Tokens are like the building blocks of language in OpenAI and Large Language Models (LLMs). They represent words, phrases, and other language elements using numbers, which computers understand much faster than humans. So, when we talk about e-commerce, tokens play a significant role!
LLMs and tokens: Computers don’t comprehend words as we do, but they excel at processing numbers. To bridge the gap, LLMs represent words as tokens. Each token is nothing but a word or a sub-word. Each token is represented by multi-dimensional vectors that are called embeddings.
These embeddings are nothing but the numerical representation of tokens.
OpenAI’s brilliance lies in using tokens to ensure text coherence and consistency, effectively addressing various e-commerce tasks like writing, translating, and answering queries.
A helpful tool in this realm is Langchain, a user-friendly framework that simplifies LLM usage for e-commerce. It handles text processing, generation, and translation seamlessly.
Token Limits of LLMs:
Token Limits are different for different models. If we are using a model with a token limit of 4096. then it means the sum of query tokens and response tokens should be less than 4096. Tokens are shared between prompt and completion. If your prompt is 4000 tokens, your completion can be 97 tokens at most.
The limit is currently a technical limitation, but there are often creative ways to solve problems within the limit, e.g. condensing your prompt, breaking the text into smaller pieces, etc.
Here are a few official token limits of OpenAI LLMs:
| LATEST MODEL | MAX TOKENS | ||
|---|---|---|---|
| gpt-3.5-turbo | 4,096 tokens | ||
| gpt-3.5-turbo-16k | 16,384 tokens | ||
| gpt-3.5-turbo-0613 | 4,096 tokens | ||
| gpt-3.5-turbo-16k-0613 | 16,384 tokens | ||
| text-davinci-003 (Legacy) | 4,097 tokens | ||
| text-davinci-002 (Legacy) | 4,097 tokens | ||
| code-davinci-002 (Legacy) | 8,001 tokens |
We have launched a new product AI Chatbot on Bagisto, this will be a 24/7 assistant on your e-commerce and will handle user queries on your behalf. This AI chatbot is using Large Language Models that are super expert in handling text queries.
We have already used OpenAI LLM in our Chatbot but there are so many use cases of LLMs from which we can leverage our e-commerce business.
Let’s explore some scenarios where LLMs and OpenAI come to the rescue:
- Building Chatbot on Custom Data: Customers love quick resolutions to their queries. By deploying an AI Chatbot on your e-commerce platform and training it on specific data, like return policy details, you can provide instant answers to users.
- Writing Product Descriptions: Instead of relying on human content creators, LLMs can generate compelling product descriptions based on product attributes with just a click.
- Translation: For a multilingual e-commerce platform, LLMs can easily translate everything from product descriptions to customer reviews, making it convenient for customers worldwide.
- Organizing Products: LLMs can categorize products based on their features and descriptions, keeping the virtual store shelves neat and tidy.
- Personalized Recommendations: LLMs can understand user preferences based on past purchases and browsing history, offering personalized product suggestions for happier customers.
- Wow Marketing Copy: Need attention-grabbing marketing words? LLMs can craft snappy copy that draws in the crowds!
Customers can simply ask the chatbot about their requirements, and it will provide relevant product links, streamlining the shopping process.
With OpenAI and Langchain at work, e-commerce can thrive with tokens! From precise product descriptions to reaching a global audience, the future looks promising. So, stay tuned for more token-tactic updates from us! We’ll keep you informed on all the exciting developments!
Be the first to comment.