from dotenv import load_dotenv
import os
from src.helper import load_file, filtering, chunking, download_embeddings
from pinecone import Pinecone
from pinecone import ServerlessSpec
from langchain_pinecone import PineconeVectorStore

load_dotenv()

PINECONE_API_KEY = os.getenv("PINECONE_API_KEY")
GROQ_API_KEY = os.getenv("GROQ_API_KEY")

os.environ["PINECONE_API_KEY"] = PINECONE_API_KEY
os.environ["GROQ_API_KEY"] = GROQ_API_KEY

file_path= "./Medical_book.pdf"
data = load_file(file_path)
docs = filtering(data)
chunks = chunking(docs)
embeddings = download_embeddings()

pinecone_api_key = PINECONE_API_KEY
pc = Pinecone(api_key=pinecone_api_key)

index_name = "virtual-doc"
if not pc.has_index(index_name):
    pc.create_index(name=index_name, dimension=384, metric="cosine", spec=ServerlessSpec(cloud="aws", region="us-east-1"))
index = pc.Index(index_name)

docsearch = PineconeVectorStore.from_documents(documents=chunks,embedding=embeddings,index_name=index_name)