Articles

Articles are the building blocks of your Knowledge Base. Create, list, update, and delete the content your AI Agent uses to answer questions.

Articles are the building blocks of your AI Agent’s Knowledge Base. Each article represents a piece of knowledge — a help page, FAQ entry, product description, or any content your AI should know about.

There are three article types: Articles (full documents with title and body), Paragraphs (short standalone text entries), and URL articles (automatically created when importing web content). You can create articles manually via the API, import them from websites using Import External Content, upload files via File Upload, or sync from Intercom.

There is no retraining step. Every article you create, update, or delete is processed automatically in the background and takes effect as soon as it’s done — usually within seconds. Track it with the embed_state field below, or with pending_embed_count in Get Knowledge Base Settings.

Optional example checks

Preview an API Action request. Render a supplied request template with synthetic sample values without sending it. Omit credential headers.
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Create Article

Scope: write_all

POST https://app.quickchat.ai/v1/api/knowledge_base/articles/

Request Body

Parameter	Description
`content` string, required	Article content
`type` string	`"Article"` (default) or `"Paragraph"`
`title` string	Article title

"Article" — A full knowledge base document with title and content. Use for FAQ entries, help articles, product descriptions.
"Paragraph" — A short standalone text entry without a title. Use for brief facts, one-liner answers, quick reference data.
"URL" (read-only) — Created automatically when content is imported from a website. Contains the scraped page content with the source URL. Cannot be set on creation.

Shell
Python

curl -X POST https://app.quickchat.ai/v1/api/knowledge_base/articles/ \
  -H 'Authorization: Bearer <API_TOKEN>' \
  -H 'Content-Type: application/json' \
  -d '{
  "content": "Our return policy allows returns within 30 days.",
  "title": "Return Policy"
}'

import requests

response = requests.post(
    url="https://app.quickchat.ai/v1/api/knowledge_base/articles/",
    headers={"Authorization": "Bearer <API_TOKEN>"},
    json={
        "content": "Our return policy allows returns within 30 days.",
        "title": "Return Policy",
    },
)
data = response.json()

Response 201 Created

{
  "id": 1234,
  "article_id": "abc-123",
  "type": "Article",
  "title": "Return Policy",
  "description": "",
  "content": "Our return policy allows returns within 30 days.",
  "state": "draft",
  "deploy_state": "draft",
  "embed_state": "pending",
  "refresh_failure_reason": "",
  "version": null,
  "max_available_version": null,
  "url": null,
  "tags": [],
  "created_timestamp": "2026-01-15",
  "last_modified_timestamp": "2026-01-15",
  "downloaded_timestamp": "2026-01-15",
  "last_updated_timestamp": "2026-01-15",
  "last_updated_from_external_source_timestamp": null
}

Field	Description
`id` integer	Article numeric ID. This is the canonical identifier used in all URL paths
`article_id` string	Legacy string identifier. May be empty — use `id` instead
`type` string	`"Article"`, `"Paragraph"`, or `"URL"`
`title` string	Article title
`description` string	Article description
`content` string	Article content
`deploy_state` string	`"draft"` or `"published"` — a label only (see note below)
`embed_state` string or null	Whether the article is live: `"pending"`, `"embedding"`, `"embedded"`, or `"failed"` (see note below)
`state` string	Internal processing status (see note below)
`refresh_failure_reason` string	Why the latest URL refresh failed. Empty when no classified refresh failure is stored
`version` integer or null	Current version number
`max_available_version` integer or null	Highest available version
`url` string or null	Source URL (for URL-type articles)
`tags` array of strings	Associated tags
`created_timestamp` string	Creation date
`last_modified_timestamp` string	Last modification date
`downloaded_timestamp` string	Download date
`last_updated_timestamp` string	Last update date
`last_updated_from_external_source_timestamp` string or null	Last external source update

Articles have three state fields. Only one of them tells you whether your AI Agent is using the article:

embed_state: The one that matters. "pending" and "embedding" mean the article is still being processed; "embedded" means it is live and your AI Agent is using it; "failed" means processing didn’t complete and the article is not being used. This is the field to poll after a write.
deploy_state: "draft" or "published". A label for your own organisation only — it does not affect whether the AI uses the article.
state: Internal content-fetching status. For most API users this can be ignored. On a URL article, "refresh_failed" means the latest refresh did not replace the saved content.
refresh_failure_reason: A stable category for a classified URL refresh failure: "http_error", "soft_404", "off_domain_redirect", "auth_wall", "error_page", "empty_content", or "thin_content". It can be empty when the scrape failed before Quickchat could classify the page. The last saved content remains live unless embed_state also failed.

List Articles

Scope: read_all

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

Query Parameters

Parameter	Description
`limit` integer	Items per page
`offset` integer	Items to skip
`types` string	Filter by type: `Article`, `Paragraph`, `URL`
`tags` string	Filter by tag
`url` string	Filter by URL
`title` string	Filter by title
`query` string	Search by content

Shell
Python

curl 'https://app.quickchat.ai/v1/api/knowledge_base/articles/?limit=10&offset=0' \
  -H 'Authorization: Bearer <API_TOKEN>'

import requests

response = requests.get(
    url="https://app.quickchat.ai/v1/api/knowledge_base/articles/",
    headers={"Authorization": "Bearer <API_TOKEN>"},
    params={"limit": 10, "offset": 0},
)
data = response.json()

Response 200 OK

{
  "items": [
    {
      "id": 1234,
      "article_id": "abc-123",
      "type": "Article",
      "title": "Return Policy",
      "description": "",
      "state": "published",
      "deploy_state": "published",
      "embed_state": "embedded",
      "refresh_failure_reason": "",
      "version": 1,
      "max_available_version": 1,
      "url": null,
      "tags": ["policies"],
      "created_timestamp": "2026-01-15",
      "last_modified_timestamp": "2026-01-15",
      "downloaded_timestamp": "2026-01-15",
      "last_updated_timestamp": "2026-01-15",
      "last_updated_from_external_source_timestamp": null
    }
  ],
  "offset": 0,
  "limit": 10,
  "count": 1
}

The list response does not include the content field. Use Get Article to retrieve the full content of a specific article.

