| |
| """ |
| 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_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" |
|
|
| |
| 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, |
| ) |
| |
| message = response.choices[0].message |
| content = message.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) |
|
|
|
|
| |
| |
| |
|
|
| 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 |
|
|
|
|
| |
| |
| |
|
|
| 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(): |
| |
| 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], |
| ) |
| |
| |
| 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], |
| ) |
| |
| |
| 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], |
| ) |
| |
| |
| 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], |
| ) |
| |
| |
| 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) |
|
|