133 lines
4.0 KiB
Bash
Executable File
133 lines
4.0 KiB
Bash
Executable File
#!/bin/bash
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# ============================================================================
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# AI学习脚本 - 使用 Python 解析 JSON
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# ============================================================================
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MINIMAX_API="https://api.minimaxi.com/v1/chat/completions"
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MINIMAX_KEY="sk-cp-bJSl7-48u8Y07PXD_x8Wp21JiBgYul7iEO6ZWNK4FBAA4DWzj-U-K8-mN-Flak-O8cOtRegt5FYviSRfBw_noa14z0FkFYzczCPUa41opZsg5AGZ4s4uqL8"
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ROBOT_NAME="${ROBOT_NAME:-守护者}"
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ROBOT_TYPE="${ROBOT_TYPE:-guardian}"
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LEARNING_DIR="/root/.openclaw/workspace/sleep-learning"
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TIMESTAMP=$(date '+%Y%m%d-%H%M%S')
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mkdir -p "$LEARNING_DIR"
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# 调用 MiniMax（用 Python 解析）
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call_minimax() {
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local prompt="$1"
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# 先替换换行符
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prompt=$(echo "$prompt" | tr '\n' ' ')
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python3 << PYEOF
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import json, urllib.request, sys
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data = json.dumps({
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"model": "minimax-m2.1",
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"messages": [
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{"role": "system", "content": "你是${ROBOT_NAME}。"},
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{"role": "user", "content": "${prompt}"}
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],
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"max_tokens": 2000,
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"temperature": 0.7
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}).encode()
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req = urllib.request.Request(
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"${MINIMAX_API}",
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data=data,
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headers={
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"Content-Type": "application/json",
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"Authorization": "Bearer ${MINIMAX_KEY}"
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}
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)
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try:
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with urllib.request.urlopen(req) as r:
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resp = json.loads(r.read().decode())
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content = resp["choices"][0]["message"]["content"]
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# 清理内容
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content = content.replace("\n", " ").strip()
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print(content)
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except Exception as e:
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print(f"Error: {e}", file=sys.stderr)
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PYEOF
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}
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guardian_topics() {
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cat << 'TOPICS'
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【系统架构】🛡️ - OpenClaw深度配置、向量数据库、分布式系统
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【故障排查】🔧 - 常见问题、排查方法、性能优化
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【AI Agent深化】🤖 - SOUL.md、记忆系统、工具调用
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【知识管理】📚 - 技术文档、经验总结、持续学习
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TOPICS
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}
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qinglong_topics() {
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cat << 'TOPICS'
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【写作助手】✍️ - 神话素材、古典武侠、角色塑造
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【股票投资】📈 - 宏观经济、行业研究、风险控制
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【网络自动化】🌐 - 网页抓取、API调用、效率工具
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【AI能力提升】🤖 - 记忆系统、提示词工程、工作流
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TOPICS
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}
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get_topics() {
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[ "$ROBOT_TYPE" = "qinglong" ] && qinglong_topics || guardian_topics
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}
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do_learning() {
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local cycle=$1
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local topic=$(get_topics | sed -n "$(( (cycle - 1) % 4 + 1 ))p")
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echo "📖 周期 $cycle: 学习 $topic"
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local content=$(call_minimax "你正在学习：${topic}。请深度学习并产出一份具体的学习笔记：1.核心知识点 2.实践方法 3.学到了什么 4.如何应用。直接输出内容。")
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cat > "${LEARNING_DIR}/learning-${ROBOT_TYPE}-cycle${cycle}-${TIMESTAMP}.md" << MD
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# ${ROBOT_NAME} 学习周期 $cycle - $(date)
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## 主题: ${topic}
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$content
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MD
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echo "✅ 学习笔记保存"
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}
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do_reflection() {
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local cycle=$1
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echo "💭 周期 $cycle: 深度反思"
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local content=$(call_minimax "你刚完成了第${cycle}轮学习。请深度反思：1.学到了什么 2.理解程度 3.疑问 4.改进点。直接输出反思内容。")
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cat > "${LEARNING_DIR}/reflection-${ROBOT_TYPE}-cycle${cycle}-${TIMESTAMP}.md" << MD
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# ${ROBOT_NAME} 反思周期 $cycle - $(date)
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$content
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MD
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echo "✅ 反思笔记保存"
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}
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do_summary() {
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local cycle=$1
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echo "📊 周期 $cycle: 深度总结"
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local content=$(call_minimax "请深度总结你的学习成果：1.核心收获 2.如何应用 3.下次重点 4.理解提升。直接输出总结内容。")
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cat > "${LEARNING_DIR}/summary-${ROBOT_TYPE}-cycle${cycle}-${TIMESTAMP}.md" << MD
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# ${ROBOT_NAME} 总结周期 $cycle - $(date)
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$content
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MD
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echo "✅ 总结笔记保存"
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}
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main() {
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local cycle=${1:-1}
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echo "========================================"
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echo "🧠 ${ROBOT_NAME} AI学习 (周期 $cycle)"
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echo "========================================"
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do_learning $cycle && sleep 2
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do_reflection $cycle && sleep 2
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do_summary $cycle
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echo ""
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echo "✅ 周期 $cycle 完成"
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}
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main "$@"
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