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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "b02n_zJ_hl3d"
},
"source": [
"## Cookbook for using OpenAI with Embedchain"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "gyJ6ui2vhtMY"
},
"source": [
"### Step-1: Install embedchain package"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "-NbXjAdlh0vJ",
"outputId": "6c630676-c7fc-4054-dc94-c613de58a037"
},
"outputs": [],
"source": [
"!pip install embedchain"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "nGnpSYAAh2bQ"
},
"source": [
"### Step-2: Set OpenAI environment variables\n",
"\n",
"You can find this env variable on your [OpenAI dashboard](https://platform.openai.com/account/api-keys)."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "0fBdQ9GAiRvK"
},
"outputs": [],
"source": [
"import os\n",
"from embedchain import App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\""
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "PGt6uPLIi1CS"
},
"source": [
"### Step-3 Create embedchain app and define your config"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "Amzxk3m-i3tD"
},
"outputs": [],
"source": [
"app = App.from_config(config={\n",
" \"llm\": {\n",
" \"provider\": \"openai\",\n",
" \"config\": {\n",
" \"model\": \"gpt-3.5-turbo\",\n",
" \"temperature\": 0.5,\n",
" \"max_tokens\": 1000,\n",
" \"top_p\": 1,\n",
" \"stream\": False\n",
" }\n",
" },\n",
" \"embedder\": {\n",
" \"provider\": \"openai\",\n",
" \"config\": {\n",
" \"model\": \"text-embedding-ada-002\"\n",
" }\n",
" }\n",
"})"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "XNXv4yZwi7ef"
},
"source": [
"### Step-4: Add data sources to your app"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "Sn_0rx9QjIY9"
},
"outputs": [],
"source": [
"app.add(\"https://www.forbes.com/profile/elon-musk\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "_7W6fDeAjMAP"
},
"source": [
"### Step-5: All set. Now start asking questions related to your data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "cvIK7dWRjN_f"
},
"outputs": [],
"source": [
"while(True):\n",
" question = input(\"Enter question: \")\n",
" if question in ['q', 'exit', 'quit']:\n",
" break\n",
" answer = app.query(question)\n",
" print(answer)"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python",
"version": "3.11.6"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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