@equinor/fusion-framework-cli-plugin-ai-search

AI search plugin for Fusion Framework CLI providing vector store search capabilities.

Installation

pnpm add -D @equinor/fusion-framework-cli-plugin-ai-search

Configuration

After installing the plugin, create a fusion-cli.config.ts file in your project root:

import { defineFusionCli } from '@equinor/fusion-framework-cli';

export default defineFusionCli(() => ({
  plugins: [
    '@equinor/fusion-framework-cli-plugin-ai-search',
  ],
}));

The CLI will automatically discover and load plugins listed in this configuration file. The config file can be .ts, .js, or .json. The defineFusionCli helper provides type safety and IntelliSense support.

Features

This plugin extends the Fusion Framework CLI with AI search capabilities:

• Vector store search for validating embeddings
• Semantic search using vector embeddings
• Configurable result limits
• Filter support for metadata-based filtering
• JSON output option for programmatic use

Usage

Once installed, the search command is automatically available:

# Search the vector store
ffc ai search "your query"

Commands

ai search

Search the vector store to validate embeddings and retrieve relevant documents.

Features:

• Semantic search using vector embeddings
• Configurable result limits
• Filter support for metadata-based filtering
• JSON output option for programmatic use
• Detailed result display with scores and metadata

Options:

• --limit <number> - Maximum number of results to return (default: 10)
• --search-type <type> - Search type: 'mmr' or 'similarity' (default: similarity)
• --filter <expression> - OData filter expression for metadata filtering
• --json - Output results as JSON
• --raw - Output raw metadata without normalization
• --verbose - Enable verbose output
• --openai-api-key <key> - API key for Azure OpenAI
• --openai-api-version <version> - API version (default: 2024-02-15-preview)
• --openai-instance <name> - Azure OpenAI instance name
• --openai-embedding-deployment <name> - Azure OpenAI embedding deployment name
• --azure-search-endpoint <url> - Azure Search endpoint URL
• --azure-search-api-key <key> - Azure Search API key
• --azure-search-index-name <name> - Azure Search index name

Examples:

$ ffc ai search "how to use the framework"
$ ffc ai search "authentication" --limit 5
$ ffc ai search "typescript" --filter "metadata/source eq 'src/index.ts'"
$ ffc ai search "documentation" --search-type mmr
$ ffc ai search "documentation" --json
$ ffc ai search "documentation" --json --raw
$ ffc ai search "API reference" --verbose

Configuration

The plugin requires Azure OpenAI and Azure Cognitive Search configuration. See the main CLI documentation for details on setting up API keys and endpoints.

License

ISC