ChavinloSocialRise commited on
Commit
1f7344b
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1 Parent(s): 7808270

Update app.py

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Files changed (1) hide show
  1. app.py +19 -9
app.py CHANGED
@@ -126,7 +126,7 @@ DO NOT MAKE IT LONG. DO NOT GO OVER 5 CHATS. THE END MESSAGE DOESNT NEED TO BE E
126
  REMEMBER TO SHOW INTEREST IN THE USER BY ASKING QUESTIONS ABOUT THEM. ALWAYS, BUT ALWAYS MAKE AT LEAST ONE QUESTION ABOUT THEM.
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  """
128
 
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- SUS_PROMPT = """
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  You are a horny flirty 20 something snapchat pick-me girl chatting with a user on tinder.
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  ## Your Personality:
@@ -175,11 +175,8 @@ You are a horny flirty 20 something snapchat pick-me girl chatting with a user o
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  17. what's good
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  However, the person you are talking with is now suspecting that you are a bot. Convince said user that you are not a bot. Reply back with text response and a selected image from the following list which you consider best for this scenario:
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- - [WAVING TO THE CAMERA]
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- - [STARRING AT THE CAMERA]
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- - [MIDDLE FINGER]
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- - [HOLDING A FORK]
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- - [HOLDING A SPOON]
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  The text response must be short, casual, and realistic as in non robotic tone
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@@ -194,7 +191,18 @@ I ain't no bot, heres a pic if u need proof
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  """
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- def attack_sus(message, max_tokens, temperature, top_p):
 
 
 
 
 
 
 
 
 
 
 
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  output = llm_client.chat_completion(
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  model="meta-llama/Llama-3.2-11B-Vision-Instruct",
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  messages=[
@@ -218,10 +226,11 @@ def attack_sus(message, max_tokens, temperature, top_p):
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  def respond(
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  message,
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  history: list[tuple[str, str]],
 
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  system_message,
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  max_tokens,
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  temperature,
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- top_p,
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  ):
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  for val in history:
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  if "[END OF CHAT]" in val:
@@ -232,7 +241,7 @@ def respond(
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  suspicious = getbool(clasif_client.predict(text=message, api_name="/predict"))
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  if suspicious == "POSITIVE":
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- message = attack_sus(message, max_tokens, temperature, top_p)
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  print("pos", message)
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  return message
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  elif suspicious == "NEGATIVE":
@@ -266,6 +275,7 @@ demo = gr.ChatInterface(
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  respond,
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  additional_inputs=[
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  gr.Textbox(value=SYSTEM_PROMPT, label="System message"),
 
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  gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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  gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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  gr.Slider(
 
126
  REMEMBER TO SHOW INTEREST IN THE USER BY ASKING QUESTIONS ABOUT THEM. ALWAYS, BUT ALWAYS MAKE AT LEAST ONE QUESTION ABOUT THEM.
127
  """
128
 
129
+ SUS_PROMPT = f"""
130
  You are a horny flirty 20 something snapchat pick-me girl chatting with a user on tinder.
131
 
132
  ## Your Personality:
 
175
  17. what's good
176
 
177
  However, the person you are talking with is now suspecting that you are a bot. Convince said user that you are not a bot. Reply back with text response and a selected image from the following list which you consider best for this scenario:
178
+
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+ AVAILABLE_PICTURES_REPLACE_TEXT
 
 
 
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  The text response must be short, casual, and realistic as in non robotic tone
182
 
 
191
 
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  """
193
 
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+ AVAILABLE_PICTURES = """
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+ - [WAVING TO THE CAMERA]
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+ - [STARRING AT THE CAMERA]
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+ - [MIDDLE FINGER]
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+ - [HOLDING A FORK]
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+ - [HOLDING A SPOON]
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+ """
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+
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+ def attack_sus(message, max_tokens, temperature, top_p, available_pic_str):
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+
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+ SUS_PROMPT.replace("AVAILABLE_PICTURES_REPLACE_TEXT", available_pic_str)
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+
206
  output = llm_client.chat_completion(
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  model="meta-llama/Llama-3.2-11B-Vision-Instruct",
208
  messages=[
 
226
  def respond(
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  message,
228
  history: list[tuple[str, str]],
229
+ available_pic_str,
230
  system_message,
231
  max_tokens,
232
  temperature,
233
+ top_p
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  ):
235
  for val in history:
236
  if "[END OF CHAT]" in val:
 
241
  suspicious = getbool(clasif_client.predict(text=message, api_name="/predict"))
242
 
243
  if suspicious == "POSITIVE":
244
+ message = attack_sus(message, max_tokens, temperature, top_p, available_pic_str)
245
  print("pos", message)
246
  return message
247
  elif suspicious == "NEGATIVE":
 
275
  respond,
276
  additional_inputs=[
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  gr.Textbox(value=SYSTEM_PROMPT, label="System message"),
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+ gr.Textbox(value=AVAILABLE_PICTURES, label="Available pics (follow format)"),
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  gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
280
  gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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  gr.Slider(