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

from pydantic_v1 import Field

from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llms.base import LLM


class Predibase(LLM):
    """Use your Predibase models with Langchain.

    To use, you should have the ``predibase`` python package installed,
    and have your Predibase API key.
    """

    model: str
    predibase_api_key: str
    model_kwargs: Dict[str, Any] = Field(default_factory=dict)

    @property
    def _llm_type(self) -> str:
        return "predibase"

    def _call(
        self,
        prompt: str,
        stop: Optional[List[str]] = None,
        run_manager: Optional[CallbackManagerForLLMRun] = None,
        **kwargs: Any
    ) -> str:
        try:
            from predibase import PredibaseClient

            pc = PredibaseClient(token=self.predibase_api_key)
        except ImportError as e:
            raise ImportError(
                "Could not import Predibase Python package. "
                "Please install it with `pip install predibase`."
            ) from e
        except ValueError as e:
            raise ValueError("Your API key is not correct. Please try again") from e
        # load model and version
        results = pc.prompt(prompt, model_name=self.model)
        return results[0].response

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