Update app.py

app.py

@@ -1,51 +1,72 @@
-# import dependencies
-import gradio as gr
-from openai import OpenAI
-import os
-import re
+# # import dependencies
+# import gradio as gr
+# from openai import OpenAI
+# import os
+# import re
+
+# # define the openai key
+# api_key = os.getenv("OPENAI_API_KEY")
+
+# # make an instance of the openai client
+# client = OpenAI(api_key = api_key)
+
 
-# define the openai key
-api_key = os.getenv("OPENAI_API_KEY")
+# # finetuned model instance
+# finetuned_model = "ft:gpt-3.5-turbo-0125:cedarbyte-business-solutions::9f4vd1FP"
 
-# make an instance of the openai client
-client = OpenAI(api_key = api_key)
+# # 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 = 0.85,
+#   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": 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()
+#   humanized_text = re.sub(r'[^A-Za-z0-9\s]', '', humanized_text)
 
-# finetuned model instance
-finetuned_model = "ft:gpt-3.5-turbo-0125:cedarbyte-business-solutions::9f4vd1FP"
+#   return humanized_text
 
-# 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 = 0.85,
-  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": 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()
-  humanized_text = re.sub(r'[^A-Za-z0-9\s]', '', humanized_text)
+# # Gradio interface definition
+# interface = gr.Interface(
+#   fn=humanize_text,
+#   inputs="textbox",
+#   outputs="textbox",
+#   title="AI Text Humanizer",
+#   description="Enter AI-generated text and get a human-written version.",
+# )
 
-  return humanized_text
+# # Launch the Gradio app
+# interface.launch(debug = True)
+
+
+
+import gradio as gr
 
+# Function to handle text submission
+def contact_info(text):
+    return "Contact [email protected] for this service"
 
 # Gradio interface definition
 interface = gr.Interface(
-  fn=humanize_text,
-  inputs="textbox",
-  outputs="textbox",
-  title="AI Text Humanizer",
-  description="Enter AI-generated text and get a human-written version.",
+    fn=contact_info,
+    inputs="textbox",
+    outputs="text",
+    title="Contact Information",
+    description="Enter text and click submit to get contact information."
 )
 
 # Launch the Gradio app
-interface.launch(debug = True)
+if __name__ == "__main__":
+    interface.launch()