This doesn't get Groq to 100% on the OpenAI API verification tests,
but it does get it to 88.2% when Llama Stack is in the middle,
compared to the 61.8% results for using an OpenAI client against Groq
directly.
The groq provider doesn't use litellm under the covers in its
openai_chat_completion endpoint, and instead directly uses an
AsyncOpenAI client with some special handling to improve conformance
of responses for response_format usage and tool calling.
Signed-off-by: Ben Browning <bbrownin@redhat.com>
# What does this PR do?
## Test Plan
export MODEL=accounts/fireworks/models/llama4-scout-instruct-basic;
LLAMA_STACK_CONFIG=verification pytest -s -v tests/integration/inference
--vision-model $MODEL --text-model $MODEL
