export as namespace lunr;
export = lunr;
/**
* lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright
* Copyright (C) 2014 Oliver Nightingale
* MIT Licensed
* @license
*/
declare namespace lunr {
namespace Builder {
/**
* A plugin is a function that is called with the index builder as its context.
* Plugins can be used to customise or extend the behaviour of the index
* in some way. A plugin is just a function, that encapsulated the custom
* behaviour that should be applied when building the index.
*
* The plugin function will be called with the index builder as its argument, additional
* arguments can also be passed when calling use. The function will be called
* with the index builder as its context.
*/
type Plugin = (this: Builder, ...args: any[]) => void;
}
/**
* lunr.Builder performs indexing on a set of documents and
* returns instances of lunr.Index ready for querying.
*
* All configuration of the index is done via the builder, the
* fields to index, the document reference, the text processing
* pipeline and document scoring parameters are all set on the
* builder before indexing.
*/
class Builder {
/**
* Internal reference to the document reference field.
*/
_ref: string;
/**
* Internal reference to the document fields to index.
*/
_fields: string[];
/**
* The inverted index maps terms to document fields.
*/
invertedIndex: object;
/**
* Keeps track of document term frequencies.
*/
documentTermFrequencies: object;
/**
* Keeps track of the length of documents added to the index.
*/
documentLengths: object;
/**
* Function for splitting strings into tokens for indexing.
*/
tokenizer: typeof tokenizer;
/**
* The pipeline performs text processing on tokens before indexing.
*/
pipeline: Pipeline;
/**
* A pipeline for processing search terms before querying the index.
*/
searchPipeline: Pipeline;
/**
* Keeps track of the total number of documents indexed.
*/
documentCount: number;
/**
* A parameter to control field length normalization, setting this to 0 disabled normalization, 1 fully normalizes field lengths, the default value is 0.75.
*/
_b: number;
/**
* A parameter to control how quickly an increase in term frequency results in term frequency saturation, the default value is 1.2.
*/
_k1: number;
/**
* A counter incremented for each unique term, used to identify a terms position in the vector space.
*/
termIndex: number;
/**
* A list of metadata keys that have been whitelisted for entry in the index.
*/
metadataWhitelist: string[];
constructor();
/**
* Sets the document field used as the document reference. Every document must have this field.
* The type of this field in the document should be a string, if it is not a string it will be
* coerced into a string by calling toString.
*
* The default ref is 'id'.
*
* The ref should _not_ be changed during indexing, it should be set before any documents are
* added to the index. Changing it during indexing can lead to inconsistent results.
*
* @param ref - The name of the reference field in the document.
*/
ref(ref: string): void;
/**
* Adds a field to the list of document fields that will be indexed. Every document being
* indexed should have this field. Null values for this field in indexed documents will
* not cause errors but will limit the chance of that document being retrieved by searches.
*
* All fields should be added before adding documents to the index. Adding fields after
* a document has been indexed will have no effect on already indexed documents.
*
* Fields can be boosted at build time. This allows terms within that field to have more
* importance when ranking search results. Use a field boost to specify that matches
* within one field are more important than other fields.
*
* @param fieldName - The name of a field to index in all documents.
* @param attributes - Optional attributes associated with this field.
*/
field(
fieldName: string,
attributes?: {
boost?: number | undefined;
extractor?: ((doc: object) => string | object | object[]) | undefined;
},
): void;
/**
* A parameter to tune the amount of field length normalisation that is applied when
* calculating relevance scores. A value of 0 will completely disable any normalisation
* and a value of 1 will fully normalise field lengths. The default is 0.75. Values of b
* will be clamped to the range 0 - 1.
*
* @param number - The value to set for this tuning parameter.
*/
b(number: number): void;
/**
* A parameter that controls the speed at which a rise in term frequency results in term
* frequency saturation. The default value is 1.2. Setting this to a higher value will give
* slower saturation levels, a lower value will result in quicker saturation.
*
* @param number - The value to set for this tuning parameter.
*/
k1(number: number): void;
/**
* Adds a document to the index.
*
* Before adding fields to the index the index should have been fully setup, with the document
* ref and all fields to index already having been specified.
*
* The document must have a field name as specified by the ref (by default this is 'id') and
* it should have all fields defined for indexing, though null or undefined values will not
* cause errors.
*
* Entire documents can be boosted at build time. Applying a boost to a document indicates that
* this document should rank higher in search results than other documents.
*
* @param doc - The document to add to the index.
