opencode-mem.jsonc

{
  // ============================================
  // OpenCode Memory Plugin Configuration
  // ============================================

  // Storage location for vector database
  "storagePath": "~/.opencode-mem/data",

  "userEmailOverride": "",
  "userNameOverride": "",

  // ============================================
  // Embedding Model (for similarity search)
  // ============================================
  // Local = Hugging Face / ONNX via @huggingface/transformers (not Apple MLX).
  // Remote = set BOTH embeddingApiUrl and embeddingApiKey (OpenAI-compatible /embeddings).

  // Default: Nomic Embed v1 (768 dimensions, 8192 context, multilingual)
  "embeddingModel": "Xenova/nomic-embed-text-v1",

  // Opt-in Nomic task prefixes (search_document: / search_query:). After enabling,
  // re-index existing memories so store and query vectors stay aligned.
  // "embeddingUseTaskPrefixes": true,

  // Auto-detected dimensions (no need to set manually)
  // "embeddingDimensions": 768,

  // Other recommended local models:
  // "embeddingModel": "Xenova/jina-embeddings-v2-base-en",  // 768 dims, English-only, 8192 context
  // "embeddingModel": "Xenova/jina-embeddings-v2-small-en", // 512 dims, faster, 8192 context
  // "embeddingModel": "Xenova/all-MiniLM-L6-v2",            // 384 dims, very fast, 512 context
  // "embeddingModel": "Xenova/all-mpnet-base-v2",           // 768 dims, good quality, 512 context

  // Optional: OpenAI-compatible API for embeddings (both URL and key required)
  // "embeddingApiUrl": "https://api.openai.com/v1",
  // "embeddingApiKey": "env://OPENAI_API_KEY",  // or "sk-..." / "file:///path/to/key"
  // "embeddingModel": "text-embedding-3-small",  // 1536 dims, auto-detected

  // ============================================
  // Web Server Settings
  // ============================================

  // Enable web UI for managing memories (accessible at http://localhost:4747)
  "webServerEnabled": true,

  // Port for web UI server
  "webServerPort": 4747,

  // Host address for web UI (use 127.0.0.1 for local only, 0.0.0.0 for network access)
  "webServerHost": "127.0.0.1",

  // Optional HTTP Basic Auth for the web UI. Accepts literal, env://, or file:// secrets.
  // "webServerAuthPassword": "",
  // "webServerAuthUsername": "",

  // Required when webServerHost is not loopback. Protects /api/* with Bearer / X-Opencode-Mem-Token.
  // "webServerApiToken": "env://OPENCODE_MEM_WEB_TOKEN",

  // ============================================
  // Database Settings
  // ============================================

  // Maximum vectors per database shard (auto-creates new shard when limit reached)
  "maxVectorsPerShard": 50000,

  // Automatically delete old memories based on retention period
  "autoCleanupEnabled": true,

  // Days to keep memories before auto-cleanup (only if autoCleanupEnabled is true)
  "autoCleanupRetentionDays": 30,

  // Automatically detect and remove duplicate memories
  "deduplicationEnabled": true,

   // Similarity threshold (0-1) for detecting duplicates (higher = stricter)
   "deduplicationSimilarityThreshold": 0.90,

  // ============================================
  // Memory Scope Settings
  // ============================================

  // Default scope for memory list/search queries
  // "project" keeps queries within the current project, "all-projects" searches across all project shards
  "memory": {
    "defaultScope": "project"
  },

  // ============================================
  // OpenCode Provider Settings (RECOMMENDED)
  // ============================================

   // Use any provider that is already authenticated in opencode for auto-capture
   // and user profile learning. The plugin calls opencode's session.prompt API
   // (with structured output) instead of talking to provider HTTPS endpoints
   // directly, so opencode owns the auth, token refresh, and provider routing.
   //
   // No separate API key is needed in this plugin — whatever you configured in
   // opencode (OAuth like Claude Pro/Max, GitHub Copilot personal/business,
   // bring-your-own API key, custom provider, ...) just works.
   //
   // If NOT set, falls back to the manual config (memoryApiKey/memoryApiUrl/memoryModel below).
   //
   // Examples (the provider name must be one returned by 'opencode providers list'):
   //   Anthropic (OAuth/API key): "opencodeProvider": "anthropic",      "opencodeModel": "claude-haiku-4-5-20251001"
   //   OpenAI (API key):          "opencodeProvider": "openai",          "opencodeModel": "gpt-4o-mini"
   //   GitHub Copilot:            "opencodeProvider": "github-copilot",  "opencodeModel": "gpt-4o-mini"
   //
   // "opencodeProvider": "anthropic",
   // "opencodeModel": "claude-haiku-4-5-20251001",

