mirror of
https://github.com/hwchase17/langchain
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238 lines
5.7 KiB
Plaintext
238 lines
5.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "959300d4",
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"metadata": {},
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"source": [
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"# PromptLayer OpenAI\n",
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"\n",
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"`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.\n",
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"\n",
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"`PromptLayer` records all your `OpenAI API` requests, allowing you to search and explore request history in the `PromptLayer` dashboard.\n",
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"\n",
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"\n",
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"This example showcases how to connect to [PromptLayer](https://www.promptlayer.com) to start recording your OpenAI requests.\n",
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"\n",
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"Another example is [here](https://python.langchain.com/en/latest/ecosystem/promptlayer.html)."
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]
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},
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{
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"cell_type": "markdown",
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"id": "6a45943e",
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"metadata": {},
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"source": [
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"## Install PromptLayer\n",
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"The `promptlayer` package is required to use PromptLayer with OpenAI. Install `promptlayer` using pip."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "dbe09bd8",
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"metadata": {
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"tags": [],
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"vscode": {
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"languageId": "powershell"
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}
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},
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"outputs": [],
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"source": [
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"!pip install promptlayer"
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]
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},
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{
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"cell_type": "markdown",
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"id": "536c1dfa",
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"metadata": {},
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"source": [
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"## Imports"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "c16da3b5",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import os\n",
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"from langchain.llms import PromptLayerOpenAI\n",
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"import promptlayer"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8564ce7d",
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"metadata": {},
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"source": [
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"## Set the Environment API Key\n",
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"You can create a PromptLayer API Key at [www.promptlayer.com](https://www.promptlayer.com) by clicking the settings cog in the navbar.\n",
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"\n",
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"Set it as an environment variable called `PROMPTLAYER_API_KEY`.\n",
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"\n",
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"You also need an OpenAI Key, called `OPENAI_API_KEY`."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "1df96674-a9fb-4126-bb87-541082782240",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdin",
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"output_type": "stream",
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"text": [
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" ········\n"
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]
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}
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],
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"source": [
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"from getpass import getpass\n",
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"\n",
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"PROMPTLAYER_API_KEY = getpass()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "46ba25dc",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"os.environ[\"PROMPTLAYER_API_KEY\"] = PROMPTLAYER_API_KEY"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "9aa68c46-4d88-45ba-8a83-18fa41b4daed",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdin",
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"output_type": "stream",
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"text": [
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" ········\n"
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]
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}
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],
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"source": [
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"from getpass import getpass\n",
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"\n",
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"OPENAI_API_KEY = getpass()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "6023b6fa-d9db-49d6-b713-0e19686119b0",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"os.environ[\"OPENAI_API_KEY\"] = OPENAI_API_KEY"
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]
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},
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{
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"cell_type": "markdown",
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"id": "bf0294de",
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"metadata": {},
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"source": [
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"## Use the PromptLayerOpenAI LLM like normal\n",
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"*You can optionally pass in `pl_tags` to track your requests with PromptLayer's tagging feature.*"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3acf0069",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"llm = PromptLayerOpenAI(pl_tags=[\"langchain\"])\n",
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"llm(\"I am a cat and I want\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a2d76826",
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"metadata": {},
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"source": [
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"**The above request should now appear on your [PromptLayer dashboard](https://www.promptlayer.com).**"
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]
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},
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{
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"cell_type": "markdown",
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"id": "05e9e2fe",
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"metadata": {},
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"source": [
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"## Using PromptLayer Track\n",
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"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. "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1a7315b9",
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"metadata": {},
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"outputs": [],
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"source": [
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"llm = PromptLayerOpenAI(return_pl_id=True)\n",
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"llm_results = llm.generate([\"Tell me a joke\"])\n",
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"\n",
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"for res in llm_results.generations:\n",
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" pl_request_id = res[0].generation_info[\"pl_request_id\"]\n",
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" promptlayer.track.score(request_id=pl_request_id, score=100)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "7eb19139",
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"metadata": {},
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"source": [
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"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",
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"Overall, this gives you the opportunity to track the performance of different templates and models in the PromptLayer dashboard."
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.6"
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},
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"vscode": {
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"interpreter": {
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"hash": "8a5edab282632443219e051e4ade2d1d5bbc671c781051bf1437897cbdfea0f1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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