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.claude/skills/slack-gif-creator/.openskills.json new file: .claude/skills/slack-gif-creator/LICENSE.txt new file: .claude/skills/slack-gif-creator/SKILL.md new file: .claude/skills/slack-gif-creator/core/easing.py new file: .claude/skills/slack-gif-creator/core/frame_composer.py new file: .claude/skills/slack-gif-creator/core/gif_builder.py new file: .claude/skills/slack-gif-creator/core/validators.py new file: .claude/skills/slack-gif-creator/requirements.txt new file: .claude/skills/template/.openskills.json new file: .claude/skills/template/SKILL.md new file: .claude/skills/theme-factory/.openskills.json new file: .claude/skills/theme-factory/LICENSE.txt new file: .claude/skills/theme-factory/SKILL.md new file: .claude/skills/theme-factory/theme-showcase.pdf new file: .claude/skills/theme-factory/themes/arctic-frost.md new file: .claude/skills/theme-factory/themes/botanical-garden.md new file: .claude/skills/theme-factory/themes/desert-rose.md new file: .claude/skills/theme-factory/themes/forest-canopy.md new file: .claude/skills/theme-factory/themes/golden-hour.md new file: .claude/skills/theme-factory/themes/midnight-galaxy.md new file: .claude/skills/theme-factory/themes/modern-minimalist.md new file: .claude/skills/theme-factory/themes/ocean-depths.md new file: .claude/skills/theme-factory/themes/sunset-boulevard.md new file: .claude/skills/theme-factory/themes/tech-innovation.md new file: .claude/skills/web-artifacts-builder/.openskills.json new file: .claude/skills/web-artifacts-builder/LICENSE.txt new file: .claude/skills/web-artifacts-builder/SKILL.md new file: .claude/skills/web-artifacts-builder/scripts/bundle-artifact.sh new file: .claude/skills/web-artifacts-builder/scripts/init-artifact.sh new file: .claude/skills/web-artifacts-builder/scripts/shadcn-components.tar.gz new file: .claude/skills/webapp-testing/.openskills.json new file: .claude/skills/webapp-testing/LICENSE.txt new file: .claude/skills/webapp-testing/SKILL.md new file: .claude/skills/webapp-testing/examples/console_logging.py new file: .claude/skills/webapp-testing/examples/element_discovery.py new file: .claude/skills/webapp-testing/examples/static_html_automation.py new file: .claude/skills/webapp-testing/scripts/with_server.py new file: .claude/skills/xlsx/.openskills.json new file: .claude/skills/xlsx/LICENSE.txt new file: .claude/skills/xlsx/SKILL.md new file: .claude/skills/xlsx/scripts/office/helpers/__init__.py new file: .claude/skills/xlsx/scripts/office/helpers/merge_runs.py new file: .claude/skills/xlsx/scripts/office/helpers/simplify_redlines.py new file: .claude/skills/xlsx/scripts/office/pack.py new file: .claude/skills/xlsx/scripts/office/schemas/ISO-IEC29500-4_2016/dml-chart.xsd new file: .claude/skills/xlsx/scripts/office/schemas/ISO-IEC29500-4_2016/dml-chartDrawing.xsd new file: .claude/skills/xlsx/scripts/office/schemas/ISO-IEC29500-4_2016/dml-diagram.xsd new file: 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config/mcp.json new file: config/models.json new file: config/personalities.json new file: docs/AGENTS.md new file: docs/AI_IMPLEMENTATION.md new file: docs/AI_INTEGRATION_COMPLETE.md new file: docs/AI_QUICKSTART.md new file: docs/AI_SUMMARY.md new file: docs/CHANGELOG.md new file: docs/CONFIG_GUIDE.md new file: docs/FIXES.md new file: docs/PROJECT_REFACTOR.md new file: docs/README.md new file: docs/README_INDEX.md new file: examples/ai_example.py new file: main.py new file: pytest.ini new file: requirements.txt new file: scripts/migrate_to_vector_db.py new file: skills/cmd_zip_skill/README.md new file: skills/cmd_zip_skill/__init__.py new file: skills/cmd_zip_skill/main.py new file: skills/cmd_zip_skill/skill.json new file: skills/cmd_zip_skill_1772465404375/README.md new file: skills/cmd_zip_skill_1772465404375/__init__.py new file: skills/cmd_zip_skill_1772465404375/main.py new file: skills/cmd_zip_skill_1772465404375/skill.json new file: skills/cmd_zip_skill_1772465434774/README.md 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file: skills/cmd_zip_skill_1772465936294/skill.json new file: skills/cmd_zip_skill_1772465966322/README.md new file: skills/cmd_zip_skill_1772465966322/__init__.py new file: skills/cmd_zip_skill_1772465966322/main.py new file: skills/cmd_zip_skill_1772465966322/skill.json new file: skills/cmd_zip_skill_1772466071278/README.md new file: skills/cmd_zip_skill_1772466071278/__init__.py new file: skills/cmd_zip_skill_1772466071278/main.py new file: skills/cmd_zip_skill_1772466071278/skill.json new file: skills/skills_creator/README.md new file: skills/skills_creator/__init__.py new file: skills/skills_creator/main.py new file: skills/skills_creator/skill.json new file: src/__init__.py new file: src/ai/__init__.py new file: src/ai/base.py new file: src/ai/client.py new file: src/ai/docs/README.md new file: src/ai/mcp/__init__.py new file: src/ai/mcp/base.py new file: src/ai/mcp/servers/__init__.py new file: src/ai/mcp/servers/filesystem.py new file: src/ai/memory.py new file: src/ai/models/__init__.py new file: src/ai/models/anthropic_model.py new file: src/ai/models/openai_model.py new file: src/ai/personality.py new file: src/ai/skills/__init__.py new file: src/ai/skills/base.py new file: src/ai/task_manager.py new file: src/ai/vector_store/__init__.py new file: src/ai/vector_store/base.py new file: src/ai/vector_store/chroma_store.py new file: src/ai/vector_store/json_store.py new file: src/core/__init__.py new file: src/core/bot.py new file: src/core/config.py new file: src/handlers/__init__.py new file: src/handlers/message_handler.py new file: src/handlers/message_handler_ai.py new file: src/utils/__init__.py new file: src/utils/logger.py new file: start.bat new file: tests/test_ai.py
