Major changes

app.py

@@ -1,7 +1,11 @@
-import streamlit as st
+import os
+import time
+import uuid
+from typing import List, Tuple, Optional, Dict, Union
+
 import google.generativeai as genai
-import sqlite3 
-from streamlit import file_uploader
+import streamlit as st
+from PIL import Image
 
 # Database setup
 conn = sqlite3.connect('chat_history.db')  
@@ -24,8 +28,65 @@ generation_config = {
 safety_settings = []
 
 # Streamlit UI
-st.title("Chatbot")
+st.set_page_config(page_title="Chatbot", page_icon="🤖")
 
+# Header
+st.markdown("""
+<style>
+.container {
+    display: flex;
+}
+.logo-text {
+    font-weight:700 !important;
+    font-size:50px !important;
+    color: #f9a01b !important;
+    padding-top: 75px !important;
+}
+.logo-img {
+    float:right;
+}
+</style>
+<div class="container">
+    <p class="logo-text">Chatbot</p>
+    <img class="logo-img" src="https://media.roboflow.com/spaces/gemini-icon.png" width=120 height=120>
+</div>
+""", unsafe_allow_html=True)
+
+# Sidebar
+st.sidebar.title("Parameters")
+temperature = st.sidebar.slider(
+    "Temperature",
+    min_value=0.0,
+    max_value=1.0,
+    value=0.9,
+    step=0.01,
+    help="Temperature controls the degree of randomness in token selection. Lower temperatures are good for prompts that expect a true or correct response, while higher temperatures can lead to more diverse or unexpected results."
+)
+max_output_tokens = st.sidebar.slider(
+    "Token limit",
+    min_value=1,
+    max_value=2048,
+    value=3000,
+    step=1,
+    help="Token limit determines the maximum amount of text output from one prompt. A token is approximately four characters. The default value is 2048."
+)
+st.sidebar.title("Model")
+model_name = st.sidebar.selectbox(
+    "Select a model",
+    options=["gemini-pro", "gemini-pro-vision"],
+    index=0,
+    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."
+)
+model_info = st.sidebar.expander("Model info", expanded=False)
+with model_info:
+    st.markdown(f"""
+    - Model name: {model_name}
+    - Model size: {genai.get_model_size(model_name)}
+    - Model description: {genai.get_model_description(model_name)}
+    """)
+
+# Chat history
+st.title("Chatbot")
 chat_history = st.session_state.get("chat_history", []) 
 
 if len(chat_history) % 2 == 0:
@@ -37,69 +98,111 @@ for message in chat_history:
     r, t = message["role"], message["parts"][0]["text"]
     st.markdown(f"**{r.title()}:** {t}")
     
-# 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 and description generation
-st.title("Image Description Generator")
-
-uploaded_file = st.image_uploader("Upload an image here or paste a screenshot", type=["png", "jpg", "jpeg"])
-
-image_question = st.text_input("Ask something about the image:")
-
-if uploaded_file and image_question:
-   image_parts = [
-     {
-       "mime_type": uploaded_file.type,
-       "data": uploaded_file.read() 
-     },
-   ]
-
-   prompt_parts = [
-     image_question,
-     image_parts[0],
-   ]
-
-   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}")
+# User input
+user_input = st.text_area("", height=5, key="user_input")  
+
+# Image uploader
+uploaded_files = st.image_uploader("Upload images here or paste screenshots", type=["png", "jpg", "jpeg"], accept_multiple_files=True, key="uploaded_files")
+
+# Run button
+run_button = st.button("Run", key="run_button")
+
+# Clear button
+clear_button = st.button("Clear", key="clear_button")
+
+# Download button
+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:
+    chat_history.clear()
+    st.session_state["chat_history"] = chat_history
+    st.session_state["user_input"] = ""
+    st.session_state["uploaded_files"] = None
+    st.experimental_rerun()
+
+# Save chat history to a text file
+if download_button:
+    chat_text = "\n".join([f"{r.title()}: {t}" for r, t in chat_history])
+    st.download_button(
+        label="Download chat history",
+        data=chat_text,
+        file_name="chat_history.txt",
+        mime="text/plain"
+    )
+
+# Generate model response
+if run_button or user_input:
+    if user_input:
+        chat_history.append({"role": role, "parts": [{"text": user_input}]}) 
+        st.session_state["user_input"] = ""
+        if role == "user":
+            
+            # Model code
+            model = genai.GenerativeModel(
+                model_name=model_name,   
+                generation_config=generation_config,
+                safety_settings=safety_settings
+            )
+            
+            if uploaded_files:
+                # Preprocess the uploaded images and convert them to image_parts
+                image_parts = []
+                for uploaded_file in uploaded_files:
+                    image = Image.open(uploaded_file).convert('RGB')
+                    image_parts.append({
+                        "mime_type": uploaded_file.type,
+                        "data": uploaded_file.read() 
+                    })
+                    # Display the uploaded images
+                    st.image(image)
+
+                # Add the user input to the prompt_parts
+                prompt_parts = [
+                    user_input,
+                ] + image_parts
+
+                # Use gemini-pro-vision model to generate the response
+                response = model.generate_content(prompt_parts, stream=True) 
+            else:
+                # Use gemini-pro model to generate the response
+                response = model.generate_content(chat_history, stream=True) 
+            
+            # Streaming effect
+            chat_history.append({"role": "model", "parts": [{"text": ""}]})
+            progress_bar.progress(0)
+            for chunk in response:
+                for i in range(0, len(chunk.text), 10):
+                    section = chunk.text[i:i + 10]
+                    chat_history[-1]["parts"][0]["text"] += section
+                    progress = min((i + 10) / len(chunk.text), 1.0)
+                    progress_bar.progress(progress)
+                    time.sleep(0.01)
+                    st.experimental_rerun()
+            progress_bar.progress(1.0)
+            
+            st.session_state["chat_history"] = chat_history
+            st.session_state["uploaded_files"] = None
+            
+    st.experimental_rerun()