# VectorAI DB

## Docs

- [Overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/home/getting-started/overview.md): High-performance vector database for AI similarity search.
- [Docker setup](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/home/installation/instructions.md): Get VectorAI DB running locally using Docker in just a few minutes.
- [Quickstart](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/home/quickstart/quickstart.md): Guide to help you get started with VectorAI DB in under five minutes.
- [Installation](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/sdks/python/installation.md): Install the Python SDK with pip install actian-vectorai-client.
- [Python SDK reference](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/sdks/python/reference.md): Core Python SDK clients, namespaces, configuration, filters, batching, and errors.
- [Installation](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/sdks/javascript/installation.md): Install the JavaScript SDK with npm install @actian/vectorai-client.
- [JavaScript SDK reference](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/sdks/javascript/reference.md): Core JavaScript SDK client, namespaces, options, filters, auth, batching, and errors.
- [Error handling](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/guides/error-handling.md): Understand error codes and exception types returned by VectorAI DB and how to handle them in your application.
- [Troubleshooting](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/guides/troubleshooting.md): Identify and fix common operational problems with VectorAI DB using guided diagnostic steps.
- [Local UI](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/guides/gui-interface.md): Manage and interact with VectorAI DB through the built-in web interface.
- [Monitoring and logging](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/guides/monitoring-and-logging.md): Set up Prometheus metrics collection, understand available metrics, configure alerts, and manage logs for VectorAI DB in production.
- [Overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/integrations/index.md): Connect VectorAI DB with embedding providers and AI frameworks to build semantic search, RAG pipelines, and AI-powered applications.
- [LangChain](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/integrations/langchain.md): Use Actian VectorAI DB as a vector store in LangChain for building RAG pipelines, semantic search, and AI-powered applications.
- [LlamaIndex](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/integrations/llama-index.md): Use Actian VectorAI DB as a vector store in LlamaIndex for building RAG pipelines, semantic search, and AI-powered applications.
- [FAQ](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/home/support/faq.md): Frequently asked questions about VectorAI DB.
- [Support](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/home/support/support.md): Resources and contact options for VectorAI DB community and licensed customers.
- [Licensing](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/home/support/license.md): Information on VectorAI DB licensing and other legal matters.
- [EULA](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/home/support/eula.md): End-User License Agreement.
- [Introduction](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/index.md): Learn the core fundamentals of Actian VectorAI DB.
- [Collections overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/collections/collections.md): Learn about collections, the primary unit of storage in VectorAI DB, including structure, distance metrics, index parameters, and lifecycle states.
- [Create a collection](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/collections/create-collection-task.md): Create collections with default or custom index parameters.
- [Get collection info](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/collections/get-collection-info-task.md): Retrieve collection metadata, statistics, and state.
- [Update collection parameters](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/collections/update-collection-task.md): Modify collection configuration after creation.
- [Delete a collection](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/collections/delete-collection-task.md): Permanently remove or recreate collections.
- [Inspect and maintain collections](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/collections/manage-collection-state-task.md): Monitor collection state, flush data, optimize storage, and rebuild indexes.
- [Collection workflow](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/collections/complete-workflow.md): A complete walkthrough of creating, populating, querying, maintaining, and deleting a collection.
- [Points overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/points/points.md): Points are the fundamental data units in Actian VectorAI DB, each containing a unique ID, a vector embedding, and an optional JSON payload. Covers point structure, supported operations, and how points relate to collections.
- [Insert points](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/points/insert-points-task.md): Add individual points or batches of points to a collection.
- [Retrieve points](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/points/retrieve-points-task.md): Fetch points from a collection by ID or through pagination.
- [Update points](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/points/update-points-task.md): Modify existing points with new vector and payload data.
- [Delete points](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/points/delete-points-task.md): Remove points from a collection by ID and compact to reclaim storage.
- [Vectors overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/vectors/vectors.md): Convert unstructured data into searchable numerical embeddings.
- [Store vectors](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/vectors/create-vectors-task.md): Store dense vectors with metadata in a collection.
- [Search with vectors](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/vectors/search-vectors-task.md): Search a collection in VectorAI DB using a query vector to retrieve the most semantically similar points, ranked by similarity score.
- [Payloads overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/payload/payload.md): Payloads are JSON objects attached to points in VectorAI DB. They store metadata such as categories, prices, and timestamps that enable hybrid search combining vector similarity with metadata filtering.
- [Create payloads](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/payload/create-payload-task.md): Add JSON metadata when inserting points into a collection.
