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Give your AI persistent memory. Store conversations, search semantically, build knowledge graphs, and watch your AI get smarter with every interaction.
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Reuven Cohen
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You can access the Ai Memory Engine programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
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Use the same Session ID to continue where you left off. Leave empty for one-time runs." }, "namespace": { "title": "Memory Namespace", "type": "string", "description": "Organize memories into separate collections (like folders). Different namespaces are completely isolated.", "default": "default" }, "memories": { "title": "Memories to Store", "type": "array", "description": "Text content to store in memory. Each item becomes a searchable memory with vector embeddings." }, "query": { "title": "Search Query", "type": "string", "description": "What are you looking for? The engine uses semantic understanding to find relevant memories even with different wording." }, "queries": { "title": "Batch Search Queries", "type": "array", "description": "Multiple search queries to run in parallel. Each query returns its own set of results." }, "memoryId": { "title": "Memory ID", "type": "string", "description": "Unique identifier of a specific memory for get/delete/update operations" }, "memoryIds": { "title": "Memory IDs (Batch)", "type": "array", "description": "Array of memory IDs for batch delete operation", "items": { "type": "string" } }, "updates": { "title": "Memory Updates", "type": "object", "description": "Fields to update on a memory. You can update text, metadata, or both." }, "metadataFilter": { "title": "Metadata Filter", "type": "object", "description": "Filter memories by metadata fields. Only memories matching ALL specified fields are affected." }, "topK": { "title": "Number of Results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of similar memories to return", "default": 10 }, "similarityThreshold": { "title": "Similarity Threshold", "minimum": 0, "maximum": 1, "type": "number", "description": "Minimum similarity score required. Higher values return more relevant but fewer results.", "default": 0.7 }, "distanceMetric": { "title": "Distance Metric", "enum": [ "cosine", "euclidean", "dot_product", "manhattan" ], "type": "string", "description": "Algorithm used to measure similarity between memory vectors", "default": "cosine" }, "keywordWeight": { "title": "Keyword Weight (Hybrid Search)", "minimum": 0, "maximum": 1, "type": "number", "description": "Weight given to exact keyword matching in hybrid search. Set to 0 for pure semantic search.", "default": 0.3 }, "semanticWeight": { "title": "Semantic Weight (Hybrid Search)", "minimum": 0, "maximum": 1, "type": "number", "description": "Weight given to semantic similarity in hybrid search. Set to 1 for pure semantic search.", "default": 0.7 }, "limit": { "title": "Results per Page", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of memories to return when listing", "default": 100 }, "offset": { "title": "Skip Results", "minimum": 0, "type": "integer", "description": "Number of memories to skip for pagination (e.g., offset=100 starts at the 101st result)", "default": 0 }, "sortBy": { "title": "Sort By", "enum": [ "createdAt", "updatedAt", "accessCount" ], "type": "string", "description": "Field to sort list results by", "default": "createdAt" }, "sortOrder": { "title": "Sort Order", "enum": [ "asc", "desc" ], "type": "string", "description": "Sort direction for list results", "default": "desc" }, "duplicateThreshold": { "title": "Duplicate Similarity Threshold", "minimum": 0.8, "maximum": 1, "type": "number", "description": "How similar memories must be to be considered duplicates. 