Update app.py

app.py

@@ -1,17 +1,7 @@
 import streamlit as st
 import google.generativeai as genai
-import sqlite3 
 from streamlit import file_uploader
 
-# Database setup
-conn = sqlite3.connect('chat_history.db')  
-c = conn.cursor()
-
-c.execute('''
-          CREATE TABLE IF NOT EXISTS history  
-          (role TEXT, message TEXT)
-          ''')
-
 # Generative AI setup
 api_key = "AIzaSyC70u1sN87IkoxOoIj4XCAPw97ae2LZwNM"   
 genai.configure(api_key=api_key)
@@ -26,61 +16,35 @@ safety_settings = []
 # Streamlit UI
 st.title("Chatbot")
 
-chat_history = st.session_state.get("chat_history", []) 
+# Use text_input for text input by typing
+user_text = st.text_input("Type your text here:")
 
-if len(chat_history) % 2 == 0:
-    role = "user"
-else:
-    role = "model"
+# Use file_uploader for image input
+user_image = st.file_uploader("Upload an image file here", type=["png", "jpg", "jpeg"])
 
-for message in chat_history:
-    r, t = message["role"], message["parts"][0]["text"]
-    st.markdown(f"**{r.title()}:** {t}")
-    
-# Use file_uploader for text and image input   
-user_input = st.file_uploader("Upload a text or an image file here", type=["txt", "png", "jpg", "jpeg"])  
-if user_input:
-    # Check the file type and create the prompt parts accordingly
-    if user_input.type == "text/plain":
-        prompt_parts = [user_input.getvalue().decode("utf-8")]
+# Check if the user has entered text or uploaded an image
+if user_text or user_image:
+    # Create the prompt parts accordingly
+    if user_text:
+        prompt_parts = [user_text]
         model_name = "gemini-pro" # Use the text-only model
     else:
         prompt_parts = [{
-            "mime_type": user_input.type,
-            "data": user_input.read() 
+            "mime_type": user_image.type,
+            "data": user_image.read() 
         }]
         model_name = "gemini-pro-vision" # Use the multimodal model
     
-    chat_history.append({"role": role, "parts": prompt_parts}) 
-    if role == "user":
-        
-        # Model code
-        model = genai.GenerativeModel(
-            model_name=model_name,   
-            generation_config=generation_config,
-            safety_settings=safety_settings
-        )
-        
-        response = model.generate_content(chat_history) 
-        response_text = response.text
-        chat_history.append({"role": "model", "parts": [{"text": response_text}]})
-        
-        st.session_state["chat_history"] = chat_history
-        
-for message in chat_history:
-    r, t = message["role"], message["parts"][0]["text"]
-    st.markdown(f"**{r.title()}:** {t}")
-if st.button("Display History"): 
-    c.execute("SELECT * FROM history") 
-    rows = c.fetchall() 
-
-    for row in rows: 
-        st.markdown(f"**{row[0].title()}:** {row[1]}") 
-        
-# Save chat history to database
-for message in chat_history: 
-    c.execute("INSERT INTO history VALUES (?, ?)", 
-            (message["role"], message["parts"][0]["text"])) 
-    conn.commit() 
-
-conn.close()
+    # Model code
+    model = genai.GenerativeModel(
+        model_name=model_name,   
+        generation_config=generation_config,
+        safety_settings=safety_settings
+    )
+    
+    response = model.generate_content(prompt_parts) 
+    response_text = response.text
+    
+    # Display the user input and the model response
+    st.markdown(f"**User:** {prompt_parts[0]['text']}")
+    st.markdown(f"**Model:** {response_text}")