   // ============================================
   // Auto-Capture Settings
   // ============================================

  // IMPORTANT: Auto-capture only runs after either opencodeProvider/opencodeModel
  // above is configured, or the manual fallback below is uncommented with real values.
  // It runs in background without blocking your main session
  // Note: Ollama may not support tool calling. Use OpenAI, Anthropic, or Groq for best results.

  "autoCaptureEnabled": true,

  // Provider type: "openai-chat" | "openai-responses" | "anthropic" | "minimax" | "orcarouter"
  // Note: "openai-chat" is a generic OpenAI API-compatible mode.
  // Any service that follows the OpenAI Chat Completions API can use it via custom "memoryApiUrl".
  "memoryProvider": "openai-chat",

  // Manual fallback. Uncomment all 3 lines and replace memoryApiKey before use:
  // "memoryModel": "gpt-4o-mini",
  // "memoryApiUrl": "https://api.openai.com/v1",
  // "memoryApiKey": "sk-...",

  // API Key Formats:
  // Direct value:        "sk-..."
  // From file:           "file://~/.config/litellm-key.txt"
  // From env variable:   "env://LITELLM_API_KEY"

  // Examples for different providers:
  // Any OpenAI-compatible endpoint can use the "openai-chat" provider pattern below.
  // Common examples: DeepSeek, Qwen (via Alibaba Cloud ModelStudio),
  // Zhipu GLM (BigModel platform), and Kimi (Moonshot AI platform).

  // OpenAI Chat Completion (default, backward compatible):
  //   "memoryProvider": "openai-chat"
  //   "memoryModel": "gpt-4o-mini"
  //   "memoryApiUrl": "https://api.openai.com/v1"
  //   "memoryApiKey": "sk-..."

  // DeepSeek (OpenAI-compatible example):
  //   "memoryProvider": "openai-chat"
  //   "memoryModel": "deepseek-chat"
  //   "memoryApiUrl": "https://api.deepseek.com/v1"
  //   "memoryApiKey": "sk-..."

  // OpenAI Responses API (recommended, with session support):
  //   "memoryProvider": "openai-responses"
  //   "memoryModel": "gpt-4o"
  //   "memoryApiUrl": "https://api.openai.com/v1"
  //   "memoryApiKey": "sk-..."

  // Anthropic (with session support):
  //   "memoryProvider": "anthropic"
  //   "memoryModel": "claude-3-5-haiku-20241022"
  //   "memoryApiUrl": "https://api.anthropic.com/v1"
  //   "memoryApiKey": "sk-ant-..."

  // MiniMax (Anthropic Messages-compatible endpoint, with session support):
  //   "memoryProvider": "minimax"
  //   "memoryModel": "MiniMax-M3"
  //   "memoryApiUrl": "https://api.minimax.io"        // global endpoint
  //   "memoryApiKey": "<MiniMax API key>"
  //   // China endpoint: "memoryApiUrl": "https://api.minimaxi.com"
  //   // Optional adaptive thinking for MiniMax-M3:
  //   "memoryExtraParams": { "thinking": { "type": "adaptive" } }

  // OrcaRouter (OpenAI-compatible gateway, namespaced model IDs, with session support):
  //   "memoryProvider": "orcarouter"
  //   "memoryApiKey": "<OrcaRouter API key>"
  //   // memoryApiUrl and memoryModel are optional — they default to
  //   // https://api.orcarouter.ai/v1 and "orcarouter/auto" (a routing alias).
  //   // OrcaRouter rejects bare model names, so if you set memoryModel, use a
  //   // namespaced ID such as "openai/gpt-5.5" or "deepseek/deepseek-v4-flash".
  //   "memoryModel": "openai/gpt-5.5"

  // Groq (OpenAI-compatible, use openai-chat provider):
  //   "memoryProvider": "openai-chat"
  //   "memoryModel": "llama-3.3-70b-versatile"
  //   "memoryApiUrl": "https://api.groq.com/openai/v1"
  //   "memoryApiKey": "gsk_..."