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# AI模型接入完整指南
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## 概述
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本系统提供了完整的AI模型接入能力，包括：
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- ✅ **多模型支持**：OpenAI、Anthropic Claude、DeepSeek、Qwen等
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- ✅ **人格系统**：可自定义AI性格特征和说话风格
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- ✅ **记忆系统**：短期记忆（滑动窗口）+ 长期记忆（RAG检索）
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- ✅ **长任务处理**：支持多步骤复杂任务的执行和管理
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- ✅ **Skills插件**：可扩展的技能插件系统
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- ✅ **MCP支持**：Model Context Protocol标准支持
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## 快速开始
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### 1. 安装依赖
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```bash
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pip install openai anthropic numpy
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```
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### 2. 配置环境变量
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在 `.env` 文件中添加：
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```env
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# AI模型配置
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AI_PROVIDER=openai # openai, anthropic, deepseek, qwen
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AI_MODEL=gpt-4
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AI_API_KEY=your_api_key_here
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AI_API_BASE=https://api.openai.com/v1 # 可选，自定义API地址
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```
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### 3. 基础使用
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```python
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from pathlib import Path
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from src.ai import AIClient
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from src.ai.base import ModelConfig, ModelProvider
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# 创建模型配置
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config = ModelConfig(
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provider=ModelProvider.OPENAI,
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model_name="gpt-4",
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api_key="your_api_key",
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temperature=0.7
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)
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# 初始化AI客户端
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client = AIClient(config, data_dir=Path("data/ai"))
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# 对话
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response = await client.chat(
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user_id="user123",
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user_message="你好，介绍一下你自己",
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use_memory=True,
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use_tools=True
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)
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print(response)
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```
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## 核心功能详解
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### 1. 人格系统
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人格系统允许你为AI定义独特的性格特征和说话风格。
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#### 使用预设人格
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```python
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# 列出所有人格
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personalities = client.list_personalities()
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print(personalities) # ['default', 'tech_expert', 'creative']
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# 切换人格
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client.set_personality('tech_expert')
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```
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#### 自定义人格
