Update app.py

app.py

@@ -5,15 +5,13 @@ from transformers import GPT2LMHeadModel, GPT2Tokenizer, LlamaTokenizer, pipelin
 from huggingface_hub import HfFolder
 from io import StringIO
 import os
-from flask import Flask, request, jsonify
 
+# Access the Hugging Face API token from environment variables
 hf_token = os.getenv('HF_API_TOKEN')
 
 if not hf_token:
     raise ValueError("Hugging Face API token is not set. Please set the HF_API_TOKEN environment variable.")
 
-# Ensure that you load the token before making API requests
-
 # Set environment variable to avoid floating-point errors
 os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
 
@@ -24,7 +22,7 @@ model_gpt2 = GPT2LMHeadModel.from_pretrained('gpt2')
 # Create a pipeline for text generation using GPT-2
 text_generator = pipeline("text-generation", model=model_gpt2, tokenizer=tokenizer)
 
-# Loading LLama3.1 tokenizer
+# Loading Llama3.1 tokenizer
 try:
     tokenizer_llama = LlamaTokenizer.from_pretrained("meta-llama/Meta-Llama-3.1-8B")
 except OSError as e:
@@ -129,5 +127,8 @@ iface = gr.Interface(
     description="Generate synthetic tabular datasets based on a description and specified columns."
 )
 
+# Set an API name for the POST request
+iface.api_name = "generate"
+
 # Run the Gradio app
 iface.launch()