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Update app.py
Browse files
app.py
CHANGED
@@ -56,7 +56,7 @@ def convert_to_wav(audio_data: bytes, mime_type: str) -> bytes:
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return header + audio_data
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def parse_audio_mime_type(mime_type: str) -> dict
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"""Parses bits per sample and rate from an audio MIME type string."""
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bits_per_sample = 16
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rate = 24000
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@@ -79,10 +79,11 @@ def parse_audio_mime_type(mime_type: str) -> dict[str, int | None]:
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return {"bits_per_sample": bits_per_sample, "rate": rate}
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def fetch_web_content(url, progress=
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"""Fetch and analyze web content using Gemini with tools."""
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try:
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progress
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logger.info("Initializing Gemini client...")
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if not GEMINI_API_KEY:
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@@ -90,10 +91,11 @@ def fetch_web_content(url, progress=gr.Progress()):
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client = genai.Client(api_key=GEMINI_API_KEY)
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progress
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logger.info(f"Fetching content from URL: {url}")
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model = "gemini-2.
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contents = [
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types.Content(
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role="user",
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@@ -118,7 +120,8 @@ def fetch_web_content(url, progress=gr.Progress()):
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response_mime_type="text/plain",
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)
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progress
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logger.info("Generating content with Gemini...")
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content_text = ""
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if chunk.text:
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content_text += chunk.text
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progress
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logger.info(f"Content generation complete. Length: {len(content_text)} characters")
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return content_text
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@@ -139,10 +143,11 @@ def fetch_web_content(url, progress=gr.Progress()):
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raise e
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def generate_podcast_from_content(content_text, speaker1_name="Anna Chope", speaker2_name="Adam Chan", progress=
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"""Generate audio podcast from text content."""
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try:
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progress
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logger.info("Starting audio generation...")
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if not GEMINI_API_KEY:
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@@ -150,7 +155,7 @@ def generate_podcast_from_content(content_text, speaker1_name="Anna Chope", spea
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client = genai.Client(api_key=GEMINI_API_KEY)
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model = "gemini-2.
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podcast_prompt = f"""Please read aloud the following content in a natural podcast interview style with two distinct speakers.
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Make it sound conversational and engaging:
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@@ -197,7 +202,8 @@ def generate_podcast_from_content(content_text, speaker1_name="Anna Chope", spea
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),
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)
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progress
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logger.info("Generating audio stream...")
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# Create temporary file
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@@ -235,7 +241,8 @@ def generate_podcast_from_content(content_text, speaker1_name="Anna Chope", spea
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# For simplicity, just use the first chunk (you might want to concatenate them)
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final_audio = audio_chunks[0]
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save_binary_file(temp_file.name, final_audio)
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progress
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logger.info(f"Audio file saved: {temp_file.name}")
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return temp_file.name
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else:
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@@ -246,10 +253,11 @@ def generate_podcast_from_content(content_text, speaker1_name="Anna Chope", spea
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raise e
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def generate_web_podcast(url, speaker1_name, speaker2_name, progress=
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"""Main function to fetch web content and generate podcast."""
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try:
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progress
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logger.info(f"Starting podcast generation for URL: {url}")
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# Validate inputs
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@@ -285,106 +293,102 @@ def generate_web_podcast(url, speaker1_name, speaker2_name, progress=gr.Progress
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# Create Gradio interface
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def create_interface():
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lines=1
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)
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audio_output = gr.Audio(label="Generated Podcast", type="filepath")
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with gr.Accordion("📝 Generated Script Preview", open=False):
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script_output = gr.Textbox(
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label="Podcast Script",
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lines=10,
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interactive=False,
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info="Preview of the conversation script generated from the website content"
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)
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# Event handlers
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generate_btn.click(
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fn=generate_web_podcast,
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inputs=[url_input, speaker1_input, speaker2_input],
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outputs=[audio_output, status_output, script_output],
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show_progress=True
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)
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# Examples
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gr.Examples(
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examples=[
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["https://github.com/weaviate/weaviate", "Anna", "Adam"],
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["https://huggingface.co/blog", "Sarah", "Mike"],
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["https://openai.com/blog", "Emma", "John"],
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],
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inputs=[url_input, speaker1_input, speaker2_input],
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)
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gr.Markdown("""
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---
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**Note:** API key is now directly embedded in the code for convenience.
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The generated podcast will feature two AI voices having a natural conversation about the website content.
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""")
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logger.error(f"Error creating interface: {e}")
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raise e
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if __name__ == "__main__":
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return header + audio_data
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def parse_audio_mime_type(mime_type: str) -> dict:
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"""Parses bits per sample and rate from an audio MIME type string."""
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bits_per_sample = 16
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rate = 24000
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return {"bits_per_sample": bits_per_sample, "rate": rate}
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def fetch_web_content(url, progress=None):
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"""Fetch and analyze web content using Gemini with tools."""
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try:
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if progress:
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progress(0.1, desc="Initializing Gemini client...")
