mirror of
https://github.com/hwchase17/langchain
synced 2024-11-06 03:20:49 +00:00
5420a0e404
- Updated `langchain/docs/modules/models/llms/integrations/` notebooks: added links to the original sites, the install information, etc. - Added the `nlpcloud` notebook. - Removed "Example" from Titles of some notebooks, so all notebook titles are consistent.
160 lines
3.2 KiB
Plaintext
160 lines
3.2 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "9597802c",
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"metadata": {},
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"source": [
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"# AI21\n",
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"\n",
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"[AI21 Studio](https://docs.ai21.com/) provides API access to `Jurassic-2` large language models.\n",
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"\n",
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"This example goes over how to use LangChain to interact with [AI21 models](https://docs.ai21.com/docs/jurassic-2-models)."
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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": "02be122d-04e8-4ec6-84d1-f1d8961d6828",
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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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"# install the package:\n",
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"!pip install ai21"
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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": "4229227e-6ca2-41ad-a3c3-5f29e3559091",
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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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"# get AI21_API_KEY. Use https://studio.ai21.com/account/account\n",
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"\n",
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"from getpass import getpass\n",
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"AI21_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": 8,
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"id": "6fb585dd",
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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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"from langchain.llms import AI21\n",
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"from langchain import PromptTemplate, LLMChain"
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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": "035dea0f",
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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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"template = \"\"\"Question: {question}\n",
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"\n",
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"Answer: Let's think step by step.\"\"\"\n",
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"\n",
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"prompt = PromptTemplate(template=template, input_variables=[\"question\"])"
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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": 10,
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"id": "3f3458d9",
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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 = AI21(ai21_api_key=AI21_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": 11,
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"id": "a641dbd9",
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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_chain = LLMChain(prompt=prompt, llm=llm)"
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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": 12,
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"id": "9f0b1960",
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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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"data": {
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"text/plain": [
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"'\\n1. What year was Justin Bieber born?\\nJustin Bieber was born in 1994.\\n2. What team won the Super Bowl in 1994?\\nThe Dallas Cowboys won the Super Bowl in 1994.'"
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]
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},
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"execution_count": 12,
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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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"question = \"What NFL team won the Super Bowl in the year Justin Beiber was born?\"\n",
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"\n",
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"llm_chain.run(question)"
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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": "22bce013",
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"metadata": {},
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"outputs": [],
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"source": []
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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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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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