786 lines
28 KiB
Python
786 lines
28 KiB
Python
"""
|
||
title: 闪记卡 (Flash Card)
|
||
author: Fu-Jie
|
||
author_url: https://github.com/Fu-Jie/openwebui-extensions
|
||
funding_url: https://github.com/open-webui
|
||
version: 0.2.4
|
||
openwebui_id: 4a31eac3-a3c4-4c30-9ca5-dab36b5fac65
|
||
icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPjxwb2x5Z29uIHBvaW50cz0iMTIgMiAyIDcgMTIgMTIgMjIgNyAxMiAyIi8+PHBvbHlsaW5lIHBvaW50cz0iMiAxNyAxMiAyMiAyMiAxNyIvPjxwb2x5bGluZSBwb2ludHM9IjIgMTIgMTIgMTcgMjIgMTIiLz48L3N2Zz4=
|
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description: 快速将文本提炼为精美的学习记忆卡片，支持核心要点提取与分类。
|
||
"""
|
||
|
||
from pydantic import BaseModel, Field
|
||
from typing import Optional, Dict, Any, List
|
||
import json
|
||
import logging
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||
import re
|
||
from open_webui.utils.chat import generate_chat_completion
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from open_webui.models.users import Users
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||
|
||
# Setup logging
|
||
logging.basicConfig(level=logging.INFO)
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||
logger = logging.getLogger(__name__)
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||
|
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HTML_WRAPPER_TEMPLATE = """
|
||
<!-- OPENWEBUI_PLUGIN_OUTPUT -->
|
||
<!DOCTYPE html>
|
||
<html lang="{user_language}">
|
||
<head>
|
||
<meta charset="UTF-8">
|
||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||
<style>
|
||
body {
|
||
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Helvetica, Arial, sans-serif;
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||
margin: 0;
|
||
padding: 10px;
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||
background-color: transparent;
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||
}
|
||
#main-container {
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||
display: flex;
|
||
flex-wrap: wrap;
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||
gap: 20px;
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||
align-items: flex-start;
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||
width: 100%;
|
||
}
|
||
.plugin-item {
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||
flex: 1 1 400px; /* 默认宽度，允许伸缩 */
|
||
min-width: 300px;
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||
background: white;
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||
border-radius: 12px;
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||
box-shadow: 0 4px 6px rgba(0,0,0,0.05);
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||
overflow: hidden;
|
||
border: 1px solid #e5e7eb;
|
||
transition: all 0.3s ease;
|
||
}
|
||
.plugin-item:hover {
|
||
box-shadow: 0 10px 15px rgba(0,0,0,0.1);
|
||
}
|
||
@media (max-width: 768px) {
|
||
.plugin-item { flex: 1 1 100%; }
|
||
}
|
||
/* STYLES_INSERTION_POINT */
|
||
</style>
|
||
</head>
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||
<body>
|
||
<div id="main-container">
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||
<!-- CONTENT_INSERTION_POINT -->
|
||
</div>
|
||
<!-- SCRIPTS_INSERTION_POINT -->
|
||
</body>
|
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</html>
|
||
"""
|
||
|
||
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class Action:
|
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class Valves(BaseModel):
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MODEL_ID: str = Field(
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||
default="",
