Update app.py

app.py

@@ -14,7 +14,7 @@ pipe_ar = pipeline('text-generation', framework='pt', model='akhooli/ap2023', to
 Generate a poetry in English.
 """
 
-pipe_en = pipeline("text-generation", model="ashiqabdulkhader/GPT2-Poet", from_tf=True)
+pipe_en = pipeline("text-generation", model="ismaelfaro/gpt2-poems.en")
 
 """### **Arabic and English: Text-To-Speech:**
 Convert the Arabic/English poetry to speech.
@@ -50,18 +50,17 @@ This function will receive 2 inputs from the Gradio interface, and execute the f
 3. The image.
 """
 
-# Generate poem based on language and convert it to audio and image
 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)
+            sampling_rate, audio_data = text_to_speech_english(poem)
+            image = generate_image_from_poem(text)
         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)
+            sampling_rate, audio_data = text_to_speech_arabic(poem)
+            translated_text = translate_arabic_to_english(text)
+            image = generate_image_from_poem(translated_text)
 
         return poem, (sampling_rate, audio_data), image
     except Exception as e:
@@ -77,32 +76,49 @@ def generate_poem_arabic(text):
     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.
+    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.
+    generated_text = pipe_en(
+        text,
+        do_sample=True,
+        max_length=100,
+        top_k=50,
+        top_p=0.9,
+        temperature=1.0,
+        num_return_sequences=1
+    )[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})
+    speech = synthesiser_arabic(text, 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})
+    speech = synthesiser_english(text, speaker_embeddings=speaker_embedding_english)
     audio_data = speech["audio"]
     sampling_rate = speech["sampling_rate"]
     return (sampling_rate, audio_data)
@@ -111,7 +127,6 @@ def text_to_speech_english(text):
 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
@@ -120,7 +135,6 @@ def generate_image_from_poem(poem_text):
 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
@@ -164,7 +178,6 @@ button:hover {
     border: 1px solid #4A90E2;
     border-radius: 4px;
 }
-
 """
 
 """### **Examples for Gradio:**
@@ -172,11 +185,10 @@ 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"]
+    ["Arabic", "أشعة الشمس المشرقة"]
 ]
 
 """### **Gradio Interface:**
@@ -184,19 +196,17 @@ Creating a Gradio interface to generate a poem, read the poem, and generate an i
 """
 
 my_model = gr.Interface(
-    fn=generate_poem,  # The primary function that will receive the inputs (language and the starter of the poem)
+    fn=generate_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
+        gr.Dropdown(["English", "Arabic"], label="Select Language"),
+        gr.Textbox(label="Enter a sentence")
     ],
-
     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
+        gr.Textbox(label="Generated Poem", lines=10),
+        gr.Audio(label="Generated Audio", type="numpy"),
+        gr.Image(label="Generated Image")
     ],
-
-    examples=examples,  # Predefined examples to guide the user
-    css=custom_css  # Applying custom CSS
+    examples=examples,
+    css=custom_css
 )
-my_model.launch()
+my_model.launch()