Delete response.py

response.py

@@ -1,28 +0,0 @@
-##stores embedding vector and corresponding text with vector custom_id
-##filter embeddings by custom_id
-##search for similar embeddings
-##return text data with given vector custom_id
-from dotenv import load_dotenv
-load_dotenv()
-
-from langchain_mistralai import ChatMistralAI
-
-llm = ChatMistralAI(
-    model="mistral-large-latest",
-    temperature=0,
-    max_retries=1,
-)
-
-prompt_tamplet = """
-    You just need to answer the question based on the following context.
-    QUESTIONS : {question}
-    CONTEXT : {context}
-"""
-
-
-
-def get_answer(question:str,context:str):
-    final_prompt = prompt_tamplet.format(question=question, context=context)
-    response = llm.invoke(final_prompt)
-    ##print("from planner :",type(response.content))
-    return response.content