Update app.py

app.py

@@ -5,46 +5,44 @@ import requests
 from PIL import Image
 from io import BytesIO
 
-# 🔐 Groq API Key
+# 🔐 API Key
 GROQ_API_KEY = os.getenv("GROQ_API_KEY") or "PASTE_YOUR_GROQ_API_KEY_HERE"
-
-# ✅ Model details
 GROQ_MODEL = "llama-3.3-70b-versatile"
 GROQ_URL = "https://api.groq.com/openai/v1/chat/completions"
 
-# 🧠 Chat history
+# 🧠 Chat history memory
 history = []
 
 def analyze_image_with_prompt(image, user_prompt):
     global history
 
     if not image or not user_prompt.strip():
-        return "⚠️ Please upload an image and enter a question or prompt."
+        return "⚠️ Please upload an image and enter your question or prompt."
 
-    # 💡 Only include user prompt — not base64 image
+    # Add system message on first prompt
     if len(history) == 0:
-        system_msg = {
+        history.append({
             "role": "system",
             "content": (
-                "You are a helpful construction engineer bot. "
-                "Given a prompt describing a construction issue (e.g., crack, damage), identify:\n"
+                "You are a helpful and professional construction engineer bot. "
+                "When provided with a prompt describing a construction issue, analyze the situation and explain:\n"
                 "- Type of damage\n"
                 "- Possible causes\n"
                 "- Recommended tools and materials\n"
-                "- Estimated repair time.\n"
-                "Then answer follow-up questions."
+                "- Estimated repair time\n"
+                "Then answer any follow-up questions helpfully."
             )
-        }
-        history.append(system_msg)
+        })
 
     # Add user message
     history.append({"role": "user", "content": user_prompt})
 
-    # ✅ Limit chat history to avoid hitting token limits
-    MAX_TURNS = 5  # 5 user-assistant exchanges
-    if len(history) > (MAX_TURNS * 2 + 1):  # +1 for system
+    # Limit history to last 5 turns (10 messages + system)
+    MAX_TURNS = 5
+    if len(history) > (MAX_TURNS * 2 + 1):
         history = [history[0]] + history[-(MAX_TURNS * 2):]
 
+    # Request setup
     headers = {
         "Authorization": f"Bearer {GROQ_API_KEY}",
         "Content-Type": "application/json"
@@ -63,49 +61,66 @@ def analyze_image_with_prompt(image, user_prompt):
         history.append({"role": "assistant", "content": reply})
         return reply
     else:
-        return f"❌ Error: {response.status_code}\n{response.text}"
+        return f"❌ Error {response.status_code}: {response.text}"
 
 def reset_history():
     global history
     history = []
     return "", ""
 
-# 🌟 Gradio GUI
-with gr.Blocks(theme=gr.themes.Soft(), css=".gradio-container { max-width: 950px; margin: auto; }") as demo:
-    gr.Markdown("## 🏗️ Construction Damage Identifier Chatbot")
+# 🎨 Custom CSS
+CUSTOM_CSS = """
+.gradio-container {
+    max-width: 960px;
+    margin: auto;
+    padding-top: 1.5rem;
+}
+footer {
+    text-align: center;
+    font-size: 0.9rem;
+    margin-top: 2rem;
+    color: gray;
+}
+"""
+
+# 🚀 Gradio App
+with gr.Blocks(theme=gr.themes.Soft(), css=CUSTOM_CSS) as demo:
+    gr.Markdown("### 🏗️ Construction Damage Identifier Bot")
     gr.Markdown(
-        "Upload a photo of construction damage (for reference) and ask a question. "
-        "The AI will try to diagnose the issue based on your prompt."
+        "Upload a construction site photo (e.g., cracks, corrosion) and ask a question. "
+        "This assistant will provide expert-level analysis based on your description."
     )
 
     with gr.Row():
-        with gr.Column(scale=1):
+        with gr.Column(scale=1, min_width=320):
             img_input = gr.Image(
                 type="pil",
-                label="🖼️ Upload Image (for your reference)",
+                label="🖼️ Upload Damage Photo",
                 height=300
             )
             prompt_input = gr.Textbox(
-                lines=3,
-                label="🧠 Your Prompt / Question",
-                placeholder="e.g., What kind of crack is this? What caused it?"
+                label="🧠 Enter Your Prompt",
+                placeholder="e.g., What kind of crack is this? What caused it?",
+                lines=4,
+                show_label=True
             )
-
             with gr.Row():
-                submit_btn = gr.Button("🔍 Analyze", variant="primary")
-                reset_btn = gr.Button("🔁 New Session")
+                analyze_btn = gr.Button("🔍 Analyze", variant="primary")
+                reset_btn = gr.Button("🔁 Reset", variant="secondary")
 
-        with gr.Column(scale=1):
+        with gr.Column(scale=1, min_width=320):
             output = gr.Textbox(
-                label="💬 Bot Response",
+                label="💬 Expert Response",
+                placeholder="Response will appear here...",
                 lines=20,
                 interactive=False,
                 show_copy_button=True
             )
 
-    submit_btn.click(analyze_image_with_prompt, inputs=[img_input, prompt_input], outputs=[output])
-    reset_btn.click(reset_history, outputs=[output, prompt_input])
+    analyze_btn.click(analyze_image_with_prompt, inputs=[img_input, prompt_input], outputs=output)
+    reset_btn.click(reset_history, outputs=[prompt_input, output])
 
-    gr.Markdown("➡️ You can continue chatting with the AI about the same issue.")
+    gr.Markdown("⚠️ Note: The model doesn't directly analyze the image, but uses your question to assist.")
+    gr.HTML("<footer>Made for field engineers and civil professionals 🛠️</footer>")
 
 demo.launch()