Update app.py

app.py

@@ -1,10 +1,3 @@
-# -*- coding: utf-8 -*-
-"""gen ai project f.ipynb
-Automatically generated by Colab.
-Original file is located at
-    https://colab.research.google.com/drive/1iF7hdOjWNeFUtGvUYdaFsBErJGnY1h5J
-"""
-
 import os
 from transformers import MarianMTModel, MarianTokenizer, GPTNeoForCausalLM, AutoTokenizer
 import gradio as gr
@@ -30,6 +23,7 @@ language_map = {
 }
 
 def translate_text(input_text, selected_languages):
+    """Translate input text into English based on the selected language."""
     if not selected_languages:
         return "Please select at least one language."
     
@@ -38,13 +32,16 @@ def translate_text(input_text, selected_languages):
     lang_prefix = f">>{lang_code}<< "
     text_with_lang = lang_prefix + input_text
     inputs = tokenizer(text_with_lang, return_tensors="pt", padding=True)
+    
+    # Generate translated tokens
     translated_tokens = model.generate(**inputs)
     translation = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
     return translation
 
 def generate_image(prompt):
+    """Generate an image based on the provided prompt."""
     API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
-    hf_token = os.getenv("HF_TOKEN")
+    hf_token = os.getenv("HF_TOKEN")  # Ensure to set this environment variable
     headers = {"Authorization": f"Bearer {hf_token}"}
     
     response = requests.post(API_URL, headers=headers, json={"inputs": prompt})
@@ -60,13 +57,17 @@ def generate_image(prompt):
         return None
 
 def generate_creative_text(translated_text):
+    """Generate creative text based on the translated sentence."""
     prompt = f"Create a creative text based on the following sentence: {translated_text}"
     inputs = gpt_neo_tokenizer(prompt, return_tensors="pt", padding=True, truncation=True, max_length=100)
+    
+    # Generate creative text
     output = gpt_neo_model.generate(inputs["input_ids"], max_length=100, do_sample=True, temperature=0.7)
     creative_text = gpt_neo_tokenizer.decode(output[0], skip_special_tokens=True)
     return creative_text
 
 def process_input(text_input, selected_languages):
+    """Process the input text: translate, generate creative text, and generate an image."""
     translated_output = translate_text(text_input, selected_languages)
     creative_text = generate_creative_text(translated_output)
     image = generate_image(translated_output)
@@ -75,12 +76,17 @@ def process_input(text_input, selected_languages):
 # Gradio interface
 interface = gr.Interface(
     fn=process_input,
-    inputs=[gr.Textbox(label="Input Text"), gr.CheckboxGroup(choices=["Tamil", "Russian", "Arabic", "Portuguese"], label="Select Language")],
-    outputs=[gr.Textbox(label="Translated Text"), gr.Textbox(label="Creative Text"), gr.Image(label="Generated Image")],
+    inputs=[
+        gr.Textbox(label="Input Text"), 
+        gr.CheckboxGroup(choices=["Tamil", "Russian", "Arabic", "Portuguese"], label="Select Language")
+    ],
+    outputs=[
+        gr.Textbox(label="Translated Text"), 
+        gr.Textbox(label="Creative Text"), 
+        gr.Image(label="Generated Image")
+    ],
     title="Multilingual Translation, Creative Text, and Image Generation",
     description="Translate Tamil, Russian, Arabic, or Portuguese text to English, generate creative text, and generate an image."
 )
 
 interface.launch()
-
-