Update app.py

app.py

@@ -104,15 +104,15 @@ def initialize_gpt_model():
 def initialize_gpt_mini_model():
     return ChatOpenAI(api_key=os.environ['OPENAI_API_KEY'], temperature=0, model='gpt-4o-mini')
 
-# Initialize the GPT-4o-mini model
-gpt_mini_model = initialize_gpt_mini_model()
 
 
 
 
-# Initialize both models
+
+# Initialize all models
 phi_pipe = initialize_phi_model()
 gpt_model = initialize_gpt_model()
+gpt_mini_model = initialize_gpt_mini_model()
 
 
 # Existing embeddings and vector store for GPT-4o
@@ -125,6 +125,11 @@ phi_embeddings = OpenAIEmbeddings(api_key=os.environ['OPENAI_API_KEY'])
 phi_vectorstore = PineconeVectorStore(index_name="phivector08252024", embedding=phi_embeddings)
 phi_retriever = phi_vectorstore.as_retriever(search_kwargs={'k': 5})
 
+#Existing embeddings and vector store for GPT-4o-mini
+gpt_mini_embeddings = OpenAIEmbeddings(api_key=os.environ['OPENAI_API_KEY'])
+gpt_mini_vectorstore = PineconeVectorStore(index_name="radarfinaldata08192024", embedding=gpt_mini_embeddings)
+gpt_mini_retriever = gpt_mini_vectorstore.as_retriever(search_kwargs={'k': 5})
+
 
 
 # Pinecone setup
@@ -626,10 +631,10 @@ def generate_answer(message, choice, retrieval_mode, selected_model):
         # Retrieval-based response
         if retrieval_mode == "VDB":
             logging.debug("Using VDB retrieval mode")
-            retriever = gpt_retriever  # Use the same retriever for all GPT models
             context = retriever.get_relevant_documents(message)
             logging.debug(f"Retrieved context: {context}")
 
+            prompt_template = QA_CHAIN_PROMPT_1 if choice == "Details" else QA_CHAIN_PROMPT_2
             prompt = prompt_template.format(context=context, question=message)
             logging.debug(f"Generated prompt: {prompt}")
 
@@ -640,7 +645,7 @@ def generate_answer(message, choice, retrieval_mode, selected_model):
                 chain_type_kwargs={"prompt": prompt_template}
             )
             response = qa_chain({"query": message})
-            logging.debug(f"Response from {selected_model}: {response}")
+            logging.debug(f"Response: {response}")
             return response['result'], extract_addresses(response['result'])
 
         elif retrieval_mode == "KGF":
@@ -659,7 +664,6 @@ def generate_answer(message, choice, retrieval_mode, selected_model):
 
 
 
-
 def add_message(history, message):
     history.append((message, None))
     return history, gr.Textbox(value="", interactive=True, show_label=False)