Update app.py

app.py

@@ -4,7 +4,6 @@ import requests
 import io
 from PIL import Image
 import os
-import time
 
 # Load the translation model and tokenizer
 model_name = "facebook/mbart-large-50-many-to-one-mmt"
@@ -18,15 +17,15 @@ if hf_api_key is None:
 else:
     headers = {"Authorization": f"Bearer {hf_api_key}"}
 
-# Define the text-to-image model URL (using a stable diffusion model)
+# Define the text-to-image model URL (using a faster text-to-image model)
 API_URL = "https://api-inference.huggingface.co/models/CompVis/stable-diffusion-v1-4"
 
-# Load the text generation model for generating detailed paragraphs
-text_generation_model_name = "EleutherAI/gpt-neo-2.7B"
+# Load a smaller text generation model to reduce generation time
+text_generation_model_name = "EleutherAI/gpt-neo-1.3B"
 text_tokenizer = AutoTokenizer.from_pretrained(text_generation_model_name)
 text_model = AutoModelForCausalLM.from_pretrained(text_generation_model_name)
 
-# Create a pipeline for text generation
+# Create a pipeline for text generation using the selected model
 text_generator = pipeline("text-generation", model=text_model, tokenizer=text_tokenizer)
 
 # Function to generate an image using Hugging Face's text-to-image model
@@ -49,19 +48,19 @@ def generate_image_from_text(translated_text):
         print(f"Error during image generation: {e}")
         return None, f"Error during image generation: {e}"
 
-# Function to generate a detailed paragraph from the translated text
-def generate_paragraph_from_text(translated_text):
+# Function to generate a shorter paragraph based on the translated text
+def generate_short_paragraph_from_text(translated_text):
     try:
-        print(f"Generating paragraph from translated text: {translated_text}")
-        # Generate detailed text from translated text using the text generation model
-        paragraph = text_generator(translated_text, max_length=250, num_return_sequences=1, temperature=0.7, top_p=0.9)[0]['generated_text']
+        print(f"Generating a short paragraph from translated text: {translated_text}")
+        # Generate a shorter paragraph from the translated text using smaller settings
+        paragraph = text_generator(translated_text, max_length=100, num_return_sequences=1, temperature=0.7, top_p=0.8)[0]['generated_text']
         print(f"Paragraph generation completed: {paragraph}")
         return paragraph
     except Exception as e:
         print(f"Error during paragraph generation: {e}")
         return f"Error during paragraph generation: {e}"
 
-# Define the function to translate Tamil text, generate a paragraph, and create an image
+# Define the function to translate Tamil text, generate a short paragraph, and create an image
 def translate_generate_paragraph_and_image(tamil_text):
     # Step 1: Translate Tamil text to English using mbart-large-50
     try:
@@ -74,8 +73,8 @@ def translate_generate_paragraph_and_image(tamil_text):
     except Exception as e:
         return f"Error during translation: {e}", "", None, None
 
-    # Step 2: Generate a detailed paragraph based on the translated English text
-    paragraph = generate_paragraph_from_text(translated_text)
+    # Step 2: Generate a shorter paragraph based on the translated English text
+    paragraph = generate_short_paragraph_from_text(translated_text)
     if "Error" in paragraph:
         return translated_text, paragraph, None, None
 
@@ -91,11 +90,11 @@ iface = gr.Interface(
     fn=translate_generate_paragraph_and_image,
     inputs=gr.Textbox(lines=2, placeholder="Enter Tamil text here..."),
     outputs=[gr.Textbox(label="Translated English Text"), 
-             gr.Textbox(label="Generated Descriptive Paragraph"),
+             gr.Textbox(label="Generated Short Paragraph"),
              gr.Image(label="Generated Image")],
-    title="Tamil to English Translation, Paragraph Generation, and Image Creation",
-    description="Translate Tamil text to English using Facebook's mbart-large-50 model, generate a detailed paragraph, and create an image using the translated text.",
+    title="Tamil to English Translation, Short Paragraph Generation, and Image Creation",
+    description="Translate Tamil text to English using Facebook's mbart-large-50 model, generate a short paragraph, and create an image using the translated text.",
 )
 
 # Launch Gradio app without `share=True`
-iface.launch()
+iface.launch()