Get Article

Scope: read_all

GET https://app.quickchat.ai/v1/api/knowledge_base/articles/{article_id}

Shell
Python

curl https://app.quickchat.ai/v1/api/knowledge_base/articles/1234 \
  -H 'Authorization: Bearer <API_TOKEN>'

import requests

response = requests.get(
    url="https://app.quickchat.ai/v1/api/knowledge_base/articles/1234",
    headers={"Authorization": "Bearer <API_TOKEN>"},
)
data = response.json()

Response 200 OK — Returns the full article object (same schema as Create Article response), including the content field.

Update Article

Scope: write_all

PATCH https://app.quickchat.ai/v1/api/knowledge_base/articles/{article_id}

Request Body

Parameter	Description
`content` string	Updated article content
`title` string	Updated title
`tags` array of strings	Updated tags
`save_mode` string	`"draft"` (default) or `"publish"`

The save_mode: "draft" option only sets the deploy_state flag — it does not hold the content back from the AI. A draft article is processed and used exactly like a published one. Don’t rely on it to stage content; only write an article once you’re ready for it to go live.

Shell
Python

curl -X PATCH https://app.quickchat.ai/v1/api/knowledge_base/articles/1234 \
  -H 'Authorization: Bearer <API_TOKEN>' \
  -H 'Content-Type: application/json' \
  -d '{
  "title": "Updated Return Policy",
  "content": "Returns accepted within 60 days.",
  "save_mode": "publish"
}'

import requests

response = requests.patch(
    url="https://app.quickchat.ai/v1/api/knowledge_base/articles/1234",
    headers={"Authorization": "Bearer <API_TOKEN>"},
    json={
        "title": "Updated Return Policy",
        "content": "Returns accepted within 60 days.",
        "save_mode": "publish",
    },
)
data = response.json()

Response 200 OK — Returns the updated article object.

Delete Articles

Delete one or more articles by ID.

Scope: write_all

DELETE https://app.quickchat.ai/v1/api/knowledge_base/articles/

Request Body — JSON array of article IDs.

Shell
Python

curl -X DELETE https://app.quickchat.ai/v1/api/knowledge_base/articles/ \
  -H 'Authorization: Bearer <API_TOKEN>' \
  -H 'Content-Type: application/json' \
  -d '[1234, 5678]'

import requests

response = requests.delete(
    url="https://app.quickchat.ai/v1/api/knowledge_base/articles/",
    headers={"Authorization": "Bearer <API_TOKEN>"},
    json=[1234, 5678],
)

Response 200 OK

Search Articles

Search through article content with text matching.

Scope: read_all

GET https://app.quickchat.ai/v1/api/knowledge_base/articles/search

Query Parameters

Parameter	Description
`query` string, required	Search query
`is_case_insensitive` boolean	Case-insensitive search (default: `true`)
`with_title_url_and_tags` boolean	Include title/URL/tags in search (default: `true`)
`strict_search` boolean	Require exact match (default: `false`)
`num_of_display_articles` integer	Number of articles to display (default: `5`)
`num_of_data_articles` integer	Number of articles to search (default: `15`)

Shell
Python

curl 'https://app.quickchat.ai/v1/api/knowledge_base/articles/search?query=return%20policy' \
  -H 'Authorization: Bearer <API_TOKEN>'

import requests

response = requests.get(
    url="https://app.quickchat.ai/v1/api/knowledge_base/articles/search",
    headers={"Authorization": "Bearer <API_TOKEN>"},
    params={"query": "return policy"},
)
data = response.json()

Response 200 OK

{
  "article_snippets": [
    {
      "article_id": 1234,
      "expository_sentence": "Our return policy allows returns within 30 days.",
      "query_words_ids": [
        {"start_char": 4, "end_char": 10, "text": "return"}
      ]
    }
  ],
  "article_snapshots": {
    "items": [],
    "offset": 0,
    "count": 1
  }
}

List Paragraphs

List all Paragraph-type articles. Paragraphs are short standalone text entries without a title — as opposed to full Articles which have both a title and content body.

Scope: read_all

GET https://app.quickchat.ai/v1/api/knowledge_base/articles/paragraphs

Query Parameters

Parameter	Description
`limit` integer	Items per page
`offset` integer	Items to skip
`query` string	Filter by content

Shell
Python

curl 'https://app.quickchat.ai/v1/api/knowledge_base/articles/paragraphs?limit=10' \
  -H 'Authorization: Bearer <API_TOKEN>'

import requests

response = requests.get(
    url="https://app.quickchat.ai/v1/api/knowledge_base/articles/paragraphs",
    headers={"Authorization": "Bearer <API_TOKEN>"},
    params={"limit": 10},
)
data = response.json()

Response 200 OK

{
  "items": [
    {
      "id": 1,
      "content": "Our return policy allows returns within 30 days."
    }
  ],
  "offset": 0,
  "count": 1
}

Articles

Optional example checks

Create Article

List Articles

Get Article

Update Article

Delete Articles

Search Articles

List Paragraphs

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