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.

Token of a user / service-user which has an admin role assigned → <yourToken>
The base URL of your application → <baseUrl>!

Assistant

Create a new assistant

...

Panel

panelIconId	2139
panelIcon	:information_source:
panelIconText	ℹ️
bgColor	#E6FCFF

To get the token and the URL check this: How to get a Token for our APIs

Assistant

Create a new assistant

This can be done with this cURL. Just replace the following placeholders:

...

<baseUrl> / <yourToken>
<assistantId>
<updateAssistant> "param1": "<paramValue>" → contains variables that should be updated. Variables that are not contained in <updateAssistant> input remain unchanged

Code Block

curl --location --globoff 'https://gateway.<baseUrl>/chat/graphql' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer <yourToken>' \
--data '{"query":"mutation UpdateAssistant($updateAssistantId: String!, $input: AssistantUpdateInput!) {\n  updateAssistant(id: $updateAssistantId, input: $input) {\n    name\n    id\n    languageModel\n    settings\n    chatUpload\n    modules {\n      id\n      name\n      configuration\n    }\n  }\n}","variables":{"updateAssistantId":"<assistantId>","input":{<updateAssistant>"param1": "<paramValue>"}}}'

Delete an assistant

To delete an assistant, use the following cURL. Update these placeholders:

<baseUrl> / <yourToken>
<assistantId>

An example command to update the languageModelused to perform function calling and module selection can be updated with the following curl command:

Code Block

curl --location --globoff 'https://gateway.<baseUrl>/chat/graphql' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer <YourToken><yourToken>' \
--data '{"query":"mutation CreateAssistantUpdateAssistant($deleteAssistantId$updateAssistantId: String!, $input: AssistantUpdateInput!) {\n  deleteAssistant    updateAssistant(id: $deleteAssistantId$updateAssistantId, input: $input) {\n     name       name\n  }\n}","variables":{"deleteAssistantId":"<assistantId>"}}'

Assistant variables and settings

The list contains various parameters that need to be set when an assistant is created/updated.

...

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

...

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 section for details about configuration of a module

...

required

Example input for an Internal Knowledge assistant containing two modules (SearchInVectorDB, Translate).

Code Block

{
  "input": {
    "name": "Internal Knowledge",
    "fallbackModule": "SearchInVectorDB",
    "languageModel": "AZURE_GPT_35_TURBO_0613",
    "chatUpload": "Disabled",
    "settings": {
        "showPdfHighlighting": true,
        "modelChoosing": "BY_FUNCTION_CALL",
        "isPinned": true        
    },
    "modules": {            id    \n            languageModel    \n            settings    \n            chatUpload    \n            modules {\n                id\n                name\n                configuration   \n            }\n       }\n}","variables":{"updateAssistantId":"<assistantID>","input":{"languageModel":"AZURE_GPT_4_0613"}}}'

Delete an assistant

To delete an assistant, use the following cURL. Update these placeholders:

<baseUrl> / <yourToken>
<assistantId>

Code Block

curl --location --globoff 'https://gateway.<baseUrl>/chat/graphql' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer <YourToken>' \
--data '{"query":"mutation CreateAssistant($deleteAssistantId: String!) {\n  deleteAssistant(id: $deleteAssistantId) {\n    name\n  }\n}","variables":{"deleteAssistantId":"<assistantId>"}}'

Assistant variables and settings

The list contains various parameters that need to be set when an assistant is created/updated.

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

Example input for an Internal Knowledge assistant containing two modules (SearchInVectorDB, Translate).

Code Block

{
  "input": {
    "name": "Internal Knowledge",
    "fallbackModule": "SearchInVectorDB",
    "languageModel": "AZURE_GPT_35_TURBO_0125",
    "chatUpload": "Disabled",
    "settings": {
        "showPdfHighlighting": true,
        "createmodelChoosing": ["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

Create a module

...

Panel

panelIconId	2139
panelIcon	:information_source:
panelIconText	ℹ️
bgColor	#E6FCFF

You can find more about assistants here: Assistants

Module

Create a module

This can be done with this cURL. Just replace the following placeholders:

...

