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An assistant and modules are created and modified via API call. This guide leads you through the calls you have to do and the settings and configurations that can be set.

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Variable	Description	Options	optional / required
`name`	Name of assistant		required
`fallbackModule`	fallbackModule if module selection could not find a suitable module		required
`languageModel`	Language module used for module selection	see below section with GPT-models default: `AZURE_GPT_35_TURBO_0125`	optional
`chatUpload`	Enable/disable upload of documents into chat	`DISABLED` (default) `ENABLED`	optional
`settings` Collection of various setting	`showPdfHighlighting`: Open references in same chat window on the right side. Referenced section is highlighted in the PDF	`showPdfHighlighting` `false` (default) `true`	optional
	`modelChoosing`: type of module selection	`modelChoosing` `BY_FUNCTION_CALL` `BY_PROMPT` (default)	optional
	`isPinned`: flag if a space is pinned (marked with a star). This is only relevant for spaces	`isPinned` `false` (default) `true`	optional
`modules`	List of modules to create. See Module dependent configurations for details about configuration of a module		required

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Code Block

{
  "input": {
    "name": "Internal Knowledge",
    "fallbackModule": "SearchInVectorDB",
    "languageModel": "AZURE_GPT_35_TURBO_06130125",
    "chatUpload": "Disabled",
    "settings": {
        "showPdfHighlighting": true,
        "modelChoosing": "BY_FUNCTION_CALL",
        "isPinned": true        
    },
    "modules": {
      "create": [
        {
            "name": "SearchInVectorDB",
            "configuration": {
            },
            "description": null,
            "isExternal": false,
            "weight": 10000
        },
        {
            "name": "Translate",
            "configuration": {
            },
            "description": null,
            "isExternal": false,
            "weight": 6000
        }
      ]
    }
  }
}

...

Module

Example

Description

Parameter

Options

SearchInVectorDB

Code Block

"configuration": {
        "languageModel": "AZURE_GPT_4_TURBO_1106",
        "scopeIds": ["scope_1", "scope_2"],
        "searchType": "COMBINED",
        "chunkedSources": true, 
        "scopeToChatOnUpload": true,
        "historyIncluded": false,
        "maxTokens": 7000,
        "ftsSearchLanguage": "english"
}

GPT model to be used

languageModel: string

see below section with GPT-models

default: AZURE_GPT_35_TURBO: GPT-35-turbo (0301)_0125

Scopes that the module can access

scopeIds: object

RAG approach to search for chunks

searchType: string

VECTOR: semantic search (similarity of input and chunk embeddings)

COMBINED: hybrid search combining vector and fulltext search

Describing if chunks of same document are appended as individual sources to GPT content or merged to one source

chunkedSources: boolean

true: each chunk is a separate source

false: chunks from the same document are merged to one source

Scope restriction to documents that are uploaded. If no documents are uploaded, then scopes in scopeIds are relevant.

scopeToChatUpload: boolean

true: Scope restriction on (if document uploaded)

false: Scope restriction off

Flag that allows to include previous chat conversation in GPT-calls only if the new user input is a follow-up question

historyIncluded: boolean

true: History always included

false: History only included for follow-up questions

Max tokens used by sources and previous conversation

maxTokens: integer

Default value depends on the used languageModel

AZURE_GPT_35_TURBO: 3000

AZURE_GPT_35_TURBO_0613: 3000

AZURE_GPT_35_TURBO_16K: 14000_0125: 16385

AZURE_GPT_4_0613: 7000

AZURE_GPT_4_32K_0613: 30000

AZURE_GPT_4_VISION_PREVIEW: 7000

AZURE_GPT_4_TURBO_1106: 126000

AZURE_GPT_4_TURBO_2024_0409: 126000

AZURE_GPT_4o_2024_0513: 126000

AZURE_GPT_4o_2024_0806: 126000

AZURE_GPT_4o_MINI_2024_0718: 126000

Specifies the primary language used for full-text search. This should match the predominant language of the documents in the knowledge centre.

ftsSearchLanguage: string

Default: english

ContextMemorySearch

Code Block
"configuration": { "languageModel": "AZURE_GPT_4_TURBO_1106", "chunkedSources": true }

GPT model to be used

languageModel: string

Describing if chunks of same document are appended as individual sources to GPT content or merged to one source

chunkedSources: boolean

true: each chunk is a separate source

false: chunks from the same document are merged to one source

DocumentSummarizer

Code Block
"configuration": { "languageModel": "AZURE_GPT_4_TURBO_1106" }

GPT model to be used

languageModel: string

EmailWriter

Code Block
"configuration": { "languageModel": "AZURE_GPT_4_TURBO_1106" }

GPT model to be used

languageModel: string

ExternalKnowledge

Code Block
"configuration": { "languageModel": "AZURE_GPT_4_TURBO_1106", "temperature": 0.5, "systemPromptExternalKnowledge": "Example system prompt", "maxHistoryInteraction": 2 }

GPT model to be used

languageModel: string

Temperature (chatGPT)

temperature: number

Range: 0-1

Default: 0.5

System prompt

systemPromptExternalKnowledge: string

Default system prompt is (depending of languageModel):

Code Block
You are ChatGPT, a large language model trained by OpenAI, based on the GPT-4 architecture.\nKnowledge cutoff: 2023-04.\nCurrent date: DAYDATE.

