Create app.py

app.py

@@ -0,0 +1,80 @@
+import os
+import gradio as gr
+import base64
+import requests
+from PIL import Image
+from io import BytesIO
+
+# 🔐 Set your Groq API key here (or use HF Secrets)
+GROQ_API_KEY = os.getenv("GROQ_API_KEY") or "PASTE_YOUR_GROQ_API_KEY_HERE"
+
+# ✅ Supported model from Groq
+GROQ_MODEL = "llama-3.3-70b-versatile"
+GROQ_URL = "https://api.groq.com/openai/v1/chat/completions"
+
+# Store history per session
+history = []
+
+def analyze_image_with_prompt(image, user_prompt):
+    global history
+
+    # Convert image to base64
+    buffered = BytesIO()
+    image.save(buffered, format="JPEG")
+    img_base64 = base64.b64encode(buffered.getvalue()).decode()
+
+    # System prompt on first message
+    if len(history) == 0:
+        system_msg = {
+            "role": "system",
+            "content": (
+                "You are a helpful construction engineer bot. "
+                "Given an image of a construction issue and a prompt, identify:\n"
+                "- Type of damage\n"
+                "- Possible causes\n"
+                "- Recommended tools and materials\n"
+                "- Estimated repair time.\n"
+                "Then answer follow-up questions."
+            )
+        }
+        history.append(system_msg)
+        user_msg = {
+            "role": "user",
+            "content": f"Image base64: {img_base64}\nPrompt: {user_prompt}"
+        }
+        history.append(user_msg)
+    else:
+        history.append({"role": "user", "content": user_prompt})
+
+    headers = {
+        "Authorization": f"Bearer {GROQ_API_KEY}",
+        "Content-Type": "application/json"
+    }
+
+    payload = {
+        "model": GROQ_MODEL,
+        "messages": history,
+        "temperature": 0.7
+    }
+
+    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
+    else:
+        return f"❌ Error: {response.status_code}\n{response.text}"
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("## 🏗️ Construction Damage Identifier Chatbot")
+    with gr.Row():
+        img_input = gr.Image(type="pil", label="Upload Damage Image")
+        prompt_input = gr.Textbox(lines=2, label="Your Prompt / Question")
+    output = gr.Textbox(label="Bot Response", lines=10)
+    submit = gr.Button("Analyze / Ask")
+    submit.click(analyze_image_with_prompt, inputs=[img_input, prompt_input], outputs=[output])
+    gr.Markdown("💬 You can continue asking questions about the uploaded image.")
+
+demo.launch()