Create app.py

app.py

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+import streamlit as st
+import os
+from helper import invoke_text_api, invoke_text_image_api
+import base64
+
+# App Title with Emoji
+st.title("🤖 ChatBot with Image Support 🖼️")
+
+# Sidebar for Image Upload
+st.sidebar.header("📂 Upload an Image (Optional)")
+uploaded_file = st.sidebar.file_uploader("📸 Upload an image", type=["png", "jpg", "jpeg"])
+
+# Sidebar Parameters for AI Model
+st.sidebar.header("⚙️ Model Parameters")
+
+max_tokens = st.sidebar.slider("📝 Max Tokens (Response Length)", 100, 2000, 1000)
+temperature = st.sidebar.slider("🔥 Temperature (Creativity)", 0.0, 1.0, 0.7)
+top_k = st.sidebar.slider("🎯 Top K (Diversity Filter)", 1, 500, 150)
+top_p = st.sidebar.slider("📊 Top P (Probability Sampling)", 0.0, 1.0, 0.98)
+
+# Initialize chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Display chat messages from history
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# Handle user input
+if prompt := st.chat_input("What would you like to ask? 🤔"):
+    # Display user message
+    st.chat_message("user").markdown(prompt)
+    st.session_state.messages.append({"role": "user", "content": prompt})
+
+    # Call the appropriate API function based on input type
+    with st.spinner("🤖 Thinking..."):
+        if uploaded_file:
+            # Convert uploaded image to Base64
+            image_bytes = uploaded_file.read()
+            base64_image = base64.b64encode(image_bytes).decode("utf-8")
+            response = invoke_text_image_api(base64_image, prompt, max_tokens, temperature, top_k, top_p)
+        else:
+            response = invoke_text_api(prompt, max_tokens, temperature, top_k, top_p)
+
+    # Display assistant response
+    with st.chat_message("assistant"):
+        st.markdown(response)
+    
+    st.session_state.messages.append({"role": "assistant", "content": response})