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app.py

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+# app.py
+import gradio as gr
+import torch
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+# ================= CONFIG ================= #
+MODEL_DIR = "finetuned_model"
+MAX_INPUT_LEN = 1024
+MAX_OUTPUT_LEN = 256
+NUM_BEAMS = 4
+
+PROMPT = (
+    "Generate a structured SOAP clinical summary with clearly separated "
+    "Subjective (S), Objective (O), Assessment (A), and Plan (P) sections "
+    "from the following medical dialogue:\n"
+)
+
+# ================= LOAD MODEL ================= #
+print("Loading model and tokenizer...")
+tokenizer = AutoTokenizer.from_pretrained(MODEL_DIR)
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_DIR)
+model.eval()
+
+# ================= INFERENCE FUNCTION ================= #
+def generate_soap(dialogue):
+    if not dialogue or len(dialogue.strip()) == 0:
+        return "Please enter a medical dialogue."
+
+    inputs = tokenizer(
+        PROMPT + dialogue,
+        return_tensors="pt",
+        truncation=True,
+        max_length=MAX_INPUT_LEN
+    )
+
+    with torch.no_grad():
+        output_ids = model.generate(
+            **inputs,
+            max_length=MAX_OUTPUT_LEN,
+            num_beams=NUM_BEAMS,
+            no_repeat_ngram_size=3,
+            repetition_penalty=1.3,
+            length_penalty=1.0,
+            early_stopping=True
+        )
+
+    return tokenizer.decode(
+        output_ids[0],
+        skip_special_tokens=True
+    )
+
+# ================= GRADIO UI ================= #
+iface = gr.Interface(
+    fn=generate_soap,
+    inputs=gr.Textbox(
+        lines=10,
+        placeholder="Enter doctor–patient medical dialogue here...",
+        label="Medical Dialogue"
+    ),
+    outputs=gr.Textbox(
+        lines=12,
+        label="Generated SOAP Clinical Summary"
+    ),
+    title="SOAP Clinical Summary Generator",
+    description="Fine-tuned FLAN-T5 model for SOAP note generation.",
+    examples=[
+        ["Patient reports fever and cough for three days. No history of chronic illness."],
+        ["Patient complains of chest pain and shortness of breath during exertion."]
+    ],
+)
+
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

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+torch
+transformers
+fastapi
+uvicorn
+pydantic
+sentencepiece