import os
import faiss
import numpy as np
from app.core.embedding import embedder
from app.core.config import settings

def load_documents(doc_folder):
    texts = []
    for fname in os.listdir(doc_folder):
        path = os.path.join(doc_folder, fname)
        if os.path.isfile(path):
            with open(path, "r", encoding="utf-8") as f:
                texts.append(f.read())
    return texts

def build_faiss_index(docs, dim):
    vectors = embedder.encode(docs)
    index = faiss.IndexFlatIP(dim)
    index.add(vectors)
    return index

if __name__ == "__main__":
    print("[BUILD] Loading documents...")
    docs = load_documents(settings.DOC_PATH)
    print(f"[BUILD] Loaded {len(docs)} documents")

    print("[BUILD] Building FAISS index...")
    index = build_faiss_index(docs, settings.EMBEDDING_DIM)

    print(f"[BUILD] Saving index to {settings.INDEX_FILE}")
    faiss.write_index(index, settings.INDEX_FILE)