Create app.py

app.py

@@ -0,0 +1,73 @@
+import gradio as gr
+import torch
+import os
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from huggingface_hub import hf_hub_download
+
+# This points to the repo where you uploaded the .pt files in Phase 1
+MODEL_REPO = "ibz18/Model_D_weights" 
+BASE_MODEL = "csebuetnlp/banglat5"
+
+hf_token = os.environ.get("HF_TOKEN")
+
+print("1. Downloading .pt file...")
+abstracter_rl_path = hf_hub_download(
+    repo_id=MODEL_REPO, 
+    filename="abstracter_rl.pt",
+    token=hf_token
+)
+
+print("2. Loading tokenizer and base model...")
+tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL)
+model = AutoModelForSeq2SeqLM.from_pretrained(BASE_MODEL)
+
+print("3. Resizing embeddings...")
+model.resize_token_embeddings(len(tokenizer))
+
+print("4. Injecting .pt weights into memory...")
+checkpoint = torch.load(abstracter_rl_path, map_location="cpu", weights_only=True)
+
+if isinstance(checkpoint, dict) and "state_dict" in checkpoint:
+    state_dict = checkpoint["state_dict"]
+else:
+    state_dict = checkpoint
+
+model.load_state_dict(state_dict, strict=False)
+model.eval()
+
+def generate_summary(text):
+    if not text.strip():
+        return "Please enter Bangla text."
+    
+    try:
+        inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)
+        
+        with torch.no_grad():
+            output_ids = model.generate(
+                **inputs, 
+                max_new_tokens=128,
+                do_sample=False,
+                num_beams=2,
+                repetition_penalty=2.5,
+                early_stopping=True,
+                decoder_start_token_id=tokenizer.pad_token_id,
+                eos_token_id=tokenizer.eos_token_id,
+                pad_token_id=tokenizer.pad_token_id
+            )
+            
+        summary = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+        return summary if summary.strip() else "ERROR: Empty string"
+
+    except Exception as e:
+        return f"CRASH ERROR: {str(e)}"
+
+# --- INTERFACE WITH NEW NAME ---
+demo = gr.Interface(
+    fn=generate_summary,
+    inputs=gr.Textbox(lines=8, label="Input Bangla Text", placeholder="এখানে আপনার বাংলা টেক্সট দিন..."),
+    outputs=gr.Textbox(label="Generated Summary"),
+    title="Model_D",
+    description="Live testing interface for Model_D"
+)
+
+demo.launch()