* @param attributes - Optional attributes associated with this document.
*/
add(doc: object, attributes?: { boost?: number | undefined }): void;
/**
* Builds the index, creating an instance of lunr.Index.
*
* This completes the indexing process and should only be called
* once all documents have been added to the index.
*/
build(): Index;
/**
* Applies a plugin to the index builder.
*
* A plugin is a function that is called with the index builder as its context.
* Plugins can be used to customise or extend the behaviour of the index
* in some way. A plugin is just a function, that encapsulated the custom
* behaviour that should be applied when building the index.
*
* The plugin function will be called with the index builder as its argument, additional
* arguments can also be passed when calling use. The function will be called
* with the index builder as its context.
*
* @param plugin The plugin to apply.
*/
use(plugin: Builder.Plugin, ...args: any[]): void;
}
namespace Index {
interface Attributes {
/**
* An index of term/field to document reference.
*/
invertedIndex: object;
/**
* Document vectors keyed by document reference.
*/
documentVectors: { [docRef: string]: Vector };
/**
* An set of all corpus tokens.
*/
tokenSet: TokenSet;
/**
* The names of indexed document fields.
*/
fields: string[];
/**
* The pipeline to use for search terms.
*/
pipeline: Pipeline;
}
/**
* A result contains details of a document matching a search query.
*/
interface Result {
/**
* The reference of the document this result represents.
*/
ref: string;
/**
* A number between 0 and 1 representing how similar this document is to the query.
*/
score: number;
/**
* Contains metadata about this match including which term(s) caused the match.
*/
matchData: MatchData;
}
/**
* A query builder callback provides a query object to be used to express
* the query to perform on the index.
*
* @param query - The query object to build up.
*/
type QueryBuilder = (this: Query, query: Query) => void;
/**
* Although lunr provides the ability to create queries using lunr.Query, it also provides a simple
* query language which itself is parsed into an instance of lunr.Query.
*
* For programmatically building queries it is advised to directly use lunr.Query, the query language
* is best used for human entered text rather than program generated text.
*
* At its simplest queries can just be a single term, e.g. `hello`, multiple terms are also supported
* and will be combined with OR, e.g `hello world` will match documents that contain either 'hello'
* or 'world', though those that contain both will rank higher in the results.
*
* Wildcards can be included in terms to match one or more unspecified characters, these wildcards can
* be inserted anywhere within the term, and more than one wildcard can exist in a single term. Adding
* wildcards will increase the number of documents that will be found but can also have a negative
* impact on query performance, especially with wildcards at the beginning of a term.
*
* Terms can be restricted to specific fields, e.g. `title:hello`, only documents with the term
* hello in the title field will match this query. Using a field not present in the index will lead
* to an error being thrown.
*
* Modifiers can also be added to terms, lunr supports edit distance and boost modifiers on terms. A term
* boost will make documents matching that term score higher, e.g. `foo^5`. Edit distance is also supported
* to provide fuzzy matching, e.g. 'hello~2' will match documents with hello with an edit distance of 2.
* Avoid large values for edit distance to improve query performance.
*
* To escape special characters the backslash character '\' can be used, this allows searches to include
* characters that would normally be considered modifiers, e.g. `foo\~2` will search for a term "foo~2" instead
* of attempting to apply a boost of 2 to the search term "foo".
*
* @example Simple single term query
* hello
* @example Multiple term query
* hello world
* @example term scoped to a field
* title:hello
* @example term with a boost of 10
* hello^10
* @example term with an edit distance of 2
* hello~2
*/
type QueryString = string;
}
/**
* An index contains the built index of all documents and provides a query interface
* to the index.
*
* Usually instances of lunr.Index will not be created using this constructor, instead
* lunr.Builder should be used to construct new indexes, or lunr.Index.load should be
* used to load previously built and serialized indexes.
*/
class Index {
/**
* @param attrs The attributes of the built search index.
*/
constructor(attrs: Index.Attributes);
/**
* Performs a search against the index using lunr query syntax.
*
* Results will be returned sorted by their score, the most relevant results
* will be returned first.
*
* For more programmatic querying use lunr.Index#query.
*
* @param queryString - A string containing a lunr query.
* @throws {lunr.QueryParseError} If the passed query string cannot be parsed.
*/
search(queryString: Index.QueryString): Index.Result[];
/**
* Performs a query against the index using the yielded lunr.Query object.
*
* If performing programmatic queries against the index, this method is preferred
* over lunr.Index#search so as to avoid the additional query parsing overhead.
