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langchain/docs/modules/chat/examples/promptlayer_chatopenai.ipynb

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{
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"source": [
"# PromptLayer ChatOpenAI\n",
"\n",
"This example showcases how to connect to [PromptLayer](https://www.promptlayer.com) to start recording your ChatOpenAI requests."
]
},
{
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"source": [
"## Install PromptLayer\n",
"The `promptlayer` package is required to use PromptLayer with OpenAI. Install `promptlayer` using pip."
]
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"pip install promptlayer"
]
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{
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"source": [
"## Imports"
]
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"source": [
"import os\n",
"from langchain.chat_models import PromptLayerChatOpenAI\n",
"from langchain.schema import HumanMessage"
]
},
{
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"source": [
"## Set the Environment API Key\n",
"You can create a PromptLayer API Key at [wwww.promptlayer.com](https://ww.promptlayer.com) by clicking the settings cog in the navbar.\n",
"\n",
"Set it as an environment variable called `PROMPTLAYER_API_KEY`."
]
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"cell_type": "code",
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"os.environ[\"PROMPTLAYER_API_KEY\"] = \"**********\""
]
},
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"source": [
"## Use the PromptLayerOpenAI LLM like normal\n",
"*You can optionally pass in `pl_tags` to track your requests with PromptLayer's tagging feature.*"
]
},
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"cell_type": "code",
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"id": "3acf0069",
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{
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"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={})"
]
},
"execution_count": 4,
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],
"source": [
"chat = PromptLayerChatOpenAI(pl_tags=[\"langchain\"])\n",
"chat([HumanMessage(content=\"I am a cat and I want\")])"
]
},
{
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"**The above request should now appear on your [PromptLayer dashboard](https://ww.promptlayer.com).**"
]
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"## Using PromptLayer Track\n",
"If you would like to use any of the [PromptLayer tracking features](https://magniv.notion.site/Track-4deee1b1f7a34c1680d085f82567dab9), you need to pass the argument `return_pl_id` when instantializing the PromptLayer LLM to get the request id. "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b7d4db01",
"metadata": {},
"outputs": [],
"source": [
"chat = PromptLayerChatOpenAI(return_pl_id=True)\n",
"chat_results = chat.generate([[HumanMessage(content=\"I am a cat and I want\")]])\n",
"\n",
"for res in chat_results.generations:\n",
" pl_request_id = res[0].generation_info[\"pl_request_id\"]\n",
" promptlayer.track.score(request_id=pl_request_id, score=100)"
]
},
{
"cell_type": "markdown",
"id": "13e56507",
"metadata": {},
"source": [
"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.\n",
"Overall, this gives you the opportunity to track the performance of different templates and models in the PromptLayer dashboard."
]
}
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