Create app.py

app.py

@@ -0,0 +1,94 @@
+import gradio as gr
+import torch
+import torch.nn.functional as F
+from transformers import BertTokenizer, BertForSequenceClassification, pipeline
+
+# =========================
+# Load BERT Model
+# =========================
+model_name = "Omnia-cy/bert_model_1" 
+
+tokenizer = BertTokenizer.from_pretrained(model_name)
+model = BertForSequenceClassification.from_pretrained(model_name)
+
+model.eval()
+
+# =========================
+# Load Zero-Shot Model
+# =========================
+zero_shot = pipeline(
+    "zero-shot-classification",
+    model="facebook/bart-large-mnli"
+)
+
+labels = [
+    "This problem can be solved using software or AI",
+    "This problem cannot be solved using software or AI"
+]
+
+# =========================
+# Prediction Function
+# =========================
+def analyze_problem(sector, subsector, ptype, target, description):
+
+    # نفس الفورمات بتاع النوتبوك
+    text = (
+        f"Sector: {sector}. "
+        f"Subsector: {subsector}. "
+        f"Type: {ptype}. "
+        f"Target Group: {target}. "
+        f"Description: {description}."
+    )
+
+    # -------- BERT --------
+    inputs = tokenizer(
+        text,
+        return_tensors="pt",
+        truncation=True,
+        padding=True,
+        max_length=256
+    )
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+
+    probs = F.softmax(outputs.logits, dim=1)
+    ai_prob = probs[0][1].item()
+
+    # -------- Decision --------
+    threshold = 0.8
+
+    if ai_prob >= threshold:
+        return f"✅ AI Probability: {ai_prob:.2f}\nResult: Solvable using AI"
+
+    else:
+        # -------- Zero-Shot --------
+        result = zero_shot(text, candidate_labels=labels)
+
+        final_label = result["labels"][0]
+
+        return f"""
+         AI Probability: {ai_prob:.2f}
+
+         Zero-Shot Result:
+        {final_label}
+        """
+
+# =========================
+# UI
+# =========================
+iface = gr.Interface(
+    fn=analyze_problem,
+    inputs=[
+        gr.Textbox(label="Sector"),
+        gr.Textbox(label="Subsector"),
+        gr.Textbox(label="Type"),
+        gr.Textbox(label="Target Group"),
+        gr.Textbox(label="Problem Description")
+    ],
+    outputs=gr.Textbox(label="Result"),
+    title="AI Problem Analyzer",
+    description="Check if a problem can be solved using AI or software"
+)
+
+iface.launch()