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b/tests/integration/recordings/responses/d0ac68cbde69.json index 78784e0ca..4dcc6a69b 100644 --- a/tests/integration/recordings/responses/d0ac68cbde69.json +++ b/tests/integration/recordings/responses/d0ac68cbde69.json @@ -13,12 +13,12 @@ "__data__": { "models": [ { - "model": "llama3.2:3b", - "name": "llama3.2:3b", - "digest": "a80c4f17acd55265feec403c7aef86be0c25983ab279d83f3bcd3abbcb5b8b72", - "expires_at": "2025-09-27T11:54:56.718552-07:00", - "size": 3367856128, - "size_vram": 3367856128, + "model": "llama3.2:3b-instruct-fp16", + "name": "llama3.2:3b-instruct-fp16", + "digest": "195a8c01d91ec3cb1e0aad4624a51f2602c51fa7d96110f8ab5a20c84081804d", + "expires_at": "2025-09-30T14:29:52.682809-07:00", + "size": 8581748736, + "size_vram": 8581748736, "details": { "parent_model": "", "format": "gguf", @@ -27,9 +27,9 @@ "llama" ], "parameter_size": "3.2B", - "quantization_level": "Q4_K_M" + "quantization_level": "F16" }, - "context_length": 4096 + "context_length": null } ] } diff --git a/tests/integration/recordings/responses/models-7d9446738fd7-d5d684a3.json b/tests/integration/recordings/responses/models-7d9446738fd7-d5d684a3.json index a76f0ba8f..d9917b2ec 100644 --- a/tests/integration/recordings/responses/models-7d9446738fd7-d5d684a3.json +++ b/tests/integration/recordings/responses/models-7d9446738fd7-d5d684a3.json @@ -22,19 +22,6 @@ "supports_tools": false } }, - { - "__type__": "openai.types.model.Model", - "__data__": { - "id": "accounts/tvergho-87e44d/models/debatecards-70b-ft-3epoch-dpo-v2", - "created": 1743381121, - "object": "model", - "owned_by": "tvergho-87e44d", - "kind": "HF_PEFT_ADDON", - "supports_chat": true, - "supports_image_input": false, - "supports_tools": false - } - }, { "__type__": "openai.types.model.Model", "__data__": { @@ -75,20 +62,6 @@ "context_length": 131072 } }, - { - "__type__": "openai.types.model.Model", - "__data__": { - "id": "accounts/fireworks/models/deepseek-v3", - "created": 1735576668, - "object": "model", - "owned_by": 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a/tests/unit/providers/agents/meta_reference/test_openai_responses.py +++ b/tests/unit/providers/agents/meta_reference/test_openai_responses.py @@ -37,7 +37,6 @@ from llama_stack.apis.inference import ( OpenAIJSONSchema, OpenAIResponseFormatJSONObject, OpenAIResponseFormatJSONSchema, - OpenAIResponseFormatText, OpenAIUserMessageParam, ) from llama_stack.apis.tools.tools import Tool, ToolGroups, ToolInvocationResult, ToolParameter, ToolRuntime @@ -148,7 +147,7 @@ async def test_create_openai_response_with_string_input(openai_responses_impl, m mock_inference_api.openai_chat_completion.assert_called_once_with( model=model, messages=[OpenAIUserMessageParam(role="user", content="What is the capital of Ireland?", name=None)], - response_format=OpenAIResponseFormatText(), + response_format=None, tools=None, stream=True, temperature=0.1, @@ -823,16 +822,16 @@ async def test_store_response_uses_rehydrated_input_with_previous_response( @pytest.mark.parametrize( "text_format, response_format", [ - (OpenAIResponseText(format=OpenAIResponseTextFormat(type="text")), OpenAIResponseFormatText()), + (OpenAIResponseText(format=OpenAIResponseTextFormat(type="text")), None), ( OpenAIResponseText(format=OpenAIResponseTextFormat(name="Test", schema={"foo": "bar"}, type="json_schema")), OpenAIResponseFormatJSONSchema(json_schema=OpenAIJSONSchema(name="Test", schema={"foo": "bar"})), ), (OpenAIResponseText(format=OpenAIResponseTextFormat(type="json_object")), OpenAIResponseFormatJSONObject()), - # ensure text param with no format specified defaults to text - (OpenAIResponseText(format=None), OpenAIResponseFormatText()), - # ensure text param of None defaults to text - (None, OpenAIResponseFormatText()), + # ensure text param with no format specified defaults to None + (OpenAIResponseText(format=None), None), + # ensure text param of None defaults to None + (None, None), ], ) async def test_create_openai_response_with_text_format( @@ -855,7 +854,6 @@ async def test_create_openai_response_with_text_format( # Verify first_call = mock_inference_api.openai_chat_completion.call_args_list[0] assert first_call.kwargs["messages"][0].content == input_text - assert first_call.kwargs["response_format"] is not None assert first_call.kwargs["response_format"] == response_format