iblai.AiAnalyticsApi

All URIs are relative to https://base.manager.iblai.app

Method	HTTP request	Description
ai_analytics_orgs_users_chat_history_filter_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/chat-history-filter/
ai_analytics_orgs_users_chat_history_list	GET /api/ai-analytics/orgs/{org}/users/{user_id}/chat-history/
ai_analytics_orgs_users_chat_history_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/chat-history/{id}/
ai_analytics_orgs_users_conversation_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/conversation/
ai_analytics_orgs_users_costs_model_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/costs/model/
ai_analytics_orgs_users_costs_model_usage_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/costs/model-usage/
ai_analytics_orgs_users_costs_permentor_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/costs/permentor/
ai_analytics_orgs_users_costs_peruser_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/costs/peruser/
ai_analytics_orgs_users_mentor_detail_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/mentor-detail/
ai_analytics_orgs_users_mentor_summary_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/mentor-summary/
ai_analytics_orgs_users_sentiment_count_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/sentiment-count/
ai_analytics_orgs_users_topics_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/topics/
ai_analytics_orgs_users_topics_summary_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/topics/summary/
ai_analytics_orgs_users_traces_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/traces/
ai_analytics_orgs_users_traces_retrieve2	GET /api/ai-analytics/orgs/{org}/users/{user_id}/traces/{trace_id}/
ai_analytics_orgs_users_traces_scores_create	POST /api/ai-analytics/orgs/{org}/users/{user_id}/traces/scores/
ai_analytics_orgs_users_traces_scores_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/traces/scores/
ai_analytics_orgs_users_transcripts_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/transcripts/
ai_analytics_orgs_users_user_feedback_retrieve	GET /api/ai-analytics/orgs/{org}/users/{user_id}/user-feedback/

ai_analytics_orgs_users_chat_history_filter_retrieve

ChatHistoryFilterData ai_analytics_orgs_users_chat_history_filter_retrieve(org, user_id)

Retrieve the chat history for a tenant Filter parameters for period are start_date and end date Accessible to tenant Admins only.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.chat_history_filter_data import ChatHistoryFilterData
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
org = 'org_example' # str | 
user_id = 'user_id_example' # str | 

try:
    api_response = api_instance.ai_analytics_orgs_users_chat_history_filter_retrieve(org, user_id)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_chat_history_filter_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_chat_history_filter_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
org	str
user_id	str

Return type

ChatHistoryFilterData

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_chat_history_list

PaginatedConversationsList ai_analytics_orgs_users_chat_history_list(org, user_id, end_date=end_date, mentor=mentor, page=page, page_size=page_size, sentiment=sentiment, start_date=start_date, topics=topics, user_id2=user_id2)

Mixin that includes the StudentTokenAuthentication and IsPlatformAdmin

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.paginated_conversations_list import PaginatedConversationsList
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
org = 'org_example' # str | 
user_id = 'user_id_example' # str | 
end_date = '2013-10-20' # date |  (optional)
mentor = 'mentor_example' # str |  (optional)
page = 56 # int | A page number within the paginated result set. (optional)
page_size = 56 # int | Number of results to return per page. (optional)
sentiment = 'sentiment_example' # str |  (optional)
start_date = '2013-10-20' # date |  (optional)
topics = 'topics_example' # str |  (optional)
user_id2 = 'user_id_example' # str |  (optional)

try:
    api_response = api_instance.ai_analytics_orgs_users_chat_history_list(org, user_id, end_date=end_date, mentor=mentor, page=page, page_size=page_size, sentiment=sentiment, start_date=start_date, topics=topics, user_id2=user_id2)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_chat_history_list:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_chat_history_list: %s\n" % e)

Parameters

Name	Type	Description	Notes
org	str
user_id	str
end_date	date		[optional]
mentor	str		[optional]
page	int	A page number within the paginated result set.	[optional]
page_size	int	Number of results to return per page.	[optional]
sentiment	str		[optional]
start_date	date		[optional]
topics	str		[optional]
user_id2	str		[optional]

