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74b76f3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | import sys
sys.path.append(r'D:\Storage\rag_project\src')
from langchain_huggingface import HuggingFaceEmbeddings
from langchain_community.vectorstores import FAISS
from test_single_file_loader import test_single_file
def test_faiss_single(filename):
print(f"\n FAISS TEST: {filename}")
docs = test_single_file(filename)
embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
vectorstore = FAISS.from_documents(docs, embeddings)
print(f" FAISS index created: {len(docs)} vectors")
# Test retrieve
retriever = vectorstore.as_retriever(search_kwargs={"k": 3})
query = "tuần hoàn" if "NHIKHOA" in filename else "đột tử"
results = retriever.get_relevant_documents(query)
print(f" Query '{query}' → Found {len(results)} docs:")
for i, doc in enumerate(results):
print(f" {i+1}. {doc.metadata['chunk_title']}")
print(" FAISS OK!")
if __name__ == "__main__":
test_faiss_single("NHIKHOA2.json")
test_faiss_single("PHACDODIEUTRI_2016.json")
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