Dynamiq Docs
  • Welcome to Dynamiq
  • Low-Code Builder
    • Extractors and Transformers
    • Chat
    • Basics
    • Connecting Nodes
    • Conditional Nodes and Multiple Outputs
    • Input and Output Transformers
    • Error Handling and Retries
    • LLM Nodes
    • Validator Nodes
    • RAG Nodes
      • Indexing Workflow
        • Pre-processing Nodes
        • Document Splitting
        • Document Embedders
        • Document Writers
      • Inference RAG workflow
        • Text embedders
        • Document retrievers
          • Complex retrievers
        • LLM Answer Generators
    • LLM Agents
      • Basics
      • Guide to Implementing LLM Agents: ReAct and Simple Agents
      • Guide to Agent Orchestration: Linear and Adaptive Orchestrators
      • Guide to Advanced Agent Orchestration: Graph Orchestrator
    • Audio and voice
    • Tools and External Integrations
    • Python Code in Workflows
    • Memory
    • Guardrails
  • Deployments
    • Workflows
      • Tracing Workflow Execution
    • LLMs
      • Fine-tuned Adapters
      • Supported Models
    • Vector Databases
  • Prompts
    • Prompt Playground
  • Connections
  • LLM Fine-tuning
    • Basics
    • Using Adapters
    • Preparing Data
    • Supported Models
    • Parameters Guide
  • Knowledge Bases
  • Evaluations
    • Metrics
      • LLM-as-a-Judge
      • Predefined metrics
        • Faithfulness
        • Context Precision
        • Context Recall
        • Factual Correctness
        • Answer Correctness
      • Python Code Metrics
    • Datasets
    • Evaluation Runs
    • Examples
      • Build Accurate vs. Inaccurate Workflows
  • Examples
    • Building a Search Assistant
      • Approach 1: Single Agent with a Defined Role
      • Approach 2: Adaptive Orchestrator with Multiple Agents
      • Approach 3: Custom Logic Pipeline with a Straightforward Workflow
    • Building a Code Assistant
  • Platform Settings
    • Access Keys
    • Organizations
    • Settings
    • Billing
  • On-premise Deployment
    • AWS
    • IBM
    • Red Hat OpenShift
  • Support Center
Powered by GitBook
On this page

Knowledge Bases

PreviousParameters GuideNextEvaluations

Last updated 2 months ago

Knowledge Bases in Dynamiq

The Knowledge Bases tab in Dynamiq is a dedicated space for creating and managing workflows specifically designed for content indexing and storage in knowledge bases. This feature streamlines the process of organizing and accessing information, making it an essential tool for building efficient RAG applications.

Key Features of the Knowledge Bases Tab

Specialized Workflows

The tab provides templates for creating indexing workflows, allowing you to efficiently manage and store content in your knowledge bases.

Workflow Management

Easily view and manage existing workflows. Each entry displays the workflow name, creator, and last edited date for quick reference.

Workflow Details

Click on any workflow to review its details, including the ingestion endpoint, runtime version, and deployment information.

File Management

Upload and manage files directly within the workflow. This feature allows you to review and organize input files, ensuring that all necessary data is available for indexing.

Ingestion Workflow

The tab provides options for making requests to ingest files through the indexing workflow, facilitating seamless integration of new content.

By utilizing the Knowledge Bases tab, you can efficiently create and manage workflows tailored for content indexing, enhancing the organization and accessibility of your knowledge bases.