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app.py

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+import gradio as gr
+from pydub import AudioSegment
+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, Tuple
+import openai
+
+class PodcastGenerator:
+    def __init__(self):
+        pass
+
+    async def generate_script(self, prompt: str, language: str, api_key: str) -> Dict:
+        """
+        非同步生成基於給定提示和語言的Podcast劇本。
+
+        引數：
+            prompt (str): 用於生成Podcast劇本的使用者輸入文字。
+            language (str): Podcast指劇本所需的語言。
+            api_key (str): 用於訪問 SambaNova API 服務的 API 金鑰。
+
+        返回：
+            Dict: 包含以 JSON 格式生成Podcast劇本的字典。
+
+        異常：
+            gr.Error: 如果 API 金鑰或速率限制出現問題。
+
+        此方法使用 SambaNova API 根據使用者的輸入生成Podcast劇本。
+        它處理語言選擇，使用適當的配置設定 AI 模型，並處理生成的響應。
+        """
+        # 定義一個示例JSON結構，用於指導AI生成類似格式的Podcast劇本
+        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."
+                }
+            ]
+        }
+        """
+
+        # 根據使用者選擇的語言設定指令
+        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"
+
+        # 設定系統提示，指導AI如何生成Podcast指令碼
+        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 carefully:
+        {example}
+        """
+
+        # 設定使用者提示，包含使用者輸入的內容
+        user_prompt = f"Please generate a podcast script based on the following user input:\n{prompt}"
+
+        # 配置 SambaNova API client
+        if api_key:
+            openai.api_key = api_key
+        else:
+            openai.api_key = os.getenv("YOUR_API_TOKEN")
+        client = openai.OpenAI(
+            api_key=openai.api_key,
+            base_url="https://api.sambanova.ai/v1",
+        )
+
+        # 嘗試生成內容
+        try:
+            response = client.chat.completions.create(
+                model='Meta-Llama-3.1-405B-Instruct',
+                messages=[
+                    {"role": "system", "content": system_prompt},
+                    {"role": "user", "content": user_prompt}
+                ],
+                temperature=0.7,
+                max_tokens=8192
+            )
+            generated_text = response.choices[0].message.content
+        except Exception as e:
+            # 處理可能的錯誤
+            if "API key not valid" in str(e):
+                raise gr.Error("Invalid API key. Please provide a valid SambaNova API key.")
+            elif "rate limit" in str(e).lower():
+                raise gr.Error("Rate limit exceeded for the API key. Please try again later or provide your own SambaNova API key.")
+            else:
+                raise gr.Error(f"Failed to generate podcast script: {e}")
+
+        # 列印生成的Podcast指令碼
+        print(f"Generated podcast script:\n{generated_text}")
+
+        # 返回解析後的JSON資料
+        return json.loads(generated_text)
+
+    async def tts_generate(self, text: str, speaker: int, speaker1: str, speaker2: str) -> str:
+        """
+        非同步生成文字轉語音音訊檔案。
+
+        引數：
+            text (str): 要轉換爲語音的文字內容。
+            speaker (int): 說話者的編號（1 或 2）。
+            speaker1 (str): 第一位說話者的語音設定。
+            speaker2 (str): 第二位說話者的語音設定。
+
+        返回：
+            str: 生成的臨時音訊檔案的檔名。
+
+        此方法使用 Edge TTS 將文字轉換爲語音，並將結果儲存爲臨時音訊檔案。
+        根據指定的說話者編號選擇相應的語音設定。
+        """
+        # 根據說話者選擇語音
+        voice = speaker1 if speaker == 1 else speaker2
+        # 建立語音合成對象
+        speech = edge_tts.Communicate(text, voice)
+
+        # 生成臨時檔名
+        temp_filename = f"temp_{uuid.uuid4()}.wav"
+        try:
+            # 儲存語音檔案
+            await speech.save(temp_filename)
+            return temp_filename
+        except Exception as e:
+            # 如果出錯，刪除臨時檔案並丟擲異常
+            if os.path.exists(temp_filename):
+                os.remove(temp_filename)
+            raise e
+
