Update app.py

app.py

@@ -5,49 +5,44 @@ import requests
 from PIL import Image
 from io import BytesIO
 
-# 🔐 Set your Groq API key here or use environment variable
+# 🔐 Set your Groq API key
 GROQ_API_KEY = os.getenv("GROQ_API_KEY") or "PASTE_YOUR_GROQ_API_KEY_HERE"
-
-# ✅ Groq LLaMA 3 model endpoint (text-only)
-GROQ_MODEL = "llama-3-70b-8192"
+GROQ_MODEL = "llama3-8b-8192"
 GROQ_URL = "https://api.groq.com/openai/v1/chat/completions"
 
-# Store history per session
+# 🧠 Conversation history per session
 history = []
 
 def analyze_image_with_prompt(image, user_prompt):
     global history
 
-    if image is None:
-        return "⚠️ Please upload an image."
-
-    if not user_prompt.strip():
-        return "⚠️ Please describe the damage or ask a question."
+    if image is None or not user_prompt.strip():
+        return "⚠️ Please upload an image and describe the problem."
 
-    # Convert image to base64 (for reference only, model won't see it)
+    # Base64 (not used by model, just for completeness)
     buffered = BytesIO()
     image.save(buffered, format="JPEG")
     img_base64 = base64.b64encode(buffered.getvalue()).decode()
 
-    # Add system message once
-    if len(history) == 0:
+    # Add system message on first use
+    if not history:
         history.append({
             "role": "system",
             "content": (
-                "You are a helpful construction engineer bot.\n"
-                "The user has uploaded an image (you can't see it).\n"
-                "Ask them to describe the visible damage and respond with:\n"
-                "- Type of damage\n"
-                "- Possible causes\n"
+                "You are a helpful construction assistant bot.\n"
+                "You cannot see images but users will describe what is shown.\n"
+                "Based on their description, provide:\n"
+                "- Type of construction damage\n"
+                "- Likely cause\n"
                 "- Recommended tools/materials\n"
-                "- Estimated repair time."
+                "- Estimated repair time\n"
+                "Be concise and professional."
             )
         })
 
-    # Add user message
     history.append({
         "role": "user",
-        "content": f"(Image uploaded by user)\nPrompt: {user_prompt}"
+        "content": f"(Image uploaded)\nProblem description: {user_prompt}"
     })
 
     headers = {
@@ -58,66 +53,67 @@ def analyze_image_with_prompt(image, user_prompt):
     payload = {
         "model": GROQ_MODEL,
         "messages": history,
-        "temperature": 0.5
+        "temperature": 0.7
     }
 
-    try:
-        response = requests.post(GROQ_URL, headers=headers, json=payload)
-        response.raise_for_status()
+    response = requests.post(GROQ_URL, headers=headers, json=payload)
+
+    if response.status_code == 200:
         reply = response.json()["choices"][0]["message"]["content"]
         history.append({"role": "assistant", "content": reply})
         return reply
-    except Exception as e:
-        return f"❌ Error: {str(e)}"
+    else:
+        return f"❌ Error: {response.status_code}\n{response.text}"
 
 def reset_session():
     global history
     history = []
-    return "🔄 Session reset. Please upload a new image and describe the damage."
+    return "Session reset. Upload a new image and ask a question."
 
 # 🌐 Gradio Interface
-def build_ui():
-    with gr.Blocks(theme=gr.themes.Soft()) as demo:
-        gr.Markdown("""
-            # 🏗️ Construction Damage Assistant
-            Upload an image of damage and briefly describe it. AI will help you analyze and recommend fixes.
-        """)
-
-        with gr.Row():
-            with gr.Column(scale=1):
-                img_input = gr.Image(
-                    type="pil",
-                    label="📷 Upload Damage Image",
-                    height=300
-                )
-
-                prompt_input = gr.Textbox(
-                    lines=3,
-                    label="✏️ Describe the Damage or Ask a Question",
-                    placeholder="e.g. What type of crack is this? What caused it?"
-                )
-
-                output = gr.Textbox(
-                    label="🧠 AI Assistant Response",
-                    lines=18,
-                    show_copy_button=True
-                )
-
-                img_input.change(analyze_image_with_prompt, inputs=[img_input, prompt_input], outputs=output)
-                prompt_input.submit(analyze_image_with_prompt, inputs=[img_input, prompt_input], outputs=output)
-
-                with gr.Row():
-                    reset_btn = gr.Button("🔁 Reset Session")
-                reset_btn.click(reset_session, outputs=output)
-
-        gr.Markdown("""
-            <hr>
-            ⚠️ <small>The AI cannot see the image — your description is essential for accurate help.</small>
-        """)
-
-    return demo
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("""
+    # 🏗️ Construction Damage Assistant
+
+    This assistant helps you understand construction damage.
+
+    **Step 1:** 📤 Upload a picture of the damaged area.  
+    **Step 2:** 📝 Describe the problem or ask a question about the image.  
+    **Step 3:** 💡 Get a smart, helpful response.
+
+    ---
+    """)
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            img_input = gr.Image(
+                type="pil",
+                label="Step 1: Upload a Picture",
+                height=300
+            )
+
+            prompt_input = gr.Textbox(
+                lines=3,
+                label="Step 2: Ask a Question / Describe the Damage",
+                placeholder="e.g. What type of crack is this? What might have caused it?"
+            )
+
+            with gr.Row():
+                submit_btn = gr.Button("🔍 Get Answer", variant="primary")
+                reset_btn = gr.Button("🔁 New Session")
+
+        with gr.Column(scale=1):
+            output = gr.Textbox(
+                label="Step 3: Assistant's Answer",
+                lines=18,
+                show_copy_button=True
+            )
+
+    submit_btn.click(analyze_image_with_prompt, inputs=[img_input, prompt_input], outputs=[output])
+    reset_btn.click(reset_session, outputs=[output])
+
+    gr.Markdown("---")
+    gr.Markdown("⚠️ **Note:** The AI does not process the image directly. Please describe what you see.")
 
 # 🚀 Launch the app
-if __name__ == "__main__":
-    ui = build_ui()
-    ui.launch()
+demo.launch()