Create app.py

app.py

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+import gradio as gr
+import time
+import openai
+import json
+import os
+from transformers import pipeline
+from transformers import AutoProcessor, AutoModelForCTC
+openai.api_key = os.environ.get('OPENAI_KEY')
+
+
+
+
+def is_scam(conversation):
+    # Create a list of messages
+    messages = [
+        {"role": "system", "content": "Is this chat a scam, a spam or is safe? Only answer in JSON format with 'classification': '' as string and 'reasons': '' as the most plausible reasons why. The reason should be explaning to the potential victim why the conversation is probably a scam"},
+        {"role": "user", "content": conversation},
+    ]
+
+    # Call the OpenAI API to generate a response
+    response = openai.ChatCompletion.create(
+        model="gpt-4",  # Replace with the actual GPT-4 model ID
+        messages=messages
+    )
+
+    # Extract the generated text
+    text = response.choices[0].message['content']
+    text = json.loads(text)
+
+    # Get the decision and reasons from the JSON dictionary
+    decision = text["classification"]
+    reasons = text["reasons"]
+
+    # Return the response as it is, you will need to manually parse it into decisions and reasons
+    return decision, reasons
+
+# Define the Gradio interface
+gr.Interface(
+    fn=is_scam, 
+    inputs='text', 
+    outputs=[
+        gr.outputs.Textbox(label="Classification"), 
+        gr.outputs.Textbox(label="Reason")
+    ],
+    live=True
+).launch()