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description="用于生成卡片内容的模型 ID。如果为空，则使用当前模型。",
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||
)
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||
MIN_TEXT_LENGTH: int = Field(
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||
default=50, description="生成闪记卡所需的最小文本长度（字符数）。"
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||
)
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||
LANGUAGE: str = Field(
|
||
default="zh", description="卡片内容的目标语言 (例如 'zh', 'en')。"
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||
)
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||
SHOW_STATUS: bool = Field(
|
||
default=True, description="是否在聊天界面显示状态更新。"
|
||
)
|
||
SHOW_DEBUG_LOG: bool = Field(
|
||
default=False,
|
||
description="是否在浏览器控制台打印调试日志。",
|
||
)
|
||
CLEAR_PREVIOUS_HTML: bool = Field(
|
||
default=False,
|
||
description="是否强制清除旧的插件结果（如果为 True，则不合并，直接覆盖）。",
|
||
)
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||
MESSAGE_COUNT: int = Field(
|
||
default=1,
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||
description="用于生成的最近消息数量。设置为1仅使用最后一条消息，更大值可包含更多上下文。",
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||
)
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||
|
||
def __init__(self):
|
||
self.valves = self.Valves()
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|
||
def _get_user_context(self, __user__: Optional[Dict[str, Any]]) -> Dict[str, str]:
|
||
"""安全提取用户上下文信息，支持多种输入格式。"""
|
||
if isinstance(__user__, (list, tuple)):
|
||
user_data = __user__[0] if __user__ else {}
|
||
elif isinstance(__user__, dict):
|
||
user_data = __user__
|
||
else:
|
||
user_data = {}
|
||
|
||
return {
|
||
"user_id": user_data.get("id", "unknown_user"),
|
||
"user_name": user_data.get("name", "用户"),
|
||
"user_language": user_data.get("language", "zh-CN"),
|
||
}
|
||
|
||
def _get_chat_context(
|
||
self, body: dict, __metadata__: Optional[dict] = None
|
||
) -> Dict[str, str]:
|
||
"""
|
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统一提取聊天上下文信息 (chat_id, message_id)。
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优先从 body 中提取，其次从 metadata 中提取。
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||
"""
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chat_id = ""
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message_id = ""
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||
|
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# 1. 尝试从 body 获取
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||
if isinstance(body, dict):
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chat_id = body.get("chat_id", "")
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message_id = body.get("id", "") # message_id 在 body 中通常是 id
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||
|
||
# 再次检查 body.metadata
|
||
if not chat_id or not message_id:
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||
body_metadata = body.get("metadata", {})
|
||
if isinstance(body_metadata, dict):
|
||
if not chat_id:
|
||
chat_id = body_metadata.get("chat_id", "")
|
||
if not message_id:
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||
message_id = body_metadata.get("message_id", "")
|
||
|
||
# 2. 尝试从 __metadata__ 获取 (作为补充)
|
||
if __metadata__ and isinstance(__metadata__, dict):
|
||
if not chat_id:
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chat_id = __metadata__.get("chat_id", "")
|
||
if not message_id:
|
||
message_id = __metadata__.get("message_id", "")
|
||
|
||
return {
|
||
