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""" |
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UltraData-Math-L3-Generator - Hugging Face Space Demo |
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""" |
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import os |
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import asyncio |
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import gradio as gr |
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from openai import AsyncOpenAI |
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from qa_synthesis import QA_PROMPTS, get_qa_prompt |
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from conversation_synthesis import CONVERSATION_PROMPTS, get_conversation_prompt |
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from multistyle_rewrite import MULTISTYLE_PROMPTS, get_multistyle_prompt |
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from knowledge_textbook import ( |
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get_knowledge_extraction_prompt, |
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get_textbook_exercise_prompt, |
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TEXTBOOK_EXERCISE_PROMPTS, |
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) |
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from run_synthesis import ( |
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parse_qa_output, |
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parse_conversation_output, |
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parse_rewrite_output, |
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parse_knowledge_output, |
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parse_textbook_output, |
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) |
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API_KEY = os.getenv("OPENAI_API_KEY") |
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BASE_URL = os.getenv("OPENAI_BASE_URL", "https://llm-center.ali.modelbest.cn/llm/openai/v1") |
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DEFAULT_MODEL = "GEMINI_anxt74" |
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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. |
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The formula states that the solutions are: |
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x = (-b ± √(b² - 4ac)) / (2a) |
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The term b² - 4ac is called the discriminant. It determines the nature of the roots: |
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- If b² - 4ac > 0, there are two distinct real roots |
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- If b² - 4ac = 0, there is exactly one real root (a repeated root) |
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- If b² - 4ac < 0, there are two complex conjugate roots |
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This formula was known to ancient mathematicians and remains one of the most important tools in solving polynomial equations.""" |
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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. |
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Key Properties: |
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1. The sum, difference, and product of continuous functions are continuous |
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2. The composition of continuous functions is continuous |
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3. A continuous function on a closed interval attains its maximum and minimum values (Extreme Value Theorem) |
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4. A continuous function on a closed interval takes on every value between its minimum and maximum (Intermediate Value Theorem)""" |
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async def call_api(prompt: str, temperature: float = 0.7) -> str: |
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"""调用 API 生成内容""" |
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if not API_KEY: |
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return "Error: API Key not configured. Please contact administrator." |
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client = AsyncOpenAI(api_key=API_KEY, base_url=BASE_URL) |
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try: |
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response = await client.chat.completions.create( |
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model=DEFAULT_MODEL, |
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messages=[{"role": "user", "content": prompt}], |
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temperature=temperature, |
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max_tokens=8192, |
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) |
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message = response.choices[0].message |
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content = message.content |
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if not content and hasattr(message, 'reasoning_content') and message.reasoning_content: |
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content = message.reasoning_content |
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return content or "" |
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except Exception as e: |
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return f"Error: {str(e)}" |
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def run_async(coro): |
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"""运行异步函数""" |
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try: |
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loop = asyncio.get_event_loop() |
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except RuntimeError: |
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loop = asyncio.new_event_loop() |
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asyncio.set_event_loop(loop) |
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return loop.run_until_complete(coro) |
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def qa_synthesis(text: str, level: str): |
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"""Q&A 问答对合成""" |
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if not text.strip(): |
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return "", "", "" |
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prompt_template = get_qa_prompt(level) |
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prompt = prompt_template.format(text=text) |
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response = run_async(call_api(prompt)) |
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parsed = parse_qa_output(response) |
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return ( |
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parsed.get("problem", ""), |
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parsed.get("solution", ""), |
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response |
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) |
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def conversation_synthesis(text: str, style: str): |
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"""多轮对话合成""" |
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if not text.strip(): |
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return "", "" |
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prompt_template = get_conversation_prompt(style) |
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prompt = prompt_template.format(text=text) |
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response = run_async(call_api(prompt)) |
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parsed = parse_conversation_output(response) |
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return parsed.get("content", response), response |
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def rewrite_synthesis(text: str, style: str): |
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"""多风格改写""" |
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if not text.strip(): |