Maximum number of user-assistant interactions taken into account in the history.

maxHistoryInteraction: number

Default: 2

InvestmentResearchDocuments

InvestmentResearchTable

LunchSearchV4

Code Block
"configuration": { "languageModel": "AZURE_GPT_4_TURBO_1106" }

GPT model to be used

languageModel: string

QueryTable

Code Block
"configuration": { "languageModel": "AZURE_GPT_4_TURBO_1106", "tableConfig": TableConfig[], "searchExamples": ChatCompletionRequestMessage[], "showTableReference": boolean }

GPT model to be used

languageModel: string

tbd

tableconfig:

tbd

searchExamples:

tbd

showTableReference: boolean

TranscriptInteraction

Code Block
"configuration": { "languageModel": "AZURE_GPT_4_TURBO_1106", "scopeId": "scope_1", "maxTokens": 7000, "templateName": "template.xlsx" }

GPT model to be used

languageModel: string

Scope that the module can access

scopeId: string

Max tokens used by sources and previous conversation

maxTokens: integer

Name of excel template file, that will be filled with extracted values. Need to uploaded to the same scopeId

templateName: string

Translate

Code Block
"configuration": { "languageModel": "AZURE_GPT_4_TURBO_1106" }

GPT model to be used

languageModel: string

WhatsappWriter

Code Block
"configuration": { "languageModel": "AZURE_GPT_4_TURBO_1106" }

GPT model to be used

languageModel: string

...

The list below contains available GPT-models with the corresponding name that has to be used in the configurations for the assistants and modules:

Model	Key
GPT-35-turbo (0301)	AZURE_GPT_35_TURBO	GPT-35-turbo (06130125)	AZURE_GPT_35_TURBO_0613	GPT-35-turbo-16K (0613)	AZURE_GPT_35_TURBO_16K0125
GPT-4 (0613)	AZURE_GPT_4_0613
GPT-4-32K (0613)	AZURE_GPT_4_32K_0613
GPT-4-turbo (0409)	AZURE_GPT_4_TURBO_2024_0409
GPT-4o (2024-0513)	AZURE_GPT_4o_2024_0513
GPT-4o (2024-0806)	AZURE_GPT_4o_2024_0806
GPT-4o-mini (2024-0718)	AZURE_GPT_4o_MINI_2024_0718

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Panel

panelIconId	2139
panelIcon	:information_source:
panelIconText	ℹ️
bgColor	#E6FCFF

You can find more about modules here: Modules

Model provisioning on Azure in terraform

When provisioning models on Azure via terraform, the following values for the name, mode_name and model_version should be used. The config map of certain Unique services will contain a mapping of the provisioned models and their respective endpoints, where the keys for the supported models will be composed from the {{model_name}}-{{model_version}} (also shown in table below).

Model	name (terraform)	model_name (terraform)	model_version (terraform)	config map key
GPT-35-turbo (0125)	`gpt-35-turbo-0125`	`gpt-35-turbo`	`0125`	`gpt-35-turbo-0125`
GPT-4 (0613)	`gpt-4`	`gpt-4`	`0613`	`gpt-4-0613`
GPT-4-32K (0613)	`gpt-4-32k`	`gpt-4-32k`	`0613`	`gpt-4-32k-0613`
GPT-4-turbo (0409)	`gpt-4-turbo-2024-04-09`	`gpt-4`	`turbo-2024-04-09`	`gpt-4-turbo-2024-04-09`
GPT-4o (2024-0513)	`gpt-4o-2024-05-13`	`gpt-4o`	`2024-05-13`	`gpt-4o-2024-05-13`
GPT-4o (2024-0806)	`gpt-4o-2024-08-06`	`gpt-4o`	`2024-08-06`	`gpt-4o-2024-08-06`
GPT-4o-mini (2024-0718)	`gpt-4o-mini-2024-07-18`	`gpt-4o-mini`	`2024-07-18`	`gpt-4o-mini-2024-07-18`
Ada text embedding (v2)	`text-embedding-ada-002`	`text-embedding-ada-002`	`2`	`text-embedding-ada-002-2`

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Author	Fabian Schläpfer

Version	Old Version 20	New Version Current
Changes made by	Fabian Schläpfer	Fabian Schläpfer
Saved on	Nov 07, 2024	Jan 29, 2025

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Model provisioning on Azure in terraform