Update app.py

app.py

@@ -1,30 +1,24 @@
-import os
-import time
-import uuid
-import sqlite3
-from typing import List, Tuple, Optional, Dict, Union
-from PIL import Image
-from io import BytesIO
-
-import google.generativeai as genai
 import streamlit as st
+import google.generativeai as genai
+import sqlite3 
+from PIL import Image
 
 # Database setup
-conn = sqlite3.connect('chat_history.db') 
+conn = sqlite3.connect('chat_history.db')  
 c = conn.cursor()
 
 c.execute('''
-       CREATE TABLE IF NOT EXISTS history 
-       (role TEXT, message TEXT)
-       ''')
+          CREATE TABLE IF NOT EXISTS history  
+          (role TEXT, message TEXT)
+          ''')
 
 # Generative AI setup
-api_key = "AIzaSyC70u1sN87IkoxOoIj4XCAPw97ae2LZwNM" 
+api_key = "AIzaSyC70u1sN87IkoxOoIj4XCAPw97ae2LZwNM"   
 genai.configure(api_key=api_key)
 
 generation_config = {
- "temperature": 0.9,
- "max_output_tokens": 3000 
+  "temperature": 0.9,
+  "max_output_tokens": 3000  
 }
 
 safety_settings = []
@@ -80,23 +74,18 @@ model_name = st.sidebar.selectbox(
  help="Gemini Pro is a text-only model that can generate natural language responses based on the chat history. Gemini Pro Vision is a multimodal model that can generate natural language responses based on the chat history and the uploaded images."
 )
 
-# Initialize user_input in session state
-if "user_input" not in st.session_state:
-    st.session_state["user_input"] = ""
-
-# Chat history
-st.title("Chatbot")
+# Initialize chat_history in session state
 if "chat_history" not in st.session_state:
-    st.session_state["chat_history"] = [] 
+    st.session_state["chat_history"] = []
 
+# Display chat history
+st.title("Chatbot")
 for message in st.session_state["chat_history"]:
     r, t = message["role"], message["parts"][0]["text"]
     st.markdown(f"**{r.title()}:** {t}")
 
 # User input
-def update_user_input():
-    st.session_state["user_input"] = st.session_state.user_input
-user_input = st.text_area("", height=5, key="user_input", on_change=update_user_input) 
+user_input = st.text_area("", height=5, key="user_input") 
 
 # File uploader
 uploaded_files = st.file_uploader("Upload images here or paste screenshots", type=["png", "jpg", "jpeg"], accept_multiple_files=True, key="uploaded_files")
@@ -107,27 +96,44 @@ if uploaded_files:
         image = Image.open(uploaded_file)
         st.image(image)
 
-# Run button
-# Run button
-run_button = st.button("Run")
-
 # Clear button
-clear_button = st.button("Clear")
+clear_button = st.button("Clear", key="clear_button")
 
 # Download button
-download_button = st.button("Download")
+download_button = st.button("Download", key="download_button")
 
 # Progress bar
 progress_bar = st.progress(0)
 
+# Footer
+st.markdown("""
+<style>
+.footer {
+ position: fixed;
+ left: 0;
+ bottom: 0;
+ width: 100%;
+ background-color: #f9a01b;
+ color: white;
+ text-align: center;
+}
+</style>
+<div class="footer">
+ <p>Made with Streamlit and Google Generative AI</p>
+</div>
+""", unsafe_allow_html=True)
+
 # Clear chat history and image uploader
 if clear_button:
     st.session_state["chat_history"] = []
     # Update progress bar
     progress_bar.progress(1)
+    
+# Handle user input
+if user_input:
+    # Add user input to chat history
+    st.session_state["chat_history"].append({"role": "user", "parts": [{"text": user_input}]})
 
-# Handle run_button click
-if run_button:
     # Create a GenerationConfig instance
     generation_config = genai.GenerationConfig(
         temperature=temperature,
@@ -139,7 +145,7 @@ if run_button:
     if model_name == "gemini-pro":
         model = genai.GenerativeModel('gemini-pro')
         response = model.generate_content(
-            contents=[st.session_state["user_input"]],
+            contents=[user_input],
             generation_config=generation_config
         )
     elif model_name == "gemini-pro-vision":
@@ -147,13 +153,18 @@ if run_button:
         image_prompts = [{'mime_type': 'image/png', 'data': image.tobytes()} for image in images]
         model = genai.GenerativeModel('gemini-pro-vision')
         response = model.generate_content(
-            contents=[st.session_state["user_input"]] + image_prompts,
+            contents=[user_input] + image_prompts,
             generation_config=generation_config
         )
 
     # Add model response to chat history
     st.session_state["chat_history"].append({"role": "model", "parts": [{"text": response}]})
 
+    # Display chat history
+    for message in st.session_state["chat_history"]:
+        r, t = message["role"], message["parts"][0]["text"]
+        st.markdown(f"**{r.title()}:** {t}")
+
     # Save chat history to database
     for message in st.session_state["chat_history"]:
         if len(st.session_state["chat_history"]) % 2 == 0:
@@ -165,26 +176,5 @@ if run_button:
     conn.commit() 
 
     # Clear user input
-    st.session_state["user_input"] = ""
-
-    # Rerun the app
-    st.experimental_rerun()
-
-# Footer
-st.markdown("""
-<style>
-.footer {
- position: fixed;
- left: 0;
- bottom: 0;
- width: 100%;
- background-color: #f9a01b;
- color: white;
- text-align: center;
-}
-</style>
-<div class="footer">
- <p>Made with Streamlit and Google Generative AI</p>
-</div>
-""", unsafe_allow_html=True)
+    st.session_state.user_input = ""