community[minor]: add support for Moonshot llm and chat model (#17100)

libs/community/langchain_community/llms/moonshot.py

@@ -0,0 +1,136 @@
+from typing import Any, Dict, List, Optional
+
+import requests
+from langchain_core.callbacks import CallbackManagerForLLMRun
+from langchain_core.language_models import LLM
+from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+
+from langchain_community.llms.utils import enforce_stop_tokens
+
+MOONSHOT_SERVICE_URL_BASE = "https://api.moonshot.cn/v1"
+
+
+class _MoonshotClient(BaseModel):
+    """An API client that talks to the Moonshot server."""
+
+    api_key: SecretStr
+    """The API key to use for authentication."""
+    base_url: str = MOONSHOT_SERVICE_URL_BASE
+
+    def completion(self, request: Any) -> Any:
+        headers = {"Authorization": f"Bearer {self.api_key.get_secret_value()}"}
+        response = requests.post(
+            f"{self.base_url}/chat/completions",
+            headers=headers,
+            json=request,
+        )
+        if not response.ok:
+            raise ValueError(f"HTTP {response.status_code} error: {response.text}")
+        return response.json()["choices"][0]["message"]["content"]
+
+
+class MoonshotCommon(BaseModel):
+    _client: _MoonshotClient
+    base_url: str = MOONSHOT_SERVICE_URL_BASE
+    moonshot_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
+    """Moonshot API key. Get it here: https://platform.moonshot.cn/console/api-keys"""
+    model_name: str = Field(default="moonshot-v1-8k", alias="model")
+    """Model name. Available models listed here: https://platform.moonshot.cn/pricing"""
+    max_tokens = 1024
+    """Maximum number of tokens to generate."""
+    temperature = 0.3
+    """Temperature parameter (higher values make the model more creative)."""
+
+    class Config:
+        """Configuration for this pydantic object."""
+
+        allow_population_by_field_name = True
+
+    @property
+    def lc_secrets(self) -> dict:
+        """A map of constructor argument names to secret ids.
+
+        For example,
+            {"moonshot_api_key": "MOONSHOT_API_KEY"}
+        """
+        return {"moonshot_api_key": "MOONSHOT_API_KEY"}
+
+    @property
+    def _default_params(self) -> Dict[str, Any]:
+        """Get the default parameters for calling OpenAI API."""
+        return {
+            "model": self.model_name,
+            "max_tokens": self.max_tokens,
+            "temperature": self.temperature,
+        }
+
+    @property
+    def _invocation_params(self) -> Dict[str, Any]:
+        return {**{"model": self.model_name}, **self._default_params}
+
+    @root_validator(pre=True)
+    def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
+        """Build extra parameters.
+        Override the superclass method, prevent the model parameter from being
+        overridden.
+        """
+        return values
+
+    @root_validator()
+    def validate_environment(cls, values: Dict) -> Dict:
+        """Validate that api key and python package exists in environment."""
+        values["moonshot_api_key"] = convert_to_secret_str(
+            get_from_dict_or_env(values, "moonshot_api_key", "MOONSHOT_API_KEY")
+        )
+
+        values["_client"] = _MoonshotClient(
+            api_key=values["moonshot_api_key"],
+            base_url=values["base_url"]
+            if "base_url" in values
+            else MOONSHOT_SERVICE_URL_BASE,
+        )
+        return values
+
+    @property
+    def _llm_type(self) -> str:
+        """Return type of llm."""
+        return "moonshot"
+
+
+class Moonshot(MoonshotCommon, LLM):
+    """Moonshot large language models.
+
+    To use, you should have the environment variable ``MOONSHOT_API_KEY`` set with your
+    API key. Referenced from https://platform.moonshot.cn/docs
+
+    Example:
+        .. code-block:: python
+
+            from langchain_community.llms.moonshot import Moonshot
+
+            moonshot = Moonshot(model="moonshot-v1-8k")
+    """
+
+    class Config:
+        """Configuration for this pydantic object."""
+
+        allow_population_by_field_name = True
+
+    def _call(
+        self,
+        prompt: str,
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        **kwargs: Any,
+    ) -> str:
+        request = self._invocation_params
+        request["messages"] = [{"role": "user", "content": prompt}]
+        request.update(kwargs)
+        text = self._client.completion(request)
+        if stop is not None:
+            # This is required since the stop tokens
+            # are not enforced by the model parameters
+            text = enforce_stop_tokens(text, stop)
+
+        return text