Return type

PaginatedConversationsList

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_chat_history_retrieve

Conversations ai_analytics_orgs_users_chat_history_retrieve(id, org, user_id, end_date=end_date, mentor=mentor, sentiment=sentiment, start_date=start_date, topics=topics, user_id2=user_id2)

Mixin that includes the StudentTokenAuthentication and IsPlatformAdmin

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.conversations import Conversations
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
id = 'id_example' # str | A UUID string identifying this session.
org = 'org_example' # str | 
user_id = 'user_id_example' # str | 
end_date = '2013-10-20' # date |  (optional)
mentor = 'mentor_example' # str |  (optional)
sentiment = 'sentiment_example' # str |  (optional)
start_date = '2013-10-20' # date |  (optional)
topics = 'topics_example' # str |  (optional)
user_id2 = 'user_id_example' # str |  (optional)

try:
    api_response = api_instance.ai_analytics_orgs_users_chat_history_retrieve(id, org, user_id, end_date=end_date, mentor=mentor, sentiment=sentiment, start_date=start_date, topics=topics, user_id2=user_id2)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_chat_history_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_chat_history_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
id	str	A UUID string identifying this session.
org	str
user_id	str
end_date	date		[optional]
mentor	str		[optional]
sentiment	str		[optional]
start_date	date		[optional]
topics	str		[optional]
user_id2	str		[optional]

Return type

Conversations

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_conversation_retrieve

ConversationVolume ai_analytics_orgs_users_conversation_retrieve(org, user_id, end_date=end_date, start_date=start_date)

Get the number of conversations for a given period of time Options include today, yesterday, 7d, 30d, 90d The start date and end date can also be specified in the format YYYY-MM-DD Accessible to tenant Admins only.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.conversation_volume import ConversationVolume
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
org = 'org_example' # str | 
user_id = 'user_id_example' # str | 
end_date = '2013-10-20' # date |  (optional)
start_date = '2013-10-20' # date |  (optional)

try:
    api_response = api_instance.ai_analytics_orgs_users_conversation_retrieve(org, user_id, end_date=end_date, start_date=start_date)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_conversation_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_conversation_retrieve: %s\n" % e)

Parameters

Name	Type	Notes
org	str
user_id	str
end_date	date	[optional]
start_date	date	[optional]

Return type

ConversationVolume

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_costs_model_retrieve

ModelCost ai_analytics_orgs_users_costs_model_retrieve(end_date, org, start_date, user_id)

Retrieve the model costs for a tenant Filter parameters for period are start_date and enddate Accessible to tenant Admins only.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.model_cost import ModelCost
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
end_date = '2013-10-20T19:20:30+01:00' # datetime | 
org = 'org_example' # str | 
start_date = '2013-10-20T19:20:30+01:00' # datetime | 
user_id = 'user_id_example' # str | 

try:
    api_response = api_instance.ai_analytics_orgs_users_costs_model_retrieve(end_date, org, start_date, user_id)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_costs_model_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_costs_model_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
end_date	datetime
org	str
start_date	datetime
user_id	str

Return type

ModelCost

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_costs_model_usage_retrieve

ModelUsage ai_analytics_orgs_users_costs_model_usage_retrieve(end_date, org, start_date, user_id)

Retrieve the model usage data for a tenant Filter parameters for period are start_date and enddate Accessible to tenant Admins only.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.model_usage import ModelUsage
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
end_date = '2013-10-20T19:20:30+01:00' # datetime | 
org = 'org_example' # str | 
start_date = '2013-10-20T19:20:30+01:00' # datetime | 
user_id = 'user_id_example' # str | 

try:
    api_response = api_instance.ai_analytics_orgs_users_costs_model_usage_retrieve(end_date, org, start_date, user_id)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_costs_model_usage_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_costs_model_usage_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
end_date	datetime
org	str
start_date	datetime
user_id	str

Return type

ModelUsage

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_costs_permentor_retrieve

TenantMentorTraces ai_analytics_orgs_users_costs_permentor_retrieve(end_date, org, start_date, user_id)