"chat_id": str(chat_id).strip(),
|
||
"message_id": str(message_id).strip(),
|
||
}
|
||
|
||
async def action(
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||
self,
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||
body: dict,
|
||
__user__: Optional[Dict[str, Any]] = None,
|
||
__event_emitter__: Optional[Any] = None,
|
||
__request__: Optional[Any] = None,
|
||
) -> Optional[dict]:
|
||
logger.info(f"Action: {__name__} 触发")
|
||
|
||
if not __event_emitter__:
|
||
return body
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||
|
||
# Get messages based on MESSAGE_COUNT
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||
messages = body.get("messages", [])
|
||
if not messages:
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||
return body
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||
|
||
# Get last N messages based on MESSAGE_COUNT
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||
message_count = min(self.valves.MESSAGE_COUNT, len(messages))
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||
recent_messages = messages[-message_count:]
|
||
|
||
# Aggregate content from selected messages with labels
|
||
aggregated_parts = []
|
||
for i, msg in enumerate(recent_messages, 1):
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||
text_content = self._extract_text_content(msg.get("content"))
|
||
if text_content:
|
||
role = msg.get("role", "unknown")
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||
role_label = (
|
||
"用户"
|
||
if role == "user"
|
||
else "助手" if role == "assistant" else role
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||
)
|
||
aggregated_parts.append(f"{text_content}")
|
||
|
||
if not aggregated_parts:
|
||
return body
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||
|
||
target_message = "\n\n---\n\n".join(aggregated_parts)
|
||
|
||
# Check text length
|
||
text_length = len(target_message)
|
||
if text_length < self.valves.MIN_TEXT_LENGTH:
|
||
await self._emit_notification(
|
||
__event_emitter__,
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||
f"文本内容过短 ({text_length} 字符)，建议至少 {self.valves.MIN_TEXT_LENGTH} 字符。",
|
||
"warning",
|
||
)
|
||
return body
|
||
|
||
# Notify user that we are generating the card
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||
await self._emit_notification(__event_emitter__, "⚡ 正在生成闪记卡...", "info")
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||
await self._emit_status(__event_emitter__, "⚡ 闪记卡: 开始生成...", done=False)
|
||
|
||
try:
|
||
# 1. Extract information using LLM
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||
await self._emit_status(
|
||
__event_emitter__, "⚡ 闪记卡: 正在调用 AI 模型分析内容...", done=False
|
||
)
|
||
|
||
user_ctx = self._get_user_context(__user__)
|
||
user_id = user_ctx["user_id"]
|
||
user_obj = Users.get_user_by_id(user_id)
|
||
|
||
target_model = (
|
||
self.valves.MODEL_ID if self.valves.MODEL_ID else body.get("model")
|
||
)
|
||
|
||
system_prompt = f"""
|
||
你是一个闪记卡生成专家，专注于创建适合学习和记忆的知识卡片。你的任务是将文本提炼成简洁、易记的学习卡片。
|
||
|
||
请提取以下字段，并以 JSON 格式返回：
|
||
1. "title": 创建一个简短、精准的标题（3-8 个词），突出核心概念
|
||
2. "summary": 用一句话总结核心要义（10-25 个词），要通俗易懂、便于记忆
|
||
3. "key_points": 列出 3-5 个关键记忆点（每个 5-15 个词）
|
||
- 每个要点应该是独立的知识点
|
||
- 使用简洁、口语化的表达
|
||
- 避免冗长的句子
|
||
4. "tags": 列出 2-4 个分类标签（每个 1-3 个词）
|
||
5. "category": 选择一个主分类（如：概念、技能、事实、方法等）
|
||
|
||
目标语言: {self.valves.LANGUAGE}
|
||
|
||
重要原则：
|
||
- **极简主义**: 每个要点都要精炼到极致
|
||
- **记忆优先**: 内容要便于记忆和回忆
|
||
- **核心聚焦**: 只提取最核心的知识点
|
||
- **口语化**: 使用通俗易懂的语言
|
||
- 只返回 JSON 对象，不要包含 markdown 格式
|
||
"""
|
||
|
||
