Update README.md

README.md

@@ -35,7 +35,68 @@ Each record in the dataset represents a news article about technology companies
 - embedding: An array of numerical values representing the vector embedding for the article, generated using the OpenAI EMBEDDING_MODEL.
 
 
-## Data Ingestion
+## Data Ingestion (Partioned)
+
+```python
+
+import os
+import requests
+import pandas as pd
+from io import BytesIO
+from pymongo import MongoClient
+
+# MongoDB Atlas URI and client setup
+uri = os.environ.get('MONGODB_ATLAS_URI')
+
+client = MongoClient(uri)
+
+# Change to the appropriate database and collection names for the tech news embeddings
+db_name = 'your_database_name'  # Change this to your actual database name
+collection_name = 'tech_news_embeddings'  # Change this to your actual collection name
+tech_news_embeddings_collection = client[db_name][collection_name]
+
+hf_token = os.environ.get('HF_TOKEN')
+headers = {
+    "Authorization": f"Bearer {hf_token}"
+}
+
+# Downloads 228012 data points
+parquet_files = [
+    "https://huggingface.co/api/datasets/AIatMongoDB/tech-news-embeddings/parquet/default/train/0000.parquet",
+    "https://huggingface.co/api/datasets/AIatMongoDB/tech-news-embeddings/parquet/default/train/0001.parquet",
+    "https://huggingface.co/api/datasets/AIatMongoDB/tech-news-embeddings/parquet/default/train/0002.parquet",
+    "https://huggingface.co/api/datasets/AIatMongoDB/tech-news-embeddings/parquet/default/train/0003.parquet",
+    "https://huggingface.co/api/datasets/AIatMongoDB/tech-news-embeddings/parquet/default/train/0004.parquet",
+    "https://huggingface.co/api/datasets/AIatMongoDB/tech-news-embeddings/parquet/default/train/0005.parquet",
+]
+
+all_dataframes = []
+combined_df = None
+
+for parquet_file_url in parquet_files:
+    response = requests.get(parquet_file_url, headers=headers)
+    if response.status_code == 200:
+
+        parquet_bytes = BytesIO(response.content)
+        df = pd.read_parquet(parquet_bytes)
+        all_dataframes.append(df)
+    else:
+        print(f"Failed to download Parquet file from {parquet_file_url}: {response.status_code}")
+
+if all_dataframes:
+    combined_df = pd.concat(all_dataframes, ignore_index=True)
+else:
+    print("No dataframes to concatenate.")
+
+
+# Ingest to database
+dataset_records = combined_df.to_dict('records')
+tech_news_embeddings_collection.insert_many(dataset_records)
+
+```
+
+
+## Data Ingestion (All Records)
 [Create a free 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=richmond.alake)
 
 ```python