Upload app.py

app.py

@@ -39,249 +39,24 @@ class PodcastGenerator:
         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."
-                }
-            ]
-        }
-        """
+        # Significantly shorten the system prompt
+        system_prompt = f"""Generate a podcast script with 2 speakers. {language} language. Be concise, engaging, and in JSON format."""
 
-        # 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",
-        )
+        example = """{"podcast":[{"speaker":1,"line":"Hello"},{"speaker":2,"line":"Hi there"}]}"""
 
         async def generate_chunk(chunk: str) -> str:
             try:
                 # Calculate the available tokens for generation
-                prompt_tokens = len(chunk.split())  # This is a rough estimate
-                system_tokens = len(system_prompt.split())  # This is a rough estimate
-                max_tokens = 4096 - prompt_tokens - system_tokens - 100  # 100 is a safety margin
-
-                if max_tokens <= 0:
-                    return {"error": "Input chunk is too long. Please provide a shorter prompt."}
+                prompt_tokens = len(chunk.split())
+                system_tokens = len(system_prompt.split())
+                max_tokens = 3000  # Reduced from 4096 to leave more room for the prompt
 
                 logger.info(f"Sending request to SambaNova API with prompt chunk: {chunk[:100]}...")
                 response = client.chat.completions.create(
                     model='Meta-Llama-3.1-405B-Instruct',
                     messages=[
                         {"role": "system", "content": system_prompt},
-                        {"role": "user", "content": chunk}
+                        {"role": "user", "content": f"Generate a podcast script based on this: {chunk}\nUse this format: {example}"}
                     ],
                     temperature=1,
                     max_tokens=max_tokens
@@ -304,8 +79,8 @@ class PodcastGenerator:
                 logger.error(f"Error generating script chunk: {str(e)}")
                 return {"error": f"Failed to generate podcast script chunk: {str(e)}"}
 
-        # Split the prompt into chunks
-        chunk_size = 1000  # Adjust this value as needed
+        # Split the prompt into smaller chunks
+        chunk_size = 500  # Reduced from 1000
         chunks = [prompt[i:i+chunk_size] for i in range(0, len(prompt), chunk_size)]
 
         # Generate script for each chunk
@@ -319,11 +94,15 @@ class PodcastGenerator:
         # Combine generated chunks
         generated_text = " ".join(generated_chunks)
 
-        # 嘗試解析JSON，如果失敗則嘗試從原始文本中提取對話
+        # Try to parse JSON, if fails then extract dialogue from raw text
         try:
-            return json.loads(generated_text)
+            parsed_json = json.loads(generated_text)
+            if "podcast" in parsed_json:
+                return parsed_json
+            else:
+                raise json.JSONDecodeError("Missing 'podcast' key", generated_text, 0)
         except json.JSONDecodeError:
-            logger.warning("Generated text is not valid JSON. Attempting to extract dialogue.")
+            logger.warning("Generated text is not valid JSON or missing 'podcast' key. Attempting to extract dialogue.")
             lines = generated_text.split('\n')
             podcast = []
             current_speaker = 1
@@ -534,6 +313,12 @@ async def process_input(input_text: str, input_file, language: str, speaker1: st
     if input_file:
         input_text = await TextExtractor.extract_text(input_file.name)
 
+    # Limit input text length
+    max_input_length = 3000  # Adjust this value as needed
+    if len(input_text) > max_input_length:
+        input_text = input_text[:max_input_length]
+        gr.Warning(f"Input text was truncated to {max_input_length} characters due to length limitations.")
+
     # 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")