llmfast is your go-to Python library for simplifying the development of Large Language Model (LLM) applications. With just a few lines of code, you can harness the power of LLMs, saving you time and reducing complexity. Our library offers effortless integration, minimal coding requirements, and full customization to meet your unique needs. It's designed for optimized performance, ensuring smooth application execution, even with extensive language model usage. Explore our comprehensive documentation and examples to kickstart your LLM application development journey with ease. Unlock the potential of LLMs today with llmfast!
Import the Chatbot
class: In your Python script, import the Chatbot
class from llmfast
. You can do this by adding the following line at the beginning of your code:
from llmfast import Chatbot
-
Obtain an OpenAI API key: To use the
llmfast
library, you'll need an API key from OpenAI. If you don't have one, sign up on the OpenAI website and obtain an API key. -
Create a
Chatbot
instance: Initialize the Chatbot class with your OpenAI API key and specify the desired role for your chatbot. Here's an example of creating aChatbot
instance: -
Replace
"YOUR-OPENAI-API-KEY"
with your actual OpenAI API key, and"ENTER-YOUR-CHATBOT-ROLE"
with the desired role for your chatbot. -
Deploy the chatbot: Set the
deploy
parameter toTrue
when creating theChatbot
instance. This will deploy the chatbot and make it available for use. -
To deploy or terminate the deployment of a chatbot created using the
mlfast
library, you can set thedeploy
parameter toTrue
orFalse
when creating theChatbot
instance, respectively.
Chatbot(api_key="YOUR-OPENAI-API-KEY",
role="ENTER-YOUR-CHATBOT-ROLE",
deploy=True)