forked from phoenix-oss/llama-stack-mirror
34ab7a3b6c
Lint check in main branch is failing. This fixes the lint check after we moved to ruff in https://github.com/meta-llama/llama-stack/pull/921. We need to move to a `ruff.toml` file as well as fixing and ignoring some additional checks. Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
77 lines
2.9 KiB
Python
77 lines
2.9 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import random
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import pytest
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@pytest.fixture(scope="function")
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def empty_vector_db_registry(llama_stack_client):
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vector_dbs = [vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()]
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for vector_db_id in vector_dbs:
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llama_stack_client.vector_dbs.unregister(vector_db_id=vector_db_id)
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@pytest.fixture(scope="function")
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def single_entry_vector_db_registry(llama_stack_client, empty_vector_db_registry):
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vector_db_id = f"test_vector_db_{random.randint(1000, 9999)}"
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llama_stack_client.vector_dbs.register(
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vector_db_id=vector_db_id,
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embedding_model="all-MiniLM-L6-v2",
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embedding_dimension=384,
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provider_id="faiss",
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)
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vector_dbs = [vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()]
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return vector_dbs
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def test_vector_db_retrieve(llama_stack_client, embedding_model, empty_vector_db_registry):
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# Register a memory bank first
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vector_db_id = f"test_vector_db_{random.randint(1000, 9999)}"
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llama_stack_client.vector_dbs.register(
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vector_db_id=vector_db_id,
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embedding_model=embedding_model,
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embedding_dimension=384,
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provider_id="faiss",
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)
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# Retrieve the memory bank and validate its properties
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response = llama_stack_client.vector_dbs.retrieve(vector_db_id=vector_db_id)
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assert response is not None
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assert response.identifier == vector_db_id
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assert response.embedding_model == embedding_model
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assert response.provider_id == "faiss"
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assert response.provider_resource_id == vector_db_id
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def test_vector_db_list(llama_stack_client, empty_vector_db_registry):
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vector_dbs_after_register = [vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()]
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assert len(vector_dbs_after_register) == 0
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def test_vector_db_register(llama_stack_client, embedding_model, empty_vector_db_registry):
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vector_db_id = f"test_vector_db_{random.randint(1000, 9999)}"
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llama_stack_client.vector_dbs.register(
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vector_db_id=vector_db_id,
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embedding_model=embedding_model,
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embedding_dimension=384,
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provider_id="faiss",
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)
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vector_dbs_after_register = [vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()]
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assert vector_dbs_after_register == [vector_db_id]
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def test_vector_db_unregister(llama_stack_client, single_entry_vector_db_registry):
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vector_dbs = [vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()]
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assert len(vector_dbs) == 1
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vector_db_id = vector_dbs[0]
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llama_stack_client.vector_dbs.unregister(vector_db_id=vector_db_id)
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vector_dbs = [vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()]
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assert len(vector_dbs) == 0
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