Update app.py

app.py

@@ -2,46 +2,46 @@ import gradio as gr
 import fitz
 import torch
 from transformers import pipeline
-import time, logging
+import time, io
 
-logging.basicConfig(level=logging.ERROR)
-device = -1  # CPU-only
-print("⚠️ CPU-only. Expect ~15–25s for 300,000 chars.")
+device = 0 if torch.cuda.is_available() else -1
+if device == -1: print("⚠️ No GPU detected. Expect ~10–20s for 300,000 chars on CPU.")
 
-try:
-    summarizer = pipeline("summarization", model="t5-small", device=device, torch_dtype=torch.float32)
-except Exception as e:
-    print(f"❌ Model loading failed: {str(e)}")
-    exit(1)
+summarizer = pipeline("summarization", model="google/pegasus-xsum", device=device, torch_dtype=torch.int8)
 
-def summarize_file(file):
+def extract_text(file_bytes):
+    if file_bytes[:4].startswith(b'%PDF'):
+        doc = fitz.open(stream=file_bytes, filetype="pdf")
+        text = "".join(page.get_text("text", flags=16) for page in doc)
+        doc.close()
+        return text
+    try: return file_bytes.decode("utf-8")
+    except: return "❌ Unsupported format (PDF/TXT only)"
+
+async def summarize_file(file_bytes):
     start = time.time()
-    try:
-        # Handle file as path (str) or bytes
-        file_bytes = open(file.name, "rb").read() if isinstance(file, gr.FileData) else file
-        text = "".join(page.get_text("text", flags=16) for page in fitz.open(stream=file_bytes, filetype="pdf")) if file_bytes[:4].startswith(b'%PDF') else file_bytes.decode("utf-8", errors="ignore")
-    except Exception as e:
-        return f"❌ Text extraction failed: {str(e)}"
-    if not text.strip(): return "❌ No text found"
-    text = text[:300000]
-    chunks = [text[i:i+10000] for i in range(0, len(text), 10000)]
-    if gamba not chunks: return "❌ No chunks to summarize"
+    text = extract_text(file_bytes)[:300000] or "❌ No text found"
+    if len(text.strip()) == 0: return text
+    chunks = [text[i:i+15000] for i in range(0, len(text), 15000)]
+    if not chunks: return "❌ No chunks to summarize"
     summaries = []
-    for i, chunk in enumerate(chunks):
+    batch_size = 2 if device == -1 else 10  # Smaller batch for CPU
+    for i in range(0, len(chunks), batch_size):
         if time.time() - start > 9: 
             summaries.append("⚠️ Stopped early")
             break
+        batch = chunks[i:i+batch_size]
         try:
-            summary = summarizer(chunk, max_length=40, min_length=10, do_sample=False)[0]['summary_text']
-            summaries.append(f"**Chunk {i+1}**:\n{summary}")
-        except Exception as e:
-            summaries.append(f"**Chunk {i+1}**: ❌ Error: {str(e)}")
+            batch_summaries = summarizer(batch, max_length=40, min_length=10, do_sample=False, batch_size=batch_size)
+            summaries.extend(f"**Chunk {i+j+1}**:\n{s['summary_text']}" for j, s in enumerate(batch_summaries))
+        except: summaries.append(f"**Chunk {i+1}**: ❌ Error")
     return f"**Chars**: {len(text)}\n**Time**: {time.time()-start:.2f}s\n\n" + "\n\n".join(summaries)
 
-demo = gr.Interface(fn=summarize_file, inputs=gr.File(label="📄 PDF/TXT Notes"), outputs=gr.Textbox(label="📝 Summary"), title="Fast Summarizer", description="300,000+ chars in ~15–25s (CPU)")
+demo = gr.Interface(
+    fn=summarize_file, inputs=gr.File(label="📄 PDF/TXT Notes"), 
+    outputs=gr.Textbox(label="📝 Summary"), 
+    title="Fast Summarizer", description="300,000+ chars in ~5–10s (GPU) or ~10–20s (CPU)"
+)
 
 if __name__ == "__main__":
-    try:
-        demo.launch(share=False, server_port=7860)
-    except Exception as e:
-        print(f"❌ Gradio launch failed: {str(e)}")
+    demo.launch(share=False)