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| # -*- coding: utf-8 -*- | |
| """ | |
| UltraData-Math-L3-Generator - Hugging Face Space Demo | |
| """ | |
| import os | |
| import asyncio | |
| import gradio as gr | |
| from openai import AsyncOpenAI | |
| from qa_synthesis import QA_PROMPTS, get_qa_prompt | |
| from conversation_synthesis import CONVERSATION_PROMPTS, get_conversation_prompt | |
| from multistyle_rewrite import MULTISTYLE_PROMPTS, get_multistyle_prompt | |
| from knowledge_textbook import ( | |
| get_knowledge_extraction_prompt, | |
| get_textbook_exercise_prompt, | |
| TEXTBOOK_EXERCISE_PROMPTS, | |
| ) | |
| from run_synthesis import ( | |
| parse_qa_output, | |
| parse_conversation_output, | |
| parse_rewrite_output, | |
| parse_knowledge_output, | |
| parse_textbook_output, | |
| ) | |
| # API 配置从环境变量读取(通过 HF Secrets 设置) | |
| API_KEY = os.getenv("OPENAI_API_KEY") | |
| BASE_URL = os.getenv("OPENAI_BASE_URL", "https://llm-center.ali.modelbest.cn/llm/openai/v1") | |
| DEFAULT_MODEL = "GEMINI_anxt74" | |
| # 示例数据 | |
| EXAMPLE_MATH_CONTENT = """The quadratic formula is a fundamental result in algebra that provides the solutions to any quadratic equation of the form ax² + bx + c = 0, where a ≠ 0. | |
| The formula states that the solutions are: | |
| x = (-b ± √(b² - 4ac)) / (2a) | |
| The term b² - 4ac is called the discriminant. It determines the nature of the roots: | |
| - If b² - 4ac > 0, there are two distinct real roots | |
| - If b² - 4ac = 0, there is exactly one real root (a repeated root) | |
| - If b² - 4ac < 0, there are two complex conjugate roots | |
| This formula was known to ancient mathematicians and remains one of the most important tools in solving polynomial equations.""" | |
| EXAMPLE_KNOWLEDGE_POINT = """Definition: A continuous function is a function f: R → R such that for every point x₀ in its domain and every ε > 0, there exists a δ > 0 such that |f(x) - f(x₀)| < ε whenever |x - x₀| < δ. | |
| Key Properties: | |
| 1. The sum, difference, and product of continuous functions are continuous | |
| 2. The composition of continuous functions is continuous | |
| 3. A continuous function on a closed interval attains its maximum and minimum values (Extreme Value Theorem) | |
| 4. A continuous function on a closed interval takes on every value between its minimum and maximum (Intermediate Value Theorem)""" | |
| async def call_api(prompt: str, temperature: float = 0.7) -> str: | |
| """调用 API 生成内容""" | |
| if not API_KEY: | |
| return "Error: API Key not configured. Please contact administrator." | |
| client = AsyncOpenAI(api_key=API_KEY, base_url=BASE_URL) | |
| try: | |
| response = await client.chat.completions.create( | |
| model=DEFAULT_MODEL, | |
| messages=[{"role": "user", "content": prompt}], | |
| temperature=temperature, | |
| max_tokens=8192, | |
| ) | |
| # 处理 reasoning model 的返回格式 | |
| message = response.choices[0].message | |
| content = message.content | |
| # 如果 content 为空,尝试获取 reasoning_content | |
| if not content and hasattr(message, 'reasoning_content') and message.reasoning_content: | |
| content = message.reasoning_content | |
| return content or "" | |
| except Exception as e: | |
| return f"Error: {str(e)}" | |
| def run_async(coro): | |
| """运行异步函数""" | |
| try: | |
| loop = asyncio.get_event_loop() | |
| except RuntimeError: | |
| loop = asyncio.new_event_loop() | |
| asyncio.set_event_loop(loop) | |
| return loop.run_until_complete(coro) | |
| # ============================================================================ | |
| # Task Handlers | |
