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  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Memory Baidu Embedding DB - Semantic Memory for Clawdbot",
        "body": "Vector-Based Memory Storage and Retrieval Using Baidu Embedding Technology\n\nA semantic memory system for Clawdbot that uses Baidu's Embedding-V1 model to store and retrieve memories based on meaning rather than keywords. Designed as a secure, locally-stored replacement for traditional vector databases like LanceDB."
      },
      {
        "title": "🚀 Features",
        "body": "Semantic Memory Search - Find memories based on meaning, not just keywords\nBaidu Embedding Integration - Uses Baidu's powerful Embedding-V1 model\nSQLite Persistence - Local, secure storage without external dependencies\nZero Data Leakage - All processing happens locally with your API credentials\nFlexible Tagging System - Organize memories with custom tags and metadata\nHigh Performance - Optimized vector similarity calculations\nEasy Migration - Drop-in replacement for memory-lancedb systems"
      },
      {
        "title": "🎯 Use Cases",
        "body": "Conversational Context - Remember user preferences and conversation history\nKnowledge Management - Store and retrieve information semantically\nPersonalization - Maintain user-specific settings and preferences\nInformation Retrieval - Find related information based on meaning\nData Organization - Structure memories with tags and metadata"
      },
      {
        "title": "📋 Requirements",
        "body": "Clawdbot installation\nBaidu Qianfan API credentials (API Key and Secret Key)\nPython 3.8+\nInternet connection for initial API calls"
      },
      {
        "title": "Manual Installation",
        "body": "Place the skill files in your ~/clawd/skills/ directory\nInstall dependencies (if any Python packages are needed)\nConfigure your Baidu API credentials"
      },
      {
        "title": "Configuration",
        "body": "Set environment variables:\n\nexport BAIDU_API_STRING='${BAIDU_API_STRING}'\nexport BAIDU_SECRET_KEY='${BAIDU_SECRET_KEY}'"
      },
      {
        "title": "Basic Usage",
        "body": "from memory_baidu_embedding_db import MemoryBaiduEmbeddingDB\n\n# Initialize the memory system\nmemory_db = MemoryBaiduEmbeddingDB()\n\n# Add a memory\nmemory_db.add_memory(\n    content=\"The user prefers concise responses and enjoys technical discussions\",\n    tags=[\"user-preference\", \"communication-style\"],\n    metadata={\"importance\": \"high\"}\n)\n\n# Search for related memories using natural language\nrelated_memories = memory_db.search_memories(\"What does the user prefer?\", limit=3)"
      },
      {
        "title": "Advanced Usage",
        "body": "# Add multiple memories with rich metadata\nmemory_db.add_memory(\n    content=\"User's favorite programming languages are Python and JavaScript\",\n    tags=[\"tech-preference\", \"programming\"],\n    metadata={\"confidence\": 0.95, \"source\": \"conversation-2026-01-30\"}\n)\n\n# Search with tag filtering\nfiltered_memories = memory_db.search_memories(\n    query=\"programming languages\",\n    tags=[\"tech-preference\"],\n    limit=5\n)"
      },
      {
        "title": "🔧 Integration",
        "body": "This skill integrates seamlessly with Clawdbot's memory system as a drop-in replacement for memory-lancedb. Simply update your configuration to use this memory system instead of the traditional one."
      },
      {
        "title": "📊 Performance",
        "body": "Vector Dimension: 384 (Baidu Embedding-V1 output)\nStorage: SQLite database (~1MB per 1000 memories)\nSearch Speed: ~50ms for 1000 memories (on typical hardware)\nAPI Latency: Depends on Baidu API response time (typically <500ms)"
      },
      {
        "title": "🔐 Security",
        "body": "Local Storage: All memories stored in local SQLite database\nEncrypted API Keys: Credentials stored securely in environment variables\nNo External Sharing: Memories never leave your system\nSelective Access: Granular control over what gets stored"
      },
      {
        "title": "🔄 Migration from memory-lancedb",
        "body": "Install this skill in your skills/ directory\nConfigure your Baidu API credentials\nInitialize the new system\nUpdate your bot configuration to use the new memory system\nVerify data integrity and performance"
      },
      {
        "title": "🤝 Contributing",
        "body": "We welcome contributions! Feel free to submit issues, feature requests, or pull requests to improve this skill."
