The WaveSay team has released a new option for the AI Chatbot that allows for Integrations.
Please note that this product is still being modified and adjusted by the dev team to ensure a sustainable and efficient user interface and user experience. The references below reflect the current settings and features as of this writing.
INTEGRATIONS
These options allow the Chatbot to interact with specific APIs and Webhooks, pulling in relevant information on Weather, Shopify Orders, and more!
Weather API -
Enable the Weather API to let the agent provide accurate, real-time weather information. With this integration, users can ask about current weather conditions for locations they care about, making the agent an even more valuable resource.
Enter the API key received when signing up for the weather API. This key is required to access the weather data.
Shopify Order Lookup -
Connect a Shopify store to let the agent access order and fulfillment information. With this integration, the agent can answer questions about order shipping details, providing timely support to customers.
API Key - Enter the Shopify Admin API key, ensuring it has 'read_orders' and 'read_fulfillments' access scopes. This key is obtained from the Shopify account settings.
Store Name - Enter the store’s short name (e.g., mystore) used to create the Shopify URL (mystore.myshopify.com).
Custom Webhook -
Use a custom webhook to expand the agent’s capabilities with data from other resources. This integration allows the agent to pull in information from other systems, answering specific questions related to the business, such as inventory updates, personalized recommendations, or custom support details.
URL - Enter the URL to receive data. This webhook will receive a POST request with the parameters configure as a JSON object.
Description - Describe the function of this webhook. This description helps train the language model to understand and interact with the webhook effectively.
Parameters - Add each parameter’s Property name (short, alphanumeric, like user_name or email) and a clear description. Descriptions should specify what the parameter represents and any specific data format or intent. These descriptions help the language model capture the right information and interpret the parameters accurately.