- [+] expand all
- Getting started
- Vespa Overview
- Features
- Getting Started
- Vespa CLI
- Getting Started with Ranking
- Tutorials
- Vespa API and Interfaces
- Frequently Asked Questions - FAQ
- Glossary
- Schemas and documents
- Documents
- Schemas
- Parent/Child
- Annotations API
- Concrete document types
- Reading and writing
- Reads and Writes
- /document/v1
- Visiting
- Vespa Feed Client
- Indexing
- Document API
- Partial Updates
- Querying
- Query API
- Vespa Query Language
- Grouping Information in Results
- Federation
- Query Profiles
- Nearest Neighbor Search
- Approximate Nearest Neighbor Search
- Nearest Neighbor Search Guide
- Text matching
- Geo Search
- Predicate Fields
- Streaming Search
- Document Summaries
- Result Renderers
- Page Templates
- Result Diversity
- Ranking and ML models
- Ranking Introduction
- Rank Features and Expressions
- Embedding
- Multivalue Query Operators
- Tensor User Guide
- Tensor Examples
- Phased Ranking
- Searcher Re-Ranking
- Cross-Encoder Transformer Ranking
- Ranking With TensorFlow Models
- Ranking With ONNX Models
- Ranking With XGBoost Models
- Ranking With LightGBM Models
- Stateless Model Evaluation
- Ranking With BM25
- Significance Model
- Ranking With nativeRank
- Accelerated OR search using the WAND algorithm
- Linguistics and text processing
- Linguistics in Vespa
- Query Rewriting
- Embedding text
- Troubleshooting character encoding
- Lucene Linguistics
- Tutorials and quick starts
- News 1: Getting Started
- News 2: Application Packages, Feeding, Query
- News 3: Sorting, Grouping and Ranking
- News 4: Embeddings
- News 5: Partial Updates, ANNs, Filtering
- News 6: Custom Searchers, Document Processors
- News 7: Parent-Child, Tensor Ranking
- Models Hot Swap
- Text Search
- Hybrid Text Search
- Text Search ML
- Quick Start
- Quick Start Java
- Applications and components
- Developer Guide
- Application Packages
- Unit Testing
- Testing
- Testing Reference
- Testing Reference Java
- Java Serving Container
- Container Components
- Request-Response Processing
- Searcher Development
- Document Processor Development
- Developing Web Service Applications
- Component Injection
- Chained Components
- Configuring Java components
- Bundles
- Using ZooKeeper
- Developing request handlers
- Building an HTTP API using request handlers and processors
- Configuring Http Servers and Filters
- Using Libraries for Pluggable Frameworks
- Developing server providers
- Server Tutorial
- LLMs in Vespa
- RAG in Vespa
- Content clusters
- Elasticity
- Proton
- Content Nodes and States
- Consistency Model
- Distribution Algorithm
- Buckets
- Performance and tuning
- Performance intro
- Practical performance guide
- Serving Sizing Guide
- Feed Sizing Guide
- Sizing Examples
- Binarizing Vectors
- Document Attributes
- Benchmarking
- Profiling
- Container Tuning
- Rate-Limiting Search Requests
- HTTP/2
- Graceful Query Coverage Degradation
- Caches
- HTTP Performance Testing
- Feature Tuning
- Valgrind
- Operations
- Metrics
- Logs
- Access Logging
- Batch delete
- Feed block
- Reindexing
- Tools
- Operations - selfhosted
- Multinode Systems
- Administrative Procedures
- Files, Processes, Ports, Environment
- Node Setup
- Content node recovery
- Using Kubernetes with Vespa
- Securing a Vespa installation
- mTLS
- Configuration Servers
- Live Vespa upgrade procedure
- Config Sentinel
- Config Proxy
- Docker Containers
- Vespa Command-line Tools
- Docker Containers GPU setup
- Service Location Broker
- Change from attribute to index procedure
- Container
- Monitoring
- Routing
- Configuration reference
- Application Package Reference
- Schema Reference
- services.xml
- services.xml - admin
- services.xml - container
- services.xml - content
- services.xml - docproc
- services.xml - http
- services.xml - processing
- services.xml - search
- hosts.xml
- validation-overrides.xml
- Indexing Language Reference
- Custom Configuration File Reference
- mTLS Reference
- Internal Configuration File Reference
- Healthchecks Reference
- /state/v1 API Reference
- Deploy API
- HTTP Config API
- /application/v2/tenant API Reference
- /cluster/v2 API Reference
- /metrics/v1 API Reference
- /metrics/v2 API Reference
- /prometheus/v1 API Reference
- Ranking and ML models reference
- Ranking Expressions
- Tensor Evaluation Reference
- nativeRank Reference
- Rank Feature Reference
- String Segment Match
- Rank Feature Configuration
- Rank Types
- Stateless Model Reference
- Embedding Model Reference
- Queries and results reference
- Query API Reference
- Query Language Reference
- Simple Query Language Reference
- Select Reference
- Grouping Reference
- Sorting Reference
- Query Profile Reference
- Semantic Rule Language Reference
- Default JSON Result Format
- Page Templates Syntax
- Page Result Format
- Inspecting Structured Data in a Searcher
- Low-level request handler APIs
- Document API reference
- /document/v1 API reference
- Document JSON Format
- Document Field Path Syntax
- Document Selector Language
- Component reference
- Component Reference
- Metrics reference
- Vespa Metric Set Reference
- Default Metric Set Reference
- Container Metrics Reference
- Distributor Metrics Reference
- Searchnode Metrics Reference
- Storage Metrics Reference
- Configserver Metrics Reference
- Logd Metrics Reference
- Node Admin Metrics Reference
- Slobrok Metrics Reference
- Clustercontroller Metrics Reference
- Sentinel Metrics Reference
- Metric Units Reference
- Utilities and libraries
- Predicate Search Java Library
- pyvespa: Getting Started
Vespa provides plugins for working with schemas and rank profiles in IDE's:
- VSCode: VS Code extension
- IntelliJ, PyCharm or WebStorm: Jetbrains plugin
- Vim: neovim
If you are working with non-trivial Vespa applications, installing a plugin is highly recommended!
