langchain/libs/cli/langchain_cli/integration_template/docs/llms.ipynb
2023-12-13 08:55:30 -08:00

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{
"cells": [
{
"cell_type": "raw",
"id": "67db2992",
"metadata": {},
"source": [
"---\n",
"sidebar_label: __ModuleName__\n",
"---"
]
},
{
"cell_type": "markdown",
"id": "9597802c",
"metadata": {},
"source": [
"# __ModuleName__LLM\n",
"\n",
"This example goes over how to use LangChain to interact with `__ModuleName__` models.\n",
"\n",
"## Installation"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "59c710c4",
"metadata": {},
"outputs": [],
"source": [
"# install package\n",
"!pip install -U __package_name__"
]
},
{
"cell_type": "markdown",
"id": "0ee90032",
"metadata": {},
"source": [
"## Environment Setup\n",
"\n",
"Make sure to set the following environment variables:\n",
"\n",
"- TODO: fill out relevant environment variables or secrets\n",
"\n",
"## Usage"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "035dea0f",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"from langchain_core.prompts import PromptTemplate\n",
"from __module_name__.llms import __ModuleName__LLM\n",
"\n",
"template = \"\"\"Question: {question}\n",
"\n",
"Answer: Let's think step by step.\"\"\"\n",
"\n",
"prompt = PromptTemplate.from_string(template)\n",
"\n",
"model = __ModuleName__LLM()\n",
"\n",
"chain = prompt | model\n",
"\n",
"chain.invoke({\"question\": \"What is LangChain?\"})"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.11.1 64-bit",
"language": "python",
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},
"file_extension": ".py",
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"pygments_lexer": "ipython3",
"version": "3.9.7"
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