prompt = f"请将以下文本提炼成一张学习记忆卡片：\n\n{target_message}"
|
||
|
||
payload = {
|
||
"model": target_model,
|
||
"messages": [
|
||
{"role": "system", "content": system_prompt},
|
||
{"role": "user", "content": prompt},
|
||
],
|
||
"stream": False,
|
||
}
|
||
|
||
response = await generate_chat_completion(__request__, payload, user_obj)
|
||
content = response["choices"][0]["message"]["content"]
|
||
|
||
await self._emit_status(
|
||
__event_emitter__, "⚡ 闪记卡: AI 分析完成，正在解析数据...", done=False
|
||
)
|
||
|
||
# Parse JSON
|
||
try:
|
||
# simple cleanup in case of markdown code blocks
|
||
if "```json" in content:
|
||
content = content.split("```json")[1].split("```")[0].strip()
|
||
elif "```" in content:
|
||
content = content.split("```")[1].split("```")[0].strip()
|
||
|
||
card_data = json.loads(content)
|
||
except Exception as e:
|
||
logger.error(f"Failed to parse JSON: {e}, content: {content}")
|
||
await self._emit_status(
|
||
__event_emitter__, "❌ 闪记卡: 数据解析失败", done=True
|
||
)
|
||
await self._emit_notification(
|
||
__event_emitter__, "❌ 生成卡片数据失败，请重试。", "error"
|
||
)
|
||
return body
|
||
|
||
# 2. Generate HTML components
|
||
await self._emit_status(
|
||
__event_emitter__, "⚡ 闪记卡: 正在渲染卡片...", done=False
|
||
)
|
||
card_content, card_style = self.generate_html_card_components(card_data)
|
||
|
||
# 3. Append to message
|
||
# Extract existing HTML if any
|
||
existing_html_block = ""
|
||
match = re.search(
|
||
r"```html\s*(<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?)```",
|
||
body["messages"][-1]["content"],
|
||
)
|
||
if match:
|
||
existing_html_block = match.group(1)
|
||
|
||
if self.valves.CLEAR_PREVIOUS_HTML:
|
||
body["messages"][-1]["content"] = self._remove_existing_html(
|
||
body["messages"][-1]["content"]
|
||
)
|
||
final_html = self._merge_html(
|
||
"", card_content, card_style, "", self.valves.LANGUAGE
|
||
)
|
||
else:
|
||
if existing_html_block:
|
||
body["messages"][-1]["content"] = self._remove_existing_html(
|
||
body["messages"][-1]["content"]
|
||
)
|
||
final_html = self._merge_html(
|
||
existing_html_block,
|
||
card_content,
|
||
card_style,
|
||
"",
|
||
self.valves.LANGUAGE,
|
||
)
|
||
else:
|
||
final_html = self._merge_html(
|
||
"", card_content, card_style, "", self.valves.LANGUAGE
|
||
)
|
||
|
||
html_embed_tag = f"```html\n{final_html}\n```"
|
||
body["messages"][-1]["content"] += f"\n\n{html_embed_tag}"
|
||
|
||
await self._emit_status(
|
||
__event_emitter__, "✅ 闪记卡: 生成完成！", done=True
|
||
)
|
||
await self._emit_notification(
|
||
__event_emitter__, "⚡ 闪记卡生成成功！", "success"
|
||
)
|
||
|
||
return body
|
||
|
||
except Exception as e:
|
||
logger.error(f"Error generating knowledge card: {e}")
|
||
await self._emit_status(__event_emitter__, "❌ 闪记卡: 生成失败", done=True)
|
||
await self._emit_notification(
|
||
__event_emitter__, f"❌ 生成知识卡片时出错: {str(e)}", "error"
|
||
)
|
||
return body
|
||
|
||
async def _emit_status(self, emitter, description: str, done: bool = False):
|
||
"""发送状态更新事件。"""
|
||
if self.valves.SHOW_STATUS and emitter:
|
||
await emitter(
|
||
{"type": "status", "data": {"description": description, "done": done}}
|
||
)
|
||
|
||
async def _emit_notification(self, emitter, content: str, ntype: str = "info"):
|
||
"""发送通知事件 (info/success/warning/error)。"""
|
||
if emitter:
|
||
await emitter(
|
||
{"type": "notification", "data": {"type": ntype, "content": content}}
|
||
)
|
||
|
||
async def _emit_debug_log(self, emitter, title: str, data: dict):
|
||
"""在浏览器控制台打印结构化调试日志"""
|
||
if not self.valves.SHOW_DEBUG_LOG or not emitter:
|
