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 Hugging Face Hub 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	"height": 1000
#28	},
#29	"id": "-NbXjAdlh0vJ",
#30	"outputId": "35ddc904-8067-44cf-dcc9-3c8b4cd29989"
#31	},
#32	"outputs": [],
#33	"source": [
#34	"!pip install embedchain[huggingface_hub,opensource]"
#35	]
#36	},
#37	{
#38	"cell_type": "markdown",
#39	"metadata": {
#40	"id": "nGnpSYAAh2bQ"
#41	},
#42	"source": [
#43	"### Step-2: Set Hugging Face Hub related environment variables\n",
#44	"\n",
#45	"You can find your `HUGGINGFACE_ACCESS_TOKEN` key on your [Hugging Face Hub dashboard](https://huggingface.co/settings/tokens)"
#46	]
#47	},
#48	{
#49	"cell_type": "code",
#50	"execution_count": null,
#51	"metadata": {
#52	"id": "0fBdQ9GAiRvK"
#53	},
#54	"outputs": [],
#55	"source": [
#56	"import os\n",
#57	"from embedchain import App\n",
#58	"\n",
#59	"os.environ[\"HUGGINGFACE_ACCESS_TOKEN\"] = \"hf_xxx\""
#60	]
#61	},
#62	{
#63	"cell_type": "markdown",
#64	"metadata": {
#65	"id": "PGt6uPLIi1CS"
#66	},
#67	"source": [
#68	"### Step-3 Create embedchain app and define your config"
#69	]
#70	},
#71	{
#72	"cell_type": "code",
#73	"execution_count": null,
#74	"metadata": {
#75	"id": "Amzxk3m-i3tD"
#76	},
#77	"outputs": [],
#78	"source": [
#79	"app = App.from_config(config={\n",
#80	" \"llm\": {\n",
#81	" \"provider\": \"huggingface\",\n",
#82	" \"config\": {\n",
#83	" \"model\": \"google/flan-t5-xxl\",\n",
#84	" \"temperature\": 0.5,\n",
#85	" \"max_tokens\": 1000,\n",
#86	" \"top_p\": 0.8,\n",
#87	" \"stream\": False\n",
#88	" }\n",
#89	" },\n",
#90	" \"embedder\": {\n",
#91	" \"provider\": \"huggingface\",\n",
#92	" \"config\": {\n",
#93	" \"model\": \"sentence-transformers/all-mpnet-base-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": 70
#115	},
#116	"id": "Sn_0rx9QjIY9",
#117	"outputId": "3c2a803a-3a93-4b0d-a6ae-17ae3c96c3c2"
#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	},
#140	"id": "cvIK7dWRjN_f",
#141	"outputId": "47a89d1c-b322-495c-822a-6c2ecef894d2"
#142	},
#143	"outputs": [],
#144	"source": [
#145	"while(True):\n",
#146	" question = input(\"Enter question: \")\n",
#147	" if question in ['q', 'exit', 'quit']:\n",
#148	" break\n",
#149	" answer = app.query(question)\n",
#150	" print(answer)"
#151	]
#152	}
#153	],
#154	"metadata": {
#155	"colab": {
#156	"provenance": []
#157	},
#158	"kernelspec": {
#159	"display_name": "Python 3",
#160	"name": "python3"
#161	},
#162	"language_info": {
#163	"name": "python"
#164	}
#165	},
#166	"nbformat": 4,
#167	"nbformat_minor": 0
#168	}
#169

z6Mkq5mY3JWtxoxUobWcfNHm7AkRubgSWEZTkBVqZXJviFZ5/my-project-public