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Emo_Play / data.py

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	# Import necessary libraries and modules
	from dotenv import load_dotenv
	import json
	import os
	from langchain.embeddings.openai import OpenAIEmbeddings
	from langchain.llms import OpenAI
	from langchain.vectorstores import DeepLake
	from names import DATASET_ID, MODEL_ID

	# Load environment variables
	load_dotenv()

	# Function to create a DeepLake database from a given dataset path and JSON file
	def create_db(dataset_path: str, json_filepath: str) -> DeepLake:
	# Load data from the JSON file
	with open(json_filepath, "r") as f:
	data = json.load(f)

	# Extract texts and metadata from the data
	texts = []
	metadatas = []
	for movie, lyrics in data.items():
	for lyric in lyrics:
	texts.append(lyric["text"])
	metadatas.append(
	{
	"movie": movie,
	"name": lyric["name"],
	"embed_url": lyric["embed_url"],
	}
	)

	# Initialize embeddings using OpenAI
	embeddings = OpenAIEmbeddings(model=MODEL_ID)

	# Create a DeepLake database from the texts and metadata
	db = DeepLake.from_texts(
	texts, embeddings, metadatas=metadatas, dataset_path=dataset_path
	)

	return db

	# Function to load an existing DeepLake database
	def load_db(dataset_path: str, args, *kwargs) -> DeepLake:
	db = DeepLake(dataset_path, args, *kwargs)
	return db

	# If the script is executed directly, create a DeepLake database using the specified dataset path and JSON file
	if __name__ == "__main__":
	dataset_path = f"hub://{os.environ['ACTIVELOOP_ORG_ID']}/{DATASET_ID}"
	create_db(dataset_path, "data/emotions_with_spotify_url.json")