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return "", "" |
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prompt_template = get_multistyle_prompt(style) |
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prompt = prompt_template.format(text=text) |
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response = run_async(call_api(prompt)) |
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parsed = parse_rewrite_output(response) |
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return parsed.get("rewritten", response), response |
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def knowledge_extraction(text: str): |
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"""知识点提取""" |
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if not text.strip(): |
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return "", "" |
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prompt_template = get_knowledge_extraction_prompt() |
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prompt = prompt_template.format(text=text) |
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response = run_async(call_api(prompt)) |
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parsed = parse_knowledge_output(response) |
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knowledge_points = parsed.get("knowledge_points", []) |
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formatted = "\n\n---\n\n".join(knowledge_points) if knowledge_points else "No knowledge points extracted." |
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return formatted, response |
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def textbook_exercise(knowledge_point: str, difficulty: str): |
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"""教材练习生成""" |
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if not knowledge_point.strip(): |
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return "", "" |
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prompt_template = get_textbook_exercise_prompt(difficulty) |
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prompt = prompt_template.format(mathematical_knowledge_point=knowledge_point) |
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response = run_async(call_api(prompt)) |
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parsed = parse_textbook_output(response) |
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return parsed.get("material", response), response |
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custom_css = """ |
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@import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;600;700&family=JetBrains+Mono:wght@400;500&display=swap'); |
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:root { |
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--bg: #f8fafc; |
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--surface: #ffffff; |
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--surface-2: #f1f5f9; |
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--border: #e2e8f0; |
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--text: #0f172a; |
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--muted: #1f2937; /* darker for readability */ |
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--accent: #4f46e5; |
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--accent-2: #6366f1; |
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} |
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body { |
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background-color: var(--bg); |
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color: var(--text); |
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} |
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.gradio-container { |
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font-family: 'Inter', sans-serif !important; |
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background: linear-gradient(180deg, #f8fafc 0%, #eef2ff 100%) !important; |
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max-width: 1440px !important; |
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width: 100% !important; |
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margin-left: auto !important; |
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margin-right: auto !important; |
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--button-primary-text-color: #ffffff; |
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--button-primary-text-color-hover: #ffffff; |
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--button-primary-text-color-active: #ffffff; |
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--button-primary-background-fill: #6366f1; |
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--button-primary-background-fill-hover: #4f46e5; |
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--button-primary-border-color: #6366f1; |
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} |
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/* Title & Header */ |
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.main-title { |
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font-family: 'Inter', sans-serif !important; |
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font-weight: 800 !important; |
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font-size: 2.6rem !important; |
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background: linear-gradient(90deg, #0f172a, #4f46e5, #7c3aed) !important; |
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-webkit-background-clip: text !important; |
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-webkit-text-fill-color: transparent !important; |
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text-align: center !important; |
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margin-bottom: 0.4rem !important; |
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} |
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.subtitle { |
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text-align: center !important; |
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color: var(--muted) !important; |
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font-size: 1.05rem !important; |
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margin-bottom: 2.5rem !important; |
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font-weight: 400 !important; |
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} |
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/* Panels */ |
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.glass-panel { |
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background: var(--surface) !important; |
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border: 1px solid var(--border) !important; |
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border-radius: 16px !important; |
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padding: 24px !important; |
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box-shadow: 0 10px 30px rgba(15, 23, 42, 0.08) !important; |
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} |
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/* Labels */ |
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.block > label > span, |
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.form > label > span, |
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.gr-form > label > span, |
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.label-wrap > span { |
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color: var(--text) !important; |
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font-weight: 600 !important; |
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font-size: 1rem !important; |
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margin-bottom: 0.5rem !important; |
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text-shadow: none !important; |
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} |
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/* Radio group title */ |
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fieldset legend, fieldset legend span, |
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.gr-radio > label, .gr-radio > label span, |
