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README.md
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license: cc-by-3.0
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---
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license: cc-by-3.0
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---
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## Overview
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This dataset consists of ~600 articles from the MongoDB Developer Center.
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## Dataset Structure
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The dataset consists of the following fields:
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- sourceName: The source of the article. This value is `devcenter` for the entire dataset.
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- url: Link to the article
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- action: Action taken on the article. This value is `created` for the entire dataset.
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- body: Content of the article in Markdown format
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- format: Format of the content. This value is `md` for all articles.
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- metadata: Metadata such as tags, content type etc. associated with the articles
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- title: Title of the article
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- updated: The last updated date of the article
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## Usage
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This dataset can be useful for prototyping RAG applications. This is a real sample of data we have used to build the MongoDB Documentation Chatbot.
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## Ingest Data
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To experiment with this dataset using MongoDB Atlas, first [create a MongoDB Atlas account](https://www.mongodb.com/cloud/atlas/register?utm_campaign=devrel&utm_source=community&utm_medium=organic_social&utm_content=Hugging%20Face%20Dataset&utm_term=apoorva.joshi).
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You can then use the following script to load this dataset into your MongoDB Atlas cluster:
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```
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import os
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from pymongo import MongoClient
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import datasets
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from datasets import load_dataset
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from bson import json_util
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uri = os.environ.get('MONGODB_ATLAS_URI')
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client = MongoClient(uri)
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db_name = 'your_database_name' # Change this to your actual database name
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collection_name = 'devcenter_articles'
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product_collection = client[db_name][collection_name]
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dataset = load_dataset("MongoDB/devcenter-articles")
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insert_data = []
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for product in dataset['train']:
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doc_product = json_util.loads(json_util.dumps(product))
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insert_data.append(doc_product)
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if len(insert_data) == 1000:
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product_collection.insert_many(insert_data)
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print("1000 records ingested")
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insert_data = []
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if len(insert_data) > 0:
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product_collection.insert_many(insert_data)
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insert_data = []
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print("Data ingested successfully!")
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```
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