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https://github.com/meta-llama/llama-stack.git
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ef684ff178
When called via the OpenAI API, ollama is responding with more brief responses than when called via its native API. This adjusts the prompting for its OpenAI calls to ask it to be more verbose.
87 lines
2.8 KiB
Python
87 lines
2.8 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 pytest
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from openai import OpenAI
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from llama_stack.distribution.library_client import LlamaStackAsLibraryClient
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from ..test_cases.test_case import TestCase
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def skip_if_model_doesnt_support_openai_completion(client_with_models, model_id):
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if isinstance(client_with_models, LlamaStackAsLibraryClient):
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pytest.skip("OpenAI completions are not supported when testing with library client yet.")
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models = {m.identifier: m for m in client_with_models.models.list()}
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models.update({m.provider_resource_id: m for m in client_with_models.models.list()})
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provider_id = models[model_id].provider_id
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providers = {p.provider_id: p for p in client_with_models.providers.list()}
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provider = providers[provider_id]
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if provider.provider_type in (
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"inline::meta-reference",
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"inline::sentence-transformers",
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"inline::vllm",
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"remote::bedrock",
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"remote::cerebras",
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"remote::databricks",
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"remote::nvidia",
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"remote::runpod",
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"remote::sambanova",
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"remote::tgi",
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):
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pytest.skip(f"Model {model_id} hosted by {provider.provider_type} doesn't support OpenAI completions.")
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@pytest.fixture
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def openai_client(client_with_models, text_model_id):
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skip_if_model_doesnt_support_openai_completion(client_with_models, text_model_id)
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base_url = f"{client_with_models.base_url}/v1/openai/v1"
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return OpenAI(base_url=base_url, api_key="bar")
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@pytest.mark.parametrize(
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"test_case",
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[
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"inference:completion:sanity",
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],
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)
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def test_openai_completion_non_streaming(openai_client, text_model_id, test_case):
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tc = TestCase(test_case)
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# ollama needs more verbose prompting for some reason here...
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prompt = "Respond to this question and explain your answer. " + tc["content"]
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response = openai_client.completions.create(
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model=text_model_id,
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prompt=prompt,
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stream=False,
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)
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assert len(response.choices) > 0
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choice = response.choices[0]
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assert len(choice.text) > 10
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@pytest.mark.parametrize(
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"test_case",
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[
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"inference:completion:sanity",
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],
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)
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def test_openai_completion_streaming(openai_client, text_model_id, test_case):
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tc = TestCase(test_case)
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# ollama needs more verbose prompting for some reason here...
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prompt = "Respond to this question and explain your answer. " + tc["content"]
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response = openai_client.completions.create(
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model=text_model_id,
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prompt=prompt,
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stream=True,
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max_tokens=50,
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)
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streamed_content = [chunk.choices[0].text for chunk in response]
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content_str = "".join(streamed_content).lower().strip()
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assert len(content_str) > 10
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