def query_and_result()

in evaluation_pipeline/retrieval.py [0:0]

• 7 lines of code
• 2 McCabe index (conditional complexity)

def query_and_result(fe, query, db, model_name, threshold, k):
    model_name_normalized = model_name.replace("/","_").replace("-","_").replace(".","_") 
    if model_name == 'nomic-ai/nomic-embed-text-v1.5':
        query = 'search_query: ' + query
   
    query_embedding = fe.get_embeddings([query])[0]
    # using cosine distance
    rows = db.execute(
    f"""