from pathlib import Path

from haystack import Document
from haystack_integrations.components.retrievers.qdrant import QdrantEmbeddingRetriever
from haystack_integrations.document_stores.qdrant import QdrantDocumentStore


document_store = QdrantDocumentStore(
    path="support-qdrant-demo",
    index="support_articles",
    embedding_dim=3,
    similarity="cosine",
    recreate_index=True,
    return_embedding=True,
    progress_bar=False,
)

documents = [
    Document(
        content="Reset passwords through the identity portal.",
        meta={"topic": "accounts"},
        embedding=[0.99, 0.03, 0.01],
    ),
    Document(
        content="Restart the search service after changing the index.",
        meta={"topic": "operations"},
        embedding=[0.02, 0.98, 0.02],
    ),
    Document(
        content="Archive old invoices from the billing dashboard.",
        meta={"topic": "billing"},
        embedding=[0.01, 0.02, 0.99],
    ),
]

written = document_store.write_documents(documents)

retriever = QdrantEmbeddingRetriever(
    document_store=document_store,
    top_k=1,
    return_embedding=True,
)
match = retriever.run(query_embedding=[1.0, 0.0, 0.0])["documents"][0]

print(f"documents written: {written}")
print(f"documents stored: {document_store.count_documents()}")
print(f"top match: {match.content}")
print(f"match topic: {match.meta['topic']}")
print(f"embedding returned: {match.embedding is not None}")
print(f"qdrant path exists: {Path('support-qdrant-demo').is_dir()}")