my-project-public

repository

loading code, commits, and activity

repositories

loading repo index

#1	{
#2	"cells": [
#3	{
#4	"cell_type": "markdown",
#5	"metadata": {
#6	"id": "b02n_zJ_hl3d"
#7	},
#8	"source": [
#9	"## Cookbook for using GPT4All with Embedchain"
#10	]
#11	},
#12	{
#13	"cell_type": "markdown",
#14	"metadata": {
#15	"id": "gyJ6ui2vhtMY"
#16	},
#17	"source": [
#18	"### Step-1: Install embedchain package"
#19	]
#20	},
#21	{
#22	"cell_type": "code",
#23	"execution_count": null,
#24	"metadata": {
#25	"colab": {
#26	"base_uri": "https://localhost:8080/"
#27	},
#28	"id": "-NbXjAdlh0vJ",
#29	"outputId": "077fa470-b51f-4c29-8c22-9c5f0a9cef47"
#30	},
#31	"outputs": [],
#32	"source": [
#33	"!pip install embedchain[opensource]"
#34	]
#35	},
#36	{
#37	"cell_type": "markdown",
#38	"metadata": {
#39	"id": "nGnpSYAAh2bQ"
#40	},
#41	"source": [
#42	"### Step-2: Set GPT4ALL related environment variables\n",
#43	"\n",
#44	"GPT4All is free for all and doesn't require any API Key to use it. So you can use it for free!"
#45	]
#46	},
#47	{
#48	"cell_type": "code",
#49	"execution_count": null,
#50	"metadata": {
#51	"id": "0fBdQ9GAiRvK"
#52	},
#53	"outputs": [],
#54	"source": [
#55	"from embedchain import App"
#56	]
#57	},
#58	{
#59	"cell_type": "markdown",
#60	"metadata": {
#61	"id": "PGt6uPLIi1CS"
#62	},
#63	"source": [
#64	"### Step-3 Create embedchain app and define your config"
#65	]
#66	},
#67	{
#68	"cell_type": "code",
#69	"execution_count": null,
#70	"metadata": {
#71	"colab": {
#72	"base_uri": "https://localhost:8080/"
#73	},
#74	"id": "Amzxk3m-i3tD",
#75	"outputId": "775db99b-e217-47db-f87f-788495d86f26"
#76	},
#77	"outputs": [],
#78	"source": [
#79	"app = App.from_config(config={\n",
#80	" \"llm\": {\n",
#81	" \"provider\": \"gpt4all\",\n",
#82	" \"config\": {\n",
#83	" \"model\": \"orca-mini-3b-gguf2-q4_0.gguf\",\n",
#84	" \"temperature\": 0.5,\n",
#85	" \"max_tokens\": 1000,\n",
#86	" \"top_p\": 1,\n",
#87	" \"stream\": False\n",
#88	" }\n",
#89	" },\n",
#90	" \"embedder\": {\n",
#91	" \"provider\": \"gpt4all\",\n",
#92	" \"config\": {\n",
#93	" \"model\": \"all-MiniLM-L6-v2\"\n",
#94	" }\n",
#95	" }\n",
#96	"})"
#97	]
#98	},
#99	{
#100	"cell_type": "markdown",
#101	"metadata": {
#102	"id": "XNXv4yZwi7ef"
#103	},
#104	"source": [
#105	"### Step-4: Add data sources to your app"
#106	]
#107	},
#108	{
#109	"cell_type": "code",
#110	"execution_count": null,
#111	"metadata": {
#112	"colab": {
#113	"base_uri": "https://localhost:8080/",
#114	"height": 52
#115	},
#116	"id": "Sn_0rx9QjIY9",
#117	"outputId": "c6514f17-3cb2-4fbc-c80d-79b3a311ff30"
#118	},
#119	"outputs": [],
#120	"source": [
#121	"app.add(\"https://www.forbes.com/profile/elon-musk\")"
#122	]
#123	},
#124	{
#125	"cell_type": "markdown",
#126	"metadata": {
#127	"id": "_7W6fDeAjMAP"
#128	},
#129	"source": [
#130	"### Step-5: All set. Now start asking questions related to your data"
#131	]
#132	},
#133	{
#134	"cell_type": "code",
#135	"execution_count": null,
#136	"metadata": {
#137	"colab": {
#138	"base_uri": "https://localhost:8080/",
#139	"height": 480
#140	},
#141	"id": "cvIK7dWRjN_f",
#142	"outputId": "c74f356a-d2fb-426d-b36c-d84911397338"
#143	},
#144	"outputs": [],
#145	"source": [
#146	"while(True):\n",
#147	" question = input(\"Enter question: \")\n",
#148	" if question in ['q', 'exit', 'quit']:\n",
#149	" break\n",
#150	" answer = app.query(question)\n",
#151	" print(answer)"
#152	]
#153	}
#154	],
#155	"metadata": {
#156	"colab": {
#157	"provenance": []
#158	},
#159	"kernelspec": {
#160	"display_name": "Python 3",
#161	"name": "python3"
#162	},
#163	"language_info": {
#164	"name": "python"
#165	}
#166	},
#167	"nbformat": 4,
#168	"nbformat_minor": 0
#169	}
#170

z6Mkq5mY3JWtxoxUobWcfNHm7AkRubgSWEZTkBVqZXJviFZ5/my-project-public