Let It Know About Your Business

Each chatbot can have its own context, where you can essentially instruct it on how to behave and provide information it may not already know. So, if you want your chatbot to be knowledgeable about your business or specific information, you can write something like this: 'You work for Meow Apps. For any questions related to Meow Apps, please use the following contact information: support@meowapps.com.' Feel free to provide further details about your business, contact details, and any contextual data. This is particularly useful for behavior-related aspects, contact information, and contextual data.

Additionally, AI Engine provides "content awareness." By enabling this feature in your chatbot settings, you can insert the placeholder {CONTENT} into your chatbot context. This placeholder will then be replaced with your page content, allowing the chatbot to have context about the page it is currently reading.

You can use vector databases to create long-term memory for an AI model. If this sounds complicated, don't worry; AI Engine handles it for you. Essentially, you can feed any textual data to be used as a resource, much like a library for your chatbot to reference when asked about anything. For instance, if you have written books, you could input them there, and your chatbot will know everything about them when asked, making this perfect for managing large corpora of data. You can simply sync all of your Wordpress posts and get the chatbot to know about their content when needed.

With Context and Embeddings, you have a wide range of capabilities, but achieving optimal results may require some manual tweaking. An alternative approach would be to leverage OpenAI assistants in AI Engine. If you already have some assistants, you're all set! If not, the setup process takes less than a minute, and you can even import files directly via OpenAI.

You can use AI Engine filters (Learn more about AI Engine filters: link) to dynamically modify the content of queries, replies, or context at runtime. This allows you to capture your user's message, check what they are looking for, and then perform a query, such as a web search or an internal search in your WooCommerce products, to set the AI model's context with this new information.

You can also use function calling (Learn more about Function Calling: link) to create a function that fetches this information when called, allowing the AI itself to decide when to use this function and automatically provide itself with the new data.

You can read the linked documentation to learn more, but this will require some technical knowledge to implement. For those who lack coding expertise, we at Meow Apps have developed add-ons that handle this for you, like the Web Search add-on or the Better Links add-on that fetch your internal posts (Learn more about add-ons: link). If you purchase them, you get access to premium support, and we ensure they are always up-to-date with AI Engine. Alternatively, you can also contact a freelancer to help you develop exactly what you are looking for.

This technique is employed when you wish to instruct the AI model on how to handle particular situations, rather than having it memorize new data. Think of it as akin to teaching a virtual assistant a new skill. The assistant may not necessarily comprehend the underlying mechanics, but it learns how to respond when encountering specific prompts. So, if you're employing AI to address a specific use case, particularly one that diverges from a typical chatbot scenario, fine-tuning is the path to consider.

This would be useful for creating a technical support assistant. You wouldn't want it to generate responses based solely on past resolved issues. Instead, you'd want it to adapt to each unique situation based on the knowledge it has acquired, because no two situations are ever exactly the same.