+    async def combine_audio_files(self, audio_files: List[str]) -> str:
+        """
+        非同步合併音訊檔案。
+
+        引數：
+            audio_files (List[str]): 包含音訊檔案路徑的列表。
+
+        返回：
+            str: 合併後的音訊檔案的檔名。
+        """
+        # 建立空的音訊段
+        combined_audio = AudioSegment.empty()
+        # 遍歷所有音訊檔案並合併
+        for audio_file in audio_files:
+            combined_audio += AudioSegment.from_file(audio_file)
+            os.remove(audio_file)  # 清理臨時檔案
+
+        # 生成輸出文件名
+        output_filename = f"output_{uuid.uuid4()}.wav"
+        # 匯出合併後的音訊
+        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:
+        """
+        非同步生成Podcast音訊檔案。
+
+        引數：
+            input_text (str): 用於生成Podcast指令碼的輸入文字。
+            language (str): Podcast使用的語言。
+            speaker1 (str): 第一位說話者的語音設定。
+            speaker2 (str): 第二位說話者的語音設定。
+            api_key (str): 用於訪問 Gemini AI 服務的 API 金鑰。
+
+        返回：
+            str: 生成的Podcast音訊檔案的檔名。
+
+        此方法執行以下步驟：
+        1. 使用 generate_script 方法生成Podcast劇本。
+        2. 使用 tts_generate 方法爲每個對話行生成音訊檔案。
+        3. 使用 combine_audio_files 方法將所有音訊檔案合併爲一個完整的Podcast。
+
+        整個過程是非同步的，以提高效率。方法還會記錄並顯示每個步驟的執行時間。
+        """
+        # 生成Podcast劇本
+        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!")
+
+        # 生成Podcast音訊檔案
+        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!")
+
+        # 合併音訊檔案
+        combined_audio = await self.combine_audio_files(audio_files)
+        return combined_audio
+
+class TextExtractor:
+    @staticmethod
+    async def extract_from_pdf(file_path: str) -> str:
+        # 從PDF檔案中提取文字
+        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:
+        # 從TXT檔案中提取文字
+        async with aiofiles.open(file_path, 'r') as file:
+            return await file.read()
+
+    @classmethod
+    async def extract_text(cls, file_path: str) -> str:
+        # 根據檔案型別選擇適當的提取方法
+        _, 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:
+    """
+    處理輸入並生成Podcast的非同步函式。
+
+    引數:
+    input_text (str): 使用者輸入的文字內容。
+    input_file: 使用者上傳的檔案（可以是 PDF 或 TXT）。
+    language (str): 選擇的語言。
+    speaker1 (str): 第一位說話者的語音選擇。
+    speaker2 (str): 第二位說話者的語音選擇。
+    api_key (str): 用於生成 AI 的 API 金鑰，預設爲空字串。
+
+    返回:
+    str: 生成的Podcast音訊檔案路徑。
+
+    此函式協調整個Podcast生成過程，包括文字提取、指令碼生成和音訊合成。
+    它處理不同的輸入型別（文字或檔案），並使用指定的語音和語言設定來建立最終的Podcast。
+    """
+    # 開始生成Podcast
+    gr.Info("Starting podcast generation...")
+    start_time = time.time()
+
+    # 定義語音名稱對映
+    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"
+    }
+
+    # 獲取實際的語音名稱
+    speaker1 = voice_names[speaker1]
+    speaker2 = voice_names[speaker2]
+
+    # 如果提供了輸入檔案，則從檔案中提取文字
+    if input_file:
+        input_text = await TextExtractor.extract_text(input_file.name)
+
+    # 如果沒有提供API金鑰，則使用環境變數中的金鑰
+    if not api_key:
+        api_key = os.getenv("Your_API_KEY")
+
+    # 建立PodcastGenerator實例並生成Podcast
+    podcast_generator = PodcastGenerator()
+    podcast = await podcast_generator.generate_podcast(input_text, language, speaker1, speaker2, api_key)
+
+    # 計算總耗時並顯示資訊
+    end_time = time.time()
+    gr.Info(f"Successfully generated podcast in {(end_time - start_time):.2f} seconds!")
+
+    return podcast
+
+# 定義Gradio介面
+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.Textbox(label="Your Gemini API Key (Optional) - In case you are getting rate limited"),
+    ],
+    outputs=[
+        gr.Audio(label="Generated Podcast Audio")
+    ],
+    title="🎙️ PodcastGen 🎙️",
+    description="Generate a 2-speaker podcast from text input or documents!",
+    allow_flagging="never"
+)
+
+if __name__ == "__main__":
+    iface.launch()
+
+

requirements.txt

@@ -0,0 +1,7 @@
+gradio
+gradio-client
+openai
+pydub
+google-generativeai
+pypdf
+edge_tts