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 PyPDF2 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) -> 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." } ] } """ system_prompt = f""" You are a professional podcast generator. Your task is to generate a professional podcast script based on the user input. The user input can also be text extracted from a document. - The podcast should have 2 speakers. - The podcast should be long. - The speakers must not mention each other by name. - The podcast should be interesting and engaging, and hook the listener from the start. - 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) -> str: voice = "en-US-AndrewMultilingualNeural" if speaker == 1 else "en-US-AvaMultilingualNeural" 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) -> str: podcast_json = await self.generate_script(input_text) print(f"Generated podcast script:\n{podcast_json}") audio_files = await asyncio.gather(*[self.tts_generate(item['line'], item['speaker']) for item in podcast_json['podcast']]) combined_audio = await self.combine_audio_files(audio_files) return combined_audio class TextExtractor: @staticmethod async def extract_from_pdf(file_path: str) -> str: async with aiofiles.open(file_path, 'rb') as file: content = await file.read() pdf_reader = PyPDF2.PdfReader(io.BytesIO(content)) return " ".join(page.extract_text() for page in pdf_reader.pages) @staticmethod async def extract_from_txt(file_path: str) -> str: async with aiofiles.open(file_path, 'r') as file: return await file.read() @classmethod 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) -> str: 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) # 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") ], 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()