- [Update payloads](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/payload/update-payload-task.md): Modify payload metadata for existing points.
- [Search with payload filters](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/payload/filter-payload-task.md): Apply must, should, and must-not filter conditions to payload fields during vector search in VectorAI DB to return results that match both similarity and metadata criteria.
- [Search overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/search/search.md): Vector search in VectorAI DB finds the most similar vectors to a query using distance metrics. Covers search parameters, result fields, score interpretation, and performance optimization strategies.
- [Basic similarity search](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/search/basic-search-task.md): Search for the most similar vectors to your query.
- [Search with filters](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/search/filtered-search-task.md): Combine vector similarity with metadata conditions.
- [Search with payload](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/search/search-with-payload-task.md): Include metadata in search results.
- [Search with vectors](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/search/search-with-vectors-task.md): Include vector embeddings in search results.
- [Filtering overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/filtering/filtering.md): Narrow vector search results using must, should, and must-not metadata conditions.
- [Filter with must conditions](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/filtering/must-filter-task.md): Apply AND logic to require all conditions match.
- [Filter with must-not conditions](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/filtering/must-not-filter-task.md): Exclude results where conditions are true.
- [Filter with should conditions](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/filtering/should-filter-task.md): Apply OR logic to match at least one condition.
- [Combine filter types](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/filtering/combined-filter-task.md): Build complex queries with must, should, and must-not conditions.
- [Overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/semantic-search/semantic-search.md): Semantic search in Actian VectorAI DB finds documents by meaning rather than keywords. Covers embedding-based retrieval, payload filtering, score thresholds, and multiconstraint search patterns for RAG pipelines.
- [Pure semantic search](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/semantic-search/pure-semantic-search-task.md): Search for documents by meaning using vector similarity.
- [Filtered semantic search](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/semantic-search/filtered-semantic-search-task.md): Combine vector similarity with keyword and range filters.
- [Score threshold search](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/semantic-search/score-threshold-search-task.md): Filter semantic search results by minimum similarity score.
- [Multiconstraint search](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/semantic-search/multi-constraint-search-task.md): Combine multiple metadata conditions with vector similarity.
- [Complete workflow](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/semantic-search/complete-workflow.md): End-to-end semantic search pipeline with embedding, indexing, and multiple search strategies.
- [Overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/hybrid-search/hybrid-search.md): Hybrid search in Actian VectorAI DB combines results from multiple search queries using fusion algorithms like Reciprocal Rank Fusion and Distribution-Based Score Fusion to improve retrieval quality.
- [Hybrid RAG retrieval](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/hybrid-search/hybrid-rag-task.md): Combine original and reformulated question embeddings for improved RAG context retrieval.
- [Reciprocal Rank Fusion](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/hybrid-search/rrf-fusion-task.md): Combine results from multiple dense vector searches using Reciprocal Rank Fusion.
- [Distribution-Based Score Fusion](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/hybrid-search/dbsf-fusion-task.md): Combine semantic and keyword search results using Distribution-Based Score Fusion.
- [Multimodel fusion](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/hybrid-search/multi-model-fusion-task.md): Combine search results from multiple embedding models using fusion.
- [Query variation fusion](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/hybrid-search/query-variation-task.md): Improve search robustness by fusing results from query vector variations.
- [Performance benchmarking](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/hybrid-search/performance-benchmark-task.md): Compare execution time between single search and hybrid search approaches.
- [Distance metrics overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/distance-metrics/distance-metrics.md): Measure similarity between vectors using cosine similarity, Euclidean distance, or dot product.
- [Configure cosine similarity](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/distance-metrics/cosine-similarity-task.md): Create a collection that measures angular similarity between vectors.
- [Configure Euclidean distance](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/distance-metrics/euclidean-distance-task.md): Create a collection that measures straight-line distance between vectors.
- [Configure dot product](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/distance-metrics/dot-product-task.md): Create a collection that measures alignment and magnitude efficiently.
- [Indexing overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/indexing/indexing.md): Learn how VectorAI DB uses HNSW indexing for fast approximate nearest neighbor search, including tunable parameters and tradeoffs between speed, accuracy, and memory.
- [Configure HNSW parameters](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/docs/fundamentals/indexing/configure-hnsw-task.md): Set HNSW parameters when creating a collection to control the tradeoff between search speed, recall accuracy, and memory usage in VectorAI DB.
- [REST API overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest.md): Complete REST API documentation for VectorAI DB operations.
