parent / \"settings.json\"\n    with open(settings_path, encoding=\"utf-8\") as f:\n        data = json.load(f)\n    return data.get(\"env\", {})\n\ndef init_chat():\n    \"\"\"完成对模型的初始化\"\"\"\n    env = read_json()\n    model = init_chat_model(\n        model=env[\"model\"],\n        model_provider=\"openai\",\n        base_url=env[\"base_url\"],\n        api_key=env[\"api_key\"],\n    )\n    return model\n\ndef change_model(group: str, model: str):\n    \"\"\"更改模型选项：根据 group 与 model 索引更新 env 并重新初始化模型\"\"\"\n    settings_path = Path(__file__).resolve().parent.parent / \"settings.json\"\n    with open(settings_path, encoding=\"utf-8\") as f:\n        data = json.load(f)\n\n    groups = data.get(\"groups\", [])\n    # 按 group_name 定位分组\n    target_group = next(\n        (g for g in groups if g.get(\"group_name\") == group), None\n    )\n    if target_group is None:\n        raise ValueError(f\"未找到分组: {group}\")\n\n    # 在该分组的 models 中按 show_id 定位模型（回退匹配 request_id）\n    models = target_group.get(\"models\", [])\n    target_model = next(\n        (m for m in models if m.get(\"show_id\") == model or m.get(\"request_id\") == model),\n        None,\n    )\n    if target_model is None:\n        raise ValueError(f\"在分组 '{group}' 中未找到模型: {model}\")\n\n    # 用分组与模型信息更新 env\n    env = data.setdefault(\"env\", {})\n    env[\"api_key\"] = target_group.get(\"api_key\", \"\")\n    env[\"base_url\"] = target_group.get(\"base_url\", \"\")\n    env[\"api_type\"] = target_group.get(\"api_type\", \"chat-completions\")\n    env[\"model\"] = target_model.get(\"request_id\", \"\")\n\n    # 写回 settings.json\n    with open(settings_path, \"w\", encoding=\"utf-8\") as f:\n        json.dump(data, f, ensure_ascii=False, indent=4)\n\n    # 应用初始化\n    return init_chat()\n        \n"}}}}