Checking the "Load Azure Cosmos DB for NoSQL" topic the last step "Execute a Vector Search with the loaded data" fails because the method "vector_search_words" from file "main_nosql.py" has two bugs. First the method doesn't set the container so the property "_ctrproxy" is never set and fail on "vector_search" method call. also the call for "vector_search" has wrong parameters and build the cosmosdb query wrong.
Here is my fix to the currently problem:
`
async def vector_search_words(natural_language):
try:
ai_svc = AiService()
resp = ai_svc.generate_embeddings(natural_language)
embedding = resp.data[0].embedding
nosql_svc = CosmosNoSQLService()
await nosql_svc.initialize()
cname = "libraries"
nosql_svc.set_container(cname)
docs = await nosql_svc.vector_search(embedding)
for idx, doc in enumerate(docs):
print("doc {}: {}".format(idx, doc))
except Exception as e:
logging.info(str(e))
logging.info(traceback.format_exc())
await nosql_svc.close()`
Checking the "Load Azure Cosmos DB for NoSQL" topic the last step "Execute a Vector Search with the loaded data" fails because the method "vector_search_words" from file "main_nosql.py" has two bugs. First the method doesn't set the container so the property "_ctrproxy" is never set and fail on "vector_search" method call. also the call for "vector_search" has wrong parameters and build the cosmosdb query wrong.
Here is my fix to the currently problem:
`