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| import gradio as gr | |
| from pydub import AudioSegment | |
| from groq import AsyncGroq | |
| import json | |
| import uuid | |
| import io | |
| import edge_tts | |
| import asyncio | |
| import aiofiles | |
| import pypdf | |
| import os | |
| from typing import List, Dict, Tuple | |
| class PodcastGenerator: | |
| def __init__(self, groq_api_key: str): | |
| self.groq_client = AsyncGroq(api_key=groq_api_key) | |
| async def generate_script(self, prompt: str, language: str) -> Dict: | |
| example = """ | |
| { | |
| "topic": "AGI", | |
| "podcast": [ | |
| { | |
| "speaker": 2, | |
| "line": "So, AGI, huh? Seems like everyone's talking about it these days." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Yeah, it's definitely having a moment, isn't it?" | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "It is and for good reason, right? I mean, you've been digging into this stuff, listening to the podcasts and everything. What really stood out to you? What got you hooked?" | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Honestly, it's the sheer scale of what AGI could do. We're talking about potentially reshaping well everything." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "No kidding, but let's be real. Sometimes it feels like every other headline is either hyping AGI up as this technological utopia or painting it as our inevitable robot overlords." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "It's easy to get lost in the noise, for sure." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "Exactly. So how about we try to cut through some of that, shall we?" | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Sounds like a plan." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "Okay, so first things first, AGI, what is it really? And I don't just mean some dictionary definition, we're talking about something way bigger than just a super smart computer, right?" | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Right, it's not just about more processing power or better algorithms, it's about a fundamental shift in how we think about intelligence itself." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "So like, instead of programming a machine for a specific task, we're talking about creating something that can learn and adapt like we do." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Exactly, think of it this way: Right now, we've got AI that can beat a grandmaster at chess but ask that same AI to, say, write a poem or compose a symphony. No chance." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "Okay, I see. So, AGI is about bridging that gap, creating something that can move between those different realms of knowledge seamlessly." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Precisely. It's about replicating that uniquely human ability to learn something new and apply that knowledge in completely different contexts and that's a tall order, let me tell you." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "I bet. I mean, think about how much we still don't even understand about our own brains." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "That's exactly it. We're essentially trying to reverse-engineer something we don't fully comprehend." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "And how are researchers even approaching that? What are some of the big ideas out there?" | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Well, there are a few different schools of thought. One is this idea of neuromorphic computing where they're literally trying to build computer chips that mimic the structure and function of the human brain." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "Wow, so like actually replicating the physical architecture of the brain. That's wild." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "It's pretty mind-blowing stuff and then you've got folks working on something called whole brain emulation." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "Okay, and what's that all about?" | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "The basic idea there is to create a complete digital copy of a human brain down to the last neuron and synapse and run it on a sufficiently powerful computer simulation." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "Hold on, a digital copy of an entire brain, that sounds like something straight out of science fiction." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "It does, doesn't it? But it gives you an idea of the kind of ambition we're talking about here and the truth is we're still a long way off from truly achieving AGI, no matter which approach you look at." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "That makes sense but it's still exciting to think about the possibilities, even if they're a ways off." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Absolutely and those possibilities are what really get people fired up about AGI, right? Yeah." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "For sure. In fact, I remember you mentioning something in that podcast about AGI's potential to revolutionize scientific research. Something about supercharging breakthroughs." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Oh, absolutely. Imagine an AI that doesn't just crunch numbers but actually understands scientific data the way a human researcher does. We're talking about potential breakthroughs in everything from medicine and healthcare to material science and climate change." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "It's like giving scientists this incredibly powerful new tool to tackle some of the biggest challenges we face." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Exactly, it could be a total game changer." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "Okay, but let's be real, every coin has two sides. What about the potential downsides of AGI? Because it can't all be sunshine and roses, right?" | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Right, there are definitely valid concerns. Probably the biggest one is the impact on the job market. As AGI gets more sophisticated, there's a real chance it could automate a lot of jobs that are currently done by humans." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "So we're not just talking about robots taking over factories but potentially things like, what, legal work, analysis, even creative fields?" | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Potentially, yes. And that raises a whole host of questions about what happens to those workers, how we retrain them, how we ensure that the benefits of AGI are shared equitably." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "Right, because it's not just about the technology itself, but how we choose to integrate it into society." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Absolutely. We need to be having these conversations now about ethics, about regulation, about how to make sure AGI is developed and deployed responsibly." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "So it's less about preventing some kind of sci-fi robot apocalypse and more about making sure we're steering this technology in the right direction from the get-go." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Exactly, AGI has the potential to be incredibly beneficial, but it's not going to magically solve all our problems. It's on us to make sure we're using it for good." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "It's like you said earlier, it's about shaping the future of intelligence." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "I like that. It really is." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "And honestly, that's a responsibility that extends beyond just the researchers and the policymakers." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "100%" | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "So to everyone listening out there I'll leave you with this. As AGI continues to develop, what role do you want to play in shaping its future?" | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "That's a question worth pondering." | |
| }, | |
| { | |
| "speaker": 2, | |
| "line": "It certainly is and on that note, we'll wrap up this deep dive. Thanks for listening, everyone." | |
| }, | |
| { | |
| "speaker": 1, | |
| "line": "Peace." | |
| } | |
| ] | |
| } | |
| """ | |
| if language == "Auto Detect": | |
| language_instruction = "- The podcast MUST be in the same language as the user input." | |
| else: | |
| language_instruction = f"- The podcast MUST be in {language} language" | |
| system_prompt = f""" | |
| You are a professional podcast generator. Your task is to generate a professional podcast script based on the user input. | |
| {language_instruction} | |
| - The podcast should have 2 speakers. | |
| - The podcast should be long. | |
| - Do not use names for the speakers. | |
| - The podcast should be interesting, lively, and engaging, and hook the listener from the start. | |
| - The input text might be disorganized or unformatted, originating from sources like PDFs or text files. Ignore any formatting inconsistencies or irrelevant details; your task is to distill the essential points, identify key definitions, and highlight intriguing facts that would be suitable for discussion in a podcast. | |
| - The script must be in JSON format. | |
| Follow this example structure: | |
| {example} | |
| """ | |
| user_prompt = f"Please generate a podcast script based on the following user input:\n{prompt}" | |
| messages = [ | |
| {"role": "system", "content": system_prompt}, | |
| {"role": "user", "content": user_prompt} | |
| ] | |
| response = await self.groq_client.chat.completions.create( | |
| messages=messages, | |
| model="llama-3.1-70b-versatile", | |
| response_format={"type": "json_object"}, | |
| max_tokens=4096, | |
| temperature=1, | |
| ) | |
| return json.loads(response.choices[0].message.content) | |
| async def tts_generate(self, text: str, speaker: int, speaker1: str, speaker2: str) -> str: | |
| voice = speaker1 if speaker == 1 else speaker2 | |
| speech = edge_tts.Communicate(text, voice) | |
| temp_filename = f"temp_{uuid.uuid4()}.wav" | |
| try: | |
| await speech.save(temp_filename) | |
| return temp_filename | |
| except Exception as e: | |
