Build Elasticsearch Full-Text Search

Build a complete Elasticsearch full-text search system for [APPLICATION_NAME] with the following specifications:

Requirements

• Application name: [APPLICATION_NAME]
• Index name: [INDEX_NAME]
• Document type: [PRODUCT/ARTICLE/USER/etc]
• Searchable fields: [FIELD_1], [FIELD_2], [FIELD_3]
• Field boosting: [FIELD_1: WEIGHT], [FIELD_2: WEIGHT]
• Filter fields: [CATEGORY/PRICE/DATE/etc]
• Price range filters: [YES/NO]
• Category facets: [YES/NO]
• Autocomplete needed: [YES/NO]
• Fuzzy matching: [YES/NO]
• Highlighting: [YES/NO]
• Pagination size: [RESULTS_PER_PAGE]
• Elasticsearch version: [7.x/8.x]

Deliverables

Generate complete Elasticsearch integration code with:

Client initialization:

• Import @elastic/elasticsearch Client
• Configure connection to [ELASTICSEARCH_HOST]
• Authentication setup if needed
• Connection pooling and retry logic

Index creation for [INDEX_NAME]:

• Index settings: shards, replicas
• Custom analyzers for autocomplete with edge_ngram
• Tokenizers and filters configuration
• Mappings for all [SEARCHABLE_FIELDS]
• Field types (text, keyword, float, date, etc.)
• Analyzer assignment to text fields

Document indexing functions:

• Single document indexing with client.index()
• Bulk indexing function for multiple documents
• Document ID generation
• Error handling and retry logic
• Index refresh strategy

Search query builders:

• Basic match query for single field
• Multi-match query across [SEARCHABLE_FIELDS] with boosting
• Bool query with must/should/filter clauses
• Fuzzy query with AUTO fuzziness if [FUZZY_MATCHING]
• Wildcard and prefix queries

Filtering implementation:

• Range filters for [PRICE/DATE] fields
• Term filters for [CATEGORY] fields
• Multiple filter combination with bool query
• Filter context vs query context

Aggregations if needed:

• Terms aggregation for category facets
• Range aggregation for price buckets
• Date histogram for time-based data
• Nested aggregations for complex analytics

Autocomplete search if [AUTOCOMPLETE]:

• Edge n-gram analyzer configuration
• Autocomplete query implementation
• Limit results to top [N] suggestions
• Debouncing strategy

Result highlighting if [HIGHLIGHTING]:

• Highlight configuration for matched fields
• Fragment size and number configuration
• Custom highlight tags
• Parse highlighted results

Pagination:

• from/size pagination for [RESULTS_PER_PAGE]
• Search after for deep pagination
• Total count handling

Response parsing:

• Extract hits from response
• Parse _source documents
• Handle aggregation results
• Format highlighted snippets

API endpoint integration:

• Express/Fastify route handlers
• Request validation
• Query parameter parsing
• Response formatting
• Error handling

TypeScript types:

• Search request types
• Search response types
• Document schema types
• Aggregation result types

Output production-ready Elasticsearch search implementation.