| # ============================================================================ | |
| def qa_synthesis(text: str, level: str): | |
| """Q&A 问答对合成""" | |
| if not text.strip(): | |
| return "", "", "" | |
| prompt_template = get_qa_prompt(level) | |
| prompt = prompt_template.format(text=text) | |
| response = run_async(call_api(prompt)) | |
| parsed = parse_qa_output(response) | |
| return ( | |
| parsed.get("problem", ""), | |
| parsed.get("solution", ""), | |
| response | |
| ) | |
| def conversation_synthesis(text: str, style: str): | |
| """多轮对话合成""" | |
| if not text.strip(): | |
| return "", "" | |
| prompt_template = get_conversation_prompt(style) | |
| prompt = prompt_template.format(text=text) | |
| response = run_async(call_api(prompt)) | |
| parsed = parse_conversation_output(response) | |
| return parsed.get("content", response), response | |
| def rewrite_synthesis(text: str, style: str): | |
| """多风格改写""" | |
| if not text.strip(): | |
| return "", "" | |
| prompt_template = get_multistyle_prompt(style) | |
| prompt = prompt_template.format(text=text) | |
| response = run_async(call_api(prompt)) | |
| parsed = parse_rewrite_output(response) | |
| return parsed.get("rewritten", response), response | |
| def knowledge_extraction(text: str): | |
| """知识点提取""" | |
| if not text.strip(): | |
| return "", "" | |
| prompt_template = get_knowledge_extraction_prompt() | |
| prompt = prompt_template.format(text=text) | |
| response = run_async(call_api(prompt)) | |
| parsed = parse_knowledge_output(response) | |
| knowledge_points = parsed.get("knowledge_points", []) | |
| formatted = "\n\n---\n\n".join(knowledge_points) if knowledge_points else "No knowledge points extracted." | |
| return formatted, response | |
| def textbook_exercise(knowledge_point: str, difficulty: str): | |
| """教材练习生成""" | |
| if not knowledge_point.strip(): | |
| return "", "" | |
| prompt_template = get_textbook_exercise_prompt(difficulty) | |
| prompt = prompt_template.format(mathematical_knowledge_point=knowledge_point) | |
| response = run_async(call_api(prompt)) | |
| parsed = parse_textbook_output(response) | |
| return parsed.get("material", response), response | |
| # ============================================================================ | |
| # Gradio UI | |
| # ============================================================================ | |
| custom_css = """ | |
| @import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;600;700&family=JetBrains+Mono:wght@400;500&display=swap'); | |
| :root { | |
| --bg: #f8fafc; | |
| --surface: #ffffff; | |
| --surface-2: #f1f5f9; | |
| --border: #e2e8f0; | |
| --text: #0f172a; | |
| --muted: #1f2937; /* darker for readability */ | |
| --accent: #4f46e5; | |
| --accent-2: #6366f1; | |
| } | |
| body { | |
| background-color: var(--bg); | |
| color: var(--text); | |
| } | |
| .gradio-container { | |
| font-family: 'Inter', sans-serif !important; | |
| background: linear-gradient(180deg, #f8fafc 0%, #eef2ff 100%) !important; | |
| max-width: 1440px !important; | |
| width: 100% !important; | |
| margin-left: auto !important; | |
| margin-right: auto !important; | |
| --button-primary-text-color: #ffffff; | |
| --button-primary-text-color-hover: #ffffff; | |
| --button-primary-text-color-active: #ffffff; | |
| --button-primary-background-fill: #6366f1; | |
| --button-primary-background-fill-hover: #4f46e5; | |
| --button-primary-border-color: #6366f1; | |
| } | |
| /* Title & Header */ | |
| .main-title { | |
| font-family: 'Inter', sans-serif !important; | |
| font-weight: 800 !important; | |
