Update llm/llm.py

llm/llm.py

@@ -1,8 +1,10 @@
+import yaml
+import logging
+
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain 
 from langchain.llms import HuggingFaceHub
 from .config import config 
-from .prompts import prompts
 
 class LLM_chain:
     def __init__(self):
@@ -10,9 +12,22 @@ class LLM_chain:
             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"]})
 
+    def __read_yaml(self):
+        try:
+            with open("./prompts.yaml", "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):
-        template = prompts[id]["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"]
+        try:
+            data = self.__read_yaml()
+            prompts = data["prompts"]
+            template = prompts["prompt_template"][1]
+            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)