||
return
|
||
|
||
try:
|
||
import json
|
||
|
||
js_code = f"""
|
||
(async function() {{
|
||
console.group("🛠️ {title}");
|
||
console.log({json.dumps(data, ensure_ascii=False)});
|
||
console.groupEnd();
|
||
}})();
|
||
"""
|
||
|
||
await emitter({"type": "execute", "data": {"code": js_code}})
|
||
except Exception as e:
|
||
print(f"Error emitting debug log: {e}")
|
||
|
||
def _remove_existing_html(self, content: str) -> str:
|
||
"""移除内容中已有的插件生成 HTML 代码块 (通过标记识别)。"""
|
||
pattern = r"```html\s*<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?```"
|
||
return re.sub(pattern, "", content).strip()
|
||
|
||
def _extract_text_content(self, content) -> str:
|
||
"""从消息内容中提取文本，支持多模态消息格式"""
|
||
if isinstance(content, str):
|
||
return content
|
||
elif isinstance(content, list):
|
||
# 多模态消息: [{"type": "text", "text": "..."}, {"type": "image_url", ...}]
|
||
text_parts = []
|
||
for item in content:
|
||
if isinstance(item, dict) and item.get("type") == "text":
|
||
text_parts.append(item.get("text", ""))
|
||
elif isinstance(item, str):
|
||
text_parts.append(item)
|
||
return "\n".join(text_parts)
|
||
return str(content) if content else ""
|
||
|
||
def _merge_html(
|
||
self,
|
||
existing_html_code: str,
|
||
new_content: str,
|
||
new_styles: str = "",
|
||
new_scripts: str = "",
|
||
user_language: str = "zh-CN",
|
||
) -> str:
|
||
"""
|
||
将新内容合并到现有的 HTML 容器中，或者创建一个新的容器。
|
||
"""
|
||
if (
|
||
"<!-- OPENWEBUI_PLUGIN_OUTPUT -->" in existing_html_code
|
||
and "<!-- CONTENT_INSERTION_POINT -->" in existing_html_code
|
||
):
|
||
base_html = existing_html_code
|
||
base_html = re.sub(r"^```html\s*", "", base_html)
|
||
base_html = re.sub(r"\s*```$", "", base_html)
|
||
else:
|
||
base_html = HTML_WRAPPER_TEMPLATE.replace("{user_language}", user_language)
|
||
|
||
wrapped_content = f'<div class="plugin-item">\n{new_content}\n</div>'
|
||
|
||
if new_styles:
|
||
base_html = base_html.replace(
|
||
"/* STYLES_INSERTION_POINT */",
|
||
f"{new_styles}\n/* STYLES_INSERTION_POINT */",
|
||
)
|
||
|
||
base_html = base_html.replace(
|
||
"<!-- CONTENT_INSERTION_POINT -->",
|
||
f"{wrapped_content}\n<!-- CONTENT_INSERTION_POINT -->",
|
||
)
|
||
|
||
if new_scripts:
|
||
base_html = base_html.replace(
|
||
"<!-- SCRIPTS_INSERTION_POINT -->",
|
||
f"{new_scripts}\n<!-- SCRIPTS_INSERTION_POINT -->",
|
||
)
|
||
|
||
return base_html.strip()
|
||
|
||
def generate_html_card_components(self, data):
|
||
# Enhanced CSS with premium styling
|
||
style = """
|
||
@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700;800&display=swap');
|
||
|
||
.knowledge-card-container {
|
||
font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif;
|
||
display: flex;
|
||
justify-content: center;
|
||
margin: 30px 0;
|
||
padding: 0 10px;
|
||
}
|
||
|
||
.knowledge-card {
|
||
width: 100%;
|
||
max-width: 500px;
|
||
border-radius: 20px;
|
||
overflow: hidden;
|
||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||
padding: 3px;
|
||
transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
|
||
position: relative;
|
||
}
|
||
|
||
.knowledge-card:hover {
|
||
transform: translateY(-8px) scale(1.02);
|
||
box-shadow: 0 25px 50px -12px rgba(102, 126, 234, 0.4);
|
||
}
|
||
|
||
.knowledge-card::before {
|
||
content: '';
|
||
position: absolute;
|
||
top: -2px;
|
||
left: -2px;
|
||
right: -2px;
|
||
bottom: -2px;
|
||
background: linear-gradient(135deg, #667eea, #764ba2, #f093fb, #4facfe);
|
||
border-radius: 20px;
|
||
opacity: 0;
|
||
transition: opacity 0.4s ease;
|
||
z-index: -1;
|
||
filter: blur(10px);