| font-size: 2.6rem !important; | |
| background: linear-gradient(90deg, #0f172a, #4f46e5, #7c3aed) !important; | |
| -webkit-background-clip: text !important; | |
| -webkit-text-fill-color: transparent !important; | |
| text-align: center !important; | |
| margin-bottom: 0.4rem !important; | |
| } | |
| .subtitle { | |
| text-align: center !important; | |
| color: var(--muted) !important; | |
| font-size: 1.05rem !important; | |
| margin-bottom: 2.5rem !important; | |
| font-weight: 400 !important; | |
| } | |
| /* Panels */ | |
| .glass-panel { | |
| background: var(--surface) !important; | |
| border: 1px solid var(--border) !important; | |
| border-radius: 16px !important; | |
| padding: 24px !important; | |
| box-shadow: 0 10px 30px rgba(15, 23, 42, 0.08) !important; | |
| } | |
| /* Labels */ | |
| .block > label > span, | |
| .form > label > span, | |
| .gr-form > label > span, | |
| .label-wrap > span { | |
| color: var(--text) !important; | |
| font-weight: 600 !important; | |
| font-size: 1rem !important; | |
| margin-bottom: 0.5rem !important; | |
| text-shadow: none !important; | |
| } | |
| /* Radio group title */ | |
| fieldset legend, fieldset legend span, | |
| .gr-radio > label, .gr-radio > label span, | |
| .gradio-container .label-wrap, .gradio-container .label-wrap span { | |
| color: var(--text) !important; | |
| font-weight: 600 !important; | |
| text-shadow: none !important; | |
| } | |
| /* Info Text (Description) */ | |
| span.description, .description { | |
| color: var(--muted) !important; | |
| font-weight: 500 !important; | |
| text-shadow: none !important; | |
| opacity: 1 !important; | |
| } | |
| /* Radio/Checkbox alignment */ | |
| fieldset label span { | |
| margin-bottom: 0 !important; | |
| text-shadow: none !important; | |
| font-weight: 500 !important; | |
| color: var(--text) !important; | |
| display: flex !important; | |
| align-items: center !important; | |
| } | |
| fieldset label.selected span { | |
| color: var(--text) !important; | |
| } | |
| fieldset label.selected { | |
| background: transparent !important; | |
| border-color: transparent !important; | |
| box-shadow: none !important; | |
| } | |
| fieldset label { | |
| border: none !important; | |
| background: transparent !important; | |
| box-shadow: none !important; | |
| } | |
| /* Inputs & Textareas */ | |
| .gr-input, textarea, input, .gr-box, .gr-check-radio, .gr-dropdown { | |
| font-family: 'JetBrains Mono', monospace !important; | |
| background-color: var(--surface) !important; | |
| border: 1px solid var(--border) !important; | |
| color: var(--text) !important; | |
| box-shadow: none !important; | |
| } | |
| .gr-input:focus, textarea:focus, input:focus { | |
| border-color: var(--accent) !important; | |
| box-shadow: 0 0 0 2px rgba(79, 70, 229, 0.15) !important; | |
| } | |
| /* Dropdown options */ | |
| ul.options, .gr-dropdown-options { | |
| background-color: var(--surface) !important; | |
| color: var(--text) !important; | |
| border: 1px solid var(--border) !important; | |
| } | |
| /* Markdown prose */ | |
| .prose, .prose p, .prose h1, .prose h2, .prose h3, .prose strong, .prose li { | |
| color: var(--text) !important; | |
| } | |
| /* Outputs */ | |
| .output-textbox textarea { | |
| background-color: var(--surface-2) !important; | |
| border: 1px solid var(--border) !important; | |
| border-radius: 8px !important; | |
| color: var(--text) !important; | |
| } | |
| .markdown-box { | |
| background: var(--surface-2) !important; | |
| border: 1px solid var(--border) !important; | |
