I’m trying to create a program to access Azure AI Search in Python. Last year,
I used the beta version of azure-search-documents, but now I’m having trouble getting it to work properly with the official version.
def retrieve_relevant_documents(emb_deployment: str, search_client: SearchClient, search_query: str) -> str:
response = client.embeddings.create(model=emb_deployment, input=search_query)
query_vector = [
VectorizedQuery(
kind="vector", vector=response.data[0].embedding, k_nearest_neighbors=3, fields="embedding"
)
]
print(query_vector)
results = search_client.search(
search_text="",
vector_queries=[query_vector],
)
results_list = [r for r in results]
contents = [r["filename"] + "-" + r["chunk"] + ": " +
replace_newlines(r["content"]) for r in results_list]
return "\n".join(contents)
When I print “query_vector” returned by “VectorizedQuery()”, it gives the following output.
Could anyone advise me on how to modify this?
[<azure.search.documents._generated.models._models_py3.VectorizedQuery object at 0x7f841f30d4b0>]