# Send memory_baidu_embedding_db to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - Download the package from Yavira. - Extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the extracted folder. ## Suggested prompts ### New install ```text I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete. ``` ### Upgrade existing ```text I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "memory-baidu-embedding-db", "name": "memory_baidu_embedding_db", "source": "tencent", "type": "skill", "category": "AI 智能", "sourceUrl": "https://clawhub.ai/xqicxx/memory-baidu-embedding-db", "canonicalUrl": "https://clawhub.ai/xqicxx/memory-baidu-embedding-db", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/memory-baidu-embedding-db", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=memory-baidu-embedding-db", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "ERROR_HANDLING_BEST_PRACTICES.md", "DISABLE_LANCEDB.md", "memory_skill_full_verification.sh", "memory_baidu_embedding_db.py", "memory_system_comprehensive_guide.md", "API_REFERENCE.md" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "memory-baidu-embedding-db", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-05-05T00:23:09.707Z", "expiresAt": "2026-05-12T00:23:09.707Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=memory-baidu-embedding-db", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=memory-baidu-embedding-db", "contentDisposition": "attachment; filename=\"memory-baidu-embedding-db-2.0.1.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "memory-baidu-embedding-db" }, "scope": "item", "summary": "Item download looks usable.", "detail": "Yavira can redirect you to the upstream package for this item.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/memory-baidu-embedding-db" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/memory-baidu-embedding-db", "downloadUrl": "https://openagent3.xyz/downloads/memory-baidu-embedding-db", "agentUrl": "https://openagent3.xyz/skills/memory-baidu-embedding-db/agent", "manifestUrl": "https://openagent3.xyz/skills/memory-baidu-embedding-db/agent.json", "briefUrl": "https://openagent3.xyz/skills/memory-baidu-embedding-db/agent.md" } } ``` ## Documentation ### Memory Baidu Embedding DB - Semantic Memory for Clawdbot Vector-Based Memory Storage and Retrieval Using Baidu Embedding Technology A 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. ### πŸš€ Features Semantic Memory Search - Find memories based on meaning, not just keywords Baidu Embedding Integration - Uses Baidu's powerful Embedding-V1 model SQLite Persistence - Local, secure storage without external dependencies Zero Data Leakage - All processing happens locally with your API credentials Flexible Tagging System - Organize memories with custom tags and metadata High Performance - Optimized vector similarity calculations Easy Migration - Drop-in replacement for memory-lancedb systems ### 🎯 Use Cases Conversational Context - Remember user preferences and conversation history Knowledge Management - Store and retrieve information semantically Personalization - Maintain user-specific settings and preferences Information Retrieval - Find related information based on meaning Data Organization - Structure memories with tags and metadata ### πŸ“‹ Requirements Clawdbot installation Baidu Qianfan API credentials (API Key and Secret Key) Python 3.8+ Internet connection for initial API calls ### Manual Installation Place the skill files in your ~/clawd/skills/ directory Install dependencies (if any Python packages are needed) Configure your Baidu API credentials ### Configuration Set environment variables: export BAIDU_API_STRING='${BAIDU_API_STRING}' export BAIDU_SECRET_KEY='${BAIDU_SECRET_KEY}' ### Basic Usage from memory_baidu_embedding_db import MemoryBaiduEmbeddingDB # Initialize the memory system memory_db = MemoryBaiduEmbeddingDB() # Add a memory memory_db.add_memory( content="The user prefers concise responses and enjoys technical discussions", tags=["user-preference", "communication-style"], metadata={"importance": "high"} ) # Search for related memories using natural language related_memories = memory_db.search_memories("What does the user prefer?", limit=3) ### Advanced Usage # Add multiple memories with rich metadata memory_db.add_memory( content="User's favorite programming languages are Python and JavaScript", tags=["tech-preference", "programming"], metadata={"confidence": 0.95, "source": "conversation-2026-01-30"} ) # Search with tag filtering filtered_memories = memory_db.search_memories( query="programming languages", tags=["tech-preference"], limit=5 ) ### πŸ”§ Integration 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. ### πŸ“Š Performance Vector Dimension: 384 (Baidu Embedding-V1 output) Storage: SQLite database (~1MB per 1000 memories) Search Speed: ~50ms for 1000 memories (on typical hardware) API Latency: Depends on Baidu API response time (typically <500ms) ### πŸ” Security Local Storage: All memories stored in local SQLite database Encrypted API Keys: Credentials stored securely in environment variables No External Sharing: Memories never leave your system Selective Access: Granular control over what gets stored ### πŸ”„ Migration from memory-lancedb Install this skill in your skills/ directory Configure your Baidu API credentials Initialize the new system Update your bot configuration to use the new memory system Verify data integrity and performance ### 🀝 Contributing We welcome contributions! Feel free to submit issues, feature requests, or pull requests to improve this skill. ## Trust - Source: tencent - Verification: Indexed source record - Publisher: xqicxx - Version: 2.0.1 ## Source health - Status: healthy - Item download looks usable. - Yavira can redirect you to the upstream package for this item. - Health scope: item - Reason: direct_download_ok - Checked at: 2026-05-05T00:23:09.707Z - Expires at: 2026-05-12T00:23:09.707Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/memory-baidu-embedding-db) - [Send to Agent page](https://openagent3.xyz/skills/memory-baidu-embedding-db/agent) - [JSON manifest](https://openagent3.xyz/skills/memory-baidu-embedding-db/agent.json) - [Markdown brief](https://openagent3.xyz/skills/memory-baidu-embedding-db/agent.md) - [Download page](https://openagent3.xyz/downloads/memory-baidu-embedding-db)