|
||
}
|
||
|
||
.knowledge-card:hover::before {
|
||
opacity: 0.7;
|
||
animation: glow 2s ease-in-out infinite;
|
||
}
|
||
|
||
@keyframes glow {
|
||
0%, 100% { opacity: 0.5; }
|
||
50% { opacity: 0.8; }
|
||
}
|
||
|
||
.card-inner {
|
||
background: #ffffff;
|
||
border-radius: 18px;
|
||
overflow: hidden;
|
||
}
|
||
|
||
.card-header {
|
||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||
color: white;
|
||
padding: 32px 28px;
|
||
position: relative;
|
||
overflow: hidden;
|
||
}
|
||
|
||
.card-header::before {
|
||
content: '';
|
||
position: absolute;
|
||
top: -50%;
|
||
right: -50%;
|
||
width: 200%;
|
||
height: 200%;
|
||
background: radial-gradient(circle, rgba(255,255,255,0.1) 0%, transparent 70%);
|
||
animation: rotate 15s linear infinite;
|
||
}
|
||
|
||
@keyframes rotate {
|
||
from { transform: rotate(0deg); }
|
||
to { transform: rotate(360deg); }
|
||
}
|
||
|
||
.card-category {
|
||
font-size: 0.7em;
|
||
text-transform: uppercase;
|
||
letter-spacing: 2px;
|
||
opacity: 0.95;
|
||
margin-bottom: 10px;
|
||
font-weight: 700;
|
||
display: inline-block;
|
||
padding: 4px 12px;
|
||
background: rgba(255, 255, 255, 0.2);
|
||
border-radius: 12px;
|
||
backdrop-filter: blur(10px);
|
||
}
|
||
|
||
.card-title {
|
||
font-size: 1.75em;
|
||
font-weight: 800;
|
||
margin: 0;
|
||
line-height: 1.3;
|
||
position: relative;
|
||
z-index: 1;
|
||
letter-spacing: -0.5px;
|
||
}
|
||
|
||
.card-body {
|
||
padding: 28px;
|
||
color: #1a1a1a;
|
||
background: linear-gradient(to bottom, #ffffff 0%, #fafafa 100%);
|
||
}
|
||
|
||
.card-summary {
|
||
font-size: 1.05em;
|
||
color: #374151;
|
||
margin-bottom: 24px;
|
||
line-height: 1.7;
|
||
border-left: 5px solid #764ba2;
|
||
padding: 16px 20px;
|
||
background: linear-gradient(135deg, rgba(102, 126, 234, 0.08) 0%, rgba(118, 75, 162, 0.08) 100%);
|
||
border-radius: 0 12px 12px 0;
|
||
font-weight: 500;
|
||
position: relative;
|
||
overflow: hidden;
|
||
}
|
||
|
||
.card-summary::before {
|
||
content: '"';
|
||
position: absolute;
|
||
top: -10px;
|
||
left: 10px;
|
||
font-size: 4em;
|
||
color: rgba(118, 75, 162, 0.1);
|
||
font-family: Georgia, serif;
|
||
font-weight: bold;
|
||
}
|
||
|
||
.card-section-title {
|
||
font-size: 0.85em;
|
||
font-weight: 700;
|
||
color: #764ba2;
|
||
margin-bottom: 14px;
|
||
text-transform: uppercase;
|
||
letter-spacing: 1.5px;
|
||
display: flex;
|
||
align-items: center;
|
||
gap: 8px;
|
||
}
|
||
|
||
.card-section-title::before {
|
||
content: '';
|
||
width: 4px;
|
||
height: 16px;
|
||
background: linear-gradient(to bottom, #667eea, #764ba2);
|
||
border-radius: 2px;
|
||
}
|
||
|
||
.card-points {
|
||
list-style: none;
|
||
padding: 0;
|
||
margin: 0;
|
||
}
|
||
|
||
.card-points li {
|
||
margin-bottom: 14px;
|
||
padding: 12px 16px 12px 44px;
|
||
position: relative;
|
||
line-height: 1.6;
|
||
color: #374151;
|
||
background: #ffffff;
|
||
border-radius: 10px;
|
||
transition: all 0.3s ease;
|
||
border: 1px solid #e5e7eb;
|
||
font-weight: 500;
|
||
}
|
||
|
||
.card-points li:hover {
|
||
transform: translateX(5px);
|
||
background: linear-gradient(135deg, rgba(102, 126, 234, 0.05) 0%, rgba(118, 75, 162, 0.05) 100%);
|
||
border-color: #764ba2;
|
||
box-shadow: 0 4px 12px rgba(118, 75, 162, 0.1);
|
||
}
|
||
|
||
.card-points li::before {
|
||
content: '✓';
|
||
color: #ffffff;
|
||
background: linear-gradient(135deg, #667eea, #764ba2);
|
||
font-weight: bold;
|
||
position: absolute;
|
||
left: 12px;
|
||
top: 50%;
|
||
transform: translateY(-50%);
|
||
width: 24px;
|
||