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```python
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from src.ai.personality import PersonalityProfile, PersonalityTrait
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# 创建自定义人格
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custom_personality = PersonalityProfile(
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name="游戏助手",
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description="专业的游戏顾问和陪玩伙伴",
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traits=[
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PersonalityTrait.FRIENDLY,
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PersonalityTrait.HUMOROUS,
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PersonalityTrait.CREATIVE
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],
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speaking_style="活泼、热情、善用游戏术语和梗",
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example_responses=[
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"哇！这个操作太秀了！",
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"让我们一起冲冲冲！",
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"别慌，稳住我们能赢！"
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],
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custom_instructions="始终保持积极乐观的态度，鼓励玩家"
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)
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# 添加到系统
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client.personality.add_personality('gamer', custom_personality)
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client.set_personality('gamer')
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```
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### 2. 记忆系统
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记忆系统分为短期记忆和长期记忆两部分。
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#### 短期记忆
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- 自动保存最近的对话（默认20条）
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- 使用滑动窗口，自动清理过期记忆（默认30分钟）
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- 无需手动管理
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#### 长期记忆
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- 自动评估重要性，重要对话会被保存
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- 支持向量检索（RAG）
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- 可手动查询历史记忆
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```python
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# 获取用户的记忆上下文
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short_term, long_term = await client.memory.get_context(
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user_id="user123",
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query="我们之前讨论过什么？",
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max_short_term=10,
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max_long_term=5
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)
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# 格式化为文本
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context = client.memory.format_context(short_term, long_term)
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print(context)
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# 清除短期记忆
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client.clear_memory("user123")
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```
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#### 记忆重要性评估
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系统会自动评估对话的重要性：
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- 内容长度（>100字符 +0.1分）
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- 关键词（"重要"、"记住"、"别忘了" +0.2分）
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- 元数据（问题 +0.1分，代码 +0.15分）
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- 阈值：≥0.6分会被保存到长期记忆
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### 3. 长任务处理
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支持将复杂任务分解为多个步骤执行。
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```python
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# 创建长任务
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task_id = await client.create_long_task(
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user_id="user123",
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title="数据分析任务",
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description="分析用户行为数据并生成报告",
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steps=[
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{
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"description": "加载数据",
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"action": "load_data",
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"params": {"file_path": "data.csv"}
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},
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{
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"description": "数据清洗",
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"action": "clean_data",
