Update app.py

app.py

@@ -1,7 +1,7 @@
 import spaces
 import torch
 import gradio as gr
-from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
+from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
 from threading import Thread
 from typing import Iterator
 import os
@@ -89,53 +89,26 @@ def generate_soap(
         outputs.append(text)
         yield "".join(outputs)
 
-# Gradio Interfaces
+# Gradio Interface combining transcription and SOAP note generation
 demo = gr.Blocks(theme=gr.themes.Ocean())
 
-# Interface for microphone or file transcription
-mf_transcribe = gr.Interface(
-    fn=transcribe,
-    inputs=[
-        gr.Audio(sources="microphone", type="filepath"),
-        gr.Radio(["transcribe", "translate"], label="Task", value="transcribe")
-    ],
-    outputs="text",
-    title="Audio Transcribe",
-    description="Transcribe long-form microphone or audio inputs."
-)
-
-file_transcribe = gr.Interface(
-    fn=transcribe,
-    inputs=[
-        gr.Audio(sources="upload", type="filepath", label="Audio file"),
-        gr.Radio(["transcribe", "translate"], label="Task", value="transcribe")
-    ],
-    outputs="text",
-    title="Audio Transcribe"
-)
-
-# SOAP Note generation interface with additional parameters
-soap_note = gr.Interface(
-    fn=generate_soap,
-    inputs=[
-        gr.Textbox(label="Transcribed Text", lines=10),
-        gr.Textbox(label="System Prompt", lines=2, value="You are a world class clinical assistant."),
-        gr.Slider(label="Max new tokens", minimum=1, maximum=2048, value=1024, step=1),
-        gr.Slider(label="Temperature", minimum=0.1, maximum=4.0, value=0.6, step=0.1),
-        gr.Slider(label="Top-p", minimum=0.05, maximum=1.0, value=0.9, step=0.05),
-        gr.Slider(label="Top-k", minimum=1, maximum=1000, value=50, step=1),
-        gr.Slider(label="Repetition penalty", minimum=1.0, maximum=2.0, value=1.2, step=0.05)
-    ],
-    outputs="text",
-    title="Generate Clinical SOAP Note",
-    description="Convert transcribed conversation to a clinical SOAP note with structured sections."
-)
-
-# Tabbed interface
 with demo:
-    gr.TabbedInterface(
-        [mf_transcribe, file_transcribe, soap_note],
-        ["Microphone", "Audio file", "SOAP Note"]
-    )
+    with gr.Tab("Clinical SOAP Note from Audio"):
+        audio_transcribe_and_soap = gr.Interface(
+            fn=lambda inputs, task: generate_soap(transcribe(inputs, task)),
+            inputs=[
+                gr.Audio(sources=["microphone", "upload"], type="filepath", label="Audio Input"),
+                gr.Radio(["transcribe", "translate"], label="Task", value="transcribe"),
+                gr.Textbox(label="System Prompt", lines=2, value="You are a world class clinical assistant."),
+                gr.Slider(label="Max new tokens", minimum=1, maximum=2048, value=1024, step=1),
+                gr.Slider(label="Temperature", minimum=0.1, maximum=4.0, value=0.6, step=0.1),
+                gr.Slider(label="Top-p", minimum=0.05, maximum=1.0, value=0.9, step=0.05),
+                gr.Slider(label="Top-k", minimum=1, maximum=1000, value=50, step=1),
+                gr.Slider(label="Repetition penalty", minimum=1.0, maximum=2.0, value=1.2, step=0.05)
+            ],
+            outputs="text",
+            title="Generate Clinical SOAP Note from Audio",
+            description="Transcribe audio input and convert it into a structured clinical SOAP note."
+        )
 
 demo.queue().launch(ssr_mode=False)