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from dotenv import load_dotenv
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
def create_db(dataset_path: str, json_filepath: str) -> DeepLake:
with open(json_filepath, "r") as f:
data = json.load(f)
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"],
}
)
embeddings = OpenAIEmbeddings(model=MODEL_ID)
db = DeepLake.from_texts(
texts, embeddings, metadatas=metadatas, dataset_path=dataset_path
)
return db
def load_db(dataset_path: str, *args, **kwargs) -> DeepLake:
db = DeepLake(dataset_path, *args, **kwargs)
return db
if __name__ == "__main__":
dataset_path = f"hub://{os.environ['ACTIVELOOP_ORG_ID']}/{DATASET_ID}"
create_db(dataset_path, "data/lyrics_with_spotify_url.json")
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