Delete llm/llm.py

llm/llm.py

@@ -1,43 +0,0 @@
-import os
-
-import yaml
-import logging
-
-from langchain.prompts import PromptTemplate
-from langchain.chains import LLMChain
-from langchain.llms import HuggingFaceEndpoint
-from .config import config
-
-os.environ["HUGGINGFACEHUB_API_TOKEN"] = "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"
-
-class LLM_chain:
-    def __init__(self):
-        self.llm = HuggingFaceEndpoint(
-            repo_id=config["model"],
-            model_kwargs={"temperature": config["temperature"], "max_new_tokens": config["max_new_tokens"],
-                          "top_k": config["top_k"], "load_in_8bit": config["load_in_8bit"]})
-
-    @staticmethod
-    def __read_yaml():
-        try:
-            # get current dir
-            current_dir = os.path.dirname(os.path.realpath(__file__))
-            yaml_file = os.path.join(current_dir, 'prompts.yaml')
-
-            with open(yaml_file, 'r') as file:
-                data = yaml.safe_load(file)
-            return data
-        except Exception as e:
-            logging.error(e)
-
-    def __call__(self, entity: str, id: int = 0):
-        try:
-            data = self.__read_yaml()
-            prompts = data["prompts"][id]  # get second prompt from yaml, need change id parameter to get other prompt
-            template = prompts["prompt_template"]
-            prompt = PromptTemplate(template=template, input_variables=["entity"])
-            llm_chain = LLMChain(prompt=prompt, llm=self.llm, verbose=True)
-            output = llm_chain.invoke(entity)
-            return output["text"]
-        except Exception as e:
-            logging.error(e)