Update app.py

app.py

@@ -4,9 +4,16 @@ from torchvision import models
 from PIL import Image
 import pandas as pd
 import matplotlib.pyplot as plt
+import os
+from openai import OpenAI
 
 # -------------------------
-# LOAD LIGHT MODEL
+# OPENAI SETUP
+# -------------------------
+client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+
+# -------------------------
+# MODEL (LIGHTWEIGHT)
 # -------------------------
 weights = models.MobileNet_V2_Weights.DEFAULT
 model = models.mobilenet_v2(weights=weights)
@@ -18,7 +25,23 @@ labels = weights.meta["categories"]
 history = []
 
 # -------------------------
-# PREDICTION FUNCTION
+# CHATGPT EXPLANATION
+# -------------------------
+def get_ai_explanation(label):
+    try:
+        response = client.chat.completions.create(
+            model="gpt-4o-mini",
+            messages=[
+                {"role": "system", "content": "You are an AI expert explaining image classification results."},
+                {"role": "user", "content": f"Explain in simple terms why this image might be classified as {label}."}
+            ]
+        )
+        return response.choices[0].message.content
+    except:
+        return "AI explanation unavailable. Check API key."
+
+# -------------------------
+# MAIN FUNCTION
 # -------------------------
 def analyze(image):
     img = transform(image).unsqueeze(0)
@@ -38,8 +61,8 @@ def analyze(image):
 
     df = pd.DataFrame(results)
 
-    # Explanation (simple AI)
-    explanation = f"This image is likely a {results[0]['label']} based on patterns like shape, color, and texture."
+    # AI Explanation
+    explanation = get_ai_explanation(results[0]["label"])
 
     # Chart
     plt.figure()
@@ -57,20 +80,30 @@ def analyze(image):
     return df, explanation, chart_path, hist_df
 
 # -------------------------
-# UI
+# UI DESIGN
 # -------------------------
-with gr.Blocks() as demo:
-    gr.Markdown("# 🧠 AI Vision App (Single App 🚀)")
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+
+    gr.Markdown("""
+    # 🧠 AI Vision Pro 🚀  
+    ### Real-time Image Recognition + ChatGPT Explanation
+    """)
 
     with gr.Row():
-        img = gr.Image(source="webcam", type="pil")
-        btn = gr.Button("Analyze")
+        with gr.Column():
+            img = gr.Image(source="webcam", type="pil", label="📷 Capture / Upload Image")
+            btn = gr.Button("🔍 Analyze", variant="primary")
 
-    output = gr.Dataframe(label="Predictions")
-    explanation = gr.Textbox(label="AI Explanation")
-    chart = gr.Image(label="Confidence Chart")
-    history_table = gr.Dataframe(label="History")
+        with gr.Column():
+            output = gr.Dataframe(label="📊 Predictions")
+            explanation = gr.Textbox(label="🧠 AI Explanation", lines=6)
+
+    chart = gr.Image(label="📈 Confidence Chart")
+    history_table = gr.Dataframe(label="🗂️ History")
 
     btn.click(analyze, inputs=img, outputs=[output, explanation, chart, history_table])
 
+    gr.Markdown("---")
+    gr.Markdown("⚡ Built with Deep Learning + OpenAI + Gradio")
+
 demo.launch()