mirror of
https://github.com/hwchase17/langchain.git
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docs: remove docs that disable ssl verification (#31254)
Remove examples that disable ssl verification
This commit is contained in:
Eugene Yurtsev
GitHub
parent
12b063eb67
commit
c178ad87b6
@ -1,117 +0,0 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"# GigaChat\n",
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"This notebook shows how to use LangChain with [GigaChat](https://developers.sber.ru/portal/products/gigachat).\n",
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"To use you need to install ```langchain_gigachat``` python package."
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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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"metadata": {
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"collapsed": true,
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"pycharm": {
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"is_executing": true
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}
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},
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"outputs": [],
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"source": [
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"%pip install --upgrade --quiet langchain-gigachat"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"To get GigaChat credentials you need to [create account](https://developers.sber.ru/studio/login) and [get access to API](https://developers.sber.ru/docs/ru/gigachat/individuals-quickstart)\n",
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"\n",
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"## Example"
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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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"metadata": {
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"collapsed": false
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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 getpass import getpass\n",
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"\n",
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"if \"GIGACHAT_CREDENTIALS\" not in os.environ:\n",
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" os.environ[\"GIGACHAT_CREDENTIALS\"] = 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": 5,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"from langchain_gigachat import GigaChat\n",
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"\n",
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"chat = GigaChat(verify_ssl_certs=False, scope=\"GIGACHAT_API_PERS\")"
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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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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The capital of Russia is Moscow.\n"
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]
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}
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],
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"source": [
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"from langchain_core.messages import HumanMessage, SystemMessage\n",
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"\n",
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"messages = [\n",
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" SystemMessage(\n",
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" content=\"You are a helpful AI that shares everything you know. Talk in English.\"\n",
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" ),\n",
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" HumanMessage(content=\"What is capital of Russia?\"),\n",
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"]\n",
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"\n",
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"print(chat.invoke(messages).content)"
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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",
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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": 2
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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": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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@ -1,118 +0,0 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"# GigaChat\n",
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"This notebook shows how to use LangChain with [GigaChat](https://developers.sber.ru/portal/products/gigachat).\n",
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"To use you need to install ```gigachat``` python package."
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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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"metadata": {
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"collapsed": true,
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"pycharm": {
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"is_executing": true
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}
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},
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"outputs": [],
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"source": [
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"%pip install --upgrade --quiet gigachat"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"To get GigaChat credentials you need to [create account](https://developers.sber.ru/studio/login) and [get access to API](https://developers.sber.ru/docs/ru/gigachat/individuals-quickstart)\n",
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"\n",
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"## Example"
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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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"metadata": {
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"collapsed": false
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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 getpass import getpass\n",
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"\n",
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"if \"GIGACHAT_CREDENTIALS\" not in os.environ:\n",
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" os.environ[\"GIGACHAT_CREDENTIALS\"] = 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": 3,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"from langchain_community.llms import GigaChat\n",
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"\n",
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"llm = GigaChat(verify_ssl_certs=False, scope=\"GIGACHAT_API_PERS\")"
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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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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The capital of Russia is Moscow.\n"
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]
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}
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],
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"source": [
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"from langchain.chains import LLMChain\n",
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"from langchain_core.prompts import PromptTemplate\n",
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"\n",
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"template = \"What is capital of {country}?\"\n",
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"\n",
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"prompt = PromptTemplate.from_template(template)\n",
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"\n",
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"llm_chain = LLMChain(prompt=prompt, llm=llm)\n",
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"\n",
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"generated = llm_chain.invoke(input={\"country\": \"Russia\"})\n",
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"print(generated[\"text\"])"
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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",
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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": 2
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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": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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@ -1,37 +0,0 @@
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# Salute Devices
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Salute Devices provides GigaChat LLM's models.
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For more info how to get access to GigaChat [follow here](https://developers.sber.ru/docs/ru/gigachat/api/integration).
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## Installation and Setup
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GigaChat package can be installed via pip from PyPI:
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```bash
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pip install langchain-gigachat
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```
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## LLMs
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See a [usage example](/docs/integrations/llms/gigachat).
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```python
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from langchain_community.llms import GigaChat
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```
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## Chat models
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See a [usage example](/docs/integrations/chat/gigachat).
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```python
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from langchain_gigachat.chat_models import GigaChat
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```
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## Embeddings
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See a [usage example](/docs/integrations/text_embedding/gigachat).
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```python
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from langchain_gigachat.embeddings import GigaChatEmbeddings
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```
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@ -1,120 +0,0 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"# GigaChat\n",
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"This notebook shows how to use LangChain with [GigaChat embeddings](https://developers.sber.ru/portal/products/gigachat).\n",
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"To use you need to install ```gigachat``` python package."
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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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"metadata": {
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"collapsed": false,
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"pycharm": {
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"is_executing": true
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}
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},
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"outputs": [],
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"source": [
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"%pip install --upgrade --quiet langchain-gigachat"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"To get GigaChat credentials you need to [create account](https://developers.sber.ru/studio/login) and [get access to API](https://developers.sber.ru/docs/ru/gigachat/individuals-quickstart)\n",
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"\n",
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"## Example"
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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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"metadata": {
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"collapsed": true
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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 getpass import getpass\n",
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"\n",
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"if \"GIGACHAT_CREDENTIALS\" not in os.environ:\n",
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" os.environ[\"GIGACHAT_CREDENTIALS\"] = 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": 3,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"from langchain_gigachat import GigaChatEmbeddings\n",
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"\n",
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"embeddings = GigaChatEmbeddings(verify_ssl_certs=False, scope=\"GIGACHAT_API_PERS\")"
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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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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"query_result = embeddings.embed_query(\"The quick brown fox jumps over the lazy dog\")"
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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": 8,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": "[0.8398333191871643,\n -0.14180311560630798,\n -0.6161925792694092,\n -0.17103666067123413,\n 1.2884578704833984]"
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"query_result[:5]"
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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",
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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": 2
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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": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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