Tags

Tags help you organize and categorize your Knowledge Base articles. They serve three key purposes:

1. Visual organization in the Inbox — Tags appear as labels on articles in the Dashboard, making it easy to visually identify and filter content by topic, department, or category.
2. AI Action targeting — When you configure AI Actions in the Dashboard, you use tags to tell the AI which subset of articles to search. For example, a “Search Returns” action can target only articles tagged returns, giving the AI focused, relevant results instead of searching the entire Knowledge Base.
3. Programmatic filtering — Use the tags parameter in List Articles to retrieve only articles matching a specific tag, enabling targeted content management workflows.
4. AI search relevance — The AI Agent is tag-aware when searching the Knowledge Base for answers. Descriptive tags help the AI narrow down the most relevant articles, improving answer accuracy and response quality.

List Tags

Retrieve all tags used across Knowledge Base articles.

Scope: read_all

GET https://app.quickchat.ai/v1/api/knowledge_base/tags/

Shell

curl https://app.quickchat.ai/v1/api/knowledge_base/tags/ \
  -H 'Authorization: Bearer <API_TOKEN>'

Python

import requests

response = requests.get(
    url="https://app.quickchat.ai/v1/api/knowledge_base/tags/",
    headers={"Authorization": "Bearer <API_TOKEN>"},
)
tags = response.json()

Response 200 OK

["policies", "faq", "product-info"]

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