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# Source code for langchain_community.llms.modal

    import logging
    from typing import Any, Dict, List, Mapping, Optional

    import requests
    from langchain_core.callbacks import CallbackManagerForLLMRun
    from langchain_core.language_models.llms import LLM
    from langchain_core.pydantic_v1 import Extra, Field, root_validator

    from langchain_community.llms.utils import enforce_stop_tokens

    logger = logging.getLogger(__name__)

    class Modal(LLM):
        """Modal large language models.

        To use, you should have the ``modal-client`` python package installed.

        Any parameters that are valid to be passed to the call can be passed
        in, even if not explicitly saved on this class.

        Example:
            .. code-block:: python

                from langchain_community.llms import Modal
                modal = Modal(endpoint_url="")

        """

        endpoint_url: str = ""
        """model endpoint to use"""

        model_kwargs: Dict[str, Any] = Field(default_factory=dict)
        """Holds any model parameters valid for `create` call not
        explicitly specified."""

        class Config:
            """Configuration for this pydantic config."""

            extra = Extra.forbid

        @root_validator(pre=True)
        def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
            """Build extra kwargs from additional params that were passed in."""
            all_required_field_names = {field.alias for field in cls.__fields__.values()}

            extra = values.get("model_kwargs", {})
            for field_name in list(values):
                if field_name not in all_required_field_names:
                    if field_name in extra:
                        raise ValueError(f"Found {field_name} supplied twice.")
                    logger.warning(
                        f"""{field_name} was transferred to model_kwargs.
                        Please confirm that {field_name} is what you intended."""
                    )
                    extra[field_name] = values.pop(field_name)
            values["model_kwargs"] = extra
            return values

        @property
        def _identifying_params(self) -> Mapping[str, Any]:
            """Get the identifying parameters."""
            return {
                **{"endpoint_url": self.endpoint_url},
                **{"model_kwargs": self.model_kwargs},
            }

        @property
        def _llm_type(self) -> str:
            """Return type of llm."""
            return "modal"

        def _call(
            self,
            prompt: str,
            stop: Optional[List[str]] = None,
            run_manager: Optional[CallbackManagerForLLMRun] = None,
            **kwargs: Any,
        ) -> str:
            """Call to Modal endpoint."""
            params = self.model_kwargs or {}
            params = {**params, **kwargs}
            response = requests.post(
                url=self.endpoint_url,
                headers={
                    "Content-Type": "application/json",
                },
                json={"prompt": prompt, **params},
            )
            try:
                if prompt in response.json()["prompt"]:
                    response_json = response.json()
            except KeyError:
                raise KeyError("LangChain requires 'prompt' key in response.")
            text = response_json["prompt"]
            if stop is not None:
                # I believe this is required since the stop tokens
                # are not enforced by the model parameters
                text = enforce_stop_tokens(text, stop)
            return text