DocumentSearchTools
Wisej.AI.Tools.DocumentSearchTools
Namespace: Wisej.AI.Tools
Assembly: Wisej.AI (3.5.0.0)
Provides tools for searching and managing documents within a specified collection.
public class DocumentSearchTools : ToolsContainerPublic Class DocumentSearchTools
Inherits ToolsContainerThis class allows for embedding questions, querying documents, listing documents, and summarizing document content. It utilizes these services: ITokenizerService, IEmbeddingStorageService.
Constructors
DocumentSearchTools(collectionName, filter)
Initializes a new instance of the DocumentSearchTools class.
Throws:
ArgumentNullException Thrown when collectionName is null.
Properties
CollectionName
String: Gets or sets the name of the document collection. (Default: null)
EmbeddingGenerationService
IEmbeddingGenerationService: Gets or sets the embedding generation service used for embedding questions.
EmbeddingStorageService
IEmbeddingStorageService: Gets or sets the embedding storage service used for storing and retrieving embedded documents.
MaxClusters
Int32: Get or sets the maximum number of vector clusters to generate when performing summarization tasks. (Default: 5)
MaxContextTokens
Int32: Gets or sets the maximum number of context tokens. (Default: 4096)
MaxDocumentsSearch
Int32: Gets or sets the maximum number of documents that can be returned. (Default: 100)
MinSimilarity
Single: Gets or sets the minimum similarity threshold for document retrieval. (Default: 0.25)
RerankingEnabled
Boolean: Gets or sets a value indicating whether reranking is enabled. (Default: False)
RerankingService
IRerankingService: Gets or sets the reranking service.
TokenizerService
ITokenizerService: Gets or sets the tokenizer service used for truncating content to fit within the maximum context tokens.
TopN
Int32: Gets or sets the number of top chunks to retrieve. (Default: 10)
Methods
EmbedQuestionAsync(question)
Asynchronously generates an embedding for the specified question.
Returns: Task<Embedding>. A task that represents the asynchronous operation. The task result contains the generated Embedding for the question, or null if the input is invalid.
This method checks if the provided question is null or empty and returns null if so. Otherwise, it delegates the embedding generation to the EmbeddingGenerationService.
list_all_documents()
Lists all documents in the collection.
Returns: Task<String>. A task that represents the asynchronous operation. The task result contains a list of document names as a string.
query_all_documents(question)
Queries all documents based on the provided question.
Returns: Task<String>. A task that represents the asynchronous operation. The task result contains the query results as a string.
This method retrieves all documents that match the embedded question.
query_single_document(document_name, question)
Queries a single document based on the provided document name and question.
Returns: Task<String>. A task that represents the asynchronous operation. The task result contains the query result as a string.
read_documents_metadata(document_names)
Reads metadata for the specified documents.
Returns: Task<String>. A task that represents the asynchronous operation. The task result contains the metadata as a string.
RerankAsync(question, chunks)
Asynchronously reranks the provided text chunks based on their relevance to the given question.
Returns: Task<String[]>. A task that represents the asynchronous operation. The task result contains an array of reranked text chunks.
This method is intended to be overridden in derived classes to implement custom reranking logic. The method should return the chunks array reordered by relevance to the question .
summarize_document(document_name)
Summarizes the content of a specified document.
Returns: Task<String>. A task that represents the asynchronous operation. The task result contains the summary as a string.
Implements
Represents a container for tools, providing access to a hub, adapter, and a collection of parameters.
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