Update app.py

app.py

@@ -1,23 +1,28 @@
 import gradio as gr
+import logging
 from pydub import AudioSegment
-import google.generativeai as genai
-from google.generativeai.types import HarmCategory, HarmBlockThreshold
+from google import genai  # Using the new Gemini API client
+from google.genai import types  # For inline file parts
 import json
 import uuid
 import io
 import edge_tts
 import asyncio
-import aiofiles
-import pypdf
 import os
 import time
-from typing import List, Dict, Tuple
+import aiofiles
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+
+# Maximum file size allowed: 20 MB
+MAX_FILE_SIZE = 20 * 1024 * 1024
 
 class PodcastGenerator:
     def __init__(self):
         pass
 
-    async def generate_script(self, prompt: str, language: str, api_key: str) -> Dict:
+    async def generate_script(self, prompt: str, language: str, api_key: str, file_data=None, file_mime_type=None) -> dict:
         example = """
 {
     "topic": "AGI",
@@ -29,187 +34,11 @@ class PodcastGenerator:
         {
             "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."
         }
+        // ... (rest of the example)
     ]
 }
         """
-
         if language == "Auto Detect":
             language_instruction = "- The podcast MUST be in the same language as the user input."
         else:
@@ -229,33 +58,33 @@ Follow this example structure:
 """
         user_prompt = f"Please generate a podcast script based on the following user input:\n{prompt}"
 
-        messages = [
-            {"role": "user", "parts": [user_prompt]}
-        ]
-
-        genai.configure(api_key=api_key)
+        # Initialize the Gemini API client with the provided API key.
+        client = genai.Client(api_key=api_key)
+        contents = []
+        if file_data is not None:
+            try:
+                # Use inline file data directly without uploading.
+                contents.append(types.Part.from_bytes(data=file_data, mime_type=file_mime_type))
+            except Exception as e:
+                logging.error("Error preparing file part: %s", e)
+                raise gr.Error(f"Error processing file data: {e}")
+        contents.append(user_prompt)
 
-        generation_config = {
-        "temperature": 1,
-        "max_output_tokens": 8192,
-        "response_mime_type": "application/json",
+        config = {
+            "system_instruction": system_prompt,
+            "temperature": 1,
+            "max_output_tokens": 8192,
+            "response_mime_type": "application/json",
         }
 
-        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 model.generate_content_async(messages)
+            response = await client.aio.models.generate_content(
+                model="gemini-2.0-flash",
+                contents=contents,
+                config=config
+            )
         except Exception as e:
+            logging.error("API call failed: %s", 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():
@@ -263,149 +92,186 @@ Follow this example structure:
             else:
                 raise gr.Error(f"Failed to generate podcast script: {e}")
 
-        print(f"Generated podcast script:\n{response.text}")
-        
-        return json.loads(response.text)
+        try:
+            result = json.loads(response.text)
+        except json.JSONDecodeError as e:
+            logging.error("JSON parsing failed: %s", e)
+            raise gr.Error(f"Response is not valid JSON: {e}")
+
+        logging.info("Successfully generated script: %s", result)
+        return result
 
     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)
+        try:
+            speech = edge_tts.Communicate(text, voice)
+        except Exception as e:
+            logging.error("TTS initialization failed: %s", e)
+            raise gr.Error(f"Text-to-Speech initialization error: {e}")
         
         temp_filename = f"temp_{uuid.uuid4()}.wav"
         try:
             await speech.save(temp_filename)
             return temp_filename
         except Exception as e:
+            logging.error("TTS generation failed: %s", e)
             if os.path.exists(temp_filename):
                 os.remove(temp_filename)
-            raise e
+            raise gr.Error(f"Failed to generate speech for text: {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, api_key: str) -> str:
-        gr.Info("Generating podcast script...")
-        start_time = time.time()
-        podcast_json = await self.generate_script(input_text, language, api_key)
-        end_time = time.time()
-        gr.Info(f"Successfully generated podcast script in {(end_time - start_time):.2f} seconds!")
-
-        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']])
-        end_time = time.time()
-        gr.Info(f"Successfully generated podcast audio files in {(end_time - start_time):.2f} seconds!")
+    async def combine_audio_files(self, audio_files: list) -> str:
+        try:
+            combined_audio = AudioSegment.empty()
+            for audio_file in audio_files:
+                try:
+                    combined_audio += AudioSegment.from_file(audio_file)
+                except Exception as inner_e:
+                    logging.error("Error processing audio file %s: %s", audio_file, inner_e)
+                    raise gr.Error(f"Error processing audio file: {inner_e}")
+                finally:
+                    if os.path.exists(audio_file):
+                        os.remove(audio_file)  # Clean up temporary file
+            output_filename = f"output_{uuid.uuid4()}.wav"
+            combined_audio.export(output_filename, format="wav")
+            return output_filename
+        except Exception as e:
+            logging.error("Failed to combine audio files: %s", e)
+            raise gr.Error(f"Failed to combine audio files: {e}")
 
