asd

app.py

@@ -1,8 +1,59 @@
-# # import dependencies
+# # # import dependencies
+# # import gradio as gr
+# # from openai import OpenAI
+# # import os
+# # import re
+
+# # # define the openai key
+# # api_key = "sk-proj-UCoZZMs4MyfyHwXdHjT8T3BlbkFJjYkSZyPfIPNqXfXwoekm"
+
+# # # make an instance of the openai client
+# # client = OpenAI(api_key = api_key)
+
+
+# # # finetuned model instance
+# # finetuned_model = "ft:gpt-3.5-turbo-0125:personal::9qGC8cwZ"
+
+# # # function to humanize the text
+# # def humanize_text(AI_text):
+# #   """Humanizes the provided AI text using the fine-tuned model."""
+# #   response = completion = client.chat.completions.create(
+# #   model=finetuned_model,
+# #   temperature = 0.86,
+# #   messages=[
+# #     {"role": "system", "content": """
+# #     You are a text humanizer.
+# #     You humanize AI generated text.
+# #     The text must appear like humanly written.
+# #     THE INPUT AND THE OUTPUT TEXT SHOULD HAVE THE SAME FORMAT.
+# #     THE HEADINGS AND THE BULLETS IN THE INPUT SHOULD REMAIN IN PLACE"""},
+# #     {"role": "user", "content": f"THE LANGUAGE OF THE INPUT AND THE OUTPUT MUST BE SAME. THE SENTENCES SHOULD NOT BE SHORT LENGTH - THEY SHOULD BE SAME AS IN THE INPUT. ALSO THE PARAGRAPHS SHOULD NOT BE SHORT EITHER - PARAGRAPHS MUST HAVE THE SAME LENGTH"},
+# #     {"role": "user", "content": f"Humanize the text. Keep the output format i.e. the bullets and the headings as it is and dont use the list of words that are not permissible. \nTEXT: {AI_text}"}
+# #   ]
+# #   )
+
+# #   humanized_text = response.choices[0].message.content.strip()
+
+# #   return humanized_text
+
+
+# # # Gradio interface definition
+# # interface = gr.Interface(
+# #   fn=humanize_text,
+# #   inputs="textbox",
+# #   outputs="textbox",
+# #   title="AI Text Humanizer: NoaiGPT.com Demo",
+# #   description="Enter AI-generated text and get a human-written version.",
+# # )
+
+# # # Launch the Gradio app
+# # interface.launch(debug = True)
+
 # import gradio as gr
 # from openai import OpenAI
 # import os
 # import re
+# from transformers import pipeline
 
 # # define the openai key
 # api_key = "sk-proj-UCoZZMs4MyfyHwXdHjT8T3BlbkFJjYkSZyPfIPNqXfXwoekm"
@@ -10,44 +61,62 @@
 # # make an instance of the openai client
 # client = OpenAI(api_key = api_key)
 
-
 # # finetuned model instance
 # finetuned_model = "ft:gpt-3.5-turbo-0125:personal::9qGC8cwZ"
 