  // Maximum iterations for multi-turn AI analysis (for openai-responses, anthropic, and minimax)
  "autoCaptureMaxIterations": 5,

  // Timeout per iteration in milliseconds (30 seconds default)
  "autoCaptureIterationTimeout": 30000,

  // Maximum number of times to retry capturing a prompt if it fails (due to network, API errors, etc.)
  "autoCaptureMaxRetries": 3,

  // Maximum UTF-8 bytes for the auto-capture markdown context sent to the summary model.
  // Prevents HTTP 400 context overflows on models with ~131K token windows (e.g. Groq Llama).
  // Rough guide: tokens ≈ bytes / 4 for mixed code/prose.
  "autoCaptureMaxContextBytes": 131072,

  // Days to keep AI session history before cleanup
  "aiSessionRetentionDays": 7,

  // Temperature for AI API requests (set to false to omit parameter for models that don't support it)
  // Some reasoning models (like o1, o3, gpt-5) don't support temperature parameter
  // Set to false and add "memoryTemperature": false in config when using such models
  "memoryTemperature": 0.3,

  // Extra parameters to include in API request body
  // Useful for local inference servers (e.g. llama-server with --jinja) that support
  // additional parameters like disabling thinking/reasoning mode
  // Example for Qwen3 models: { "enable_thinking": false }
  // "memoryExtraParams": {},

  // Language for auto-capture summaries (default: "auto" for auto-detection)
  // Options: "auto", "en", "id", "zh", "ja", "es", "fr", "de", "ru", "pt", "ar", "ko"
  // "autoCaptureLanguage": "auto",

  // ============================================
  // Toast Notifications
  // ============================================

  // Show toast when memory is auto-captured
  "showAutoCaptureToasts": true,

  // Show toast when user profile is updated
  "showUserProfileToasts": true,

  // Show toast for error messages
  "showErrorToasts": true,

  // ============================================
  // User Profile System
  // ============================================

  // Analyze user prompts every N prompts to build/update your user profile
  // When N uncaptured prompts accumulate, AI will analyze them to identify:
  // - User preferences (code style, communication style, tool preferences)
  // - User patterns (recurring topics, problem domains, technical interests)
  // - User workflows (development habits, sequences, learning style)
  // - Skill level (overall and per-domain assessment)
  "userProfileAnalysisInterval": 10,

  // Days before inactive items (all types) are eligible for removal
  "userProfileStaleDays": 2,

  // Number of preferences shown in UI
  "userProfileDisplayPreferences": 20,

  // Number of patterns shown in UI
  "userProfileDisplayPatterns": 15,

  // Number of workflows shown in UI
  "userProfileDisplayWorkflows": 10,

  // Number of preferences injected into LLM conversation context
  // Keep this small — the strongest signals are enough; more dilute LLM attention
  "userProfileInjectPreferences": 5,

  // Number of patterns injected into LLM conversation context
  "userProfileInjectPatterns": 5,

  // Number of workflows injected into LLM conversation context
  "userProfileInjectWorkflows": 3,

  // Days before preference confidence starts to decay (if not reinforced)
  // Preferences that aren't seen again will gradually lose confidence and be removed
  "userProfileConfidenceDecayDays": 30,

  // Number of profile versions to keep in changelog (for rollback/debugging)
  // Older versions are automatically cleaned up
  "userProfileChangelogRetentionCount": 5,

  // Minimum evidence count for a preference/pattern to survive confidence decay
  // Items confirmed fewer times are more likely to be pruned when confidence decays
  "userProfileMinEvidenceForRetention": 3,

  // Periodically merge duplicate or irrelevant profile items with the configured AI provider
  "userProfileAutoCleanupEnabled": true,
  // Number of analyzed user prompts between automatic AI cleanup runs
  "userProfileAutoCleanupInterval": 100,

  // Enable LLM validation of existing preferences against recent behavior.
  // When enabled, each analysis round checks if top-5 preferences still match recent prompts.
  // Experimental — disabled by default.
  "userProfileValidationEnabled": false,

  // ============================================
  // Search Settings
  // ============================================

  // Minimum similarity score (0-1) for memory search results
  "similarityThreshold": 0.6,

  // Maximum number of memories to return in search results
  "maxMemories": 10,

  // ============================================
  // Advanced Settings
  // ============================================

  // Inject user profile into AI context (preferences, patterns, workflows)
  "injectProfile": true
}