Update app.py

app.py

@@ -1,20 +1,23 @@
 import gradio as gr
 from pydub import AudioSegment
-from google import genai
-from google.genai import types
+import google.generativeai as genai
+from google.generativeai.types import HarmCategory, HarmBlockThreshold
 import json
 import uuid
+import io
 import edge_tts
 import asyncio
+import aiofiles
+import pypdf
 import os
 import time
-from typing import List, Dict
+from typing import List, Dict, Tuple
 
 class PodcastGenerator:
     def __init__(self):
         pass
 
-    async def generate_script(self, contents: list, language: str, api_key: str) -> Dict:
+    async def generate_script(self, prompt: str, language: str, api_key: str) -> Dict:
         example = """
 {
     "topic": "AGI",
@@ -23,7 +26,186 @@ class PodcastGenerator:
             "speaker": 2,
             "line": "So, AGI, huh? Seems like everyone's talking about it these days."
         },
-        # ... (rest of the example JSON structure remains the same)
+        {
+            "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."
+        }
     ]
 }
         """
@@ -45,45 +227,45 @@ You are a professional podcast generator. Your task is to generate a professiona
 Follow this example structure:
 {example}
 """
-        client = genai.Client(api_key=api_key)
+        user_prompt = f"Please generate a podcast script based on the following user input:\n{prompt}"
 
-        generation_config = types.GenerationConfig(
-            temperature=1,
-            max_output_tokens=8192,
-            response_mime_type="application/json",
-        )
+        messages = [
+            {"role": "user", "parts": [user_prompt]}
+        ]
 
-        safety_settings = {
-            types.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: types.HarmBlockThreshold.BLOCK_NONE,
-            types.HarmCategory.HARM_CATEGORY_HARASSMENT: types.HarmBlockThreshold.BLOCK_NONE,
-            types.HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: types.HarmBlockThreshold.BLOCK_NONE,
-            types.HarmCategory.HARM_CATEGORY_HATE_SPEECH: types.HarmBlockThreshold.BLOCK_NONE
+        genai.configure(api_key=api_key)
+
+        generation_config = {
+        "temperature": 1,
+        "max_output_tokens": 8192,
+        "response_mime_type": "application/json",
         }
 
-        config = types.GenerateContentConfig(
-            system_instruction=system_prompt,
-            generation_config=generation_config,
-            safety_settings=safety_settings
+        model = genai.GenerativeModel(
+        model_name="gemini-2.0-flash",
+        generation_config=generation_config,
+        safety_settings={
+            HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
+            HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
+            HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
+            HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE
+        },
+        system_instruction=system_prompt
         )
 
         try:
-            response = await client.aio.models.generate_content(
-                model="gemini-1.5-flash",
-                contents=contents,
-                config=config
-            )
+            response = await model.generate_content_async(messages)
         except Exception as e:
             if "API key not valid" in str(e):
                 raise gr.Error("Invalid API key. Please provide a valid Gemini API key.")
             elif "rate limit" in str(e).lower():
-                raise gr.Error("Rate limit exceeded. Please try again later or use your own API key.")
+                raise gr.Error("Rate limit exceeded for the API key. Please try again later or provide your own Gemini API key.")
             else:
                 raise gr.Error(f"Failed to generate podcast script: {e}")
 
-        try:
-            return json.loads(response.text)
-        except json.JSONDecodeError:
-            raise gr.Error("Failed to parse generated script. Please try again.")
+        print(f"Generated podcast script:\n{response.text}")
+        
+        return json.loads(response.text)
 
     async def tts_generate(self, text: str, speaker: int, speaker1: str, speaker2: str) -> str:
         voice = speaker1 if speaker == 1 else speaker2
@@ -102,29 +284,50 @@ Follow this example structure:
         combined_audio = AudioSegment.empty()
         for audio_file in audio_files:
             combined_audio += AudioSegment.from_file(audio_file)
-            os.remove(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, contents: list, language: str, speaker1: str, speaker2: str, api_key: str) -> str:
+    async def generate_podcast(self, input_text: str, language: str, speaker1: str, speaker2: str, api_key: str) -> str:
         gr.Info("Generating podcast script...")
         start_time = time.time()
-        podcast_json = await self.generate_script(contents, language, api_key)
+        podcast_json = await self.generate_script(input_text, language, api_key)
         end_time = time.time()
-        gr.Info(f"Script generated in {(end_time - start_time):.2f}s")
+        gr.Info(f"Successfully generated podcast script in {(end_time - start_time):.2f} seconds!")
 
