Update app.py

app.py

@@ -1,10 +1,22 @@
 import whisper
 import gradio as gr
+import openai 
+import os
+openai.api_key = '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'
 
 # load model and processor
 
 model = whisper.load_model("medium")
 
+def get_completion(prompt, model='gpt-3.5-turbo'):
+    messages = [{"role": "user", "content": prompt}]
+    response = openai.ChatCompletion.create(
+        model = model, 
+        messages = messages, 
+        temperature = 0, 
+        
+    ) 
+    return response.choices[0].message['content']
 
 def transcribe(audio):
     
@@ -26,7 +38,24 @@ def transcribe(audio):
     return result.text
     
     
- 
+prompt = f"""
+You are a world class nurse practitioner. You are provided with text delimited by triple quotes. \
+Summarize the text and put it in a table format with rows as follows: \ 
+    
+1. Patient identification: 
+2. Chief complaint: 
+3. Medical history: 
+4. Family history: 
+5. Social history: 
+6. Review of systems: 
+7. Current medications: 
+8. Vaccination status: 
+9. Emotional well-being: 
+10. Patient concerns and expectations: 
+
+\"\"\"{text_1}\"\"\"
+"""
+
 # gr.Interface(
 #     title = 'Talk to NP', 
 #     fn=transcribe, 
@@ -59,7 +88,7 @@ with demo:
     b2 = gr.Button("Summarize")
 
     b1.click(transcribe, inputs=audio_file, outputs=text1)
-    b2.click(text_to_sentiment, inputs=text1, outputs=text2)
+    b2.click(get_completion, inputs=text1, outputs=text2)
 
 demo.launch()