Update app.py

app.py

@@ -32,55 +32,7 @@ print("creating llm ended")
 
 def greet(question, model_type):
     print(f"question is {question}")
-    if model_type == "With memory":
-        retriever = TFIDFRetriever.from_texts(
-            ["Finatial AI"])
-        
-        
-        template = """You are the Finiantial expert:
-        {history}
-        {context}
-        ### Instruction:
-        {question}
-        
-        ### Input:
-        
-        
-        ### Response:
-        """
-        
-        prompt1 = PromptTemplate(
-            input_variables=["history", "context", "question"],
-            template=template,
-        )
-        
-        llm_chain_model = RetrievalQA.from_chain_type(
-            llm=llm,
-            chain_type='stuff',
-            retriever=retriever,
-            verbose=False,
-            chain_type_kwargs={
-                "verbose": False,
-                "prompt": prompt1,
-                "memory": ConversationBufferMemory(
-                    memory_key="history",
-                    input_key="question"),
-            }
-        )
-        print("creating model created")
-    else:
-        template = """You are the Finiantial expert:
-        ### Instruction:
-        {question}
-        ### Input:
-        ### Response:
-        """
-        
-        prompt = PromptTemplate(template=template, input_variables=["question"])
-        
-        llm_chain_model = LLMChain(prompt=prompt, llm=llm)
-    out_gen = llm_chain_model.run(question)  
-    print(f"out is: {out_gen}")
+    out_gen = "testsetestestetsetsets"
     return out_gen
 
 demo = gr.Interface(fn=greet, inputs=["text", gr.Dropdown(