*
* A query object is yielded to the supplied function which should be used to
* express the query to be run against the index.
*
* Note that although this function takes a callback parameter it is _not_ an
* asynchronous operation, the callback is just yielded a query object to be
* customized.
*
* @param fn - A function that is used to build the query.
*/
query(fn: Index.QueryBuilder): Index.Result[];
/**
* Prepares the index for JSON serialization.
*
* The schema for this JSON blob will be described in a
* separate JSON schema file.
*/
toJSON(): object;
/**
* Loads a previously serialized lunr.Index
*
* @param serializedIndex - A previously serialized lunr.Index
*/
static load(serializedIndex: object): Index;
}
/**
* Contains and collects metadata about a matching document.
* A single instance of lunr.MatchData is returned as part of every
* lunr.IndexResult.
*/
class MatchData {
/**
* A cloned collection of metadata associated with this document.
*/
metadata: object;
/**
* @param term - The term this match data is associated with
* @param field - The field in which the term was found
* @param metadata - The metadata recorded about this term in this field
*/
constructor(term: string, field: string, metadata: object);
/**
* An instance of lunr.MatchData will be created for every term that matches a
* document. However only one instance is required in a lunr.Index~Result. This
* method combines metadata from another instance of lunr.MatchData with this
* objects metadata.
*
* @param otherMatchData - Another instance of match data to merge with this one.
* @see {@link lunr.Index~Result}
*/
combine(otherMatchData: MatchData): void;
}
/**
* A pipeline function maps lunr.Token to lunr.Token. A lunr.Token contains the token
* string as well as all known metadata. A pipeline function can mutate the token string
* or mutate (or add) metadata for a given token.
*
* A pipeline function can indicate that the passed token should be discarded by returning
* null. This token will not be passed to any downstream pipeline functions and will not be
* added to the index.
*
* Multiple tokens can be returned by returning an array of tokens. Each token will be passed
* to any downstream pipeline functions and all will returned tokens will be added to the index.
*
* Any number of pipeline functions may be chained together using a lunr.Pipeline.
*
* @param token - A token from the document being processed.
* @param i - The index of this token in the complete list of tokens for this document/field.
* @param tokens - All tokens for this document/field.
*/
type PipelineFunction = (
token: Token,
i: number,
tokens: Token[],
) => null | Token | Token[];
/**
* lunr.Pipelines maintain an ordered list of functions to be applied to all
* tokens in documents entering the search index and queries being ran against
* the index.
*
* An instance of lunr.Index created with the lunr shortcut will contain a
* pipeline with a stop word filter and an English language stemmer. Extra
* functions can be added before or after either of these functions or these
* default functions can be removed.
*
* When run the pipeline will call each function in turn, passing a token, the
* index of that token in the original list of all tokens and finally a list of
* all the original tokens.
*
* The output of functions in the pipeline will be passed to the next function
* in the pipeline. To exclude a token from entering the index the function
* should return undefined, the rest of the pipeline will not be called with
* this token.
*
* For serialisation of pipelines to work, all functions used in an instance of
* a pipeline should be registered with lunr.Pipeline. Registered functions can
* then be loaded. If trying to load a serialised pipeline that uses functions
* that are not registered an error will be thrown.
*
* If not planning on serialising the pipeline then registering pipeline functions
* is not necessary.
*/
class Pipeline {
constructor();
/**
* Register a function with the pipeline.
*
* Functions that are used in the pipeline should be registered if the pipeline
* needs to be serialised, or a serialised pipeline needs to be loaded.
*
* Registering a function does not add it to a pipeline, functions must still be
* added to instances of the pipeline for them to be used when running a pipeline.
*
* @param fn - The function to check for.
* @param label - The label to register this function with
*/
static registerFunction(fn: PipelineFunction, label: string): void;
/**
* Loads a previously serialised pipeline.
*
* All functions to be loaded must already be registered with lunr.Pipeline.
* If any function from the serialised data has not been registered then an
* error will be thrown.
*
* @param serialised - The serialised pipeline to load.
*/
static load(serialised: object): Pipeline;
/**
* Adds new functions to the end of the pipeline.
*
* Logs a warning if the function has not been registered.
*
* @param functions - Any number of functions to add to the pipeline.
*/
add(...functions: PipelineFunction[]): void;
/**
* Adds a single function after a function that already exists in the
* pipeline.
*
* Logs a warning if the function has not been registered.
*
* @param existingFn - A function that already exists in the pipeline.
* @param newFn - The new function to add to the pipeline.
