openclaw-vector-storage-plugin/openclaw.plugin.json at main · maxyo/openclaw-vector-storage-plugin · GitHub

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{
  "id": "sqlite-doc-store",
  "name": "SQLite Document Store",
  "description": "Buffered document storage for OpenClaw using SQLite, FTS5, chunking, optional OpenAI-compatible embeddings, and future sqlite-vec support.",
  "version": "0.1.0",
  "kind": "extension",
  "skills": ["./skills"],
  "configSchema": {
    "type": "object",
    "additionalProperties": false,
    "properties": {
      "dbPath": {
        "type": "string",
        "default": "/config/.openclaw/sqlite-doc-store/documents.sqlite",
        "description": "Path to the SQLite database file."
      },
      "defaultChunkTargetTokens": {
        "type": "integer",
        "minimum": 100,
        "maximum": 4000,
        "default": 900,
        "description": "Default target chunk size in approximate tokens."
      },
      "defaultChunkOverlapTokens": {
        "type": "integer",
        "minimum": 0,
        "maximum": 1000,
        "default": 120,
        "description": "Default overlap between adjacent chunks in approximate tokens."
      },
      "enableFts": {
        "type": "boolean",
        "default": true,
        "description": "Enable SQLite FTS5 indexes for keyword search."
      },
      "vectorMode": {
        "type": "string",
        "enum": ["disabled", "sqlite-vec"],
        "default": "disabled",
        "description": "Vector search mode. sqlite-vec support is scaffolded but not enabled by default yet."
      },
      "sqliteVecExtensionPath": {
        "type": "string",
        "description": "Optional path to the sqlite-vec extension shared library."
      },
      "embedding": {
        "type": "object",
        "additionalProperties": false,
        "description": "Optional OpenAI-compatible embeddings provider used to generate chunk embeddings during save/backfill.",
        "properties": {
          "enabled": {
            "type": "boolean",
            "default": false,
            "description": "Enable chunk embedding generation. When false, documents are stored without calling the embeddings API."
          },
          "apiUrl": {
            "type": "string",
            "default": "https://api.openai.com/v1/embeddings",
            "description": "Full OpenAI-compatible embeddings endpoint URL."
          },
          "apiKey": {
            "type": "string",
            "description": "Bearer token for the OpenAI-compatible embeddings API."
          },
          "model": {
            "type": "string",
            "default": "text-embedding-3-small",
            "description": "Embedding model name sent to the upstream API."
          },
          "timeoutMs": {
            "type": "integer",
            "minimum": 1000,
            "maximum": 120000,
            "default": 30000,
            "description": "HTTP timeout for embedding requests in milliseconds."
          },
          "batchSize": {
            "type": "integer",
            "minimum": 1,
            "maximum": 128,
            "default": 32,
            "description": "Number of chunk texts batched into one embeddings request."
          },
          "dimensions": {
            "type": "integer",
            "minimum": 1,
            "description": "Optional embedding dimensionality, for providers/models that support overriding dimensions."
          }
        },
        "required": []
      }
    },
    "required": []
  },
  "uiHints": {
    "dbPath": {
      "label": "Database Path",
      "help": "SQLite file used as the buffered document store."
    },
    "defaultChunkTargetTokens": {
      "label": "Default Chunk Target Tokens",
      "advanced": true
    },
    "defaultChunkOverlapTokens": {
      "label": "Default Chunk Overlap Tokens",
      "advanced": true
    },
    "enableFts": {
      "label": "Enable FTS5"
    },
    "vectorMode": {
      "label": "Vector Mode",
      "advanced": true
    },
    "sqliteVecExtensionPath": {
      "label": "sqlite-vec Extension Path",
      "advanced": true
    },
    "embedding": {
      "label": "Embeddings Provider",
      "help": "OpenAI-compatible endpoint used to generate chunk embeddings."
    }
  }
}