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PromptLayer ChatOpenAI

该示例演示如何连接到PromptLayer以开始记录您的ChatOpenAI请求。

安装 PromptLayer​

使用pip安装promptlayer，以便将其与OpenAI一起使用。

pip install promptlayer

Imports​

import os
from langchain.chat_models import PromptLayerChatOpenAI
from langchain.schema import HumanMessage

Set the Environment API Key​

You can create a PromptLayer API Key at www.promptlayer.com by clicking the settings cog in the navbar.

Set it as an environment variable called PROMPTLAYER_API_KEY.

os.environ["PROMPTLAYER_API_KEY"] = "**********"

Use the PromptLayerOpenAI LLM like normal​

You can optionally pass in pl_tags to track your requests with PromptLayer's tagging feature.

chat = PromptLayerChatOpenAI(pl_tags=["langchain"])
chat([HumanMessage(content="I am a cat and I want")])
AIMessage(content='to take a nap in a cozy spot. I search around for a suitable place and finally settle on a soft cushion on the window sill. I curl up into a ball and close my eyes, relishing the warmth of the sun on my fur. As I drift off to sleep, I can hear the birds chirping outside and feel the gentle breeze blowing through the window. This is the life of a contented cat.', additional_kwargs={})

现在，您应该在PromptLayer仪表板上看到上述请求。

使用 PromptLayer Track​

如果您想使用任何PromptLayer跟踪功能，在实例化PromptLayer LLM时，您需要传递参数return_pl_id以获取请求ID。

chat = PromptLayerChatOpenAI(return_pl_id=True)
chat_results = chat.generate([[HumanMessage(content="I am a cat and I want")]])

for res in chat_results.generations:
    pl_request_id = res[0].generation_info["pl_request_id"]
    promptlayer.track.score(request_id=pl_request_id, score=100)

使用PromptLayer可以在PromptLayer仪表板上跟踪模型的性能。如果您正在使用提示模板，还可以将模板附加到请求中。总体而言，这使您有机会在PromptLayer仪表板上跟踪不同模板和模型的性能。