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feat(tests): make inference_recorder into api_recorder (include tool_invoke)

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This commit is contained in:
Ashwin Bharambe 2025-10-04 11:53:44 -07:00
parent b96640eca3
commit 9205731cd6
19 changed files with 849 additions and 666 deletions
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18
tests/integration/responses/test_tool_responses.py
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@ -46,11 +46,13 @@ def test_response_non_streaming_web_search(compat_client, text_model_id, case):
@pytest.mark.parametrize("case", file_search_test_cases)
def test_response_non_streaming_file_search(compat_client, text_model_id, tmp_path, case):
def test_response_non_streaming_file_search(
compat_client, text_model_id, embedding_model_id, embedding_dimension, tmp_path, case
):
if isinstance(compat_client, LlamaStackAsLibraryClient):
pytest.skip("Responses API file search is not yet supported in library client.")
vector_store = new_vector_store(compat_client, "test_vector_store")
vector_store = new_vector_store(compat_client, "test_vector_store", embedding_model_id, embedding_dimension)
if case.file_content:
file_name = "test_response_non_streaming_file_search.txt"
@ -101,11 +103,13 @@ def test_response_non_streaming_file_search(compat_client, text_model_id, tmp_pa
assert case.expected.lower() in response.output_text.lower().strip()
def test_response_non_streaming_file_search_empty_vector_store(compat_client, text_model_id):
def test_response_non_streaming_file_search_empty_vector_store(
compat_client, text_model_id, embedding_model_id, embedding_dimension
):
if isinstance(compat_client, LlamaStackAsLibraryClient):
pytest.skip("Responses API file search is not yet supported in library client.")
vector_store = new_vector_store(compat_client, "test_vector_store")
vector_store = new_vector_store(compat_client, "test_vector_store", embedding_model_id, embedding_dimension)
# Create the response request, which should query our vector store
response = compat_client.responses.create(
@ -127,12 +131,14 @@ def test_response_non_streaming_file_search_empty_vector_store(compat_client, te
assert response.output_text
def test_response_sequential_file_search(compat_client, text_model_id, tmp_path):
def test_response_sequential_file_search(
compat_client, text_model_id, embedding_model_id, embedding_dimension, tmp_path
):
"""Test file search with sequential responses using previous_response_id."""
if isinstance(compat_client, LlamaStackAsLibraryClient):
pytest.skip("Responses API file search is not yet supported in library client.")
vector_store = new_vector_store(compat_client, "test_vector_store")
vector_store = new_vector_store(compat_client, "test_vector_store", embedding_model_id, embedding_dimension)
# Create a test file with content
file_content = "The Llama 4 Maverick model has 128 experts in its mixture of experts architecture."