*/
after(existingFn: PipelineFunction, newFn: PipelineFunction): void;
/**
* Adds a single function before a function that already exists in the
* pipeline.
*
* Logs a warning if the function has not been registered.
*
* @param existingFn - A function that already exists in the pipeline.
* @param newFn - The new function to add to the pipeline.
*/
before(existingFn: PipelineFunction, newFn: PipelineFunction): void;
/**
* Removes a function from the pipeline.
*
* @param fn The function to remove from the pipeline.
*/
remove(fn: PipelineFunction): void;
/**
* Runs the current list of functions that make up the pipeline against the
* passed tokens.
*
* @param tokens The tokens to run through the pipeline.
*/
run(tokens: Token[]): Token[];
/**
* Convenience method for passing a string through a pipeline and getting
* strings out. This method takes care of wrapping the passed string in a
* token and mapping the resulting tokens back to strings.
*
* @param str - The string to pass through the pipeline.
*/
runString(str: string): string[];
/**
* Resets the pipeline by removing any existing processors.
*/
reset(): void;
/**
* Returns a representation of the pipeline ready for serialisation.
*
* Logs a warning if the function has not been registered.
*/
toJSON(): PipelineFunction[];
}
namespace Query {
/**
* Constants for indicating what kind of presence a term must have in matching documents.
*/
enum presence {
/**
* Term's presence in a document is optional, this is the default value.
*/
OPTIONAL = 1,
/**
* Term's presence in a document is required, documents that do not contain this term will not be returned.
*/
REQUIRED = 2,
/**
* Term's presence in a document is prohibited, documents that do contain this term will not be returned.
*/
PROHIBITED = 3,
}
enum wildcard {
NONE = 0,
LEADING = 1 << 0,
TRAILING = 1 << 1,
}
/**
* A single clause in a {@link lunr.Query} contains a term and details on how to
* match that term against a {@link lunr.Index}.
*/
interface Clause {
term: string;
/** The fields in an index this clause should be matched against. */
fields: string[];
/** Any boost that should be applied when matching this clause. */
boost: number;
/** Whether the term should have fuzzy matching applied, and how fuzzy the match should be. */
editDistance: number;
/** Whether the term should be passed through the search pipeline. */
usePipeline: boolean;
/** Whether the term should have wildcards appended or prepended. */
wildcard: number;
}
}
/**
* A lunr.Query provides a programmatic way of defining queries to be performed
* against a {@link lunr.Index}.
*
* Prefer constructing a lunr.Query using the {@link lunr.Index#query} method
* so the query object is pre-initialized with the right index fields.
*/
class Query {
/**
* An array of query clauses.
*/
clauses: Query.Clause[];
/**
* An array of all available fields in a lunr.Index.
*/
allFields: string[];
/**
* @param allFields An array of all available fields in a lunr.Index.
*/
constructor(allFields: string[]);
/**
* Adds a {@link lunr.Query~Clause} to this query.
*
* Unless the clause contains the fields to be matched all fields will be matched. In addition
* a default boost of 1 is applied to the clause.
*
* @param clause - The clause to add to this query.
* @see lunr.Query~Clause
*/
clause(clause: Query.Clause): Query;
/**
* Adds a term to the current query, under the covers this will create a {@link lunr.Query~Clause}
* to the list of clauses that make up this query.
*
* The term is used as is, i.e. no tokenization will be performed by this method. Instead conversion
* to a token or token-like string should be done before calling this method.
*
* The term will be converted to a string by calling `toString`. Multiple terms can be passed as an
* array, each term in the array will share the same options.
*
* @param term - The term to add to the query.
* @param [options] - Any additional properties to add to the query clause.
* @see lunr.Query#clause
* @see lunr.Query~Clause
* @example adding a single term to a query
* query.term("foo")
* @example adding a single term to a query and specifying search fields, term boost and automatic trailing wildcard
* query.term("foo", {
* fields: ["title"],
* boost: 10,
* wildcard: lunr.Query.wildcard.TRAILING
* })
*/
term(term: string | string[] | Token | Token[], options: object): Query;
}
class QueryParseError extends Error {
name: "QueryParseError";
message: string;
start: number;
end: number;
constructor(message: string, start: string, end: string);
}
/**
* lunr.stemmer is an english language stemmer, this is a JavaScript
* implementation of the PorterStemmer taken from http://tartarus.org/~martin
*
* Implements {lunr.PipelineFunction}
*
* @param token - The string to stem
* @see {@link lunr.Pipeline}
*/
function stemmer(token: Token): Token;
/**
* lunr.generateStopWordFilter builds a stopWordFilter function from the provided
* list of stop words.
