PromptLayer OpenAI
PromptLayer
is the first platform that allows you to track, manage, and share your GPT prompt engineering. PromptLayer
acts a middleware between your code and OpenAI’s
python library.
PromptLayer
records all your OpenAI API
requests, allowing you to search and explore request history in the PromptLayer
dashboard.
This example showcases how to connect to PromptLayer to start recording your OpenAI requests.
Another example is here.
Install PromptLayer
The promptlayer
package is required to use PromptLayer with OpenAI. Install promptlayer
using pip.
%pip install --upgrade --quiet promptlayer
Imports
import os
import promptlayer
from langchain_community.llms import PromptLayerOpenAI
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
.
You also need an OpenAI Key, called OPENAI_API_KEY
.
from getpass import getpass
PROMPTLAYER_API_KEY = getpass()
········
os.environ["PROMPTLAYER_API_KEY"] = PROMPTLAYER_API_KEY
from getpass import getpass
OPENAI_API_KEY = getpass()
··· ·····
os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
Use the PromptLayerOpenAI LLM like normal
You can optionally pass in pl_tags
to track your requests with PromptLayer's tagging feature.
llm = PromptLayerOpenAI(pl_tags=["langchain"])
llm("I am a cat and I want")
The above request should now appear on your PromptLayer dashboard.
Using PromptLayer Track
If you would like to use any of the PromptLayer tracking features, you need to pass the argument return_pl_id
when instantiating the PromptLayer LLM to get the request id.
llm = PromptLayerOpenAI(return_pl_id=True)
llm_results = llm.generate(["Tell me a joke"])
for res in llm_results.generations:
pl_request_id = res[0].generation_info["pl_request_id"]
promptlayer.track.score(request_id=pl_request_id, score=100)
Using this allows you to track the performance of your model in the PromptLayer dashboard. If you are using a prompt template, you can attach a template to a request as well. Overall, this gives you the opportunity to track the performance of different templates and models in the PromptLayer dashboard.
Related
- LLM conceptual guide
- LLM how-to guides