text: set it as an environment variabled called PROMPTLAYER_API_KEYUsageâ€‹Getting started with PromptLayerCallbackHandler is fairly simple, it takes two optional arguments:pl_tags - an optional list of strings that will be tracked as tags on PromptLayer.pl_id_callback - an optional function that will take promptlayer_request_id as an argument. This ID can be used with all of PromptLayer's tracking features to track, metadata, scores, and prompt usage.Simple OpenAI Exampleâ€‹In this simple example we use PromptLayerCallbackHandler with ChatOpenAI. We add a PromptLayer tag named chatopenaiimport promptlayer  # Don't forget this ğŸ�°from langchain.callbacks import PromptLayerCallbackHandlerfrom langchain.chat_models import ChatOpenAIfrom langchain.schema import (    HumanMessage,)chat_llm = ChatOpenAI(    temperature=0,    callbacks=[PromptLayerCallbackHandler(pl_tags=["chatopenai"])],)llm_results = chat_llm(    [        HumanMessage(content="What comes after 1,2,3 ?"),        HumanMessage(content="Tell me another joke?"),    ])print(llm_results)GPT4All Exampleâ€‹import promptlayer  # Don't forget this ğŸ�°from langchain.callbacks import PromptLayerCallbackHandlerfrom langchain.llms import GPT4Allmodel = GPT4All(model="./models/gpt4all-model.bin", n_ctx=512, n_threads=8)response = model(    "Once upon a time, ",    callbacks=[PromptLayerCallbackHandler(pl_tags=["langchain", "gpt4all"])],)Full Featured Exampleâ€‹In this example we unlock more of the power of PromptLayer.PromptLayer allows you to visually create,