Update app.py

app.py

@@ -5,14 +5,15 @@ from langchain.document_loaders import WebBaseLoader
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.llms import HuggingFacePipeline
 from transformers import pipeline
+from gtts import gTTS
 import tempfile
 import os
 
-# Step 1: CPU-friendly summarization LLM (Flan-T5 Small)
+# CPU-friendly summarization LLM
 summary_pipe = pipeline("text2text-generation", model="google/flan-t5-base", device=-1)
 llm = HuggingFacePipeline(pipeline=summary_pipe)
 
-# Step 2: Summarization Prompt
+# Summarization prompt
 summary_prompt = PromptTemplate.from_template("""
 Summarize the following webpage content in a clear, concise way:
 
@@ -23,36 +24,26 @@ Summary:
 
 summary_chain = LLMChain(llm=llm, prompt=summary_prompt)
 
-# Step 3: URL to Text -> Summarize -> Text to Speech
-
 def url_to_audio_summary(url):
     try:
-        # Load and split text
         loader = WebBaseLoader(url)
         docs = loader.load()
         splitter = RecursiveCharacterTextSplitter(chunk_size=2000, chunk_overlap=100)
         splits = splitter.split_documents(docs)
-        
+
         full_text = "\n".join([s.page_content for s in splits])
-        
-        # Summarize
         summary = summary_chain.run(text=full_text)
 
-        # Text to Speech
-        tts_pipe = pipeline("text-to-speech", model="espnet/kan-bayashi_ljspeech_vits", device=-1)
-        audio = tts_pipe(summary)["audio"]
-
-        # Save audio to temp WAV
-        with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as f:
-            f.write(audio)
-            audio_path = f.name
+        # Use gTTS for TTS since Hugging Face TTS model failed
+        tts = gTTS(text=summary)
+        temp_path = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
+        tts.save(temp_path.name)
 
-        return summary, audio_path
+        return summary, temp_path.name
 
     except Exception as e:
         return f"Error: {str(e)}", None
 
-# Step 4: Gradio Interface
 iface = gr.Interface(
     fn=url_to_audio_summary,
     inputs=gr.Textbox(label="Article URL", placeholder="Paste a news/blog URL here..."),
@@ -60,8 +51,8 @@ iface = gr.Interface(
         gr.Textbox(label="Summary"),
         gr.Audio(label="Audio Summary")
     ],
-    title="🗣️ URL to Audio Summary Agent",
-    description="An agent that reads web articles and gives you an audio summary. CPU-only. Built with LangChain + Hugging Face."
+    title="URL to Audio Summary Agent",
+    description="Summarizes article from a URL and gives an audio summary. CPU-only using gTTS."
 )
 
 if __name__ == "__main__":