ValueError
langchain.vectorstores.faiss.FaissIndexError
Stack trace
ValueError: Invalid FAISS index format or corrupted index file
File "/usr/local/lib/python3.9/site-packages/langchain/vectorstores/faiss.py", line 123, in load_local
index = faiss.read_index(index_path)
File "faiss/__init__.py", line 456, in read_index
raise ValueError("Invalid FAISS index format or corrupted index file") Why it happens
This error occurs when the FAISS index file is missing, corrupted, or saved in an incompatible format. LangChain expects the index file to be a valid FAISS binary index. If the file is incomplete, overwritten incorrectly, or generated by a different FAISS version, loading fails with this error.
Detection
Check for this error during index loading by wrapping the load call in try/except and verifying the index file exists and is not empty before loading.
Causes & fixes
The FAISS index file path is incorrect or the file does not exist.
Verify the index file path is correct and the file exists before calling load_local.
The FAISS index file is corrupted or partially overwritten.
Rebuild the FAISS index from the original data and save it again to ensure a valid file.
The FAISS index was saved with a different FAISS version incompatible with the current one.
Use the same FAISS version for saving and loading the index, or rebuild the index with the current FAISS version.
Code: broken vs fixed
from langchain.vectorstores import FAISS
# This will raise ValueError if index file is invalid
faiss_index = FAISS.load_local("./faiss_index", embeddings=None) # broken lineimport os
from langchain.vectorstores import FAISS
index_path = "./faiss_index"
if os.path.exists(index_path) and os.path.getsize(index_path) > 0:
faiss_index = FAISS.load_local(index_path, embeddings=None) # fixed: check file exists and not empty
print("FAISS index loaded successfully")
else:
raise FileNotFoundError(f"FAISS index file not found or empty: {index_path}")Workaround
Catch the ValueError on load failure, then rebuild the FAISS index from your original data source and save it again before retrying the load.
Prevention
Implement robust index file management by verifying file integrity after saving and using consistent FAISS versions for saving and loading indexes.