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"params": {}
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},
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{
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"description": "统计分析",
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"action": "analyze",
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"params": {"metrics": ["avg", "max", "min"]}
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},
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{
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"description": "生成报告",
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"action": "generate_report",
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"params": {"format": "pdf"}
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}
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]
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)
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# 定义进度回调
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async def on_progress(task_id, progress, message):
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print(f"任务 {task_id}: {progress*100:.1f}% - {message}")
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# 启动任务
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await client.start_task(task_id, progress_callback=on_progress)
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# 查询任务状态
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status = client.get_task_status(task_id)
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print(status)
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```
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#### 注册任务动作处理器
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```python
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# 注册动作处理器
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async def load_data_handler(file_path: str):
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# 实现数据加载逻辑
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return {"rows": 1000, "columns": 10}
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client.task_manager.register_action("load_data", load_data_handler)
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```
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### 4. Skills插件系统
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Skills系统允许你扩展AI的能力。
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#### 加载技能
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```python
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from pathlib import Path
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from src.ai.skills import SkillsManager
|
||||
|
||||
# 创建技能管理器
|
||||
skills_manager = SkillsManager(skills_dir=Path("skills"))
|
||||
|
||||
# 加载单个技能
|
||||
await skills_manager.load_skill("weather")
|
||||
|
||||
# 加载所有技能
|
||||
await skills_manager.load_all_skills()
|
||||
|
||||
# 获取所有工具
|
||||
tools = skills_manager.get_all_tools()
|
||||
```
|
||||
|
||||
#### 创建自定义技能
|
||||
|
||||
```python
|
||||
from src.ai.skills import create_skill_template
|
||||
|
||||
# 创建技能模板
|
||||
create_skill_template("my_skill", Path("skills"))
|
||||
```
|
||||
|
||||
技能目录结构：
|
||||
|
||||
```
|
||||
skills/
|
||||
└── my_skill/
|
||||
├── skill.json # 元数据
|
||||
├── main.py # 主要实现
|
||||
├── __init__.py
|
||||
└── README.md
|
||||
```
|
||||
|
||||
`main.py` 示例：
|
||||
|
||||
```python
|
||||
from src.ai.skills.base import Skill
|
||||
|
||||
class MySkill(Skill):
|
||||
async def initialize(self):
|
||||
# 注册工具
|
||||
self.register_tool("my_tool", self.my_tool)
|
||||
|
||||
async def my_tool(self, param: str) -> str:
|
||||
return f"处理: {param}"
|
||||
|
||||
async def cleanup(self):
|
||||
pass
|
||||
```
|
||||
|
||||
### 5. MCP支持
|
||||
|
||||
MCP (Model Context Protocol) 提供标准化的上下文访问接口。
|
||||
|
||||
#### 使用内置MCP服务器
|
||||
|
||||
```python
|
||||
from pathlib import Path
|
||||
from src.ai.mcp import MCPManager
|
||||
from src.ai.mcp.servers import FileSystemMCPServer
|
||||
|
||||
# 创建MCP管理器
|
||||
mcp_manager = MCPManager(config_path=Path("config/mcp.json"))
|
||||
|
||||
# 注册文件系统服务器
|
||||
fs_server = FileSystemMCPServer(root_path=Path("data"))
|
||||
await mcp_manager.register_server(fs_server)
|
||||
|
||||
# 获取所有工具
|
||||
tools = await mcp_manager.get_all_tools_for_ai()
|
||||
|
||||
# 执行工具
|
||||
result = await mcp_manager.execute_tool(
|
||||
"filesystem.read_file",
|
||||
{"path": "test.txt"}
|
||||
)
|
||||
```
|
||||
|
||||
#### 创建自定义MCP服务器
|
||||
|
||||
```python
|
||||
from src.ai.mcp.base import MCPServer
|
||||
|
||||
class MyMCPServer(MCPServer):
|
||||
def __init__(self):
|
||||
super().__init__(name="my_server", version="1.0.0")
|
||||
|
||||
async def initialize(self):
|
||||
self.register_tool(
|
||||
name="my_tool",
|
||||
description="我的工具",
|
||||
input_schema={
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"param": {"type": "string"}
|
||||
},
|
||||
"required": ["param"]
|
||||
},
|
||||
