Update app.py

app.py

@@ -6,6 +6,7 @@ import os
 from langchain.llms import HuggingFaceHub
 
 from langchain.chains import RetrievalQA
+from langchain import PromptTemplate, LLMChain
 
 # Embed and store
 from langchain.vectorstores import Chroma
@@ -51,7 +52,10 @@ chain_type_kwargs = {"prompt": PROMPT}
 
 llm = HuggingFaceHub(repo_id="mistralai/Mistral-7B-v0.1", model_kwargs={"temperature":0.1, "max_new_tokens":250})
 
-qachain=RetrievalQA.from_chain_type(llm, retriever=vectorstore.as_retriever(), memory=memory, chain_type_kwargs=chain_type_kwargs)
+# qachain=RetrievalQA.from_chain_type(llm, retriever=vectorstore.as_retriever(), memory=memory, chain_type_kwargs=chain_type_kwargs)
+
+llm_chain = LLMChain(prompt=prompt, llm=llm)
+
 st.header("#CodeWars localGPT", divider='rainbow')
 
 option = st.selectbox('What is your role?', ('Support', 'Sales'))
@@ -63,6 +67,6 @@ context = [] # the context stores a conversation history, you can use this to ma
 if(prompt):
     with st.chat_message(option):
          st.write(f"{datetime.datetime.now()} :red[{option}:] ", prompt)
-    context = qachain({"query": prompt})
+    context = llm_chain.run(prompt)
     
     st.write(f"{datetime.datetime.now()}", context)