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ibl-data-manager (3.59.0-ai-plus)

API for iblai

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Languages
Servers
Mock server

https://docs.ibl.ai/_mock/apis/ibl/

https://base.manager.iblai.app/

ai-account

Operations

ai-analytics

Operations

ai-bot

Operations

ai-finetuning

Operations

ai-index

Operations

ai-marketing

Operations

ai-media

Operations

ai-mentor

Operations

ai_mentor_orgs_users_create_mentor_wizard_create

Request

Create a new mentor using the wizard interface.

Args: request: The HTTP request containing the mentor data. org: The organization/tenant identifier. user_id: The ID of the user creating the mentor.

Returns: Response: The created mentor.

Raises: BadRequest: If the provided data is invalid.

Security
PlatformApiKeyAuthentication
Path
orgstringrequired
user_idstringrequired
Bodyrequired
namestring<= 100 charactersrequired
descriptionstring[ 20 .. 1000 ] charactersrequired
curl -i -X POST \
  'https://docs.ibl.ai/_mock/apis/ibl/api/ai-mentor/orgs/{org}/users/{user_id}/create-mentor-wizard/' \
  -H 'Authorization: YOUR_API_KEY_HERE' \
  -H 'Content-Type: application/json' \
  -d '{
    "name": "Data Science Mentor",
    "description": "A mentor specialized in data science and machine learning concepts."
  }'

Responses

Bodyapplication/json
namestring<= 255 charactersrequired
unique_idstring(uuid)
flowanyrequired

The langflow json for the mentor

slugstring<= 255 characters^[-a-zA-Z0-9_]+$
platformstring<= 255 characters
allow_anonymousboolean
metadataany or null
enable_moderationboolean
enable_post_processing_systemboolean
enable_openai_assistantboolean

(Deprecated) Set template mentor to openai-agent instead.

enable_total_groundingboolean

Whether to force mentor to only use information within the provided documents.

enable_suggested_promptsboolean

Whether to show suggested prompts for the mentor or not. Note: Suggested prompts are created by tenant admins.

enable_guided_promptsboolean

Whether to show suggested prompts for the mentor or not. Note: Guided prompts are created with an llm based on chat history.

guided_prompt_instructionsstring

Instructions to determine how prompt suggestions are generated.

google_voiceinteger or null
openai_voiceinteger or null
categoriesArray of objects(MentorCategory)required
categories[].​idintegerread-onlyrequired
categories[].​namestring<= 255 charactersrequired
categories[].​descriptionstring or null<= 255 characters
categories[].​category_groupinteger or null
categories[].​audienceobject(MentorAudience)required
categories[].​audience.​idintegerread-onlyrequired
categories[].​audience.​namestring<= 255 charactersrequired
categories[].​audience.​descriptionstring or null<= 255 characters
categories[].​audiencesArray of objects(MentorAudience)required
categories[].​audiences[].​idintegerread-onlyrequired
categories[].​audiences[].​namestring<= 255 charactersrequired
categories[].​audiences[].​descriptionstring or null<= 255 characters
proactive_promptstring

Prompt template used to start a conversation with the user when greeting_type is proactive_prompt. This will be sent to the LLM so it can respond naturally

moderation_system_promptstring

The prompt for the moderation system. This prompt must clearly distinguish between 'Approapriate' and 'Not Appropriate' queries.

post_processing_promptstring

Prompt to be used to alter or modify final llm response into any desired form.

moderation_responsestring

Desired feedback to return to the user when their prompt is deemed inappropriate.

safety_system_promptstring

Prompt to check whether the models response is appropriate or not.

safety_responsestring

Feedback given to the user when a model generates an inappropriate response

enable_safety_systemboolean
proactive_responsestring

Response to start a conversation with a user.

greeting_methodstring
  • proactive_prompt - Proactive Prompt
  • proactive_response - Proactive Response
Enum"proactive_prompt""proactive_response"
call_configurationobject(CallConfiguration)
mcp_serversArray of objects(MCPServer)required
mcp_servers[].​idintegerread-onlyrequired
mcp_servers[].​platformintegerread-onlyrequired
mcp_servers[].​namestring<= 255 charactersrequired
mcp_servers[].​urlstring(uri)<= 200 charactersrequired