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logger.info("Initializing Gemini client...")
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if not GEMINI_API_KEY:
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client = genai.Client(api_key=GEMINI_API_KEY)
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if progress:
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progress(0.2, desc="Fetching web content...")
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logger.info(f"Fetching content from URL: {url}")
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model = "gemini-2.0-flash-exp" # Updated model name
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contents = [
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types.Content(
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role="user",
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response_mime_type="text/plain",
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)
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if progress:
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progress(0.4, desc="Analyzing content with AI...")
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logger.info("Generating content with Gemini...")
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content_text = ""
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if chunk.text:
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content_text += chunk.text
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if progress:
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progress(0.6, desc="Content analysis complete!")
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logger.info(f"Content generation complete. Length: {len(content_text)} characters")
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return content_text
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raise e
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def generate_podcast_from_content(content_text, speaker1_name="Anna Chope", speaker2_name="Adam Chan", progress=None):
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"""Generate audio podcast from text content."""
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try:
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if progress:
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progress(0.7, desc="Generating podcast audio...")
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logger.info("Starting audio generation...")
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if not GEMINI_API_KEY:
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client = genai.Client(api_key=GEMINI_API_KEY)
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model = "gemini-2.0-flash-exp" # Updated model name
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podcast_prompt = f"""Please read aloud the following content in a natural podcast interview style with two distinct speakers.
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Make it sound conversational and engaging:
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),
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)
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if progress:
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progress(0.8, desc="Converting to audio...")
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logger.info("Generating audio stream...")
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# Create temporary file
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# For simplicity, just use the first chunk (you might want to concatenate them)
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final_audio = audio_chunks[0]
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save_binary_file(temp_file.name, final_audio)
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if progress:
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progress(1.0, desc="Podcast generated successfully!")
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logger.info(f"Audio file saved: {temp_file.name}")
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return temp_file.name
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else:
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raise e
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def generate_web_podcast(url, speaker1_name, speaker2_name, progress=None):
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"""Main function to fetch web content and generate podcast."""
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try:
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if progress:
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progress(0.0, desc="Starting podcast generation...")
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logger.info(f"Starting podcast generation for URL: {url}")
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# Validate inputs
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# Create Gradio interface
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def create_interface():
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"""Create and return the Gradio interface."""
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with gr.Blocks(
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title="🎙️ Web-to-Podcast Generator",
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theme=gr.themes.Soft(),
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analytics_enabled=False
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) as demo:
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gr.Markdown("""
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# 🎙️ Web-to-Podcast Generator
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Transform any website into an engaging podcast conversation between two AI hosts!
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Simply paste a URL and let AI create a natural dialogue discussing the content.
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""")
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with gr.Row():
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with gr.Column(scale=2):
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url_input = gr.Textbox(
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label="Website URL",
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placeholder="https://example.com",
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info="Enter the URL of the website you want to convert to a podcast",
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lines=1
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)
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with gr.Row():
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speaker1_input = gr.Textbox(
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label="Host 1 Name",
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value="Anna Chope",
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info="Name of the first podcast host",
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lines=1
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)
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speaker2_input = gr.Textbox(
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label="Host 2 Name",
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value="Adam Chan",
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info="Name of the second podcast host",
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lines=1
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)
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generate_btn = gr.Button("🎙️ Generate Podcast", variant="primary", size="lg")
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with gr.Column(scale=1):
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gr.Markdown("""
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### Instructions:
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1. Enter a website URL
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2. Customize host names (optional)
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3. Click "Generate Podcast"
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4. Wait for the AI to analyze content and create audio
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5. Download your podcast!
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### Examples:
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- News articles
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- Blog posts
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- Product pages
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- Documentation
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- Research papers
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""")
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with gr.Row():
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status_output = gr.Textbox(label="Status", interactive=False, lines=2)
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with gr.Row():
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audio_output = gr.Audio(label="Generated Podcast", type="filepath")
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with gr.Accordion("📝 Generated Script Preview", open=False):
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script_output = gr.Textbox(
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label="Podcast Script",
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lines=10,
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interactive=False,
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info="Preview of the conversation script generated from the website content"
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)
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# Event handlers
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generate_btn.click(
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fn=generate_web_podcast,
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inputs=[url_input, speaker1_input, speaker2_input],
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outputs=[audio_output, status_output, script_output],
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show_progress=True
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)
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# Examples
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gr.Examples(
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examples=[
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["https://github.com/weaviate/weaviate", "Anna", "Adam"],
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["https://huggingface.co/blog", "Sarah", "Mike"],
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["https://openai.com/blog", "Emma", "John"],
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],
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inputs=[url_input, speaker1_input, speaker2_input],
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)
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gr.Markdown("""
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---
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**Note:** API key is now directly embedded in the code for convenience.
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The generated podcast will feature two AI voices having a natural conversation about the website content.
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""")
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return demo
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if __name__ == "__main__":
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