mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
103 lines
2.1 KiB
Plaintext
103 lines
2.1 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "raw",
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"id": "67db2992",
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"metadata": {},
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"source": [
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"---\n",
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"sidebar_label: __ModuleName__\n",
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"---"
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]
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},
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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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"# __ModuleName__LLM\n",
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"\n",
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"This example goes over how to use LangChain to interact with `__ModuleName__` models.\n",
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"\n",
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"## Installation"
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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": "59c710c4",
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"metadata": {},
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"outputs": [],
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"source": [
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"# install package\n",
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"!pip install -U __package_name__"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0ee90032",
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"metadata": {},
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"source": [
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"## Environment Setup\n",
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"\n",
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"Make sure to set the following environment variables:\n",
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"\n",
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"- TODO: fill out relevant environment variables or secrets\n",
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"\n",
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"## Usage"
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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": 4,
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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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"from langchain_core.prompts import PromptTemplate\n",
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"from __module_name__.llms import __ModuleName__LLM\n",
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"\n",
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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.from_string(template)\n",
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"\n",
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"model = __ModuleName__LLM()\n",
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"\n",
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"chain = prompt | model\n",
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"\n",
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"chain.invoke({\"question\": \"What is LangChain?\"})"
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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 3.11.1 64-bit",
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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": "3.9.7"
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},
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"vscode": {
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"interpreter": {
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"hash": "e971737741ff4ec9aff7dc6155a1060a59a8a6d52c757dbbe66bf8ee389494b1"
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}
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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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