Update app.py

app.py

@@ -1,78 +1,37 @@
 import gradio as gr
-from transformers import pipeline, set_seed
-
-# Define the questions
-questions = [
-    "Which grade is the child studying?",
-    "How old is the child?",
-    "What is the gender?",
-    "Can you provide the name and location of the child's school?",
-    "What are the names of the child's guardians or parents?",
-    "What is the chief complaint regarding the child's oral health? If there is none, just say the word 'none', else elaborate only on medication history",
-    "Can you provide any relevant medical history for the child? If there is none, just say the word 'none', else elaborate",
-    "Does the child take any medications regularly? If there is none, just say the word 'none'. If yes, please specify.",
-    "When was the child's previous dental visit? If no visits before, just say the word 'first' or mention the visit number and nothing else",
-    "Does the child have any habits such as thumb sucking, tongue thrusting, nail biting, or lip biting? If yes, just list them and don't provide any further details",
-    "Does the patient brush their teeth? Just use the words 'once daily', 'twice daily', or 'thrice daily' to answer, nothing else",
-    "Does the child experience bleeding gums? Just say 'yes' or 'no' for this and nothing else",
-    "Has the child experienced early childhood caries? Just say 'yes' or 'no' and nothing else",
-    "Please mention if tooth decay is present with tooth number(s), else just say the word 'none' and nothing else",
-    "Have any teeth been fractured? If yes, please mention the tooth number(s), else just say 'none' and nothing else",
-    "Is there any pre-shedding mobility of teeth? If yes, please specify, else just say 'none' and nothing else",
-    "Does the child have malocclusion? If yes, please provide details, else just say the word 'none' and nothing else",
-    "Does the child experience pain, swelling, or abscess? If yes, please provide details, else just say 'none' and nothing else",
-    "Are there any other findings you would like to note?",
-    "What treatment plan do you recommend? Choose only from Options: (Scaling, Filling, Pulp therapy/RCT, Extraction, Medication, Referral) and nothing else"
-]
-
-# Initialize answers
-answers = {q: '' for q in questions}
-
-# Define the default context
-default_context = (
-    "My child, Sarah, is studying in the 3rd grade. She is 8 years old and is a girl. "
-    "Sarah attends Greenwood Elementary School, located in Springfield. "
-    "Her guardians are myself, Emma Johnson, and her father, Michael Johnson.\n\n"
-    "Sarah's chief complaint regarding her oral health is that she has been experiencing some discomfort due to a cavity in her molar. "
-    "Other than that, she has no significant medication history. She has no relevant medical history to report. "
-    "Sarah does not take any medications regularly.\n\n"
-    "Her last dental visit was about a year ago, so this is her second visit. "
-    "Sarah has a habit of occasionally biting her nails, but she doesn't have any other habits like thumb sucking or tongue thrusting.\n\n"
-    "Sarah brushes her teeth twice daily. She does not experience bleeding gums. "
-    "Sarah has not experienced early childhood caries. Unfortunately, she does have tooth decay present in tooth numbers 14 and 15. "
-    "None of her teeth have been fractured. There is no pre-shedding mobility of teeth to report.\n\n"
-    "Sarah does not have malocclusion. She does not experience any pain, swelling, or abscess at the moment. "
-    "There are no other significant findings to note.\n\n"
-    "As for the treatment plan, I would recommend a filling for the decayed teeth."
-)
-
-# Load the GPT-2 model for text generation
-generator = pipeline('text-generation', model='gpt2')
-
-# Function to generate answers
-def generate_answers(context):
-    prompt = context + "\n\n" + "\n\n".join(questions)
-    set_seed(42)  # Ensure reproducibility
-    generated_text = generator(prompt, max_length=300, num_return_sequences=1)[0]['generated_text']
-    generated_answers = generated_text.split("\n\n")
-    return generated_answers
-
-# Function to display the form
-def form_display():
-    return gr.Interface(
-        fn=form_submit,
-        inputs=gr.inputs.Textbox(lines=20, label="Context", default=default_context),
-        outputs=gr.outputs.Textbox(label="Generated Answers", type="text"),
-        title="Dental Health Record Form with GPT-2",
-        description="Fill out the context and click submit to generate answers to the questions.",
-        examples=[default_context],
-        allow_flagging=False
-    )
-
-# Function to submit the form
-def form_submit(context):
-    generated_answers = generate_answers(context)
-    return generated_answers
-
-# Launch the interface
-form_display().launch()
+import assemblyai as aai
+import os
+
+# Replace with your AssemblyAI API key
+aai.settings.api_key = "62acec891bb04c339ec059b738bedac6"
+
+# Function to handle audio recording and transcription
+def transcribe_audio(audio):
+    # Save the recorded audio to a file
+    audio_path = "recorded_audio.wav"
+    audio.save(audio_path)
+    
+    # Transcribe the audio file using AssemblyAI
+    transcriber = aai.Transcriber()
+    transcript = transcriber.transcribe(audio_path)
+    
+    # Handle the transcription result
+    if transcript.status == aai.TranscriptStatus.error:
+        return transcript.error
+    else:
+        return transcript.text
+
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Audio Transcription App")
+    with gr.Row():
+        with gr.Column():
+            audio_input = gr.Audio(source="microphone", type="file", label="Record your audio")
+            output_text = gr.Textbox(label="Transcription")
+        with gr.Column():
+            transcribe_button = gr.Button("Transcribe")
+
+    transcribe_button.click(fn=transcribe_audio, inputs=audio_input, outputs=output_text)
+
+# Launch the app
+demo.launch()