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Update app.py
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app.py
CHANGED
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@@ -8,11 +8,13 @@ openai.api_key = os.environ["OPENAI_API_KEY"]
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model = whisper.load_model("small")
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def transcribe(audio):
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model = whisper.load_model("base")
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result = model.transcribe(audio)
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return result["text"]
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# def transcribe(audio):
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# #time.sleep(3)
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@@ -40,28 +42,10 @@ def process_text(input_text):
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def get_completion(prompt, model='gpt-3.5-turbo'):
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messages = [
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{"role": "system", "content": """You are a
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Extract the following information from the transcription, replace curly brackets with relevant extracted information
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Demographic information: {name, age, gender, address, phone number}
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Medical history: {chronic health conditions, any past surgery, any hospitalization, current medications}
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Symptoms: {current symptoms, when did they start, how did they progress}
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Allergies: {any known allergies, any allergic reaction to medications}
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Family history: {any family members with chronic health condition, anyone in the family with a hereditary condition?}
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Lifestyle factors: {typical diet, how often you exercise, smoking, drinking alcohol}
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Psychosocial factors: {stress, anxiety, any mental health condition}
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Review of systems: {any issues with vision or hearing, digestive issues, any problems with skin or nails, any problems with joints or muscles}
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All information in the report needs to be in English only.
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Only use the information from the provided transcription. Do not make up stuff. If information is not available just put "N/A" next to the relevant line.
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"""
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},
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{"role": "user", "content": prompt}
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@@ -77,16 +61,14 @@ def get_completion(prompt, model='gpt-3.5-turbo'):
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with gr.Blocks() as demo:
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gr.Markdown("""
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#
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This is to make life of non-English speaking patients easier.
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Describe your complaints and symptoms in your native language , have it emailed to your doctor prior to your visit.
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Information that is useful to include: your name, age, gender, address, phone number, medical history, symptoms, allergies, family medical history, lifestyle factors.
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Have it all recorded, transcribed, and presented in a standard form.
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""")
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title = "
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audio = gr.Audio(type="filepath")
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b1 = gr.Button("Transcribe audio")
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model = whisper.load_model("small")
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#option 1
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def transcribe(audio):
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model = whisper.load_model("base")
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result = model.transcribe(audio)
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return result["text"]
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#option 2
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# def transcribe(audio):
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# #time.sleep(3)
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def get_completion(prompt, model='gpt-3.5-turbo'):
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messages = [
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{"role": "system", "content": """You are a .... You are provided with the transcription of a ... . \
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Extract the following information from the transcription, replace curly brackets {} with relevant extracted information ... \
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...the rest of your prompt...
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"""
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},
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{"role": "user", "content": prompt}
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with gr.Blocks() as demo:
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gr.Markdown("""
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# Title <br>
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Description
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""")
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title = "title"
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audio = gr.Audio(type="filepath")
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b1 = gr.Button("Transcribe audio")
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