Create app.py

app.py

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+import gradio as gr
+import assemblyai as aai
+from anthropic import Anthropic
+import os
+from pydub import AudioSegment
+import tempfile
+
+# Initialize API clients
+aai.settings.api_key = os.getenv("AAI_KEY")
+anthropic = Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))
+model_name = "claude-3-5-sonnet-20240620"
+
+# Default prompts from the initial Python file
+DEFAULT_TITLE_PROMPT = """
+Suggest a title for the podcast episode
+Dwarkesh is the host, not the guest.
+The format should be:
+Guest Name - Title
+
+Make it sexy! Enticing! No boilerplate!!
+
+Don't output anything but the suggested podcast title. Don't use hashtags or Emojis. Titles should be around 80 characters long. The best titles take a number of ideas from the episode
+
+Here are some examples of previous podcast episode titles:
+
+Patrick Collison (Stripe CEO) - Craft, Beauty, & The Future of Payments
+Tyler Cowen - Hayek, Keynes, & Smith on AI, Animal Spirits, Anarchy, & Growth
+Jung Chang - Living through Cultural Revolution and the Crimes of Mao
+Andrew Roberts - SV's Napoleon Cult, Why Hitler Lost WW2, Churchill as Applied Historian
+Dominic Cummings - COVID, Brexit, & Fixing Western Governance
+Paul Christiano - Preventing an AI Takeover
+Shane Legg (DeepMind Founder) - 2028 AGI, New Architectures, Aligning Superhuman Models
+Grant Sanderson (3Blue1Brown) - Past, Present, & Future of Mathematics
+Sarah C. M. Paine - WW2, Taiwan, Ukraine, & Maritime vs Continental Powers
+Dario Amodei (Anthropic CEO) - Scaling, Alignment, & AI Progress
+Francois Chollet - LLMs won’t lead to AGI - $1,000,000 Prize to find true solution
+Leopold Aschenbrenner - 2027 AGI, China/US Super-Intelligence Race, & The Return of History
+John Schulman (OpenAI Cofounder) - Reasoning, RLHF, & Plan for 2027 AGI
+
+Come up with a title for the following transcript using guidance above.
+
+Come up 10 titles, each on a new line, so I can select the best one.
+Titles:
+"""
+
+DEFAULT_CLIP_PROMPT = """
+Suggest some best portions of these episodes to make clips of.
+Format this as "Aprox Timestamp: ____ - ____ || Title: "
+
+Clips should be the most intriguing and critical parts of the episode. They should start right at the action and end once the topic has been resolved. They should be
+2-10 minutes in length. Good clips often feature debate, appealing rhetoric, core ideas, intresting stories, or counterintuitve facts.
+
+Titles should be your 2-10 word description of what is in the clip. e.g: AGI Timelines debate, Lee Kuan Yu's best choices, Why LLMs are enough for AGI, etc.
+
+Example Output: Aprox Timestamp: 1:10 - 5:12 || Title: The Million Dollar Prize for AGI
+"""
+
+
+def transcribe_audio(audio_file):
+    # Handle both file objects and file paths
+    if isinstance(audio_file, str):
+        audio_path = audio_file
+    else:
+        audio_path = audio_file.name
+
+    # Convert audio to MP3 if it's not already
+    with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as temp_file:
+        audio = AudioSegment.from_file(audio_path)
+        audio.export(temp_file.name, format="mp3")
+
+        # Transcribe the audio file
+        transcriber = aai.Transcriber()
+        transcript = transcriber.transcribe(
+            temp_file.name, config=aai.TranscriptionConfig(speaker_labels=True)
+        )
+
+    # Format the transcript
+    formatted_transcript = ""
+    for utterance in transcript.utterances:
+        formatted_transcript += f"{utterance.speaker} {format_timestamp(utterance.start)}\n{utterance.text}\n\n"
+
+    return formatted_transcript
+
+
+def format_timestamp(milliseconds):
+    seconds = int(milliseconds / 1000)
+    minutes, seconds = divmod(seconds, 60)
+    hours, minutes = divmod(minutes, 60)
+    return f"{hours:02d}:{minutes:02d}:{seconds:02d}"
+
+
+def generate_titles(transcript, prompt):
+    message = anthropic.messages.create(
+        model=model_name,
+        max_tokens=1024,
+        messages=[
+            {"role": "user", "content": f"{prompt}\n\nTranscript:\n{transcript}"},
+        ],
+    )
+    return message.content[0].text
+
+
+def generate_clips(transcript, prompt):
+    message = anthropic.messages.create(
+        model=model_name,
+        max_tokens=1024,
+        messages=[
+            {"role": "user", "content": f"{prompt}\n\nTranscript:\n{transcript}"},
+        ],
+    )
+    return message.content[0].text
+
+
+def process_transcript(audio_file):
+    transcript = transcribe_audio(audio_file)
+
+    # Save transcript to a temporary file
+    with tempfile.NamedTemporaryFile(
+        mode="w", delete=False, suffix=".txt"
+    ) as temp_file:
+        temp_file.write(transcript)
+        temp_file_path = temp_file.name
+
+    return transcript, temp_file_path
+
+
+def process_title_and_clips(transcript, title_prompt, clip_prompt):
+    titles = generate_titles(transcript, title_prompt)
+    clips = generate_clips(transcript, clip_prompt)
+    return titles, clips
+
+
+# Define the Gradio interface
+with gr.Blocks() as app:
+    gr.Markdown("# Podcast Helper")
+
+    # with gr.Row():
+    audio_input = gr.Audio(type="filepath", label="Upload MP3")
+    transcribe_button = gr.Button("Generate Transcript")
+
+    with gr.Row():
+        transcript_output = gr.Textbox(label="Transcript", lines=10)
+        transcript_file = gr.File(label="Download Transcript")
+
+    with gr.Row():
+        title_prompt = gr.Textbox(
+            label="Title Generation Prompt", lines=3, value=DEFAULT_TITLE_PROMPT
+        )
+        clip_prompt = gr.Textbox(
+            label="Clip Search Prompt", lines=3, value=DEFAULT_CLIP_PROMPT
+        )
+
+    generate_button = gr.Button("Generate Title and Clips")
+
+    with gr.Row():
+        titles_output = gr.Textbox(label="Generated Titles", lines=10)
+        clips_output = gr.Textbox(label="Generated Clips", lines=10)
+
+    transcribe_button.click(
+        process_transcript,
+        inputs=[audio_input],
+        outputs=[transcript_output, transcript_file],
+    )
+
+    generate_button.click(
+        process_title_and_clips,
+        inputs=[transcript_output, title_prompt, clip_prompt],
+        outputs=[titles_output, clips_output],
+    )
+
+# Launch the app
+if __name__ == "__main__":
+    app.launch()