handler=self.my_tool_handler
|
||||
)
|
||||
|
||||
async def my_tool_handler(self, param: str):
|
||||
return f"处理: {param}"
|
||||
```
|
||||
|
||||
## 集成到QQ机器人
|
||||
|
||||
### 修改消息处理器
|
||||
|
||||
```python
|
||||
# src/handlers/message_handler.py
|
||||
from src.ai import AIClient
|
||||
from src.ai.base import ModelConfig, ModelProvider
|
||||
from pathlib import Path
|
||||
|
||||
class MessageHandler:
|
||||
def __init__(self, bot):
|
||||
self.bot = bot
|
||||
|
||||
# 初始化AI客户端
|
||||
config = ModelConfig(
|
||||
provider=ModelProvider.OPENAI,
|
||||
model_name="gpt-4",
|
||||
api_key=Config.AI_API_KEY,
|
||||
api_base=Config.AI_API_BASE
|
||||
)
|
||||
self.ai_client = AIClient(config, data_dir=Path("data/ai"))
|
||||
|
||||
# 加载技能
|
||||
from src.ai.skills import SkillsManager
|
||||
self.skills = SkillsManager(Path("skills"))
|
||||
asyncio.create_task(self.skills.load_all_skills())
|
||||
|
||||
async def handle_at_message(self, message: Message):
|
||||
try:
|
||||
# 提取用户消息
|
||||
user_message = message.content.strip()
|
||||
user_id = message.author.id
|
||||
|
||||
# 调用AI
|
||||
response = await self.ai_client.chat(
|
||||
user_id=user_id,
|
||||
user_message=user_message,
|
||||
use_memory=True,
|
||||
use_tools=True
|
||||
)
|
||||
|
||||
# 发送回复
|
||||
await message.reply(content=response)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"处理消息失败: {e}")
|
||||
await message.reply(content="抱歉，处理消息时出错了")
|
||||
```
|
||||
|
||||
## 配置文件
|
||||
|
||||
### config/personalities.json
|
||||
|
||||
```json
|
||||
{
|
||||
"default": {
|
||||
"name": "小助手",
|
||||
"description": "友好的AI助手",
|
||||
"traits": ["FRIENDLY", "PROFESSIONAL", "EMPATHETIC"],
|
||||
"speaking_style": "温和、清晰、有条理",
|
||||
"example_responses": [
|
||||
"我明白你的意思了，让我来帮你解决这个问题。",
|
||||
"这是个很好的问题！我来详细解释一下。"
|
||||
],
|
||||
"custom_instructions": ""
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### config/mcp.json
|
||||
|
||||
```json
|
||||
{
|
||||
"filesystem": {
|
||||
"enabled": true,
|
||||
"root_path": "data"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## 高级用法
|
||||
|
||||
### 1. 流式响应
|
||||
|
||||
```python
|
||||
async for chunk in client.chat(
|
||||
user_id="user123",
|
||||
user_message="讲个故事",
|
||||
stream=True
|
||||
):
|
||||
print(chunk, end='', flush=True)
|
||||
```
|
||||
|
||||
### 2. 自定义工具
|
||||
|
||||
```python
|
||||
# 定义工具函数
|
||||
async def search_web(query: str) -> str:
|
||||
# 实现搜索逻辑
|
||||
return f"搜索结果: {query}"
|
||||
|
||||
# 注册工具
|
||||
client.register_tool(
|
||||
name="search_web",
|
||||
description="搜索网络信息",
|
||||
parameters={
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"query": {
|
||||
"type": "string",
|
||||
"description": "搜索关键词"
|
||||
}
|
||||
},
|
||||
"required": ["query"]
|
||||
},
|
||||
function=search_web
|
||||
)
|
||||
```
|
||||
|
||||
### 3. 多模型切换
|
||||
|
||||
```python
|
||||
# 切换到Claude
|
||||
claude_config = ModelConfig(
|
||||
provider=ModelProvider.ANTHROPIC,
|
||||
model_name="claude-3-5-sonnet-20241022",
|
||||
api_key="your_anthropic_key"
|
||||
)
|
||||
client.model = client._create_model(claude_config)
|
||||
|
||||
# 切换到DeepSeek
|
||||
deepseek_config = ModelConfig(
|
||||
provider=ModelProvider.DEEPSEEK,
|
||||
model_name="deepseek-chat",
|
||||
api_key="your_deepseek_key",
|
||||
api_base="https://api.deepseek.com/v1"
|
||||
)
|
||||
client.model = client._create_model(deepseek_config)
|
||||
```
|
||||
|
||||
## 性能优化
|
||||
|
||||
### 1. 记忆系统优化
|
||||
|
||||
```python
|
||||
# 调整短期记忆大小
|
||||
client.memory.short_term.max_size = 30 # 默认20
|
||||
|
||||
# 调整记忆过期时间
|
||||
from datetime import timedelta
|
||||
client.memory.short_term.max_age = timedelta(hours=1) # 默认30分钟
|
||||
|
||||
# 调整重要性阈值
|
||||
client.memory.importance_threshold = 0.7 # 默认0.6
|
||||
```
|
||||
|
||||
### 2. 并发任务处理
|
||||
|
||||
```python
|
||||
# 同时启动多个任务
|
||||
tasks = []
|
||||
for i in range(5):
|
||||
task_id = await client.create_long_task(...)
|
||||
tasks.append(client.start_task(task_id))
|
||||
|
||||
# 等待所有任务完成
|
||||
await asyncio.gather(*tasks)
|
||||
```
|
||||
|
||||
## 故障排查
|
||||
|
||||
### 常见问题
|
||||
|
||||
1. **API调用失败**
|
||||
- 检查API密钥是否正确
|
||||
- 检查网络连接
|
||||
- 检查API地址是否正确
|
||||
|
||||
2. **记忆系统不工作**
|
||||
- 确保 `use_memory=True`
|
||||
- 检查数据目录权限
|
||||
- 查看日志文件
|
||||
|
||||
3. **技能加载失败**
|
||||
- 检查 `skill.json` 格式
|
||||
- 确保 `main.py` 中有Skill子类
|
||||
- 查看错误日志
|
||||
|
||||
## 最佳实践
|
||||
|
||||
1. **合理使用记忆系统**
|
||||
- 不要在每次对话都查询长期记忆
|
||||
- 定期清理不重要的记忆
|
||||
- 为重要对话添加元数据标记
|
||||
|
||||
2. **技能开发**
|
||||
- 保持技能功能单一
|
||||
- 提供清晰的工具描述
|
||||
- 处理异常情况
|
||||
|
||||
3. **长任务设计**
|
||||
- 将任务分解为合理的步骤
|
||||
- 提供进度反馈
|
||||
- 支持任务暂停和恢复
|
||||
|
||||
## 更新日志
|
||||
|
||||
### v1.0.0 (2024-03-02)
|
||||
- ✅ 初始版本发布
|
||||
- ✅ 支持OpenAI、Anthropic、DeepSeek、Qwen
|
||||
- ✅ 人格系统
|
||||
- ✅ 记忆系统（短期+长期+RAG）
|
||||
- ✅ 长任务处理
|
||||
- ✅ Skills插件系统
|
||||
- ✅ MCP支持
|
||||
|
||||
## 贡献
|
||||
|
||||
欢迎提交Issue和Pull Request！
|
||||
|
||||
## 许可证
|
||||
|
||||
MIT License
|
||||
Reference in New Issue
Block a user