added chat history

.gitignore

@@ -2,4 +2,5 @@ venv
 data/__pycache__
 models/__pycache__
 .env
-__pycache__
+__pycache__
+vectorStores

app.py

@@ -31,9 +31,12 @@ if input_text is not None:
         st.session_state.messages.append(('User', input_text))
         with st.spinner("Processing your query..."):
             bot_response = get_response(index, input_text)
-        
+        print("bot: ", bot_response)
         st.session_state.messages.append(('Bot', bot_response))
 
 # Display previous messages
+msg_key = 0
 for sender, msg in st.session_state.messages[::-1]:
-    message(msg, is_user = (sender=='User'))
+    is_user = sender == "User"
+    message(str(msg), is_user, key=str(msg_key)+f'_{sender}')
+    msg_key += 1

models/bloom.py

@@ -2,6 +2,7 @@ import os
 from json import dumps, loads
 
 import numpy as np
+import openai
 import pandas as pd
 from dotenv import load_dotenv
 from llama_index import (Document, GPTVectorStoreIndex, LLMPredictor,
@@ -12,6 +13,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 from utils.customLLM import CustomLLM
 
 load_dotenv()
+openai.api_key = os.getenv("OPENAI_API_KEY")
 
 # get model
 # model_name = "bigscience/bloom-560m" 
@@ -68,7 +70,7 @@ def initialize_index(index_name):
         storage_context = StorageContext.from_defaults(persist_dir=file_path)
         # load index
         index = load_index_from_storage(storage_context)
-        return GPTVectorStoreIndex.load_from_disk(file_path)
+        return index
     else:
         documents = prepare_data(r"./assets/regItems.json")
         index = GPTVectorStoreIndex.from_documents(documents, service_context=service_context)