*
* The built in lunr.stopWordFilter is built using this generator and can be used
* to generate custom stopWordFilters for applications or non English languages.
*
* @param stopWords - The list of stop words
* @see lunr.Pipeline
* @see lunr.stopWordFilter
*/
function generateStopWordFilter(stopWords: string[]): PipelineFunction;
/**
* lunr.stopWordFilter is an English language stop word list filter, any words
* contained in the list will not be passed through the filter.
*
* This is intended to be used in the Pipeline. If the token does not pass the
* filter then undefined will be returned.
*
* Implements {lunr.PipelineFunction}
*
* @param token - A token to check for being a stop word.
* @see {@link lunr.Pipeline}
*/
function stopWordFilter(token: Token): Token;
namespace Token {
/**
* A token update function is used when updating or optionally
* when cloning a token.
*
* @param str - The string representation of the token.
* @param metadata - All metadata associated with this token.
*/
type UpdateFunction = (str: string, metadata: object) => void;
}
/**
* A token wraps a string representation of a token
* as it is passed through the text processing pipeline.
*/
class Token {
/**
* @param [str=''] - The string token being wrapped.
* @param [metadata={}] - Metadata associated with this token.
*/
constructor(str: string, metadata: object);
/**
* Returns the token string that is being wrapped by this object.
*/
toString(): string;
/**
* Applies the given function to the wrapped string token.
*
* @example
* token.update(function (str, metadata) {
* return str.toUpperCase()
* })
*
* @param fn - A function to apply to the token string.
*/
update(fn: Token.UpdateFunction): Token;
/**
* Creates a clone of this token. Optionally a function can be
* applied to the cloned token.
*
* @param fn - An optional function to apply to the cloned token.
*/
clone(fn?: Token.UpdateFunction): Token;
}
/**
* A token set is used to store the unique list of all tokens
* within an index. Token sets are also used to represent an
* incoming query to the index, this query token set and index
* token set are then intersected to find which tokens to look
* up in the inverted index.
*
* A token set can hold multiple tokens, as in the case of the
* index token set, or it can hold a single token as in the
* case of a simple query token set.
*
* Additionally token sets are used to perform wildcard matching.
* Leading, contained and trailing wildcards are supported, and
* from this edit distance matching can also be provided.
*
* Token sets are implemented as a minimal finite state automata,
* where both common prefixes and suffixes are shared between tokens.
* This helps to reduce the space used for storing the token set.
*/
class TokenSet {
constructor();
/**
* Creates a TokenSet instance from the given sorted array of words.
*
* @param arr - A sorted array of strings to create the set from.
* @throws Will throw an error if the input array is not sorted.
*/
fromArray(arr: string[]): TokenSet;
/**
* Creates a token set representing a single string with a specified
* edit distance.
*
* Insertions, deletions, substitutions and transpositions are each
* treated as an edit distance of 1.
*
* Increasing the allowed edit distance will have a dramatic impact
* on the performance of both creating and intersecting these TokenSets.
* It is advised to keep the edit distance less than 3.
*
* @param str - The string to create the token set from.
* @param editDistance - The allowed edit distance to match.
*/
fromFuzzyString(str: string, editDistance: number): Vector;
/**
* Creates a TokenSet from a string.
*
* The string may contain one or more wildcard characters (*)
* that will allow wildcard matching when intersecting with
* another TokenSet.
*
* @param str - The string to create a TokenSet from.
*/
fromString(str: string): TokenSet;
/**
* Converts this TokenSet into an array of strings
* contained within the TokenSet.
*/
toArray(): string[];
/**
* Generates a string representation of a TokenSet.
*
* This is intended to allow TokenSets to be used as keys
* in objects, largely to aid the construction and minimisation
* of a TokenSet. As such it is not designed to be a human
* friendly representation of the TokenSet.
*/
toString(): string;
/**
* Returns a new TokenSet that is the intersection of
* this TokenSet and the passed TokenSet.
*
* This intersection will take into account any wildcards
* contained within the TokenSet.
*
* @param b - An other TokenSet to intersect with.
*/
intersect(b: TokenSet): TokenSet;
}
namespace tokenizer {
/**
* The separator used to split a string into tokens. Override this property to change the behaviour of
* `lunr.tokenizer` behaviour when tokenizing strings. By default this splits on whitespace and hyphens.