Code Block

{
    "name": "SearchInVectorDB",
    "configuration": {
      <collectionOfParameters>
    },
    "isExternal": false,
    "weight": 10000,
    "toolDefinition": {
        "type": "function",
        "function": {
            "name": "SearchInVectorDB",
            "description": "Search information in the employee knowledge base for a specific question or assignment, e.g. explain, elaborate or describe. If the employee mentions a specific document and you do not know it, ALWAYS use this function. The employee can ask specific formats. Some examples: 'summarise directive 76 in bullet points', 'how to export data to third-parties', 'what are employee benefits'.",
            "parameters": {
                "type": "object",
                "properties": {
                    "instruction": {
     The employee can ask specific formats. Some examples: 'summarise directive 76 in bullet points', 'how to export data to third-parties', 'what are employee benefits'.",
            "parameters": {
                "type": "object",
                "properties": {
                    "instruction": {
                        "type": "string",
                        "description": "The question to search in the knowledge base, e.g. Was gibt es zu essen?"
                    }
                }
            }
        }
    }
}

Module dependent configurations

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_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_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":

...

Module dependent configurations

"configuration": { "languageModel": "AZURE_GPT_4_TURBO_1106", "scopeIds": ["scope_1", "scope_2"],searchTypeCOMBINED", "chunkedSources": true, scopeToChatOnUploadtrueincludeHistoryfalse "maxTokens":7000 }ContextMemorySearch, "chunkedSources": true "

Module

Example

Description

Parameter

Options

SearchInVectorDB

Code Block

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[],

GPT model to be used

languageModel: string

see below section with GPT-models

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

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

AZURE_GPT_4_0613: 7000

AZURE_GPT_4_32K_0613: 30000

AZURE_GPT_4_VISION_PREVIEW: 7000

AZURE_GPT_4_TURBO_1106: 7000

  "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

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

WhatsappWriter

Code Block
"configuration": { "languageModel":

 "AZURE_GPT_4_TURBO_1106"
}

GPT model to be used

languageModel: string

Available GPT models

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 (0125)	AZURE_GPT_

4

35_TURBO_

1106" }

0125

GPT

model to be used

languageModel: string

EmailWriter

Code Block"configuration": { "languageModel": "

-4 (0613)	AZURE_GPT_4_0613
GPT-4-32K (0613)	AZURE_GPT_4_32K_0613
GPT-4-turbo (0409)	AZURE_GPT_4_TURBO

_1106" }

GPT model to be used

languageModel: string

ExternalKnowledge

Code Block"configuration": { "languageModel": "

_2024_0409
GPT-4o (2024-0513)	AZURE_GPT_4o_2024_0513
GPT-4o (2024-0806)	AZURE_GPT_

4

4o_

TURBO_1106", "temperature": 0.5 }

GPT model to be used

languageModel: string

Temperature (chatGPT)

temperature: number

Range: 0-1

Default: 0.5

InvestmentResearchDocuments

InvestmentResearchTable

LunchSearchV4

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

GPT model to be used

languageModel: string

QueryTable

Code Block"configuration": { "languageModel": "

2024_0806
GPT-4o-mini (2024-0718)	AZURE_GPT_4o_MINI_2024_0718

GPT versions available in Preview mode (not recommended to be used in productive applications):

Model	Key
GPT-4-turbo (1106)	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

Available GPT models

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

...

GPT-35-turbo (0301): AZURE_GPT_35_TURBO

...

GPT-35-turbo (0613): AZURE_GPT_35_TURBO_0613

...

GPT-35-turbo-16K (0613): AZURE_GPT_35_TURBO_16K

...

GPT-4 (0613): AZURE_GPT_4_0613

...

GPT-4-32K (0613): AZURE_GPT_4_32K_0613

...

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`

...

Author	Fabian Schläpfer

Version	Old Version 3	New Version Current
Changes made by	Daylan Araz	Fabian Schläpfer
Saved on	Mar 29, 2024	Jan 29, 2025

Content Comparison

Versions Compared

Key

Assistant

Create a new assistant

Assistant

Create a new assistant

Delete an assistant

Assistant variables and settings

Delete an assistant

Assistant variables and settings

Module

Create a module

Module

Create a module

Module dependent configurations

Module dependent configurations

Available GPT models

Available GPT models

Model provisioning on Azure in terraform