Update app.py

app.py

@@ -1,4 +1,4 @@
-from transformers import pipeline
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
 from datasets import load_dataset
 import gradio as gr
 import torch
@@ -11,10 +11,12 @@ Generate a poetry in Arabic.
 pipe_ar = pipeline('text-generation', framework='pt', model='akhooli/ap2023', tokenizer='akhooli/ap2023')
 
 """### **English: Text-Generation:**
-Generate a poetry in English.
+Generate a poetry in English using GPT-2 Poet model with AutoTokenizer and AutoModelForCausalLM.
 """
 
-pipe_en = pipeline("text-generation", model="ashiqabdulkhader/GPT2-Poet", from_tf=True)
+# Load the tokenizer and model for the GPT-2 poetry model
+tokenizer_en = AutoTokenizer.from_pretrained("ashiqabdulkhader/GPT2-Poet")
+model_en = AutoModelForCausalLM.from_pretrained("ashiqabdulkhader/GPT2-Poet")
 
 """### **Arabic and English: Text-To-Speech:**
 Convert the Arabic/English poetry to speech.
@@ -54,149 +56,14 @@ This function will receive 2 inputs from the Gradio interface, and execute the f
 def generate_poem(selected_language, text):
     try:
         if selected_language == "English":
-            poem = generate_poem_english(text) # Return the generated poem from the generate_poem_english function
-            sampling_rate, audio_data = text_to_speech_english(poem) # Return the audio from the text_to_speech_english function
-            image = generate_image_from_poem(text) # Return the image from the generate_image_from_poem function
+            poem = generate_poem_english(text)  # Return the generated poem from the generate_poem_english function
+            sampling_rate, audio_data = text_to_speech_english(poem)  # Return the audio from the text_to_speech_english function
+            image = generate_image_from_poem(poem)  # Return the image from the generate_image_from_poem function
         elif selected_language == "Arabic":
-            poem = generate_poem_arabic(text) # Return the generated poem from the generate_poem_arabic function
-            sampling_rate, audio_data = text_to_speech_arabic(poem) # Return the audio from the text_to_speech_arabic function
-            translated_text = translate_arabic_to_english(text) # Return the translated poem from Arabic to English
-            image = generate_image_from_poem(translated_text) # Return the image from the generate_image_from_poem function
+            poem = generate_poem_arabic(text)  # Return the generated poem from the generate_poem_arabic function
+            sampling_rate, audio_data = text_to_speech_arabic(poem)  # Return the audio from the text_to_speech_arabic function
+            translated_text = translate_arabic_to_english(poem)  # Return the translated poem from Arabic to English
+            image = generate_image_from_poem(translated_text)  # Return the image from the generate_image_from_poem function
 
         return poem, (sampling_rate, audio_data), image
-    except Exception as e:
-        return f"Error: {str(e)}", None, None
-
-"""### **Poem Generation Function:**
-This function is responsible for generating a poem (text) in Arabic or English, based on the provided text.
-"""
-
-# Poem generation for Arabic
-def generate_poem_arabic(text):
-    temp = 1.0
-    topk = 50
-    topp = 0.9
-    penalty = 1.2
-    generated_text = pipe_ar(text, max_length=96, do_sample=True, temperature=temp, top_k=topk, top_p=topp, repetition_penalty=penalty,
-                             min_length=64, no_repeat_ngram_size=3, return_full_text=True,
-                             num_beams=5, num_return_sequences=1)[0]["generated_text"]
-    clean_text = generated_text.replace("-", "") # To get rid of the dashes generated by the model.
-    return clean_text
-
-# Poem generation for English
-def generate_poem_english(text):
-    generated_text = pipe_en(text, do_sample=True, max_length=100, top_k=50, top_p=0.9, temperature=1.0, num_return_sequences=3)[0]['generated_text']
-    clean_text = generated_text.replace("</s>", "") # To get rid of the </s> generated by the model.
-    return clean_text
-
-"""### **Audio Function:**
-This function is responsible for generating audio in Arabic or English, based on the provided text.
-"""
-
-# Text-to-speech conversion for Arabic
-def text_to_speech_arabic(text):
-    speech = synthesiser_arabic(text, forward_params={"speaker_embeddings": speaker_embedding_arabic})
-    audio_data = speech["audio"]
-    sampling_rate = speech["sampling_rate"]
-    return (sampling_rate, audio_data)
-
-# Text-to-speech conversion for English
-def text_to_speech_english(text):
-    speech = synthesiser_english(text, forward_params={"speaker_embeddings": speaker_embedding_english})
-    audio_data = speech["audio"]
-    sampling_rate = speech["sampling_rate"]
-    return (sampling_rate, audio_data)
-
-"""### **Image Function:**
-This function is responsible for generating an image based on the provided text.
-"""
-
-# Image generation function
-def generate_image_from_poem(poem_text):
-    image = pipe_image(poem_text).images[0]
-    return image
-
-"""### **Translation Function:**
-This function is responsible for translating Arabic input to English, to be used for the image function, which accepts only English inputs.
-"""
-
-# Translation function from Arabic to English
-def translate_arabic_to_english(text):
-    translated_text = pipe_translator(text)[0]['translation_text']
-    return translated_text
-
-"""### **CSS Styling:**"""
-
-custom_css = """
-body {
-    background-color: #f4f4f9;
-    color: #333;
-}
-.gradio-container {
-    border-radius: 10px;
-    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
-    background-color: #fff;
-}
-label {
-    color: #4A90E2;
-    font-weight: bold;
-}
-
-input[type="text"],
-textarea {
-    border: 1px solid #4A90E2;
-}
-textarea {
-    height: 150px;
-}
-
-button {
-    background-color: #4A90E2;
-    color: #fff;
-    border-radius: 5px;
-    cursor: pointer;
-}
-button:hover {
-    background-color: #357ABD;
-}
-
-.dropdown {
-    border: 1px solid #4A90E2;
-    border-radius: 4px;
-}
-
-"""
-
-"""### **Examples for Gradio:**
-Provide 4 predefined inputs to demonstrate how the interface works.
-"""
-
-examples = [
-    # First parameter is for the dropdown menu, and the second parameter is for the starter of the poem
-    ["English", "The shining sun rises over the calm ocean"],
-    ["Arabic", "الورود تتفتح في الربيع"],
-    ["English", "The night sky is filled with stars and dreams"],
-    ["Arabic", "اشعة الشمس المشرقة"]
-]
-
-"""### **Gradio Interface:**
-Creating a Gradio interface to generate a poem, read the poem, and generate an image based on that poem.
-"""
-
-my_model = gr.Interface(
-    fn=generate_poem,  # The primary function that will receive the inputs (language and the starter of the poem)
-    inputs=[
-        gr.Dropdown(["English", "Arabic"], label="Select Language"), # Dropdown menu to select the language, either "English" or "Arabic"
-        gr.Textbox(label="Enter a sentence")  # Textbox where the user will input a sentence or phrase to generate the poem
-    ],
-
-    outputs=[
-        gr.Textbox(label="Generated Poem", lines=10),  # Textbox to display the generated poem
-        gr.Audio(label="Generated Audio", type="numpy"),  # Audio output for the generated poem
-        gr.Image(label="Generated Image")  # Image output for the generated image
-    ],
-
-    examples=examples,  # Predefined examples to guide the user
-    css=custom_css  # Applying custom CSS
-)
-my_model.launch()
+    except Exc