src/apps/utils/retriever.py

import os
os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"  # Temporary fix
os.environ["FAISS_NO_OPENMP"] = "1"  # Prevent FAISS from using OpenMP

import faiss
from numpy.linalg import norm

BASE_DIR = os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
def get_path(folder, filename):
    # Try the standard 'volumes/' path
    path1 = os.path.join(BASE_DIR, "volumes", folder, filename)
    if os.path.exists(path1):
        return path1
    # Try the root-level path
    path2 = os.path.join(BASE_DIR, folder, filename)
    if os.path.exists(path2):
        return path2
    return path1

index_path = get_path("indexes", "law_corpus_index2.bin")

if not os.path.exists(index_path):
    print(f"⚠️ ERROR: Index file not found at {index_path}")
    # Fail gracefully or provide a placeholder for the index if needed
    # (Leaving it to crash on faiss.read_index if it truly doesn't exist)
    pass

index = faiss.read_index(index_path)
print("Index loaded successfully!")
print("Number of vectors in the index:", index.ntotal)

def vector_db_retriever(query_embeddings, top_k=10):
    query_embeddings = query_embeddings / norm(query_embeddings[0])
    distances, indices = index.search(query_embeddings, top_k)
    return indices, distances