Update app.py

app.py

@@ -1,113 +1,92 @@
 import streamlit as st
-import google.generativeai as genai
-import sqlite3 
-from streamlit import file_uploader
+from PIL import Image
+import io
+import base64
 
-# Database setup
-conn = sqlite3.connect('chat_history.db')  
-c = conn.cursor()
 
-c.execute('''
-          CREATE TABLE IF NOT EXISTS history  
-          (role TEXT, message TEXT)
-          ''')
+import google.generativeai as genai
 
-# Generative AI setup
-api_key = "AIzaSyC70u1sN87IkoxOoIj4XCAPw97ae2LZwNM"   
+# Configure the API key (should be set as an environment variable or secure storage in production)
+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 = []
 
-# Streamlit UI
-st.title("Chatbot")
+# Initialize session state
+if "chat_history" not in st.session_state:
+    st.session_state.chat_history = []
+
+# UI layout
+st.title("Gemini Chatbot")
 
-chat_history = st.session_state.get("chat_history", []) 
+# Display the chat history
+for message in st.session_state.chat_history:
+    role, text = message
+    st.text_area(f"{role.title()} says:", value=text, height=75, disabled=True)
 
-if len(chat_history) % 2 == 0:
-    role = "user"
-else:
-    role = "model"
+# Text input for the user to send messages
+user_input = st.text_input("Enter your message here:")
 
-for message in chat_history:
-    r, t = message["role"], message["parts"][0]["text"]
-    st.markdown(f"**{r.title()}:** {t}")
+# File uploader for images
+uploaded_files = st.file_uploader("Upload images:", type=["png", "jpg", "jpeg"], accept_multiple_files=True)
+
+# Function to convert image to base64
+def get_image_base64(image):
+    buffered = io.BytesIO()
+    image.save(buffered, format="JPEG")
+    img_str = base64.b64encode(buffered.getvalue()).decode()
+    return f"data:image/jpeg;base64,{img_str}"
+
+# When the 'Send' button is clicked, process the input and generate a response
+if st.button("Send"):
+    # Save user input to the chat history if it's not empty
+    if user_input.strip():
+        st.session_state.chat_history.append(("user", user_input))
     
-# Use text_area for multiline input   
-user_input = st.text_area("", height=5)  
-if user_input:
-    chat_history.append({"role": role, "parts": [{"text": user_input}]}) 
-    if role == "user":
-        
-        # Model code
-        model_name = "gemini-pro"
-        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()
-
-# Separate section for image uploading
-st.title("Image Description Generator")
-
-# Change the file_uploader to accept multiple files
-uploaded_files = st.file_uploader("Upload one or more images here", type=["png", "jpg", "jpeg"], accept_multiple_files=True)
-
-# Text input for asking questions about the images
-image_question = st.text_input("Ask something about the images:")
-
-# Check if the user has entered a question
-if image_question:
-    # Create a list of image parts from the uploaded files
+    # Process and save uploaded images to the chat history
     image_parts = []
     for uploaded_file in uploaded_files:
+        bytes_data = uploaded_file.read()
+        image = Image.open(io.BytesIO(bytes_data))
+        image_base64 = get_image_base64(image)
         image_parts.append({
             "mime_type": uploaded_file.type,
-            "data": uploaded_file.read() 
+            "data": image_base64
         })
-    
-    # Create a prompt parts list with the question and the image parts
-    prompt_parts = [image_question] + image_parts
-
-    # Use the gemini-pro-vision model to generate a response
-    model = genai.GenerativeModel(
-        model_name="gemini-pro-vision", 
-        generation_config=generation_config, 
-        safety_settings=safety_settings 
-    )
-    
-    response = model.generate_content(prompt_parts)
-    st.markdown(f"**Model's answer:** {response.text}")
+        st.session_state.chat_history.append(("user", f"Uploaded image: {uploaded_file.name}"))
+
+    # Prepare the prompts for the model
+    prompts = []
+    if user_input.strip():
+        prompts.append({"role": "user", "parts": [{"text": user_input}]})
+    for image_part in image_parts:
+        prompts.append({"role": "user", "parts": [image_part]})
+
+    # Generate the response
+    if image_parts:
+        model = genai.GenerativeModel(
+            model_name='gemini-pro-vision',
+            generation_config=generation_config,
+            safety_settings=safety_settings
+        )
+    else:
+        model = genai.GenerativeModel(
+            model_name='gemini-pro',
+            generation_config=generation_config,
+            safety_settings=safety_settings
+        )
+    response = model.generate_content(prompts)
+    response_text = response['text']
+
+    # Save the model response to the chat history
+    st.session_state.chat_history.append(("model", response_text))
 
-# Loop through the uploaded files and display them
-for uploaded_file in uploaded_files:
-    # Display the image
-    st.image(uploaded_file)
+# Display the updated chat history
+for message in st.session_state.chat_history:
+    role, text = message
+    st.text_area(f"{role.title()} says:", value=text, height=75, disabled=True)