+# # Load the AI detection model
+# pipe = pipeline("text-classification", model="tommyliphys/ai-detector-distilbert")
+
+# # Define the function to get predictions
+# def get_prediction(text):
+#     return pipe(text)[0]
+
 # # function to humanize the text
 # def humanize_text(AI_text):
-#   """Humanizes the provided AI text using the fine-tuned model."""
-#   response = completion = client.chat.completions.create(
-#   model=finetuned_model,
-#   temperature = 0.86,
-#   messages=[
-#     {"role": "system", "content": """
-#     You are a text humanizer.
-#     You humanize AI generated text.
-#     The text must appear like humanly written.
-#     THE INPUT AND THE OUTPUT TEXT SHOULD HAVE THE SAME FORMAT.
-#     THE HEADINGS AND THE BULLETS IN THE INPUT SHOULD REMAIN IN PLACE"""},
-#     {"role": "user", "content": f"THE LANGUAGE OF THE INPUT AND THE OUTPUT MUST BE SAME. THE SENTENCES SHOULD NOT BE SHORT LENGTH - THEY SHOULD BE SAME AS IN THE INPUT. ALSO THE PARAGRAPHS SHOULD NOT BE SHORT EITHER - PARAGRAPHS MUST HAVE THE SAME LENGTH"},
-#     {"role": "user", "content": f"Humanize the text. Keep the output format i.e. the bullets and the headings as it is and dont use the list of words that are not permissible. \nTEXT: {AI_text}"}
-#   ]
-#   )
-
-#   humanized_text = response.choices[0].message.content.strip()
-
-#   return humanized_text
+#     """Humanizes the provided AI text using the fine-tuned model."""
+#     humanized_text = AI_text
+#     attempts = 0
+#     max_attempts = 5
+
+#     while attempts < max_attempts:
+#         response = client.chat.completions.create(
+#             model=finetuned_model,
+#             temperature=0.85,
+#             messages=[
+#                 {"role": "system", "content": """
+#                 You are a text humanizer.
+#                 You humanize AI generated text.
+#                 The text must appear like humanly written.
+#                 THE INPUT AND THE OUTPUT TEXT SHOULD HAVE THE SAME FORMAT.
+#                 THE HEADINGS AND THE BULLETS IN THE INPUT SHOULD REMAIN IN PLACE"""},
+#                 {"role": "user", "content": "THE LANGUAGE OF THE INPUT AND THE OUTPUT MUST BE SAME. THE SENTENCES SHOULD NOT BE SHORT LENGTH - THEY SHOULD BE SAME AS IN THE INPUT. ALSO THE PARAGRAPHS SHOULD NOT BE SHORT EITHER - PARAGRAPHS MUST HAVE THE SAME LENGTH"},
+#                 {"role": "user", "content": f"Humanize the text. Keep the output format i.e. the bullets and the headings as it is and dont use the list of words that are not permissible. \nTEXT: {humanized_text}"}
+#             ]
+#         )
+
+#         humanized_text = response.choices[0].message.content.strip()
+        
+#         # Check if the humanized text is still detected as AI
+#         prediction = get_prediction(humanized_text)
+        
+#         if prediction['label'] != 'AI':
+#             break
+        
+#         attempts += 1
 
+#     return humanized_text
 
 # # Gradio interface definition
 # interface = gr.Interface(
-#   fn=humanize_text,
-#   inputs="textbox",
-#   outputs="textbox",
-#   title="AI Text Humanizer: NoaiGPT.com Demo",
-#   description="Enter AI-generated text and get a human-written version.",
+#     fn=humanize_text,
+#     inputs="textbox",
+#     outputs="textbox",
+#     title="AI Text Humanizer: NoaiGPT.com Demo",
+#     description="Enter AI-generated text and get a human-written version.",
 # )
 
 # # Launch the Gradio app
-# interface.launch(debug = True)
+# interface.launch(debug=True)
 
 import gradio as gr
 from openai import OpenAI
@@ -59,7 +128,7 @@ from transformers import pipeline
 api_key = "sk-proj-UCoZZMs4MyfyHwXdHjT8T3BlbkFJjYkSZyPfIPNqXfXwoekm"
 
 # make an instance of the openai client
-client = OpenAI(api_key = api_key)
+client = OpenAI(api_key=api_key)
 
 # finetuned model instance
 finetuned_model = "ft:gpt-3.5-turbo-0125:personal::9qGC8cwZ"
@@ -71,6 +140,7 @@ pipe = pipeline("text-classification", model="tommyliphys/ai-detector-distilbert
 def get_prediction(text):
     return pipe(text)[0]
 
+# Function to clean the text
 def clean_text(text):
     # Remove double asterisks
     text = re.sub(r'\*\*', '', text)
@@ -78,7 +148,6 @@ def clean_text(text):
     text = re.sub(r'##', '', text)
     return text
 
-
 # function to humanize the text
 def humanize_text(AI_text):
     """Humanizes the provided AI text using the fine-tuned model."""
@@ -111,10 +180,10 @@ def humanize_text(AI_text):
             break
         
         attempts += 1
-    
-    humanize_text=clean_text(clean_text)
 
-    return humanized_text
+    # Clean the humanized text
+    cleaned_text = clean_text(humanized_text)
+    return cleaned_text
 
 # Gradio interface definition
 interface = gr.Interface(
@@ -126,4 +195,4 @@ interface = gr.Interface(
 )
 
 # Launch the Gradio app
-interface.launch(debug=True)
+interface.launch(debug=True)