Update app.py

app.py

@@ -7,6 +7,8 @@ from bs4 import BeautifulSoup
 import requests
 from TTS.api import TTS
 import tempfile
+import os
+import shutil
 
 # Setup summarization LLM
 summary_pipe = pipeline("text2text-generation", model="google/flan-t5-base", device=-1)
@@ -23,17 +25,15 @@ Summary:
 
 summary_chain = LLMChain(llm=llm, prompt=summary_prompt)
 
-# TTS model setup (multi-lingual, expressive)
+# TTS model setup
 tts_model = TTS(model_name="tts_models/multilingual/multi-dataset/your_tts", progress_bar=False, gpu=False)
 
 def extract_main_content(url):
     try:
         response = requests.get(url, timeout=10)
         soup = BeautifulSoup(response.content, "html.parser")
-
         for tag in soup(["nav", "header", "footer", "aside", "script", "style", "noscript"]):
             tag.decompose()
-
         paragraphs = soup.find_all("p")
         content = "\n".join([p.get_text() for p in paragraphs if len(p.get_text()) > 60])
         return content.strip()
@@ -42,39 +42,54 @@ def extract_main_content(url):
 
 def generate_human_like_audio(text):
     try:
-        temp_path = tempfile.NamedTemporaryFile(delete=False, suffix=".wav")
-        tts_model.tts_to_file(text=text, file_path=temp_path.name)
-        return temp_path.name
+        temp_dir = tempfile.mkdtemp()
+        wav_path = os.path.join(temp_dir, "summary.wav")
+        mp3_path = os.path.join(temp_dir, "summary.mp3")
+
+        tts_model.tts_to_file(text=text, file_path=wav_path)
+
+        # Convert to mp3 for download link (requires ffmpeg in Hugging Face Spaces)
+        os.system(f"ffmpeg -y -i {wav_path} -codec:a libmp3lame -qscale:a 4 {mp3_path}")
+
+        if os.path.exists(mp3_path):
+            return wav_path, mp3_path
+        else:
+            return wav_path, None
     except Exception as e:
-        return None
+        print(f"TTS ERROR: {e}")
+        return None, None
 
 def url_to_audio_summary(url):
     try:
         article_text = extract_main_content(url)
         if article_text.startswith("Error"):
-            return article_text, None
+            return article_text, None, None
 
-        # Truncate for model's 512-token limit
         if len(article_text) > 1500:
             article_text = article_text[:1500] + "..."
-        
+
         summary = summary_chain.invoke({"text": article_text})
         summary = summary["text"] if isinstance(summary, dict) and "text" in summary else summary
 
-        audio_path = generate_human_like_audio(summary)
-        if not audio_path:
-            return summary, None
-
-        return summary, audio_path
+        wav_path, mp3_path = generate_human_like_audio(summary)
+        return summary, wav_path, mp3_path
     except Exception as e:
-        return f"Error: {str(e)}", None
+        return f"Error: {str(e)}", None, None
+
+def interface_wrapper(url):
+    summary, wav_path, mp3_path = url_to_audio_summary(url)
+    download_html = ""
+    if mp3_path and os.path.exists(mp3_path):
+        download_html = f'<a href="file/{os.path.basename(mp3_path)}" download target="_blank">Click to download MP3</a>'
+    return summary, wav_path, download_html
 
 iface = gr.Interface(
-    fn=url_to_audio_summary,
+    fn=interface_wrapper,
     inputs=gr.Textbox(label="Article URL", placeholder="Paste a news/blog URL here..."),
     outputs=[
         gr.Textbox(label="Summary"),
-        gr.Audio(label="Preacher-style Audio Summary")
+        gr.Audio(label="Preacher-style Audio Summary", type="filepath"),
+        gr.HTML(label="Download MP3")
     ],
     title="Preaching-Style URL to Audio Agent",
     description="Summarizes article content and reads it aloud in a warm, preacher-style voice using YourTTS. CPU-only."