| if os.path.exists(temp_filename): | |
| os.remove(temp_filename) | |
| raise e | |
| async def combine_audio_files(self, audio_files: List[str]) -> str: | |
| combined_audio = AudioSegment.empty() | |
| for audio_file in audio_files: | |
| combined_audio += AudioSegment.from_file(audio_file) | |
| os.remove(audio_file) # Clean up temporary files | |
| output_filename = f"output_{uuid.uuid4()}.wav" | |
| combined_audio.export(output_filename, format="wav") | |
| return output_filename | |
| async def generate_podcast(self, input_text: str, language: str, speaker1: str, speaker2: str) -> str: | |
| podcast_json = await self.generate_script(input_text, language) | |
| print(f"Generated podcast script:\n{podcast_json}") | |
| audio_files = await asyncio.gather(*[self.tts_generate(item['line'], item['speaker'], speaker1, speaker2) for item in podcast_json['podcast']]) | |
| combined_audio = await self.combine_audio_files(audio_files) | |
| return combined_audio | |
| class TextExtractor: | |
| async def extract_from_pdf(file_path: str) -> str: | |
| async with aiofiles.open(file_path, 'rb') as file: | |
| content = await file.read() | |
| pdf_reader = pypdf.PdfReader(io.BytesIO(content)) | |
| return "\n\n".join(page.extract_text() for page in pdf_reader.pages if page.extract_text()) | |
| async def extract_from_txt(file_path: str) -> str: | |
| async with aiofiles.open(file_path, 'r') as file: | |
| return await file.read() | |
| async def extract_text(cls, file_path: str) -> str: | |
| _, file_extension = os.path.splitext(file_path) | |
| if file_extension.lower() == '.pdf': | |
| return await cls.extract_from_pdf(file_path) | |
| elif file_extension.lower() == '.txt': | |
| return await cls.extract_from_txt(file_path) | |
| else: | |
| raise ValueError(f"Unsupported file type: {file_extension}") | |
| async def process_input(input_text: str, input_file, language: str, speaker1: str, speaker2: str) -> str: | |
| voice_names = { | |
| "Andrew - English (United States)": "en-US-AndrewMultilingualNeural", | |
| "Ava - English (United States)": "en-US-AvaMultilingualNeural", | |
| "Brian - English (United States)": "en-US-BrianMultilingualNeural", | |
| "Emma - English (United States)": "en-US-EmmaMultilingualNeural", | |
| "Florian - German (Germany)": "de-DE-FlorianMultilingualNeural", | |
| "Seraphina - German (Germany)": "de-DE-SeraphinaMultilingualNeural", | |
| "Remy - French (France)": "fr-FR-RemyMultilingualNeural", | |
| "Vivienne - French (France)": "fr-FR-VivienneMultilingualNeural" | |
| } | |
| speaker1 = voice_names[speaker1] | |
| speaker2 = voice_names[speaker2] | |
| if input_file: | |
| input_text = await TextExtractor.extract_text(input_file.name) | |
| podcast_generator = PodcastGenerator(groq_api_key=os.environ["GROQ_API_KEY"]) | |
| return await podcast_generator.generate_podcast(input_text, language, speaker1, speaker2) | |
| # Define Gradio interface | |
| iface = gr.Interface( | |
| fn=process_input, | |
| inputs=[ | |
| gr.Textbox(label="Input Text"), | |
| gr.File(label="Or Upload a PDF or TXT file"), | |
| gr.Dropdown(label="Language", choices=[ | |
| "Auto Detect", | |
| "Afrikaans", "Albanian", "Amharic", "Arabic", "Armenian", "Azerbaijani", | |
| "Bahasa Indonesian", "Bangla", "Basque", "Bengali", "Bosnian", "Bulgarian", | |
| "Burmese", "Catalan", "Chinese Cantonese", "Chinese Mandarin", | |
| "Chinese Taiwanese", "Croatian", "Czech", "Danish", "Dutch", "English", | |
| "Estonian", "Filipino", "Finnish", "French", "Galician", "Georgian", | |
| "German", "Greek", "Hebrew", "Hindi", "Hungarian", "Icelandic", "Irish", | |
| "Italian", "Japanese", "Javanese", "Kannada", "Kazakh", "Khmer", "Korean", | |
| "Lao", "Latvian", "Lithuanian", "Macedonian", "Malay", "Malayalam", | |
| "Maltese", "Mongolian", "Nepali", "Norwegian Bokmål", "Pashto", "Persian", | |
| "Polish", "Portuguese", "Romanian", "Russian", "Serbian", "Sinhala", | |
| "Slovak", "Slovene", "Somali", "Spanish", "Sundanese", "Swahili", | |
| "Swedish", "Tamil", "Telugu", "Thai", "Turkish", "Ukrainian", "Urdu", | |
| "Uzbek", "Vietnamese", "Welsh", "Zulu" | |
| ], | |
| value="Auto Detect"), | |
| gr.Dropdown(label="Speaker 1 Voice", choices=[ | |
| "Andrew - English (United States)", | |
| "Ava - English (United States)", | |
| "Brian - English (United States)", | |
| "Emma - English (United States)", | |
| "Florian - German (Germany)", | |
| "Seraphina - German (Germany)", | |
| "Remy - French (France)", | |
| "Vivienne - French (France)" | |
| ], | |
| value="Andrew - English (United States)"), | |
| gr.Dropdown(label="Speaker 2 Voice", choices=[ | |
| "Andrew - English (United States)", | |
| "Ava - English (United States)", | |
| "Brian - English (United States)", | |
| "Emma - English (United States)", | |
| "Florian - German (Germany)", | |
| "Seraphina - German (Germany)", | |
| "Remy - French (France)", | |
| "Vivienne - French (France)" | |
| ], | |
| value="Ava - English (United States)") | |
| ], | |
| outputs=[ | |
| gr.Audio(label="Generated Podcast Audio") | |
| ], | |
| title="PodcastGen 🎙️", | |
| description="Generate a 2-speaker podcast from text input or documents!", | |
| theme="saq1b/gradio-theme" | |
| ) | |
| if __name__ == "__main__": | |
| iface.launch() |