Get the cost of chats per mentor for a tenant. Filter parameters for period are start_date and end_date Accessible to tenant Admins only.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.tenant_mentor_traces import TenantMentorTraces
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
end_date = '2013-10-20T19:20:30+01:00' # datetime | 
org = 'org_example' # str | 
start_date = '2013-10-20T19:20:30+01:00' # datetime | 
user_id = 'user_id_example' # str | 

try:
    api_response = api_instance.ai_analytics_orgs_users_costs_permentor_retrieve(end_date, org, start_date, user_id)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_costs_permentor_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_costs_permentor_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
end_date	datetime
org	str
start_date	datetime
user_id	str

Return type

TenantMentorTraces

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_costs_peruser_retrieve

LLMTracesListResponse ai_analytics_orgs_users_costs_peruser_retrieve(end_date, org, start_date, user_id)

Get the cost of chats per user for a tenant. Filter parameters for period are start_date and end_date Accessible to tenant Admins only.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.llm_traces_list_response import LLMTracesListResponse
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
end_date = '2013-10-20T19:20:30+01:00' # datetime | 
org = 'org_example' # str | 
start_date = '2013-10-20T19:20:30+01:00' # datetime | 
user_id = 'user_id_example' # str | 

try:
    api_response = api_instance.ai_analytics_orgs_users_costs_peruser_retrieve(end_date, org, start_date, user_id)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_costs_peruser_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_costs_peruser_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
end_date	datetime
org	str
start_date	datetime
user_id	str

Return type

LLMTracesListResponse

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_mentor_detail_retrieve

MentorDetailAnalytics ai_analytics_orgs_users_mentor_detail_retrieve(org, user_id)

This view returns analytics for the mentors such as total mentors, total active mentors and ratings for the mentors.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.mentor_detail_analytics import MentorDetailAnalytics
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
org = 'org_example' # str | 
user_id = 'user_id_example' # str | 

try:
    api_response = api_instance.ai_analytics_orgs_users_mentor_detail_retrieve(org, user_id)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_mentor_detail_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_mentor_detail_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
org	str
user_id	str

Return type

MentorDetailAnalytics

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_mentor_summary_retrieve

MentorDetailAnalytics ai_analytics_orgs_users_mentor_summary_retrieve(org, user_id)

This view returns analytics for the mentors such as total mentors, total active mentors and ratings for the mentors.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.mentor_detail_analytics import MentorDetailAnalytics
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
org = 'org_example' # str | 
user_id = 'user_id_example' # str | 

try:
    api_response = api_instance.ai_analytics_orgs_users_mentor_summary_retrieve(org, user_id)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_mentor_summary_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_mentor_summary_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
org	str
user_id	str

Return type

MentorDetailAnalytics

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_sentiment_count_retrieve

UserSentimentCountView ai_analytics_orgs_users_sentiment_count_retrieve(org, user_id, period=period)

Get the number of messages for a given period of time Filter parameters for period are today, yesterday, 7d, 30d, 90d Accessible to tenant Admins only.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.user_sentiment_count_view import UserSentimentCountView
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
org = 'org_example' # str | 
user_id = 'user_id_example' # str | 
period = '7d' # str |  (optional) (default to '7d')

try:
    api_response = api_instance.ai_analytics_orgs_users_sentiment_count_retrieve(org, user_id, period=period)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_sentiment_count_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_sentiment_count_retrieve: %s\n" % e)

Parameters

Name	Type	Notes
org	str
user_id	str
period	str	[optional] [default to '7d']

Return type

UserSentimentCountView

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_topics_retrieve

Topic ai_analytics_orgs_users_topics_retrieve(org, user_id, period=period, topics=topics, user_ratings=user_ratings, user_sentiments=user_sentiments)

Get all topics relevant to the chat histories of the users in the organization. Topics can be filtered by period: today, yesterday, 7d, 30d, 90d. Topics can be filtered by user_sentiments: positive, negative, neutral. Topics can be filtered by user_ratings: ThumbsUp, ThumbsDown, No Rating. Accessible to tenant Admins only An example of a valid request is: /orgs/ibl/users/ben/topics/?period=7d&user_sentiments=positive&user_ratings=ThumbsUp

