mirror of
https://github.com/hwchase17/langchain.git
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168 lines
3.6 KiB
Plaintext
168 lines
3.6 KiB
Plaintext
{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {
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"id": "vm8vn9t8DvC_"
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},
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"source": [
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"# MongoDB"
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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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"source": [
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"[MongoDB](https://www.mongodb.com/) is a NoSQL , document-oriented database that supports JSON-like documents with a dynamic schema."
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {
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"id": "5WjXERXzFEhg"
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},
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"source": [
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"## Overview"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {
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"id": "juAmbgoWD17u"
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},
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"source": [
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"The MongoDB Document Loader returns a list of Langchain Documents from a MongoDB database.\n",
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"\n",
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"The Loader requires the following parameters:\n",
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"\n",
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"* MongoDB connection string\n",
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"* MongoDB database name\n",
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"* MongoDB collection name\n",
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"* (Optional) Content Filter dictionary\n",
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"* (Optional) List of field names to include in the output\n",
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"\n",
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"The output takes the following format:\n",
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"\n",
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"- pageContent= Mongo Document\n",
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"- metadata=\\{'database': '[database_name]', 'collection': '[collection_name]'\\}"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Load the Document Loader"
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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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"outputs": [],
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"source": [
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"# add this import for running in jupyter notebook\n",
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"import nest_asyncio\n",
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"\n",
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"nest_asyncio.apply()"
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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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"outputs": [],
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"source": [
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"from langchain_community.document_loaders.mongodb import MongodbLoader"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"loader = MongodbLoader(\n",
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" connection_string=\"mongodb://localhost:27017/\",\n",
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" db_name=\"sample_restaurants\",\n",
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" collection_name=\"restaurants\",\n",
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" filter_criteria={\"borough\": \"Bronx\", \"cuisine\": \"Bakery\"},\n",
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" field_names=[\"name\", \"address\"],\n",
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")"
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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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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"71"
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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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"docs = loader.load()\n",
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"\n",
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"len(docs)"
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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": 13,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Document(page_content=\"Morris Park Bake Shop {'building': '1007', 'coord': [-73.856077, 40.848447], 'street': 'Morris Park Ave', 'zipcode': '10462'}\", metadata={'database': 'sample_restaurants', 'collection': 'restaurants'})"
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]
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},
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"execution_count": 13,
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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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"docs[0]"
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]
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}
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],
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"metadata": {
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"colab": {
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"collapsed_sections": [
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"5WjXERXzFEhg"
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],
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"provenance": []
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},
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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": "3.9.18"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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