0.95 = very similar, 1.0 = exact match.", "default": 0.95 }, "chatMessage": { "title": "Your Message", "type": "string", "description": "Your message to the AI assistant. The assistant will use stored memories to provide context-aware responses." }, "chatHistory": { "title": "Conversation History", "type": "array", "description": "Previous messages in the conversation for context. Each message has a 'role' (user/assistant) and 'content'." }, "provider": { "title": "AI Provider", "enum": [ "gemini", "openrouter", "local" ], "type": "string", "description": "Which AI service to use for chat and advanced features", "default": "gemini" }, "apiKey": { "title": "AI Provider API Key", "type": "string", "description": "Your API key for the selected provider. Get free Gemini key at ai.google.dev" }, "model": { "title": "AI Model", "enum": [ "gemini-2.0-flash-exp", "gemini-2.0-flash-thinking-exp", "gemini-1.5-pro", "openai/gpt-4o", "openai/gpt-4o-mini", "anthropic/claude-3.5-sonnet", "meta-llama/llama-3.3-70b-instruct" ], "type": "string", "description": "Which language model to use for chat and generation", "default": "gemini-2.0-flash-exp" }, "sonaEnabled": { "title": "Enable SONA Learning", "type": "boolean", "description": "SONA (Self-Optimizing Neural Architecture) continuously improves search quality based on usage patterns", "default": true }, "learningEnabled": { "title": "Enable Interaction Learning", "type": "boolean", "description": "Learn from search queries and feedback to improve future results", "default": true }, "forceBackgroundLearning": { "title": "Force Learning Cycle", "type": "boolean", "description": "Run a SONA background learning cycle after this operation completes", "default": false }, "ewcLambda": { "title": "Anti-Forgetting Strength (EWC++)", "minimum": 100, "maximum": 15000, "type": "number", "description": "How strongly to prevent forgetting old patterns when learning new ones. Higher = more conservative learning.", "default": 2000 }, "patternThreshold": { "title": "Pattern Confidence Threshold", "minimum": 0.5, "maximum": 1, "type": "number", "description": "Minimum confidence required to learn a new pattern. Higher = only learn strong patterns.", "default": 0.85 }, "knowledgeGraphEnabled": { "title": "Build Knowledge Graph", "type": "boolean", "description": "Automatically extract entities and relationships from stored memories to build a knowledge graph", "default": false }, "feedbackRating": { "title": "Result Rating", "minimum": 1, "maximum": 5, "type": "integer", "description": "Rate the quality of a search result or recommendation to help SONA learn (5 = perfect, 1 = irrelevant)", "default": 5 }, "feedbackCorrection": { "title": "Correction Text", "type": "string", "description": "If a memory is incorrect, provide the correct text here. SONA will learn from this correction." }, "exportFormat": { "title": "Export Format", "enum": [ "json", "csv", "embeddings" ], "type": "string", "description": "File format for exporting your memory database", "default": "json" }, "vectorDbFormat": { "title": "Vector DB Export Format", "enum": [ "pinecone", "weaviate", "chromadb", "qdrant", "langchain", "openai" ], "type": "string", "description": "Export in a format compatible with popular vector databases", "default": "pinecone" }, "importData": { "title": "Import Data", "type": "object", "description": "JSON data to import into memory. Should contain an array of memories with text and optional metadata." }, "actorId": { "title": "Actor to Integrate", "enum": [ "apify/google-maps-scraper", "apify/yelp-scraper", "apify/tripadvisor-scraper", "apify/instagram-scraper", "apify/twitter-scraper", "apify/tiktok-scraper", "apify/reddit-scraper", "apify/facebook-scraper", "apify/linkedin-scraper", "apify/youtube-scraper", "apify/amazon-scraper", "apify/shopify-scraper", "apify/ebay-scraper", "apify/walmart-scraper", "apify/booking-scraper", "apify/airbnb-scraper", "apify/expedia-scraper", "apify/glassdoor-scraper", "apify/indeed-scraper", "apify/crunchbase-scraper", "apify/google-search-scraper", "apify/news-scraper", "apify/rss-feed-scraper", "apify/zillow-scraper", "apify/realtor-scraper", "ruv/ai-synthetic-data-generator", "ruv/neural-trader-system", "custom" ], "type": "string", "description": "Select a popular actor or enter any Apify actor ID (owner/actor-name)", "default": "apify/google-maps-scraper" }, "customActorId": { "title": "Custom Actor ID", "type": "string", "description": "Enter the full actor ID (e.g., username/actor-name) when using 'Custom Actor' option" }, "actorCategory": { "title": "Filter by Category", "enum": [ "all", "local", "social", "ecommerce", "travel", "professional", "content", "realestate", "data" ], "type": "string", "description": "Filter actors by category to find the right one