Create app.py

app.py

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+import gradio as gr
+from TTS.api import TTS
+from transformers import T5ForConditionalGeneration, T5Tokenizer, pipeline
+import feedparser
+import re
+
+language_map = {
+    'en': 'English',
+    'fr': 'French'
+}
+
+# Add default RSS feeds
+
+rss_feed_map = {
+    "NY Times": 'https://rss.nytimes.com/services/xml/rss/nyt/HomePage.xml',
+    "Fox News": 'https://moxie.foxnews.com/google-publisher/latest.xml',
+    "Yahoo! News": 'https://www.yahoo.com/news/rss',
+    "France 24": 'https://www.france24.com/fr/rss',
+    "France Info": 'https://www.francetvinfo.fr/titres.rss'
+}
+
+def get_rss_feeds(default_choices, custom_choices):
+  custom_rss_feeds = custom_choices.split("\n")
+  if custom_rss_feeds == ['']:
+    return list(set([rss_feed_map[key] for key in default_choices]))
+  return list(set(custom_rss_feeds + [rss_feed_map[key] for key in default_choices]))
+
+# RSS feeds
+
+def is_url(string):
+    url_pattern = re.compile(
+        r'^(?:http|ftp)s?://'  # http:// or https://
+        r'(?:(?:[A-Z0-9](?:[A-Z0-9-]{0,61}[A-Z0-9])?\.)+(?:[A-Z]{2,6}\.?|[A-Z0-9-]{2,}\.?)|'  # domain...
+        r'localhost|'  # localhost...
+        r'\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3})'  # ...or ip
+        r'(?::\d+)?'  # optional port
+        r'(?:/?|[/?]\S+)$', re.IGNORECASE)
+    return re.match(url_pattern, string) is not None
+
+def fetch_news(rss_feed):
+  if not is_url(rss_feed):
+    raise ValueError(f"{rss_feed} is not a valid RSS feed.")
+  news = []
+  feed = feedparser.parse(rss_feed)
+  for entry in feed.entries:
+    news.append(entry.title)
+  return news
+
+def fetch_news_multiple_urls(rss_feeds):
+  return [news for rss_feed in rss_feeds for news in fetch_news(rss_feed)]
+
+# Language_id
+
+model_ckpt = "papluca/xlm-roberta-base-language-detection"
+pipe = pipeline("text-classification", model=model_ckpt)
+
+def language_id(strings:list[str]):
+  return [(string,language_map[pipe(string, top_k=1, truncation=True)[0]['label']]) for string in strings]
+
+# Translation
+
+## Initialize T5 model and tokenizer
+model_name = "t5-small"
+tokenizer = T5Tokenizer.from_pretrained(model_name)
+model = T5ForConditionalGeneration.from_pretrained(model_name)
+
+def translate(source_text_with_id, target_language):
+  # source_text_with_id = ('text','French') for example
+  source_language = source_text_with_id[1]
+  assert source_language in language_map.values(), f"{source_language} language is not supported."
+  assert target_language in language_map.values(), f"{target_language} language is not supported."
+
+  source_text = f"translate {source_language} to {target_language}: " + source_text_with_id[0]
+
+  # Tokenize input text
+  input_ids = tokenizer.encode(source_text, return_tensors="pt")
+
+  # Generate translation
+  translated_ids = model.generate(input_ids=input_ids, max_length=100, num_beams=4, early_stopping=True)
+
+  # Decode translated text
+  return tokenizer.decode(translated_ids[0], skip_special_tokens=True)
+
+def translate_multiple(source_texts_with_id, target_language):
+  return [translate(source_text_with_id, target_language) for source_text_with_id in source_texts_with_id]
+
+# Speech generation
+
+tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2")
+
+def read_news(text,input,output,language):
+  assert language in language_map.keys(), f"{language} language is not supported."
+  print("speech generation starting")
+  tts.tts_to_file(text=text,
+                file_path=output,
+                speaker_wav=input,
+                language=language)
+  print("speech generation done")
+  return output
+
+# Gradio interface
+
+def process(radio_value, textbox_value, audio_value, checkbox_value):
+    inputs = {
+        "language": radio_value,
+        "rss_feed_urls": textbox_value,
+        "audio": audio_value,
+        "selected_feeds": checkbox_value
+    }
+    print("Inputs to Gradio Blocks:")
+    print(inputs)
+
+    rss_feeds = get_rss_feeds(checkbox_value,textbox_value)
+    print("rss_feeds=",rss_feeds)
+
+    news = fetch_news_multiple_urls(rss_feeds)
+    print("news=",news[:2])
+
+    news_with_language_id = language_id(news)
+    print("news_with_language_id=",news_with_language_id[:2])
+
+    translated_news = translate_multiple(news_with_language_id, radio_value)
+    print("translated_news=",translated_news[:2])
+
+    language = next((key for key, val in language_map.items() if val == radio_value), None)
+    print("language=",language)
+
+    all_news = ' '.join(translated_news)
+    print("all_news=",all_news[:80])
+
+    output_path = "output.wav"
+
+    return read_news(all_news,audio_value,output_path,language)
+
+with gr.Blocks() as demo:
+    gr.Markdown("Customize your newsletter and then click **Fetch News** to download the audio output.")
+    with gr.Row():
+        radio = gr.Radio(
+            label='Choose the language of the output',
+            info="If the output language doesn't match the language of an RSS feed, an AI model will take care of translation",
+            choices=["English", "French"]
+        )
+    with gr.Row():
+        textbox = gr.Textbox(
+            placeholder='https://www.francetvinfo.fr/titres.rss',
+            label='Add custom RSS feeds to your newsletter',
+            info='The provided urls needed to be written each in a separate line'
+        )
+    with gr.Row():
+        audio = gr.Audio(
+            label="Upload a sample audio of someone speaking. The voice of the output will match the voice of the input.",
+            type='filepath'
+        )
+    with gr.Row():
+        checkboxgroup = gr.CheckboxGroup(
+            ["NY Times", "Fox News", "Yahoo! News", "France 24", "France Info"],
+            label="RSS feeds",
+            info="Default RSS feeds"
+        )
+    with gr.Row():
+        btn = gr.Button(value='Fetch News')
+    with gr.Row():
+        out = gr.DownloadButton("📂 Click to download file")
+    btn.click(
+        fn=process,
+        inputs=[radio, textbox, audio, checkboxgroup],
+        outputs=out
+    )
+
+
+demo.launch(debug=True)