The url of the MCP server.

mcp_servers[].​transportstring(TransportEnum)
  • sse - Sse
  • websocket - Websocket
Enum"sse""websocket"
mcp_servers[].​headersany

Headers to send to the MCP server. Useful for authentication,

mcp_servers[].​platform_keystringread-onlyrequired
mcp_servers[].​created_atstring(date-time)read-onlyrequired
mcp_servers[].​updated_atstring(date-time)read-onlyrequired
last_accessed_byinteger or null[ 0 .. 2147483647 ]

edX user ID

recently_accessed_atstring or null(date-time)
created_bystring or null<= 255 characters
created_atstring or null(date-time)read-onlyrequired
updated_atstring or null(date-time)read-onlyrequired
Response
application/json
{ "id": 1, "name": "Data Science Mentor", "description": "A mentor specialized in data science and machine learning concepts.", "platform": "main", "categories": [], "unique_id": "937d3d46-3048-4f9d-aa5c-ce7c51d85332", "created_by": "admin", "date_created": "2023-01-01T12:00:00Z" }

ai_mentor_orgs_users_custom_instruction_retrieve

Request

Retrieve custom instructions for a specific user.

Args: request: The HTTP request. org: The organization/tenant identifier. user_id: The ID of the user to retrieve custom instructions for.

Returns: Response: The custom instructions for the user.

Raises: NotFound: If no custom instructions exist for the user.

Security
PlatformApiKeyAuthentication
Path
orgstringrequired
user_idstringrequired
curl -i -X GET \
  'https://docs.ibl.ai/_mock/apis/ibl/api/ai-mentor/orgs/{org}/users/{user_id}/custom-instruction/' \
  -H 'Authorization: YOUR_API_KEY_HERE'

Responses

Bodyapplication/json
idintegerread-onlyrequired
about_userstring or null
mentor_tonestring or null
professionstring<= 100 characters

Position or work. eg: Engineer, student etc.

desired_mentor_traitsstring

Comma separated list of expected traits for mentor.

Response
application/json
{ "id": 1, "username": "johndoe", "platform_key": "main", "content": "Always explain concepts in simple terms with examples.", "created_at": "2023-01-01T12:00:00Z", "updated_at": "2023-01-02T14:30:00Z" }

ai_mentor_orgs_users_custom_instruction_create

Request

Create a new custom instruction for a user.

Args: request: The HTTP request containing the custom instruction data. org: The organization/tenant identifier. user_id: The ID of the user to create custom instructions for.

Returns: Response: The created custom instruction.

Raises: BadRequest: If the provided data is invalid.

Security
PlatformApiKeyAuthentication
Path
orgstringrequired
user_idstringrequired
Body
about_userstring or null
mentor_tonestring or null
professionstring<= 100 characters

Position or work. eg: Engineer, student etc.

desired_mentor_traitsstring

Comma separated list of expected traits for mentor.

curl -i -X POST \
  'https://docs.ibl.ai/_mock/apis/ibl/api/ai-mentor/orgs/{org}/users/{user_id}/custom-instruction/' \
  -H 'Authorization: YOUR_API_KEY_HERE' \
  -H 'Content-Type: application/json' \
  -d '{
    "content": "Always explain concepts in simple terms with examples."
  }'

Responses

Bodyapplication/json
idintegerread-onlyrequired
about_userstring or null
mentor_tonestring or null
professionstring<= 100 characters

Position or work. eg: Engineer, student etc.

desired_mentor_traitsstring

Comma separated list of expected traits for mentor.

Response
application/json
{ "id": 1, "username": "johndoe", "platform_key": "main", "content": "Always explain concepts in simple terms with examples.", "created_at": "2023-01-01T12:00:00Z", "updated_at": "2023-01-01T12:00:00Z" }

ai-prompt

Operations

career

Operations

catalog

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core

Operations

credentials

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features

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media

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notifications

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scim

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commerce

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recommendations

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reports

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skills

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