hack/tools/scripts/llm-key-hunter/results/_cache/content/auto-actions_hyperagent.json

{"repo": "auto-actions/hyperagent", "files": {"MetaGPT/metagpt/configs/llm_config.py": {"1154fe3fb6aaa174acec2a818f1a50008d896eb0": {"t": 1785674648.5572047, "n": 2830, "h": "8eb9e806f70126c9", "c": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"\n@Time    : 2024/1/4 16:33\n@Author  : alexanderwu\n@File    : llm_config.py\n\"\"\"\nfrom enum import Enum\nfrom typing import Optional\n\nfrom pydantic import field_validator\n\nfrom metagpt.const import LLM_API_TIMEOUT\nfrom metagpt.utils.yaml_model import YamlModel\n\n\nclass LLMType(Enum):\n    OPENAI = \"openai\"\n    ANTHROPIC = \"anthropic\"\n    CLAUDE = \"claude\"  # alias name of anthropic\n    SPARK = \"spark\"\n    ZHIPUAI = \"zhipuai\"\n    FIREWORKS = \"fireworks\"\n    OPEN_LLM = \"open_llm\"\n    GEMINI = \"gemini\"\n    METAGPT = \"metagpt\"\n    AZURE = \"azure\"\n    OLLAMA = \"ollama\"\n    QIANFAN = \"qianfan\"  # Baidu BCE\n    DASHSCOPE = \"dashscope\"  # Aliyun LingJi DashScope\n    MOONSHOT = \"moonshot\"\n    MISTRAL = \"mistral\"\n    YI = \"yi\"  # lingyiwanwu\n    OPENROUTER = \"openrouter\"\n    BEDROCK = \"bedrock\"\n    ARK = \"ark\"\n\n    def __missing__(self, key):\n        return self.OPENAI\n\n\nclass LLMConfig(YamlModel):\n    \"\"\"Config for LLM\n\n    OpenAI: https://github.com/openai/openai-python/blob/main/src/openai/resources/chat/completions.py#L681\n    Optional Fields in pydantic: https://docs.pydantic.dev/latest/migration/#required-optional-and-nullable-fields\n    \"\"\"\n\n    api_key: str = \"sk-\"\n    api_type: LLMType = LLMType.OPENAI\n    base_url: str = \"https://api.openai.com/v1\"\n    api_version: Optional[str] = None\n\n    model: Optional[str] = None  # also stands for DEPLOYMENT_NAME\n    pricing_plan: Optional[str] = None  # Cost Settlement Plan Parameters.\n\n    # For Cloud Service Provider like Baidu/ Alibaba\n    access_key: Optional[str] = None\n    secret_key: Optional[str] = None\n    endpoint: Optional[str] = None  # for self-deployed model on the cloud\n\n    # For Spark(Xunfei), maybe remove later\n    app_id: Optional[str] = None\n    api_secret: Optional[str] = None\n    domain: Optional[str] = None\n\n    # For Chat Completion\n    max_token: int = 4096\n    temperature: float = 0.0\n    top_p: float = 1.0\n    top_k: int = 0\n    repetition_penalty: float = 1.0\n    stop: Optional[str] = None\n    presence_penalty: float = 0.0\n    frequency_penalty: float = 0.0\n    best_of: Optional[int] = None\n    n: Optional[int] = None\n    stream: bool = True\n    # https://cookbook.openai.com/examples/using_logprobs\n    logprobs: Optional[bool] = None\n    top_logprobs: Optional[int] = None\n    timeout: int = 600\n\n    # For Amazon Bedrock\n    region_name: str = None\n\n    # For Network\n    proxy: Optional[str] = None\n\n    # Cost Control\n    calc_usage: bool = True\n\n    @field_validator(\"api_key\")\n    @classmethod\n    def check_llm_key(cls, v):\n        if v in [\"\", None, \"YOUR_API_KEY\"]:\n            raise ValueError(\"Please set your API key in config2.yaml\")\n        return v\n\n    @field_validator(\"timeout\")\n    @classmethod\n    def check_timeout(cls, v):\n        return v or LLM_API_TIMEOUT\n"}}, "metagpt/configs/llm_config.py": {"1154fe3fb6aaa174acec2a818f1a50008d896eb0": {"t": 1785674649.217987, "n": 3425, "h": "89b79cfe07edf0bc", "c": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"\n@Time    : 2024/1/4 16:33\n@Author  : alexanderwu\n@File    : llm_config.py\n\"\"\"\nfrom enum import Enum\nfrom typing import Optional\n\nfrom pydantic import field_validator\n\nfrom metagpt.const import CONFIG_ROOT, LLM_API_TIMEOUT, METAGPT_ROOT\nfrom metagpt.utils.yaml_model import YamlModel\n\n\nclass LLMType(Enum):\n    OPENAI = \"openai\"\n    ANTHROPIC = \"anthropic\"\n    CLAUDE = \"claude\"  # alias name of anthropic\n    SPARK = \"spark\"\n    ZHIPUAI = \"zhipuai\"\n    FIREWORKS = \"fireworks\"\n    OPEN_LLM = \"open_llm\"\n    GEMINI = \"gemini\"\n    METAGPT = \"metagpt\"\n    AZURE = \"azure\"\n    OLLAMA = \"ollama\"\n    QIANFAN = \"qianfan\"  # Baidu BCE\n    DASHSCOPE = \"dashscope\"  # Aliyun LingJi DashScope\n    MOONSHOT = \"moonshot\"\n    MISTRAL = \"mistral\"\n    YI = \"yi\"  # lingyiwanwu\n    OPENROUTER = \"openrouter\"\n    BEDROCK = \"bedrock\"\n    ARK = \"ark\"\n\n    def __missing__(self, key):\n        return self.OPENAI\n\n\nclass LLMConfig(YamlModel):\n    \"\"\"Config for LLM\n\n    OpenAI: https://github.com/openai/openai-python/blob/main/src/openai/resources/chat/completions.py#L681\n    Optional Fields in pydantic: https://docs.pydantic.dev/latest/migration/#required-optional-and-nullable-fields\n    \"\"\"\n\n    api_key: str = \"sk-\"\n    api_type: LLMType = LLMType.OPENAI\n    base_url: str = \"https://api.openai.com/v1\"\n    api_version: Optional[str] = None\n\n    model: Optional[str] = None  # also stands for DEPLOYMENT_NAME\n    pricing_plan: Optional[str] = None  # Cost Settlement Plan Parameters.\n\n    # For Cloud Service Provider like Baidu/ Alibaba\n    access_key: Optional[str] = None\n    secret_key: Optional[str] = None\n    endpoint: Optional[str] = None  # for self-deployed model on the cloud\n\n    # For Spark(Xunfei), maybe remove later\n    app_id: Optional[str] = None\n    api_secret: Optional[str] = None\n    domain: Optional[str] = None\n\n    # For Chat Completion\n    max_token: int = 4096\n    temperature: float = 0.0\n    top_p: float = 1.0\n    top_k: int = 0\n    repetition_penalty: float = 1.0\n    stop: Optional[str] = None\n    presence_penalty: float = 0.0\n    frequency_penalty: float = 0.0\n    best_of: Optional[int] = None\n    n: Optional[int] = None\n    stream: bool = True\n    # https://cookbook.openai.com/examples/using_logprobs\n    logprobs: Optional[bool] = None\n    top_logprobs: Optional[int] = None\n    timeout: int = 600\n\n    # For Amazon Bedrock\n    region_name: str = None\n\n    # For Network\n    proxy: Optional[str] = None\n\n    # Cost Control\n    calc_usage: bool = True\n\n    @field_validator(\"api_key\")\n    @classmethod\n    def check_llm_key(cls, v):\n        if v in [\"\", None, \"YOUR_API_KEY\"]:\n            repo_config_path = METAGPT_ROOT / \"config/config2.yaml\"\n            root_config_path = CONFIG_ROOT / \"config2.yaml\"\n            if root_config_path.exists():\n                raise ValueError(\n                    f\"Please set your API key in {root_config_path}. If you also set your config in {repo_config_path}, \\nthe former will overwrite the latter. This may cause unexpected result.\\n\"\n                )\n            elif repo_config_path.exists():\n                raise ValueError(f\"Please set your API key in {repo_config_path}\")\n            else:\n                raise ValueError(\"Please set your API key in config2.yaml\")\n        return v\n\n    @field_validator(\"timeout\")\n    @classmethod\n    def check_timeout(cls, v):\n        return v or LLM_API_TIMEOUT\n"}}}}