{ "cells": [ { "attachments": {}, "cell_type": "markdown", "id": "959300d4", "metadata": {}, "source": [ "# PromptLayer OpenAI\n", "\n", "This example showcases how to connect to [PromptLayer](https://www.promptlayer.com) to start recording your OpenAI requests." ] }, { "attachments": {}, "cell_type": "markdown", "id": "6a45943e", "metadata": {}, "source": [ "## Install PromptLayer\n", "The `promptlayer` package is required to use PromptLayer with OpenAI. Install `promptlayer` using pip." ] }, { "cell_type": "code", "execution_count": null, "id": "dbe09bd8", "metadata": { "vscode": { "languageId": "powershell" } }, "outputs": [], "source": [ "pip install promptlayer" ] }, { "cell_type": "markdown", "id": "536c1dfa", "metadata": {}, "source": [ "## Imports" ] }, { "cell_type": "code", "execution_count": null, "id": "c16da3b5", "metadata": {}, "outputs": [], "source": [ "import os\n", "from langchain.llms import PromptLayerOpenAI\n", "import promptlayer" ] }, { "attachments": {}, "cell_type": "markdown", "id": "8564ce7d", "metadata": {}, "source": [ "## Set the Environment API Key\n", "You can create a PromptLayer API Key at [www.promptlayer.com](https://www.promptlayer.com) by clicking the settings cog in the navbar.\n", "\n", "Set it as an environment variable called `PROMPTLAYER_API_KEY`." ] }, { "cell_type": "code", "execution_count": null, "id": "46ba25dc", "metadata": {}, "outputs": [], "source": [ "os.environ[\"PROMPTLAYER_API_KEY\"] = \"********\"" ] }, { "attachments": {}, "cell_type": "markdown", "id": "bf0294de", "metadata": {}, "source": [ "## Use the PromptLayerOpenAI LLM like normal\n", "*You can optionally pass in `pl_tags` to track your requests with PromptLayer's tagging feature.*" ] }, { "cell_type": "code", "execution_count": 4, "id": "3acf0069", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "' to go outside\\n\\nUnfortunately, cats cannot go outside without being supervised by a human. Going outside can be dangerous for cats, as they may come into contact with cars, other animals, or other dangers. If you want to go outside, ask your human to take you on a supervised walk or to a safe, enclosed outdoor space.'" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "llm = PromptLayerOpenAI(pl_tags=[\"langchain\"])\n", "llm(\"I am a cat and I want\")" ] }, { "attachments": {}, "cell_type": "markdown", "id": "a2d76826", "metadata": {}, "source": [ "**The above request should now appear on your [PromptLayer dashboard](https://ww.promptlayer.com).**" ] }, { "attachments": {}, "cell_type": "markdown", "id": "05e9e2fe", "metadata": {}, "source": [ "## 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": "1a7315b9", "metadata": {}, "outputs": [], "source": [ "llm = PromptLayerOpenAI(return_pl_id=True)\n", "llm_results = llm.generate([\"Tell me a joke\"])\n", "\n", "for res in llm_results.generations:\n", " pl_request_id = res[0].generation_info[\"pl_request_id\"]\n", " promptlayer.track.score(request_id=pl_request_id, score=100)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "7eb19139", "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." ] } ], "metadata": { "kernelspec": { "display_name": "base", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.8 (default, Apr 13 2021, 12:59:45) \n[Clang 10.0.0 ]" }, "vscode": { "interpreter": { "hash": "8a5edab282632443219e051e4ade2d1d5bbc671c781051bf1437897cbdfea0f1" } } }, "nbformat": 4, "nbformat_minor": 5 }