faster", "default": "all" }, "actorRunMode": { "title": "Data Source", "enum": [ "latest", "specific", "fresh", "dataset", "discovery" ], "type": "string", "description": "Where to get the actor's data from", "default": "latest" }, "actorRunId": { "title": "Specific Run ID", "type": "string", "description": "Run ID to fetch data from (when using 'Specific Run' mode)" }, "actorDatasetId": { "title": "Dataset ID", "type": "string", "description": "Dataset ID to fetch data from (when using 'Dataset Only' mode)" }, "actorInput": { "title": "Actor Input (Fresh Run)", "type": "object", "description": "Input configuration for starting a fresh actor run" }, "actorConfig": { "title": "Memory Settings", "type": "object", "description": "Configure how actor data is processed and stored in memory" }, "actorTimeout": { "title": "Actor Timeout", "minimum": 30, "maximum": 600, "type": "integer", "description": "Maximum wait time for fresh actor runs (in seconds). Longer timeouts allow more data but cost more.", "default": 120 }, "actorMemoryLimit": { "title": "Actor Memory (MB)", "minimum": 256, "maximum": 8192, "type": "integer", "description": "Memory allocation for fresh actor runs (higher = faster but costs more)", "default": 1024 }, "integrationConfig": { "title": "Synthetic Data Configuration", "type": "object", "description": "Settings for generating and memorizing synthetic test data" }, "scraperConfig": { "title": "Web Scraper Configuration", "type": "object", "description": "Configure web pages to scrape and memorize" }, "tradingSymbols": { "title": "Trading Symbols", "type": "array", "description": "Crypto/stock symbols to analyze and generate trading signals for", "items": { "type": "string" } }, "tradingStrategy": { "title": "Trading Strategy", "enum": [ "ensemble", "neural_momentum", "lstm_prediction", "transformer_attention", "reinforcement" ], "type": "string", "description": "Neural network strategy to use for signal generation", "default": "ensemble" }, "memorizeSignals": { "title": "Store Trading Signals", "type": "boolean", "description": "Save generated trading signals as searchable memories for later analysis", "default": true }, "memorizeMarketData": { "title": "Store Market Data", "type": "boolean", "description": "Also store market data (price, volume, indicators) alongside signals", "default": false }, "signalConfidenceThreshold": { "title": "Signal Confidence Threshold", "minimum": 0, "maximum": 100, "type": "integer", "description": "Minimum confidence level required to store a signal (0-100). Higher = only store high-conviction signals.", "default": 70 }, "searchTradingHistory": { "title": "Search Trading History", "type": "boolean", "description": "Instead of generating new signals, search existing trading memories", "default": false }, "tradingHistoryQuery": { "title": "Trading History Query", "type": "string", "description": "Search query for finding relevant trading signals and market data in memory" }, "tradingActorConfig": { "title": "Neural Trader Actor Settings", "type": "object", "description": "Advanced configuration for the Neural Trader System actor" }, "template": { "title": "Template", "enum": [ "lead-intelligence", "customer-support", "research-assistant", "competitor-intelligence", "content-library", "product-catalog" ], "type": "string", "description": "Load a pre-built memory template optimized for specific use cases" }, "command": { "title": "Natural Language Command", "type": "string", "description": "Tell the AI what you want in plain English. Examples: 'remember that John prefers email', 'what do you know about customers', 'find similar products'" }, "numClusters": { "title": "Number of Clusters", "minimum": 2, "maximum": 20, "type": "integer", "description": "How many groups to organize your memories into based on similarity", "default": 5 }, "embeddingModel": { "title": "Embedding Model", "enum": [ "ruvllm-768", "ruvllm-384", "gemini", "openai" ], "type": "string", "description": "Model used to convert text into vector embeddings for semantic search", "default": "ruvllm-768" }, "seed": { "title": "Random Seed", "type": "string", "description": "Set a seed for reproducible results across runs" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } }}OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. 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