Create app.py

app.py

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+import gradio as gr
+from langchain.chains import LLMChain
+from langchain.prompts import PromptTemplate
+from langchain.document_loaders import WebBaseLoader
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.llms import HuggingFacePipeline
+from transformers import pipeline
+import tempfile
+import os
+
+# Step 1: CPU-friendly summarization LLM (Flan-T5 Small)
+summary_pipe = pipeline("text2text-generation", model="google/flan-t5-base", device=-1)
+llm = HuggingFacePipeline(pipeline=summary_pipe)
+
+# Step 2: Summarization Prompt
+summary_prompt = PromptTemplate.from_template("""
+Summarize the following webpage content in a clear, concise way:
+
+{text}
+
+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
+
+        return summary, audio_path
+
+    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..."),
+    outputs=[
+        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."
+)
+
+if __name__ == "__main__":
+    iface.launch()