Guiyom commited on
Commit
9501bbf
·
1 Parent(s): da74a56

Update app.py

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Files changed (1) hide show
  1. app.py +20 -19
app.py CHANGED
@@ -115,21 +115,6 @@ with gr.Blocks() as demo:
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  else:
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  return gr.update(visible=False), gr.update(visible=True), gr.update(value="", placeholder="Use a valid API key"), gr.update(visible=False)
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- def parse_participants(input_string: str) -> list:
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- # Replace <br> tags with newline characters
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- input_string = input_string.replace("<br>", "\n")
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-
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- # Split the input string using a regular expression for “Participant X”
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- participants = re.split(r'Participant \d+:\n', input_string)[1:] # Ignore the first split item since it’s empty
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-
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- # Parse each participant’s details and add them to a list
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- participant_details = []
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- for participant in participants:
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- details = '\n'.join(participant.strip().split("\n"))
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- participant_details.append(details)
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-
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- return participant_details
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-
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  def summarize(title, question1, question2, question3, expert1, expert2, expert3, expert4, expert5, expert6, expert7, expert8, expert9, expert10, response1, response2, response3, response4, response5, response6, response7, response8, response9, response10):
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  prompt = f"""
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  You are asked to make a report summarizing the inputs from 10 participants from a focus groups on this topic:
@@ -348,7 +333,22 @@ Now please provide your results.
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  results.append(result)
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  return results[0], results[1], results[2], results[3], results[4], results[5], results[6], results[7], results[8], results[9]
 
 
 
 
 
 
 
 
 
 
 
 
 
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  def generateprofiles(title, question1, question2, question3, focusgroupdescription):
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  prompt = f"""
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  Please generate 10 profiles for a focus group that would have the following features:
@@ -413,10 +413,11 @@ Here are 2 examples of profiles for inspiration (for a focus group on sparkling
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  Now please provide your results.
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  """
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  formattedprompt = [{'role':'system','content':system_message},{'role':'user','content':prompt}]
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- result = answer(formattedprompt, "gpt-3.5-turbo-16k")
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-
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- #break it down
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- list = parse_participants(result)
 
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  return list[0], list[1], list[2], list[3], list[4], list[5], list[6], list[7], list[8], list[9]
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  def answer(formmatedprompt, model):
 
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  else:
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  return gr.update(visible=False), gr.update(visible=True), gr.update(value="", placeholder="Use a valid API key"), gr.update(visible=False)
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  def summarize(title, question1, question2, question3, expert1, expert2, expert3, expert4, expert5, expert6, expert7, expert8, expert9, expert10, response1, response2, response3, response4, response5, response6, response7, response8, response9, response10):
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  prompt = f"""
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  You are asked to make a report summarizing the inputs from 10 participants from a focus groups on this topic:
 
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  results.append(result)
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  return results[0], results[1], results[2], results[3], results[4], results[5], results[6], results[7], results[8], results[9]
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+
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+ def parse_participants(input_string: str) -> list:
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+ # Replace <br> tags with newline characters
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+ input_string = input_string.replace("<br>", "\n")
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+
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+ # Split the input string using a regular expression for “Participant X”
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+ participants = re.split(r'Participant \d+:\n', input_string)[1:] # Ignore the first split item since it’s empty
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+
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+ # Parse each participant’s details and add them to a list
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+ participant_details = []
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+ for participant in participants:
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+ details = '\n'.join(participant.strip().split("\n"))
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+ participant_details.append(details)
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+ return participant_details
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+
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  def generateprofiles(title, question1, question2, question3, focusgroupdescription):
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  prompt = f"""
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  Please generate 10 profiles for a focus group that would have the following features:
 
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  Now please provide your results.
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  """
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  formattedprompt = [{'role':'system','content':system_message},{'role':'user','content':prompt}]
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+ list = []
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+ while len(list) <10:
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+ result = answer(formattedprompt, "gpt-3.5-turbo-16k")
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+ #break it down
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+ list = parse_participants(result)
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  return list[0], list[1], list[2], list[3], list[4], list[5], list[6], list[7], list[8], list[9]
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  def answer(formmatedprompt, model):