Update app.py

app.py

@@ -5,11 +5,6 @@ import os
 
 openai.api_key = os.environ["OPENAI_API_KEY"]
 
-#openai.api_key = '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'
-
-import whisper
-import gradio as gr
-
 model = whisper.load_model("small")
 
 def transcribe(audio):
@@ -38,7 +33,29 @@ def process_text(input_text):
     return output_text
 
 def get_completion(prompt, model='gpt-3.5-turbo'):
-    messages = [{"role": "user", "content": prompt}]
+    messages = [
+        {"role": "system", "content": """You are a world class nurse practitioner. You are provided with the transcription. \
+    Summarize the text and put it in a table format with rows as follows: \ 
+        
+    Date of Alert
+    Claimant
+    Client/Employer
+    Claim #
+    DOI (Date of Injury)
+    Date of Visit
+    Provider
+    Diagnosis Treated
+    Subjective findings
+    Objective Findings
+    Treatment plan
+    Medications
+    RTW (Return to Work) Status
+    Restrictions
+    NOV (Next Office Visit)
+         """
+        },
+        {"role": "user", "content": prompt}
+        ]
     response = openai.ChatCompletion.create(
         model = model, 
         messages = messages, 
@@ -59,30 +76,16 @@ with demo:
     text1 = gr.Textbox()
     text2 = gr.Textbox()
 
-    prompt = f"""
-    You are a world class nurse practitioner. You are provided with the transcription. \
-    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: 
+    prompt = text1
     
   
-    """
     
     b1.click(transcribe, inputs=audio, outputs=text1)
     b2.click(get_completion, inputs=text1, outputs=text2)
 
 
     # b1.click(transcribe, inputs=audio, outputs=text1)
-    # b2.click(get_completion, inputs=text1, outputs=text2)
+    # b2.click(get_completion, inputs=prompt, outputs=text2)