-        gr.Info("Generating audio files...")
+        gr.Info("Generating podcast audio files...")
         start_time = time.time()
-        audio_files = await asyncio.gather(*[
-            self.tts_generate(item['line'], item['speaker'], speaker1, speaker2)
-            for item in podcast_json['podcast']
-        ])
+        audio_files = await asyncio.gather(*[self.tts_generate(item['line'], item['speaker'], speaker1, speaker2) for item in podcast_json['podcast']])
         end_time = time.time()
-        gr.Info(f"Audio generated in {(end_time - start_time):.2f}s")
+        gr.Info(f"Successfully generated podcast audio files in {(end_time - start_time):.2f} seconds!")
+
+        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 = pypdf.PdfReader(io.BytesIO(content))
+            return "\n\n".join(page.extract_text() for page in pdf_reader.pages if page.extract_text())
+
+    @staticmethod
+    async def extract_from_txt(file_path: str) -> str:
+        async with aiofiles.open(file_path, 'r') as file:
+            return await file.read()
 
-        return await self.combine_audio_files(audio_files)
+    @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 gr.Error(f"Unsupported file type: {file_extension}")
 
 async def process_input(input_text: str, input_file, language: str, speaker1: str, speaker2: str, api_key: str = "") -> str:
     gr.Info("Starting podcast generation...")
@@ -144,49 +347,32 @@ async def process_input(input_text: str, input_file, language: str, speaker1: st
     speaker1 = voice_names[speaker1]
     speaker2 = voice_names[speaker2]
 
-    contents = []
     if input_file:
-        file_path = input_file.name
-        file_size = os.path.getsize(file_path)
-        
-        if file_size > 20 * 1024 * 1024:  # 20MB
-            client = genai.Client(api_key=api_key or os.getenv("GENAI_API_KEY"))
-            uploaded_file = await client.aio.files.upload(file_path)
-            file_part = uploaded_file
-        else:
-            with open(file_path, 'rb') as f:
-                file_bytes = f.read()
-            mime_type = 'application/pdf' if file_path.lower().endswith('.pdf') else 'text/plain'
-            file_part = types.Part.from_bytes(file_bytes, mime_type)
-        
-        contents = [file_part, types.Part.from_text("Generate podcast script from document")]
-    else:
-        contents = [
-            types.Part.from_text(input_text),
-            types.Part.from_text("Generate podcast script from text")
-        ]
+        input_text = await TextExtractor.extract_text(input_file.name)
+
+    if not api_key:
+        api_key = os.getenv("GENAI_API_KEY")
 
     podcast_generator = PodcastGenerator()
-    podcast = await podcast_generator.generate_podcast(
-        contents, language, speaker1, speaker2, 
-        api_key or os.getenv("GENAI_API_KEY")
-    )
+    podcast = await podcast_generator.generate_podcast(input_text, language, speaker1, speaker2, api_key)
 
     end_time = time.time()
-    gr.Info(f"Total time: {(end_time - start_time):.2f}s")
+    gr.Info(f"Successfully generated podcast in {(end_time - start_time):.2f} seconds!")
+
     return podcast
 
+# Define Gradio interface
 iface = gr.Interface(
     fn=process_input,
     inputs=[
         gr.Textbox(label="Input Text"),
-        gr.File(label="Or Upload PDF/TXT (≤20GB)", file_types=["pdf", "txt"]),
+        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 Tiwanese", "Croatian", "Czech", "Danish", "Dutch", "English",
+            "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",
@@ -196,7 +382,8 @@ iface = gr.Interface(
             "Slovak", "Slovene", "Somali", "Spanish", "Sundanese", "Swahili",
             "Swedish", "Tamil", "Telugu", "Thai", "Turkish", "Ukrainian", "Urdu",
             "Uzbek", "Vietnamese", "Welsh", "Zulu"
-        ], value="Auto Detect"),
+        ],
+        value="Auto Detect"),
         gr.Dropdown(label="Speaker 1 Voice", choices=[
             "Andrew - English (United States)",
             "Ava - English (United States)",
@@ -206,7 +393,8 @@ iface = gr.Interface(
             "Seraphina - German (Germany)",
             "Remy - French (France)",
             "Vivienne - French (France)"
-        ], value="Andrew - English (United States)"),
+        ],
+        value="Andrew - English (United States)"),
         gr.Dropdown(label="Speaker 2 Voice", choices=[
             "Andrew - English (United States)",
             "Ava - English (United States)",
@@ -216,12 +404,15 @@ iface = gr.Interface(
             "Seraphina - German (Germany)",
             "Remy - French (France)",
             "Vivienne - French (France)"
-        ], value="Ava - English (United States)"),
-        gr.Textbox(label="Gemini API Key (Optional)"),
+        ],
+        value="Ava - English (United States)"),
+        gr.Textbox(label="Your Gemini API Key (Optional) - In case you are getting rate limited"),
+    ],
+    outputs=[
+        gr.Audio(label="Generated Podcast Audio")
     ],
-    outputs=gr.Audio(label="Generated Podcast"),
     title="PodcastGen 🎙️",
-    description="Generate 2-speaker podcasts from text or documents using Gemini!",
+    description="Generate a 2-speaker podcast from text input or documents!",
     allow_flagging="never"
 )