Pinecone similarity_search Returning Null

Im learning to use Pinecone but i'm encountering an issue while performing a similarity_search operation in Pinecone. Despite successfully creating and populating the index, the search always returns null results. Here's a summary of my setup:

This is the whole code, Thank you in advance.

import os
import time
from dotenv import load_dotenv, find_dotenv
from langchain_community.document_loaders import PDFMinerLoader
from langchain_text_splitters import RecursiveCharacterTextSplitter
from langchain_openai import OpenAIEmbeddings
from pinecone import Pinecone
from langchain_pinecone import PineconeVectorStore
from pinecone import ServerlessSpec
from langchain.chains.question_answering import load_qa_chain
from langchain.chat_models import ChatOpenAI

load_dotenv(find_dotenv(), override=True)

pdf_file_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'pdf_files', 'document_1.pdf')
loader = PDFMinerLoader(pdf_file_path)
document = loader.load()

embedding = OpenAIEmbeddings()

text_splitter = RecursiveCharacterTextSplitter(
    chunk_size = 512,
    chunk_overlap = 100,
    separators=[""])
chunks = text_splitter.split_documents(document)

pc = Pinecone()

index_name = 'tenders-index'

for i in pc.list_indexes().names():
    pc.delete_index(i)
    print('Index deleted')

if index_name not in pc.list_indexes().names():
    print(f'Creating index {index_name}')
    pc.create_index(
        name=index_name,
        dimension=1536,
        metric='cosine',
        spec=ServerlessSpec(
            cloud="aws",
            region="us-east-1"
        )
    )
    print('Index created!')
else:
    print(f'Index {index_name} already exists!')

while not pc.describe_index(index_name).status['ready']:
    time.sleep(1)

vector_store = PineconeVectorStore.from_documents(
    documents= chunks,
    embedding=embedding,
    index_name=index_name
)

query = 'The goal of this document is ...'

vstore = PineconeVectorStore.from_existing_index(index_name=index_name, embedding=embedding)

llm = ChatOpenAI(model='gpt-3.5-turbo')

docs = vstore.similarity_search(query=query, k=3)

chain = load_qa_chain(
    llm = llm,
    chain_type = 'stuff'
)

response = chain.run(input_documents = docs , question = query)

print(response)

print('Done!')

I’ve checked the following:

• Index exists
• Pinecone Index and OpenAIEmbedding have the same dimension
• VectorStore is generated