| border-radius: 8px !important; | |
| padding: 16px !important; | |
| color: var(--text) !important; | |
| } | |
| .markdown-box * { | |
| color: var(--text) !important; | |
| } | |
| .markdown-box code, .markdown-box pre { | |
| background: #e2e8f0 !important; | |
| } | |
| /* Buttons */ | |
| .gr-button-primary { | |
| background: #6366f1 !important; /* purple */ | |
| border: none !important; | |
| color: #ffffff !important; | |
| font-weight: 600 !important; | |
| box-shadow: 0 6px 14px rgba(79, 70, 229, 0.25) !important; | |
| } | |
| .gr-button-primary, | |
| .gr-button-primary span, | |
| .gr-button-primary p, | |
| .gr-button-primary .label, | |
| .gr-button-primary svg { | |
| color: #ffffff !important; | |
| -webkit-text-fill-color: #ffffff !important; | |
| fill: #ffffff !important; | |
| } | |
| .gr-button-primary, | |
| .gr-button-primary * { | |
| --button-primary-text-color: #ffffff !important; | |
| --button-primary-text-color-hover: #ffffff !important; | |
| --button-primary-text-color-active: #ffffff !important; | |
| } | |
| .gradio-container button.gr-button-primary, | |
| .gradio-container button.gr-button-primary span, | |
| .gradio-container button.primary, | |
| .gradio-container button.primary span { | |
| color: #ffffff !important; | |
| -webkit-text-fill-color: #ffffff !important; | |
| } | |
| .gr-button-secondary { | |
| background: #475569 !important; | |
| border: 1px solid #334155 !important; | |
| color: #ffffff !important; | |
| box-shadow: 0 4px 10px rgba(15, 23, 42, 0.15) !important; | |
| } | |
| .gr-button-secondary:hover { | |
| background: #334155 !important; | |
| border-color: #1f2937 !important; | |
| } | |
| .gr-button-secondary, | |
| .gr-button-secondary span, | |
| .gr-button-secondary p, | |
| .gr-button-secondary .label { | |
| color: #ffffff !important; | |
| -webkit-text-fill-color: #ffffff !important; | |
| } | |
| /* Tabs */ | |
| /* Tabs */ | |
| .tabs button { | |
| color: #0f172a !important; /* dark text for readability */ | |
| font-weight: 600 !important; | |
| } | |
| .tabs button.selected { | |
| color: #ffffff !important; | |
| background: var(--accent) !important; | |
| border-radius: 0 !important; | |
| padding: 4px 10px !important; | |
| border-bottom: none !important; | |
| box-shadow: none !important; | |
| } | |
| .tabs button.selected::after { | |
| display: none !important; | |
| content: none !important; | |
| border-bottom: none !important; | |
| } | |
| /* Radio buttons */ | |
| .gr-radio-label { | |
| color: var(--text) !important; | |
| } | |
| /* Radio: custom filled dot */ | |
| .gr-check-radio input[type="radio"] { | |
| appearance: none !important; | |
| -webkit-appearance: none !important; | |
| -moz-appearance: none !important; | |
| width: 16px !important; | |
| height: 16px !important; | |
| border-radius: 999px !important; | |
| border: 2px solid #cbd5e1 !important; | |
| background: transparent !important; | |
| display: inline-block !important; | |
| position: relative !important; | |
| box-sizing: border-box !important; | |
| vertical-align: middle !important; | |
| } | |
| fieldset label.selected input[type="radio"] { | |
| border-color: var(--accent) !important; | |
| background: radial-gradient(circle at center, #4f46e5 0 5px, transparent 5px) !important; | |
| } | |
| /* Footer */ | |
| .footer-text, .footer-text p { | |
| color: var(--muted) !important; | |
| } | |
| .footer-text a { | |
| color: var(--accent) !important; | |
| } | |
| """ | |
| extra_css = """ | |
| <style> | |
| .gradio-container button.gr-button-primary, | |