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.gradio-container .label-wrap, .gradio-container .label-wrap span { |
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color: var(--text) !important; |
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font-weight: 600 !important; |
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text-shadow: none !important; |
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} |
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/* Info Text (Description) */ |
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span.description, .description { |
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color: var(--muted) !important; |
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font-weight: 500 !important; |
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text-shadow: none !important; |
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opacity: 1 !important; |
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} |
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|
/* Radio/Checkbox alignment */ |
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fieldset label span { |
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margin-bottom: 0 !important; |
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text-shadow: none !important; |
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font-weight: 500 !important; |
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color: var(--text) !important; |
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display: flex !important; |
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align-items: center !important; |
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} |
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fieldset label.selected span { |
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color: var(--text) !important; |
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} |
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fieldset label.selected { |
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background: transparent !important; |
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border-color: transparent !important; |
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box-shadow: none !important; |
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} |
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|
fieldset label { |
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border: none !important; |
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background: transparent !important; |
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box-shadow: none !important; |
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} |
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|
/* Inputs & Textareas */ |
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.gr-input, textarea, input, .gr-box, .gr-check-radio, .gr-dropdown { |
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|
font-family: 'JetBrains Mono', monospace !important; |
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|
background-color: var(--surface) !important; |
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|
border: 1px solid var(--border) !important; |
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|
color: var(--text) !important; |
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|
box-shadow: none !important; |
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|
} |
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|
.gr-input:focus, textarea:focus, input:focus { |
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|
border-color: var(--accent) !important; |
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|
box-shadow: 0 0 0 2px rgba(79, 70, 229, 0.15) !important; |
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} |
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|
/* Dropdown options */ |
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|
ul.options, .gr-dropdown-options { |
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|
background-color: var(--surface) !important; |
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|
color: var(--text) !important; |
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|
border: 1px solid var(--border) !important; |
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|
} |
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|
/* Markdown prose */ |
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|
.prose, .prose p, .prose h1, .prose h2, .prose h3, .prose strong, .prose li { |
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|
color: var(--text) !important; |
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|
} |
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|
/* Outputs */ |
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|
.output-textbox textarea { |
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|
background-color: var(--surface-2) !important; |
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|
border: 1px solid var(--border) !important; |
|
|
border-radius: 8px !important; |
|
|
color: var(--text) !important; |
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|
} |
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|
.markdown-box { |
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|
background: var(--surface-2) !important; |
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|
border: 1px solid var(--border) !important; |
|
|
border-radius: 8px !important; |
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padding: 16px !important; |
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|
color: var(--text) !important; |
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} |
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|
.markdown-box * { |
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|
color: var(--text) !important; |
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|
} |
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|
.markdown-box code, .markdown-box pre { |
|
|
background: #e2e8f0 !important; |
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|
} |
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|
/* Buttons */ |
|
|
.gr-button-primary { |
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|
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, |
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|
.gr-button-primary span, |
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|
.gr-button-primary p, |
|
|
.gr-button-primary .label, |
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|
.gr-button-primary svg { |
|
|
color: #ffffff !important; |
|
|
-webkit-text-fill-color: #ffffff !important; |
|
|
fill: #ffffff !important; |
|
|
} |
|
|
.gr-button-primary, |
|
|
.gr-button-primary * { |
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|
--button-primary-text-color: #ffffff !important; |
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|
--button-primary-text-color-hover: #ffffff !important; |
|
|
--button-primary-text-color-active: #ffffff !important; |
|
|
} |
|
|
.gradio-container button.gr-button-primary, |
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|
.gradio-container button.gr-button-primary span, |
|
|
.gradio-container button.primary, |
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|
.gradio-container button.primary span { |
|
|
color: #ffffff !important; |
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|
-webkit-text-fill-color: #ffffff !important; |
|
|
} |
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|
.gr-button-secondary { |
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|
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; |
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|
border-color: #1f2937 !important; |
|
|
} |
|
|
.gr-button-secondary, |
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|
.gr-button-secondary span, |
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|
.gr-button-secondary p, |
|
|
.gr-button-secondary .label { |
|
|
color: #ffffff !important; |
|
|
-webkit-text-fill-color: #ffffff !important; |
|
|
} |
|
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|
|
|
/* 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) |
|
|
|