{ "openapi": "3.0.1", "info": { "title": "Ai Memory Engine", "description": "Give your AI persistent memory. Store conversations, search semantically, build knowledge graphs, and watch your AI get smarter with every interaction.", "version": "1.0", "x-build-id": "G3BXtbIu47JCtaLU1" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ruv~ai-memory-engine/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ruv-ai-memory-engine", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ruv~ai-memory-engine/runs": { "post": { "operationId": "runs-sync-ruv-ai-memory-engine", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ruv~ai-memory-engine/run-sync": { "post": { "operationId": "run-sync-ruv-ai-memory-engine", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "action" ], "properties": { "action": { "title": "Action", "enum": [ "demo", "store", "search", "get", "list", "delete", "update", "clear", "stats", "batch_search", "hybrid_search", "find_duplicates", "deduplicate", "chat", "build_knowledge", "recommend", "analyze", "feedback", "export", "import", "integrate_synthetic", "integrate_scraper", "integrate_actor", "integrate_trading", "template", "natural", "cluster", "export_vectordb", "learn" ], "type": "string", "description": "Select the operation to perform on your memory database", "default": "demo" }, "sessionId": { "title": "Session ID", "type": "string", "description": "Unique identifier to persist memories across multiple Actor runs. 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 } } } } } } } } } }