#!/usr/bin/env python
"""Quick test of retriever with re-ranking."""

from components.vector_store import VectorStore
from components.embedder import HuggingFaceEmbedder
from components.retriever import Retriever
from app.config import VECTOR_DB_PATH

# Create embedder and vector store
embedder = HuggingFaceEmbedder()
vs = VectorStore(embedder=embedder, index_path=VECTOR_DB_PATH)
vs.load()

# Create retriever with reranking enabled
retriever = Retriever(vs, use_reranker=True)

# Test query
query = 'Tell me about the culture'
results = retriever.retrieve(query)

print(f'\n🔍 Query: "{query}"')
print(f'📊 Retrieved {len(results)} chunks (with cross-encoder re-ranking)\n')

for i, (doc, score) in enumerate(results, 1):
    topic = doc.metadata.get('topic', 'untagged')
    source = doc.metadata.get('source', 'unknown')
    preview = doc.page_content[:80].replace('\n', ' ')
    print(f'{i}. [{topic:12}] Score: {score:.3f}')
    print(f'   Source: {source}')
    print(f'   Preview: {preview}...\n')

print("\n✅ Re-ranking test complete!")