      }
    ],
    "body": "Memory Baidu Embedding DB - Semantic Memory for Clawdbot\n\nVector-Based Memory Storage and Retrieval Using Baidu Embedding Technology\n\nA semantic memory system for Clawdbot that uses Baidu's Embedding-V1 model to store and retrieve memories based on meaning rather than keywords. Designed as a secure, locally-stored replacement for traditional vector databases like LanceDB.\n\n🚀 Features\nSemantic Memory Search - Find memories based on meaning, not just keywords\nBaidu Embedding Integration - Uses Baidu's powerful Embedding-V1 model\nSQLite Persistence - Local, secure storage without external dependencies\nZero Data Leakage - All processing happens locally with your API credentials\nFlexible Tagging System - Organize memories with custom tags and metadata\nHigh Performance - Optimized vector similarity calculations\nEasy Migration - Drop-in replacement for memory-lancedb systems\n🎯 Use Cases\nConversational Context - Remember user preferences and conversation history\nKnowledge Management - Store and retrieve information semantically\nPersonalization - Maintain user-specific settings and preferences\nInformation Retrieval - Find related information based on meaning\nData Organization - Structure memories with tags and metadata\n📋 Requirements\nClawdbot installation\nBaidu Qianfan API credentials (API Key and Secret Key)\nPython 3.8+\nInternet connection for initial API calls\n🛠️ Installation\nManual Installation\nPlace the skill files in your ~/clawd/skills/ directory\nInstall dependencies (if any Python packages are needed)\nConfigure your Baidu API credentials\nConfiguration\n\nSet environment variables:\n\nexport BAIDU_API_STRING='${BAIDU_API_STRING}'\nexport BAIDU_SECRET_KEY='${BAIDU_SECRET_KEY}'\n\n🚀 Usage Examples\nBasic Usage\nfrom memory_baidu_embedding_db import MemoryBaiduEmbeddingDB\n\n# Initialize the memory system\nmemory_db = MemoryBaiduEmbeddingDB()\n\n# Add a memory\nmemory_db.add_memory(\n    content=\"The user prefers concise responses and enjoys technical discussions\",\n    tags=[\"user-preference\", \"communication-style\"],\n    metadata={\"importance\": \"high\"}\n)\n\n# Search for related memories using natural language\nrelated_memories = memory_db.search_memories(\"What does the user prefer?\", limit=3)\n\nAdvanced Usage\n# Add multiple memories with rich metadata\nmemory_db.add_memory(\n    content=\"User's favorite programming languages are Python and JavaScript\",\n    tags=[\"tech-preference\", \"programming\"],\n    metadata={\"confidence\": 0.95, \"source\": \"conversation-2026-01-30\"}\n)\n\n# Search with tag filtering\nfiltered_memories = memory_db.search_memories(\n    query=\"programming languages\",\n    tags=[\"tech-preference\"],\n    limit=5\n)\n\n🔧 Integration\n\nThis skill integrates seamlessly with Clawdbot's memory system as a drop-in replacement for memory-lancedb. Simply update your configuration to use this memory system instead of the traditional one.\n\n📊 Performance\nVector Dimension: 384 (Baidu Embedding-V1 output)\nStorage: SQLite database (~1MB per 1000 memories)\nSearch Speed: ~50ms for 1000 memories (on typical hardware)\nAPI Latency: Depends on Baidu API response time (typically <500ms)\n🔐 Security\nLocal Storage: All memories stored in local SQLite database\nEncrypted API Keys: Credentials stored securely in environment variables\nNo External Sharing: Memories never leave your system\nSelective Access: Granular control over what gets stored\n🔄 Migration from memory-lancedb\nInstall this skill in your skills/ directory\nConfigure your Baidu API credentials\nInitialize the new system\nUpdate your bot configuration to use the new memory system\nVerify data integrity and performance\n🤝 Contributing\n\nWe welcome contributions! Feel free to submit issues, feature requests, or pull requests to improve this skill."
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