For the complete documentation index, see llms.txt. This page is also available as Markdown.

Question & Answer

Allows to query the knowledge base using a specific AI model.

The Knowledge Base model

Key
Type
Description

id

String

The unique identifier for the knowledge base which is given by Tiledesk.

name

String

The knowledge base name.

id_project

String

The unique identifier of the project

preview_settings

Object

The settings for the knowledge base preview

default

Boolean

Specifies if the knowledge base is the default one

hybrid

Boolean

Specifies if the knowledge base is hybrid. Default is false (standard type)

engine

Object

Specifies the configuration of the vector store system used by the knowledge base. A default engine is provided.

embedding

Object

Indicates which embeddings are used for vector-based search. A default embedding is present.

Ask the Knowledge Base

POST https://api.tiledesk.com/v3/:project_id/kb/qa

Allows to query the knowledge base using a specific AI model.

Path Parameters

Name
Type
Description

project_id

string

The Project Id is a unique code assigned to your project when you create it in Tiledesk.

Headers

Name
Type
Description

Authorization

string

Authorization token. Basic Auth or JWT

Request Body

Name
Type
Description

question

string

The question submitted

namespace

string

The id of the Knowledge Base in which to search for the answer

llm

string

(Optional) The LLM to use to generate the response (Default: "openai")

model

string

The model to use to generate the response (e.g. gpt-4o)

max_tokens

Number

The maximum number of tokens that can be consumed to generate the response

temperature

Number

Defines creativity in generating responses (low values ​​determine more specific and predictable responses)

top_k

Number

The number of nearby chunks to use to generate the response

engine

Object

(Optional) The engine configuration object to use for the vector store system if different from the Default Engine

embedding

Object

(Optional) The embedding object to use for the embedding generation if different from the Default Engine

system_context

string

(Optional) The context to give to the AI ​​to shape its behavior in generating the response.

alpha

Number

(Optional) Defines the balance of hybrid search (0 = full-text focused, 1 = semantic/vector focused).

chunks_only

Boolean

(Optional) Returns only the retrieved text chunks without generating a final answer.

stream

Boolean

(Optional) Enables real-time streaming of the response as it is generated.

citations

Boolean

(Optional) Includes source references for the retrieved or generated content.

tags

Array

(Optional) Filters or categorizes results based on associated tags.

rereanking

Boolean

(Optional) Applies a secondary ranking step to improve the relevance of retrieved results.

Example


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