| .gradio-container button.gr-button-primary span, | |
| .gradio-container button.gr-button-primary p { | |
| color: #ffffff !important; | |
| -webkit-text-fill-color: #ffffff !important; | |
| } | |
| </style> | |
| """ | |
| with gr.Blocks(title="UltraData-Math-L3-Generator", css=custom_css, theme=gr.themes.Soft()) as demo: | |
| gr.HTML('<h1 class="main-title">UltraData-Math-L3-Generator</h1>') | |
| gr.HTML('<p class="subtitle">✨ Next-Gen Mathematical Data Synthesis Powered by LLM ✨</p>') | |
| gr.HTML(extra_css) | |
| with gr.Tabs(): | |
| # Q&A Synthesis Tab | |
| with gr.TabItem("📝 Q&A Synthesis"): | |
| with gr.Column(elem_classes=["glass-panel"]): | |
| gr.Markdown("### 💡 Transform Text into Q&A Pairs\nGenerate high-quality question-answer pairs from mathematical content, tailored to different educational levels.") | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| qa_input = gr.Textbox( | |
| label="Input Mathematical Content", | |
| placeholder="Paste your mathematical text here (e.g., definitions, theorems, proofs)...", | |
| lines=10, | |
| ) | |
| qa_level = gr.Radio( | |
| choices=list(QA_PROMPTS.keys()), | |
| value="high_school", | |
| label="Difficulty Level", | |
| info="Select the target audience level" | |
| ) | |
| with gr.Row(): | |
| qa_example_btn = gr.Button("Load Example", variant="secondary") | |
| qa_btn = gr.Button("Generate", variant="primary") | |
| with gr.Column(scale=1): | |
| qa_problem = gr.Textbox(label="Generated Problem", lines=5) | |
| qa_solution = gr.Textbox(label="Generated Solution", lines=12) | |
| qa_raw = gr.Textbox(label="Raw Response", lines=4, visible=False) | |
| qa_example_btn.click( | |
| lambda: EXAMPLE_MATH_CONTENT, | |
| outputs=[qa_input], | |
| ) | |
| qa_btn.click( | |
| qa_synthesis, | |
| inputs=[qa_input, qa_level], | |
| outputs=[qa_problem, qa_solution, qa_raw], | |
| ) | |
| # Conversation Synthesis Tab | |
| with gr.TabItem("💬 Conversation Synthesis"): | |
| with gr.Column(elem_classes=["glass-panel"]): | |
| gr.Markdown("### 🗣️ Create Multi-turn Dialogues\nConvert static mathematical text into dynamic, engaging multi-turn conversations between students and teachers.") | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| conv_input = gr.Textbox( | |
| label="Input Mathematical Content", | |
| placeholder="Paste your mathematical text here...", | |
| lines=10, | |
| ) | |
| conv_style = gr.Radio( | |
| choices=list(CONVERSATION_PROMPTS.keys()), | |
| value="teacher_student", | |
| label="Conversation Style", | |
| info="Choose the persona and tone of the conversation" | |
| ) | |
| with gr.Row(): | |
| conv_example_btn = gr.Button("Load Example", variant="secondary") | |
| conv_btn = gr.Button("Generate", variant="primary") | |
| with gr.Column(scale=1): | |
| conv_output = gr.Textbox(label="Generated Conversation", lines=20) | |
| conv_raw = gr.Textbox(label="Raw Response", lines=4, visible=False) | |
| conv_example_btn.click( | |
| lambda: EXAMPLE_MATH_CONTENT, | |
| outputs=[conv_input], | |
| ) | |
| conv_btn.click( | |
| conversation_synthesis, | |
| inputs=[conv_input, conv_style], | |
| outputs=[conv_output, conv_raw], | |
| ) | |
| # Rewrite Tab | |
| with gr.TabItem("✨ Multi-style Rewrite"): | |
| with gr.Column(elem_classes=["glass-panel"]): | |
| gr.Markdown("### 🎨 Style Transfer\nRewrite mathematical content into various styles, from rigorous textbooks to engaging blog posts.") | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| rewrite_input = gr.Textbox( | |
| label="Input Mathematical Content", | |
| placeholder="Paste your mathematical text here...", | |
