ivyanalytics

Python bindings for ingesting conversational data into ivyanalytics

Requirements

Python 3.7+

Installation

pip install ivyanalytics

Tests

Execute pytest to run the tests.

Getting Started

Please follow the installation procedure and then run the following:

import ivyanalytics
from ivyanalytics.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to https://api.ivyanalytics.io
# See configuration.py for a list of all supported configuration parameters.
configuration = ivyanalytics.Configuration(
    host = "https://api.ivyanalytics.io"
)

# 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.

# Configure HTTP basic authorization: HTTPBasic
configuration = ivyanalytics.Configuration(
    username = os.environ["USERNAME"],
    password = os.environ["PASSWORD"]
)


# Enter a context with an instance of the API client
with ivyanalytics.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = ivyanalytics.ConversationApi(api_client)
    conversation_data_schema = ivyanalytics.ConversationDataSchema(conversation_data_schema = ivyanalytics.ConversationDataSchema(conversations=
        [
            {
                "conversation_id": "my_historical_conv_id_1",
                "tenant_id": "<my_unique_tenant_id>",
                "conversation_created_at": "2020-02-20T20:19:34Z",
                "messages": [
                    {
                        "id": "message_id",
                        "role": "user",
                        "body": "What time does the team arrive?",
                        "created_at": "2020-02-20T20:19:34Z",
                    },
                    {
                        "id": "message_id",
                        "role": "assistant",
                        "body": "The team arrives at 6pm.",
                        "created_at": "2020-02-20T20:20:23Z",
                    },
                ],
                "metadata": {
                    "model": "gpt-3.5-turbo-16k",
                    "user_id": "2947451",
                    "metadata_1": "value",
                    "metadata_2": "value",
                },
            },
            {
                "conversation_id": "my_historical_conv_id_2",
                "tenant_id": "<my_unique_tenant_id>",
                "conversation_created_at": "2020-02-20T20:19:34Z",

                "messages": [
                    {
                        "id": "message_id",
                        "role": "user",
                        "body": "What time does the team arrive?",
                        "created_at": "2020-02-20T20:19:34Z",
                    },
                    {
                        "id": "message_id",
                        "role": "assistant",
                        "body": "The team arrives at 6pm.",
                        "created_at": "2020-02-20T20:20:23Z",
                    },
                ],
                "metadata": {
                    "model": "gpt-3.5-turbo-16k",
                    "user_id": "2947451",
                    "metadata_1": "value",
                    "metadata_2": "value",
                },
            },
        ]) )  

    try:
        # Log a batch of conversations to BigQuery
        api_response = api_instance.ingest_conversations(conversation_data_schema)
        print("The response of ConversationApi->ingest_conversations:\n")
        pprint(api_response)
    except ApiException as e:
        print("Exception when calling ConversationApi->ingest_conversations: %s\n" % e)

Documentation for API Endpoints

All URIs are relative to https://api.ivyanalytics.io