Create app.py

app.py

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+import spaces
+import gradio as gr
+from transformers import pipeline, TextIteratorStreamer
+import torch
+import threading
+
+# Load model and tokenizer
+model_name = "krish10/Qwen3_14B_16bit_TA_screen_v1.0"
+pipe = pipeline("text-generation", model=model_name, device=0)
+tokenizer = pipe.tokenizer
+model = pipe.model
+
+# Fixed generation config
+MAX_TOKENS = 3000
+TEMPERATURE = 0.1
+TOP_P = 0.9
+
+@spaces.GPU
+def respond_stream(title, abstract):
+    if not title.strip() or not abstract.strip():
+        return "❌ Error: Title and Abstract are required."
+
+    prompt = f"Title: {title.strip()}\nAbstract: {abstract.strip()}"
+
+    messages = [{"role": "user", "content": prompt}]
+    prompt_text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+    inputs = tokenizer(prompt_text, return_tensors="pt").to("cuda")
+    streamer = TextIteratorStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+
+    generation_kwargs = dict(
+        input_ids=inputs["input_ids"],
+        streamer=streamer,
+        max_new_tokens=MAX_TOKENS,
+        temperature=TEMPERATURE,
+        top_p=TOP_P,
+        do_sample=True,
+        pad_token_id=tokenizer.eos_token_id,
+    )
+
+    thread = threading.Thread(target=model.generate, kwargs=generation_kwargs)
+    thread.start()
+
+    partial_text = ""
+    for token in streamer:
+        partial_text += token
+        yield partial_text
+
+# Build Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("## 🤖 Qwen Streaming Chat — Medical Abstract Evaluator")
+
+    with gr.Column():
+        title = gr.Textbox(label="Title", lines=2, placeholder="Required")
+        abstract = gr.Textbox(label="Abstract", lines=10, placeholder="Required")
+
+    output_box = gr.Textbox(label="Model Response", lines=15, interactive=False)
+    generate_btn = gr.Button("Generate")
+
+    generate_btn.click(
+        fn=respond_stream,
+        inputs=[title, abstract],
+        outputs=[output_box]
+    )
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()