| lines=10, | |
| ) | |
| rewrite_style = gr.Radio( | |
| choices=list(MULTISTYLE_PROMPTS.keys()), | |
| value="textbook", | |
| label="Target Style", | |
| info="Select the desired output style" | |
| ) | |
| with gr.Row(): | |
| rewrite_example_btn = gr.Button("Load Example", variant="secondary") | |
| rewrite_btn = gr.Button("Generate", variant="primary") | |
| with gr.Column(scale=1): | |
| rewrite_output = gr.Textbox(label="Rewritten Content", lines=20) | |
| rewrite_raw = gr.Textbox(label="Raw Response", lines=4, visible=False) | |
| rewrite_example_btn.click( | |
| lambda: EXAMPLE_MATH_CONTENT, | |
| outputs=[rewrite_input], | |
| ) | |
| rewrite_btn.click( | |
| rewrite_synthesis, | |
| inputs=[rewrite_input, rewrite_style], | |
| outputs=[rewrite_output, rewrite_raw], | |
| ) | |
| # Knowledge Extraction Tab | |
| with gr.TabItem("📚 Knowledge Extraction"): | |
| with gr.Column(elem_classes=["glass-panel"]): | |
| gr.Markdown("### 🧠 Extract Core Knowledge\nAutomatically identify and extract key definitions, theorems, and properties from unstructured text.") | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| know_input = gr.Textbox( | |
| label="Input Mathematical Content", | |
| placeholder="Paste your mathematical text here...", | |
| lines=12, | |
| ) | |
| with gr.Row(): | |
| know_example_btn = gr.Button("Load Example", variant="secondary") | |
| know_btn = gr.Button("Generate", variant="primary") | |
| with gr.Column(scale=1): | |
| know_output = gr.Textbox(label="Extracted Knowledge Points", lines=20) | |
| know_raw = gr.Textbox(label="Raw Response", lines=4, visible=False) | |
| know_example_btn.click( | |
| lambda: EXAMPLE_MATH_CONTENT, | |
| outputs=[know_input], | |
| ) | |
| know_btn.click( | |
| knowledge_extraction, | |
| inputs=[know_input], | |
| outputs=[know_output, know_raw], | |
| ) | |
| # Textbook Exercise Tab | |
| with gr.TabItem("📖 Textbook Exercise"): | |
| with gr.Column(elem_classes=["glass-panel"]): | |
| gr.Markdown("### 📝 Generate Exercises\nCreate comprehensive textbook-style exercises and problems based on specific knowledge points.") | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| textbook_input = gr.Textbox( | |
| label="Input Knowledge Point", | |
| placeholder="Enter a specific mathematical concept or theorem...", | |
| lines=8, | |
| ) | |
| textbook_diff = gr.Radio( | |
| choices=list(TEXTBOOK_EXERCISE_PROMPTS.keys()), | |
| value="easy", | |
| label="Difficulty", | |
| info="Select the problem difficulty" | |
| ) | |
| with gr.Row(): | |
| textbook_example_btn = gr.Button("Load Example", variant="secondary") | |
| textbook_btn = gr.Button("Generate", variant="primary") | |
| with gr.Column(scale=1): | |
| textbook_output = gr.Textbox(label="Generated Exercise Material", lines=20) | |
| textbook_raw = gr.Textbox(label="Raw Response", lines=4, visible=False) | |
| textbook_example_btn.click( | |
| lambda: EXAMPLE_KNOWLEDGE_POINT, | |
| outputs=[textbook_input], | |
| ) | |
| textbook_btn.click( | |
| textbook_exercise, | |
| inputs=[textbook_input, textbook_diff], | |
| outputs=[textbook_output, textbook_raw], | |
| ) | |
| gr.HTML(""" | |
| <div class="footer-text"> | |
| <p>🔬 <strong>UltraData-Math-L3-Generator</strong> - Part of the UltraData-Math Project</p> | |
| <p>Powered by OpenBMB & ModelBest • <a href="https://huggingface.co/spaces/openbmb/UltraData-Math-L3-Generator" target="_blank" style="color: #818cf8; text-decoration: none;">View on Hugging Face</a></p> | |
| </div> | |
| """) | |
| if __name__ == "__main__": | |
| demo.launch(ssr_mode=False) | |