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.topic import Topic
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
org = 'org_example' # str | 
user_id = 'user_id_example' # str | 
period = 'period_example' # str |  (optional)
topics = ['topics_example'] # List[str] |  (optional)
user_ratings = ['user_ratings_example'] # List[str] |  (optional)
user_sentiments = ['user_sentiments_example'] # List[str] |  (optional)

try:
    api_response = api_instance.ai_analytics_orgs_users_topics_retrieve(org, user_id, period=period, topics=topics, user_ratings=user_ratings, user_sentiments=user_sentiments)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_topics_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_topics_retrieve: %s\n" % e)

Parameters

Name	Type	Notes
org	str
user_id	str
period	str	[optional]
topics	List[str]	[optional]
user_ratings	List[str]	[optional]
user_sentiments	List[str]	[optional]

Return type

Topic

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_topics_summary_retrieve

TopicSummaryView ai_analytics_orgs_users_topics_summary_retrieve(org, user_id)

Get the summary of topics relevant to the chat histories of the users in the organization. This returns the total conversations and the top three topics relevant to the conversations. Accessible to tenant Admins only

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.topic_summary_view import TopicSummaryView
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
org = 'org_example' # str | 
user_id = 'user_id_example' # str | 

try:
    api_response = api_instance.ai_analytics_orgs_users_topics_summary_retrieve(org, user_id)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_topics_summary_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_topics_summary_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
org	str
user_id	str

Return type

TopicSummaryView

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_traces_retrieve

LLMTracesListResponse ai_analytics_orgs_users_traces_retrieve(end_date, org, start_date, user_id, mentor=mentor)

Retrieve the llm summerized traces for a tenant Filter parameters for period are start_date and enddate Accessible to tenant Admins only.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.llm_traces_list_response import LLMTracesListResponse
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
end_date = '2013-10-20T19:20:30+01:00' # datetime | 
org = 'org_example' # str | 
start_date = '2013-10-20T19:20:30+01:00' # datetime | 
user_id = 'user_id_example' # str | 
mentor = 'mentor_example' # str | Mentor unique id (optional)

try:
    api_response = api_instance.ai_analytics_orgs_users_traces_retrieve(end_date, org, start_date, user_id, mentor=mentor)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_traces_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_traces_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
end_date	datetime
org	str
start_date	datetime
user_id	str
mentor	str	Mentor unique id	[optional]

Return type

LLMTracesListResponse

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_traces_retrieve2

LLMTraceDetail ai_analytics_orgs_users_traces_retrieve2(org, trace_id, user_id)

Get the trace detail. Accessible to tenant Admins only.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.llm_trace_detail import LLMTraceDetail
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
org = 'org_example' # str | 
trace_id = 'trace_id_example' # str | 
user_id = 'user_id_example' # str | 

try:
    api_response = api_instance.ai_analytics_orgs_users_traces_retrieve2(org, trace_id, user_id)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_traces_retrieve2:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_traces_retrieve2: %s\n" % e)

Parameters

Name	Type	Description	Notes
org	str
trace_id	str
user_id	str

Return type

LLMTraceDetail

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_traces_scores_create

LLMScoresViewResponse ai_analytics_orgs_users_traces_scores_create(org, user_id, llm_scores_view_request)

Add message scores for chat. Filter parameters for period are start_date and enddate Accessible to tenant Admins only.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.llm_scores_view_request import LLMScoresViewRequest
from iblai.models.llm_scores_view_response import LLMScoresViewResponse
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
org = 'org_example' # str | 
user_id = 'user_id_example' # str | 
llm_scores_view_request = iblai.LLMScoresViewRequest() # LLMScoresViewRequest | 

try:
    api_response = api_instance.ai_analytics_orgs_users_traces_scores_create(org, user_id, llm_scores_view_request)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_traces_scores_create:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_traces_scores_create: %s\n" % e)

Parameters

Name	Type	Description	Notes
org	str
user_id	str
llm_scores_view_request	LLMScoresViewRequest

Return type

LLMScoresViewResponse

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: application/json, application/x-www-form-urlencoded, multipart/form-data
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_traces_scores_retrieve

LLMScoresView ai_analytics_orgs_users_traces_scores_retrieve(end_date, org, start_date, user_id, mentor=mentor)

