JamAI Base Docs
  • GETTING STARTED
    • Welcome to JamAI Base
      • Why Choose JamAI Base?
      • Key Features
      • Architecture
    • Use Case
      • Chatbot (Frontend Only)
      • Chatbot
      • Create a simple food recommender with JamAI and Flutter
      • Create a simple fitness planner app with JamAI and Next.js with streaming text.
      • Customer Service Chatbot
      • Women Clothing Reviews Analysis Dashboard
      • Geological Survey Investigation Report Generation
      • Medical Insurance Underwriting Automation
      • Medical Records Extraction
    • Frequently Asked Questions (FAQ)
    • Quick Start
      • Quick Start with Chat Table
      • Quick Start: Action Table (Multimodal)
      • ReactJS
      • Next JS
      • SvelteKit
      • Nuxt
      • NLUX (Frontend Only)
      • NLUX + Express.js
  • Using The Platform
    • Action Table
    • Chat Table
    • Knowledge Table
    • Supported Models
      • Which LLM Should You Choose?
      • Comparative Analysis of Large Language Models in Vision Tasks
    • Roadmap
  • 🦉API
    • OpenAPI
    • TS/JS SDK
  • 🦅SDK
    • Flutter
    • TS/JS
    • Python SDK Documentation
      • Quick Start with Chat Table
      • Quick Start: Action Table (Mutimodal)
        • Action Table - Image
        • Action Table - Audio
      • Quick Start: Knowledge Table File Upload
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  1. Using The Platform

Knowledge Table

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Last updated 1 year ago

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  1. Go to >> Project >> Knowledge Table

  1. Create a New Knowledge Table with your desired Table ID (table name) and pick a Text Embedding Model.

  1. Open the table that you have just created. Upload your files to fill up the Knowledge Table.

And.... Let the magic begins. Jamjam will cast an extraction spell to process your files into Knowledge Rows which you can quickly search up later.

When it is done you will see the Knowledge Table is filled with Knowledge Rows.

  1. Now it is ready to be used for Searching! Checkout Action Table and Chat Table on How-To -Use the Knowledge Table.

Advanced LLM Magic

  1. After you created a new Knowledge Table, add new Output Column (>> Action >> Add output column)

  1. Setup your Knowledge LLM Agent. It will help you to further process the text content to enrich your Knowledge Row.

To setup LLM Agent, follow this spell template:

  • Column ID: <The title of the column>

  • Data Type: str

  • Models: The LLM models.

  • Temperature: 0.1

  • Max Tokens: 512

  • Top-p: 1.0

  • Customize prompt: <Prompt to process the Input columns>

To refer to the column content, you can click on the Columns Title listed and it will be automatically referenced in the prompt in the form of ${Column ID}.

  • Customize system prompt: <Agent system prompt>

  1. Let's start using the Knowledge Table and see the LLM agent magically process your Knowledge Row when you upload files to the Knowledge Table.

Demo of Knowledge Table Usage