We are eager to add new features to our API. Our newest API solution is advanced product descriptions.
There are multiple ways to use the TextCortex API. At the core of interaction is the "prompt" that gives instruction to our AI models about what it should create.
Our users need a tool that is reliable in it's output and serves them in what they need. While in the past we used only "product titles" to generate descriptions. We have now added "product features" which can be added to make more accurate descriptions and keep a high input to output relevancy for our users.
At the core of every API call is the "prompt" which tells our AI models what they should write about. In general, more information helps the AI to create better and more relevant text to your needs.
If you have created your "prompt", you just need send it to our API endpoint with the API key.
Let's say your product details are like the following:
Product Name: Gucci Skinny women jeans
Category: 'Clothing, Shoes & Jewelry', 'Women'
Features: 'Size: Medium', 'Color: Pink', 'Style:Slim Fit', 'Materials:Cotton 98%, Elastane 2%'
in this case you need to build a complete string like the below to send to our API. Complete Prompt for that would be:
Product name: 'Gucci Skinny women jeans' Brand: 'Gucci' Category: ['Clothing, Shoes & Jewelry', 'Women'] Features: ['Size: Medium', 'Color: Pink', 'Style:Slim Fit', 'Materials:Cotton 98%, Elastane 2%'] Product Description:
In order to achieve high input to output relevancy it
As mentioned earlier it is important to keep the general prompt structure and add the product information within the pipeline accordingly from your data management system into our API.
In the below Request-Response example, you can see that within the call's "prompt" there is a defined structure of features that must be kept and send as a string to our API.
For example, if you have detailed product features at your disposal, you can send a prompt like the following:
In case you don't have enough product data, you can send only the "product title" to get product description.
As the AI does not have instructions on product features it might include or use common characteristics related to the product.
In order to control and maintain a high input to output relevancy add as much information to the model as possible. Similar to a human the more instruction and onboarding somebody has to a task, the better and faster they can operate.
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