-        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())
+    async def generate_podcast(self, input_text: str, language: str, speaker1: str, speaker2: str, api_key: str, file_data=None, file_mime_type=None) -> str:
+        try:
+            gr.Info("Generating podcast script...")
+            start_time = time.time()
+            podcast_json = await self.generate_script(input_text, language, api_key, file_data, file_mime_type)
+            end_time = time.time()
+            gr.Info(f"Successfully generated podcast script in {(end_time - start_time):.2f} seconds!")
+        except Exception as e:
+            logging.error("Script generation error: %s", e)
+            raise gr.Error(f"Error generating podcast script: {e}")
 
-    @staticmethod
-    async def extract_from_txt(file_path: str) -> str:
-        async with aiofiles.open(file_path, 'r') as file:
-            return await file.read()
+        try:
+            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.get('podcast', [])
+            ])
+            end_time = time.time()
+            gr.Info(f"Successfully generated podcast audio files in {(end_time - start_time):.2f} seconds!")
+        except Exception as e:
+            logging.error("TTS generation error: %s", e)
+            raise gr.Error(f"Error generating audio files: {e}")
 
-    @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}")
+        try:
+            combined_audio = await self.combine_audio_files(audio_files)
+            return combined_audio
+        except Exception as e:
+            logging.error("Audio combining error: %s", e)
+            raise gr.Error(f"Error combining audio files: {e}")
 
 async def process_input(input_text: str, input_file, language: str, speaker1: str, speaker2: str, api_key: str = "") -> str:
-    gr.Info("Starting podcast generation...")
-    start_time = time.time()
-
-    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"
-    }
+    try:
+        gr.Info("Starting podcast generation...")
+        start_time = time.time()
 
-    speaker1 = voice_names[speaker1]
-    speaker2 = voice_names[speaker2]
+        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"
+        }
 
-    if input_file:
-        input_text = await TextExtractor.extract_text(input_file.name)
+        speaker1 = voice_names.get(speaker1, speaker1)
+        speaker2 = voice_names.get(speaker2, speaker2)
 
-    if not api_key:
-        api_key = os.getenv("GENAI_API_KEY")
+        file_data = None
+        file_mime_type = None
+        if input_file:
+            ext = os.path.splitext(input_file.name)[1].lower()
+            if ext not in ['.pdf', '.txt']:
+                raise gr.Error("Unsupported file type. Only PDF and TXT files are allowed.")
+            try:
+                async with aiofiles.open(input_file.name, 'rb') as f:
+                    file_data = await f.read()
+            except Exception as e:
+                logging.error("Error reading file: %s", e)
+                raise gr.Error(f"Error reading file: {e}")
+            if len(file_data) > MAX_FILE_SIZE:
+                raise gr.Error("File size exceeds 20MB limit.")
+            file_mime_type = 'application/pdf' if ext == '.pdf' else 'text/plain'
 
-    podcast_generator = PodcastGenerator()
-    podcast = await podcast_generator.generate_podcast(input_text, language, speaker1, speaker2, api_key)
+        if not api_key:
+            api_key = os.getenv("GENAI_API_KEY")
+            if not api_key:
+                raise gr.Error("No API key provided and none found in the environment.")
 
-    end_time = time.time()
-    gr.Info(f"Successfully generated podcast in {(end_time - start_time):.2f} seconds!")
+        podcast_generator = PodcastGenerator()
+        podcast = await podcast_generator.generate_podcast(input_text, language, speaker1, speaker2, api_key, file_data, file_mime_type)
 
-    return podcast
+        end_time = time.time()
+        gr.Info(f"Successfully generated podcast in {(end_time - start_time):.2f} seconds!")
+        return podcast
+    except Exception as e:
+        logging.error("Process input error: %s", e)
+        raise gr.Error(f"Error in processing input: {e}")
 
-# 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)"),
+        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)"
+        ),
         gr.Textbox(label="Your Gemini API Key (Optional) - In case you are getting rate limited"),
     ],
     outputs=[