*
* @see lunr.tokenizer
*/
let separator: RegExp;
}
/**
* A function for splitting a string into tokens ready to be inserted into
* the search index. Uses `lunr.tokenizer.separator` to split strings, change
* the value of this property to change how strings are split into tokens.
*
* This tokenizer will convert its parameter to a string by calling `toString` and
* then will split this string on the character in `lunr.tokenizer.separator`.
* Arrays will have their elements converted to strings and wrapped in a lunr.Token.
*
* @param obj - The object to convert into tokens
*/
function tokenizer(obj?: null | string | object | object[]): Token[];
/**
* lunr.trimmer is a pipeline function for trimming non word
* characters from the beginning and end of tokens before they
* enter the index.
*
* This implementation may not work correctly for non latin
* characters and should either be removed or adapted for use
* with languages with non-latin characters.
*
* Implements {lunr.PipelineFunction}
*
* @param token The token to pass through the filter
* @see lunr.Pipeline
*/
function trimmer(token: Token): Token;
/**
* A namespace containing utils for the rest of the lunr library
*/
namespace utils {
/**
* Print a warning message to the console.
*
* @param message The message to be printed.
*/
function warn(message: string): void;
/**
* Convert an object to a string.
*
* In the case of `null` and `undefined` the function returns
* the empty string, in all other cases the result of calling
* `toString` on the passed object is returned.
*
* @param obj The object to convert to a string.
* @return string representation of the passed object.
*/
function asString(obj: any): string;
}
/**
* A vector is used to construct the vector space of documents and queries. These
* vectors support operations to determine the similarity between two documents or
* a document and a query.
*
* Normally no parameters are required for initializing a vector, but in the case of
* loading a previously dumped vector the raw elements can be provided to the constructor.
*
* For performance reasons vectors are implemented with a flat array, where an elements
* index is immediately followed by its value. E.g. [index, value, index, value]. This
* allows the underlying array to be as sparse as possible and still offer decent
* performance when being used for vector calculations.
*/
class Vector {
/**
* @param [elements] - The flat list of element index and element value pairs.
*/
constructor(elements: number[]);
/**
* Calculates the position within the vector to insert a given index.
*
* This is used internally by insert and upsert. If there are duplicate indexes then
* the position is returned as if the value for that index were to be updated, but it
* is the callers responsibility to check whether there is a duplicate at that index
*
* @param insertIdx - The index at which the element should be inserted.
*/
positionForIndex(index: number): number;
/**
* Inserts an element at an index within the vector.
*
* Does not allow duplicates, will throw an error if there is already an entry
* for this index.
*
* @param insertIdx - The index at which the element should be inserted.
* @param val - The value to be inserted into the vector.
*/
insert(insertIdx: number, val: number): void;
/**
* Inserts or updates an existing index within the vector.
*
* @param insertIdx - The index at which the element should be inserted.
* @param val - The value to be inserted into the vector.
* @param fn - A function that is called for updates, the existing value and the
* requested value are passed as arguments
*/
upsert(
insertIdx: number,
val: number,
fn: (existingVal: number, val: number) => number,
): void;
/**
* Calculates the magnitude of this vector.
*/
magnitude(): number;
/**
* Calculates the dot product of this vector and another vector.
*
* @param otherVector - The vector to compute the dot product with.
*/
dot(otherVector: Vector): number;
/**
* Calculates the cosine similarity between this vector and another
* vector.
*
* @param otherVector - The other vector to calculate the
* similarity with.
*/
similarity(otherVector: Vector): number;
/**
* Converts the vector to an array of the elements within the vector.
*/
toArray(): number[];
/**
* A JSON serializable representation of the vector.
*/
toJSON(): number[];
}
const version: string;
type ConfigFunction = (this: Builder, builder: Builder) => void;
}
/**
* Convenience function for instantiating a new lunr index and configuring it with the default
* pipeline functions and the passed config function.
*
* When using this convenience function a new index will be created with the following functions
* already in the pipeline:
*
* * lunr.StopWordFilter - filters out any stop words before they enter the index
*
* * lunr.stemmer - stems the tokens before entering the index.
*
* Example:
*
* ```javascript
* var idx = lunr(function () {
* this.field('title', 10);
* this.field('tags', 100);
* this.field('body');
*
* this.ref('cid');
*
* this.pipeline.add(function () {
* // some custom pipeline function
* });
* });
* ```
*/
declare function lunr(config: lunr.ConfigFunction): lunr.Index;