Create app.py

app.py

@@ -0,0 +1,48 @@
+import gradio as gr
+import os
+import openai
+from dotenv import load_dotenv
+
+
+# Load .env file
+load_dotenv()
+
+
+openai.api_type = "azure"
+openai.api_base = os.getenv("AZURE_API_ENDPOINT")
+openai.api_version = "2024-02-01"
+openai.api_key = os.getenv("AZURE_API_KEY")
+print(f"Azure API token: {azure_api_key}")
+
+
+def compare_claims(claim1, claim2):
+try:
+    response = openai.ChatCompletion.create(
+        engine="gpt-4",
+        messages=[
+            {"role": "system", "content": "You are an AI specialized in claim comparison."},
+            {"role": "user", "content": f"Compare these two claims:\nClaim 1: {claim1}\nClaim 2: {claim2}\nWhat are the differences?"}
+        ]
+    )
+    return response["choices"][0]["message"]["content"]
+ except Exception as e:
+        return {"error": str(e)}
+        
+def main():
+    """
+    Launch the Gradio interface for sentiment analysis.
+    """
+    # Define the Gradio interface
+    interface = gr.Interface(
+        fn=compare_claims,
+        inputs=gr.Textbox(lines=2, placeholder="Enter Text Here..."),
+        outputs="json",
+        title="Text Classification with Azure Text Analytics",
+        description="This interface uses Azure Text Analytics to classify text sentiments. Enter a sentence to see its classification."
+    )
+
+    # Launch the Gradio app
+    interface.launch()
+
+if __name__ == "__main__": 
+    main()