knowledge

Agent Forge's Knowledge Base is a powerful native feature that enables you to create, manage, and query custom knowledge bases directly within the platform. Using advanced AI embeddings and vector search technology, the Knowledge Base block allows you to build intelligent search capabilities into your workflows, making it easy to find and utilize relevant information across your organization.

The Knowledge Base system provides a comprehensive solution for managing organizational knowledge through its flexible and scalable architecture. With its built-in vector search capabilities, teams can perform semantic searches that understand meaning and context, going beyond traditional keyword matching.

Key features of the Knowledge Base include:

• Semantic Search: Advanced AI-powered search that understands meaning and context, not just keywords

• Vector Embeddings: Automatic conversion of text into high-dimensional vectors for intelligent similarity matching

• Custom Knowledge Bases: Create and manage multiple knowledge bases for different purposes or departments

• Flexible Content Types: Support for various document formats and content types

• Real-time Updates: Immediate indexing of new content for instant searchability

In Agent Forge, the Knowledge Base block enables your agents to perform intelligent semantic searches across your custom knowledge bases. This creates opportunities for automated information retrieval, content recommendations, and knowledge discovery as part of your AI workflows. The integration allows agents to search and retrieve relevant information programmatically, facilitating automated knowledge management tasks and ensuring that important information is easily accessible. By leveraging the Knowledge Base block, you can build intelligent agents that enhance information discovery while automating routine knowledge management tasks, improving team efficiency and ensuring consistent access to organizational knowledge.

Usage Instructions

Perform semantic vector search across knowledge bases, upload individual chunks to existing documents, or create new documents from text content. Uses advanced AI embeddings to understand meaning and context for search operations.

Tools

knowledge_search

Search for similar content in a knowledge base using vector similarity

Input

Parameter	Type	Required	Description
knowledgeBaseId	string	Yes	ID of the knowledge base to search in
query	string	Yes	Search query text
topK	number	No	Number of most similar results to return (1-100)
tagFilters	any	No	Array of tag filters with tagName and tagValue properties

Output

Parameter	Type	Description
results	json	Search results
query	string	Query used
totalResults	number	Total results count

knowledge_upload_chunk

Upload a new chunk to a document in a knowledge base

Input

Parameter	Type	Required	Description
knowledgeBaseId	string	Yes	ID of the knowledge base containing the document
documentId	string	Yes	ID of the document to upload the chunk to
content	string	Yes	Content of the chunk to upload

Output

Parameter	Type	Description
results	json	Search results
query	string	Query used
totalResults	number	Total results count

knowledge_create_document

Create a new document in a knowledge base

Input

Parameter	Type	Required	Description
knowledgeBaseId	string	Yes	ID of the knowledge base containing the document
name	string	Yes	Name of the document
content	string	Yes	Content of the document
tag1	string	No	Tag 1 value for the document
tag2	string	No	Tag 2 value for the document
tag3	string	No	Tag 3 value for the document
tag4	string	No	Tag 4 value for the document
tag5	string	No	Tag 5 value for the document
tag6	string	No	Tag 6 value for the document
tag7	string	No	Tag 7 value for the document
documentTagsData	array	No	Structured tag data with names, types, and values

Output

Parameter	Type	Description
results	json	Search results
query	string	Query used
totalResults	number	Total results count

Notes

• Category: blocks

• Type: knowledge