height: 24px;
|
||
display: flex;
|
||
align-items: center;
|
||
justify-content: center;
|
||
border-radius: 50%;
|
||
font-size: 0.85em;
|
||
box-shadow: 0 2px 8px rgba(118, 75, 162, 0.3);
|
||
}
|
||
|
||
.card-footer {
|
||
padding: 20px 28px;
|
||
background: linear-gradient(to right, #f8fafc 0%, #f1f5f9 100%);
|
||
display: flex;
|
||
flex-wrap: wrap;
|
||
gap: 10px;
|
||
border-top: 2px solid #e5e7eb;
|
||
align-items: center;
|
||
}
|
||
|
||
.card-tag-label {
|
||
font-size: 0.75em;
|
||
font-weight: 700;
|
||
color: #64748b;
|
||
text-transform: uppercase;
|
||
letter-spacing: 1px;
|
||
margin-right: 4px;
|
||
}
|
||
|
||
.card-tag {
|
||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||
color: white;
|
||
padding: 6px 16px;
|
||
border-radius: 20px;
|
||
font-size: 0.85em;
|
||
font-weight: 600;
|
||
transition: all 0.3s ease;
|
||
border: 2px solid transparent;
|
||
cursor: default;
|
||
letter-spacing: 0.3px;
|
||
}
|
||
|
||
.card-tag:hover {
|
||
transform: translateY(-2px);
|
||
box-shadow: 0 4px 12px rgba(102, 126, 234, 0.4);
|
||
border-color: rgba(255, 255, 255, 0.3);
|
||
}
|
||
|
||
/* Dark mode support */
|
||
@media (prefers-color-scheme: dark) {
|
||
.card-inner {
|
||
background: #1e1e1e;
|
||
}
|
||
|
||
.card-body {
|
||
background: linear-gradient(to bottom, #1e1e1e 0%, #252525 100%);
|
||
color: #e5e7eb;
|
||
}
|
||
|
||
.card-summary {
|
||
background: linear-gradient(135deg, rgba(102, 126, 234, 0.15) 0%, rgba(118, 75, 162, 0.15) 100%);
|
||
color: #d1d5db;
|
||
}
|
||
|
||
.card-summary::before {
|
||
color: rgba(118, 75, 162, 0.2);
|
||
}
|
||
|
||
.card-points li {
|
||
color: #d1d5db;
|
||
background: #2d2d2d;
|
||
border-color: #404040;
|
||
}
|
||
|
||
.card-points li:hover {
|
||
background: linear-gradient(135deg, rgba(102, 126, 234, 0.15) 0%, rgba(118, 75, 162, 0.15) 100%);
|
||
border-color: #667eea;
|
||
}
|
||
|
||
.card-footer {
|
||
background: linear-gradient(to right, #252525 0%, #2d2d2d 100%);
|
||
border-top-color: #404040;
|
||
}
|
||
|
||
.card-tag-label {
|
||
color: #9ca3af;
|
||
}
|
||
}
|
||
|
||
/* Mobile responsive */
|
||
@media (max-width: 640px) {
|
||
.knowledge-card {
|
||
max-width: 100%;
|
||
}
|
||
|
||
.card-header {
|
||
padding: 24px 20px;
|
||
}
|
||
|
||
.card-title {
|
||
font-size: 1.5em;
|
||
}
|
||
|
||
.card-body {
|
||
padding: 20px;
|
||
}
|
||
|
||
.card-footer {
|
||
padding: 16px 20px;
|
||
}
|
||
}
|
||
"""
|
||
|
||
# Generate tags HTML
|
||
tags_html = ""
|
||
if "tags" in data and data["tags"]:
|
||
for tag in data["tags"]:
|
||
tags_html += f'<div class="card-tag"><span class="card-tag-label">#</span>{tag}</div>'
|
||
|
||
# Generate key points HTML
|
||
points_html = ""
|
||
if "key_points" in data and data["key_points"]:
|
||
for point in data["key_points"]:
|
||
points_html += f"<li>{point}</li>"
|
||
|
||
# Build the card HTML structure
|
||
content = f"""
|
||
<div class="knowledge-card-container">
|
||
<div class="knowledge-card">
|
||
<div class="card-inner">
|
||
<div class="card-header">
|
||
<div class="card-category">{data.get('category', 'Knowledge')}</div>
|
||
<h2 class="card-title">{data.get('title', 'Flash Card')}</h2>
|
||
</div>
|
||
<div class="card-body">
|
||
<div class="card-summary">
|
||
{data.get('summary', '')}
|
||
</div>
|
||
|
||
<div class="card-section-title">KEY POINTS</div>
|
||
<ul class="card-points">
|
||
{points_html}
|
||
</ul>
|
||
</div>
|
||
<div class="card-footer">
|
||
{tags_html}
|
||
</div>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
"""
|
||
|
||
return content, style
|