- [Create collection](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/collections/collections/create-collection.md): Create a new collection with a specified vector configuration. You must provide the vector dimension and distance metric. Supported distance metrics are `Cosine`, `Euclid`, `Dot`, and `Manhattan`.
- [List all collections](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/collections/collections/list-all-collections.md): Get a list of all existing collection names in the database. Use `GET /collections/{collection_name}` to get detailed information about a specific collection.
- [Get collection info](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/collections/collections/get-collection-info.md): Get detailed information about a specific collection, including vector configuration, index type and parameters, point count, and collection status.
- [Check if collection exists](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/collections/collections/check-if-collection-exists.md): Check whether a collection with the given name exists in the database.
- [Update collection](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/collections/collections/update-collection.md): Update parameters of an existing collection, such as optimizer configuration and HNSW search settings. Vector dimension and distance metric cannot be changed after creation.
- [Delete collection](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/collections/collections/delete-collection.md): Delete a collection and all its data permanently. This operation is irreversible. All vectors, payloads, and indexes will be permanently removed.
- [Upsert points](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/points/points/upsert-points.md): Insert or update points in a collection. If a point with the given ID already exists, it is overwritten. All points in the request are inserted or updated atomically.
- [Get single point](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/points/points/get-single-point.md): Retrieve full information for a single point by its ID, including its vector and payload.
- [Get points by IDs](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/points/points/get-points-by-ids.md): Retrieve multiple points by their IDs. Returns the matching points with their vectors and payloads based on the request parameters.
- [Update vectors](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/points/points/update-vectors.md): Update vector data for existing points without modifying their payloads. This is useful when re-embedding content or correcting vector values.
- [Overwrite payload](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/points/points/overwrite-payload.md): Replace the entire payload on the specified points. All existing payload fields are removed and replaced with the provided object. Use the set payload endpoint to merge instead.
- [Set payload](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/points/points/set-payload.md): Merge payload fields onto existing points identified by ID. Existing payload fields that are not specified in the request are preserved.
- [Delete payload keys](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/points/points/delete-payload-keys.md): Remove specific payload fields from the specified points. Only explicitly listed point IDs are supported; filter-based targeting is not available for this operation. If a key does not exist on a given point, it is silently ignored.
- [Clear payload](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/points/points/clear-payload.md): Remove all payload fields from the specified points, leaving them with an empty payload. Only explicitly listed point IDs are supported; filter-based targeting is not available for this operation. Points that already have an empty payload are unaffected.
- [Delete points](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/points/points/delete-points.md): Delete points from a collection by specifying a list of point IDs.
- [Search vectors](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/search/search/search-vectors.md): Find the most similar vectors in a collection using approximate nearest neighbor search. Supports score thresholds, payload filtering, and tunable HNSW parameters.
- [Batch search](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/search/search/batch-search.md): Execute multiple search queries in a single request. This is more efficient than sending individual search requests when you have several queries to run.
- [Scroll points](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/search/scroll/scroll-points.md): Paginate through all points in a collection. The response includes a `next_page_offset` cursor that you pass as `offset` in subsequent requests to retrieve the next page. Useful for exporting data, iterating large datasets, or processing points in batches.
- [Count points](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/search/count/count-points.md): Count the number of points in a collection, optionally filtered by payload conditions. Useful for checking collection size, validating data loads, or counting points matching specific criteria.
- [Filter examples](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/rest/filters/filters/filter-examples.md): Filters narrow the results of search, scroll, count, and other point operations by applying conditions to payload fields. You pass a filter object in the `filter` parameter of these operations.
- [Create access token](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/access-tokens/create-access-token.md): Creates a new access token with the specified name, description, expiration, and permissions.
- [List access tokens](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/access-tokens/list-access-tokens.md): Returns a list of all access tokens. The response does not include the raw token values.
- [Delete access token](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/access-tokens/delete-access-token.md): Deletes an access token by its ID. The token is immediately invalidated and can no longer be used for authentication.
- [Rotate access token](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/access-tokens/rotate-access-token.md): Generates a new raw token for an existing access token and invalidates the previous raw token immediately. The token `id`, `name`, `description`, `permission`, `will_expire`, and `expired_at` values are preserved.
- [Create admin user](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/admin-user/create-admin-user.md): Creates the built-in admin user with the given password. The username is always fixed to `admin`.
- [Reset admin password](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/admin-user/reset-admin-password.md): Resets the built-in admin user's password. The username is always fixed to `admin`.
- [Admin login](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/admin-user/admin-login.md): Authenticates the admin user and returns a JWT token. The username is always fixed to `admin`. No authorization header is required for this endpoint.