Get the scores of messages for a tenant. Filter parameters for period are start_date and end_date Accessible to tenant Admins only.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.llm_scores_view import LLMScoresView
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
end_date = '2013-10-20T19:20:30+01:00' # datetime | 
org = 'org_example' # str | 
start_date = '2013-10-20T19:20:30+01:00' # datetime | 
user_id = 'user_id_example' # str | 
mentor = 'mentor_example' # str | Mentor unique id (optional)

try:
    api_response = api_instance.ai_analytics_orgs_users_traces_scores_retrieve(end_date, org, start_date, user_id, mentor=mentor)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_traces_scores_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_traces_scores_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
end_date	datetime
org	str
start_date	datetime
user_id	str
mentor	str	Mentor unique id	[optional]

Return type

LLMScoresView

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_transcripts_retrieve

ConversationMessage ai_analytics_orgs_users_transcripts_retrieve(org, user_id, end_date=end_date, mentor=mentor, start_date=start_date, topics=topics)

Get the number of messages for a given period of time Filter parameters for period are today, yesterday, 7d, 30d, 90d Accessible to tenant Admins only.

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.conversation_message import ConversationMessage
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
org = 'org_example' # str | 
user_id = 'user_id_example' # str | 
end_date = '2013-10-20' # date |  (optional)
mentor = 'mentor_example' # str |  (optional)
start_date = '2013-10-20' # date |  (optional)
topics = 'topics_example' # str |  (optional)

try:
    api_response = api_instance.ai_analytics_orgs_users_transcripts_retrieve(org, user_id, end_date=end_date, mentor=mentor, start_date=start_date, topics=topics)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_transcripts_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_transcripts_retrieve: %s\n" % e)

Parameters

Name	Type	Notes
org	str
user_id	str
end_date	date	[optional]
mentor	str	[optional]
start_date	date	[optional]
topics	str	[optional]

Return type

ConversationMessage

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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ai_analytics_orgs_users_user_feedback_retrieve

UserChatFeedbackCount ai_analytics_orgs_users_user_feedback_retrieve(org, user_id)

Return the total number of user chat feedback per week

Example

Api Key Authentication (PlatformApiKeyAuthentication):

import iblai
from iblai.models.user_chat_feedback_count import UserChatFeedbackCount
from iblai.rest import ApiException
from pprint import pprint

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# The APIs use bearer tokens for authentication with a prefix of: `Api-Key`
# You can generate an authenticated client using the following helper method
client = get_platform_api_client(
    host="https://base.manager.iblai.app", 
    key=os.environ["API_KEY"]
)

# Create an instance of the API class
api_instance = iblai.AiAnalyticsApi(api_client)
org = 'org_example' # str | 
user_id = 'user_id_example' # str | 

try:
    api_response = api_instance.ai_analytics_orgs_users_user_feedback_retrieve(org, user_id)
    print("The response of AiAnalyticsApi->ai_analytics_orgs_users_user_feedback_retrieve:\n")
    pprint(api_response)
except Exception as e:
    print("Exception when calling AiAnalyticsApi->ai_analytics_orgs_users_user_feedback_retrieve: %s\n" % e)

Parameters

Name	Type	Description	Notes
org	str
user_id	str

Return type

UserChatFeedbackCount

Authorization

PlatformApiKeyAuthentication

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200		-

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iblai.AiAnalyticsApi

ai_analytics_orgs_users_chat_history_filter_retrieve

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Authorization

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ai_analytics_orgs_users_chat_history_list

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ai_analytics_orgs_users_chat_history_retrieve

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ai_analytics_orgs_users_conversation_retrieve

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ai_analytics_orgs_users_costs_model_retrieve

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ai_analytics_orgs_users_costs_model_usage_retrieve

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ai_analytics_orgs_users_costs_permentor_retrieve

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ai_analytics_orgs_users_costs_peruser_retrieve

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ai_analytics_orgs_users_mentor_detail_retrieve

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Authorization

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ai_analytics_orgs_users_mentor_summary_retrieve

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Authorization

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ai_analytics_orgs_users_sentiment_count_retrieve

Example

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