custom_llm.py

import cohere
from langchain.llms.base import LLM

co = cohere.Client('3FZy1Q1sd9Yfs289shdPgwjAt4MEuMxUmQx3oecK')  # This is my trial API key

# 24222433-2a40-410c-af5c-65a5422282fb-ft
class CustomLLM(LLM):
    model: str = '24222433-2a40-410c-af5c-65a5422282fb-ft'   # The custom model we used.

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

    def _call(self,prompt: str,stop = None,run_manager = None,) -> str:
        """ This is where the main logic of the """
        if stop is not None:
            raise ValueError("stop kwargs are not permitted.")

        response = co.generate(model=self.model, prompt=f'{prompt}', max_tokens=1700, temperature=0.9)
        print(response.generations[0].text)

        return f' ```python \n {response.generations[0].text} \n ``` '

    @property
    def _identifying_params(self):
        """Get the identifying parameters."""
        return {"model_type": f'COHERE_CUSTOM-<{self.model}>'}


""" Now, this thing can be used as a custom LLM. Use it in the LLM Chain thing. Done mi boy. """