- [Check admin exists](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/admin-user/check-admin-exists.md): Returns whether the admin user has been created. No authorization is required for this endpoint.
- [Set auth enabled](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/admin-user/set-auth-enabled.md): Enables or disables authentication enforcement for the server. When auth is disabled, endpoints that normally require access tokens or JWT authorization can be called without credentials.
- [Error codes](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/error-codes.md): HTTP status codes and error responses returned by the VectorAI DB REST API.
- [gRPC endpoints](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/api-reference/grpc/index.md): gRPC endpoints for VectorAI DB.
- [Overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/index.md): Learn Actian VectorAI DB through hands-on tutorials, deep-dive articles, and ready-to-run examples.
- [Overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/tutorials/index.md): Hands-on tutorials to build vector search applications with Actian VectorAI DB.
- [Build your first application](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/tutorials/first-application.md): Step-by-step guide to building a semantic search app with Actian VectorAI DB: install, connect, create collections, embed, store, search, filter, update, and delete.
- [Similarity search fundamentals](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/tutorials/similarity-search.md): Learn the core vector similarity search workflow with Actian VectorAI DB: embedding, storing, searching, scoring, tuning, batching, and paginating results.
- [Predicate filters](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/tutorials/predicate-filters.md): Learn how to combine vector similarity search with structured payload filters using Actian VectorAI DB's type-safe Filter DSL.
- [Use open-source embedding models](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/tutorials/leverage-open-source-embedding-models.md): Learn how to choose, configure, and integrate open-source embedding models with Actian VectorAI DB — covering model selection, dimensionality trade-offs, distance metrics, batch ingestion, quantization for large models, named vectors for multimodel search, and reembedding workflows.
- [Building a multimodal system](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/tutorials/multimodel-system.md): Work with multiple embedding models in one system
- [Optimizing retrieval quality](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/tutorials/retrieval-quality.md): Learn how to measure and improve similarity search accuracy in Actian VectorAI DB by tuning HNSW parameters, choosing the right distance metric, configuring quantization, using multistage prefetch, adjusting score thresholds, and leveraging payload indexes.
- [Adaptive RAG systems](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/tutorials/adaptive-rag.md): Learn how to build a Retrieval-Augmented Generation system that adapts its retrieval strategy at runtime based on query type, confidence signals, and user feedback — using Actian VectorAI DB's multistage prefetch, fusion, score thresholds, payload-driven routing, and feedback loops.
- [Overview](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/articles/index.md): Browse and choose from deep-dive articles on building AI agents and intelligent applications with Actian VectorAI DB.
- [AI legal contract intelligence agent](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/articles/building-a-scalable-agent-memory-with-Actian-vector-AI-database.md): Build an AI-powered legal contract analysis system using Actian VectorAI DB with cross-collection lookup, payload-sorted retrieval, connection pooling, and quantization-aware search.
- [AI recipe recommendation agent](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/articles/AI-recipe-recommendation-agent.md): Build an AI-powered recipe recommendation agent using Actian VectorAI DB that matches user cravings to recipes through semantic search, filters by dietary restrictions and available ingredients, and learns preferences over time.
- [AI supply chain inventory risk intelligence agent](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/articles/supply-chain-inventory-management-agent.md): Build an AI-powered supply chain risk intelligence workflow using Actian VectorAI DB, semantic retrieval, payload filters, and lightweight reasoning.
- [Multivector document intelligence with visual RAG](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/articles/Multivector-Document-Intelligence-with-Visual-RAG.md): Build a multimodal document intelligence system that embeds PDF pages as images with CLIP, retrieves them via Actian VectorAI DB, and generates answers using GPT-4o vision.
- [Next-gen product discovery with multimodal AI](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/academy/articles/Next-Gen-Product-Discovery-with-Multimodal-AI.md): Build a multimodal hybrid search system combining CLIP dense embeddings and BM25 sparse scoring for semantic and keyword product retrieval using Actian VectorAI DB.

## OpenAPI Specs

- [search-api](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/openapi_prepared/search-api.yaml)
- [points-api](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/openapi_prepared/points-api.yaml)
- [grouped-search-api](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/openapi_prepared/grouped-search-api.yaml)
- [filters-api](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/openapi_prepared/filters-api.yaml)
- [collections-api](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/openapi_prepared/collections-api.yaml)
- [authentication-api](https://actianvectorai-ml-crtx-1153-academy-tutorial-rewrites.mintlify.site/openapi_prepared/authentication-api.yaml)