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d23607483f
# What does this PR do? update Groq inference provider to use OpenAIMixin for openai-compat endpoints changes on api.groq.com - - json_schema is now supported for specific models, see https://console.groq.com/docs/structured-outputs#supported-models - response_format with streaming is now supported for models that support response_format - groq no longer returns a 400 error if tools are provided and tool_choice is not "required" ## Test Plan ``` $ GROQ_API_KEY=... uv run llama stack build --image-type venv --providers inference=remote::groq --run ... $ LLAMA_STACK_CONFIG=http://localhost:8321 uv run --group test pytest -v -ra --text-model groq/llama-3.3-70b-versatile tests/integration/inference/test_openai_completion.py -k 'not store' ... SKIPPED [3] tests/integration/inference/test_openai_completion.py:44: Model groq/llama-3.3-70b-versatile hosted by remote::groq doesn't support OpenAI completions. SKIPPED [3] tests/integration/inference/test_openai_completion.py:94: Model groq/llama-3.3-70b-versatile hosted by remote::groq doesn't support vllm extra_body parameters. SKIPPED [4] tests/integration/inference/test_openai_completion.py:73: Model groq/llama-3.3-70b-versatile hosted by remote::groq doesn't support n param. SKIPPED [1] tests/integration/inference/test_openai_completion.py💯 Model groq/llama-3.3-70b-versatile hosted by remote::groq doesn't support chat completion calls with base64 encoded files. ======================= 8 passed, 11 skipped, 8 deselected, 2 warnings in 5.13s ======================== ``` --------- Co-authored-by: raghotham <rsm@meta.com>
89 lines
3.9 KiB
Python
89 lines
3.9 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 json
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from unittest.mock import MagicMock
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from llama_stack.core.request_headers import request_provider_data_context
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from llama_stack.providers.remote.inference.groq.config import GroqConfig
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from llama_stack.providers.remote.inference.groq.groq import GroqInferenceAdapter
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from llama_stack.providers.remote.inference.llama_openai_compat.config import LlamaCompatConfig
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from llama_stack.providers.remote.inference.llama_openai_compat.llama import LlamaCompatInferenceAdapter
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from llama_stack.providers.remote.inference.openai.config import OpenAIConfig
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from llama_stack.providers.remote.inference.openai.openai import OpenAIInferenceAdapter
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from llama_stack.providers.remote.inference.together.config import TogetherImplConfig
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from llama_stack.providers.remote.inference.together.together import TogetherInferenceAdapter
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def test_groq_provider_openai_client_caching():
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"""Ensure the Groq provider does not cache api keys across client requests"""
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config = GroqConfig()
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inference_adapter = GroqInferenceAdapter(config)
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inference_adapter.__provider_spec__ = MagicMock()
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inference_adapter.__provider_spec__.provider_data_validator = (
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"llama_stack.providers.remote.inference.groq.config.GroqProviderDataValidator"
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)
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for api_key in ["test1", "test2"]:
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with request_provider_data_context(
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{"x-llamastack-provider-data": json.dumps({inference_adapter.provider_data_api_key_field: api_key})}
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):
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assert inference_adapter.client.api_key == api_key
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def test_openai_provider_openai_client_caching():
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"""Ensure the OpenAI provider does not cache api keys across client requests"""
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config = OpenAIConfig()
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inference_adapter = OpenAIInferenceAdapter(config)
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inference_adapter.__provider_spec__ = MagicMock()
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inference_adapter.__provider_spec__.provider_data_validator = (
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"llama_stack.providers.remote.inference.openai.config.OpenAIProviderDataValidator"
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)
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for api_key in ["test1", "test2"]:
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with request_provider_data_context(
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{"x-llamastack-provider-data": json.dumps({inference_adapter.provider_data_api_key_field: api_key})}
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):
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openai_client = inference_adapter.client
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assert openai_client.api_key == api_key
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def test_together_provider_openai_client_caching():
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"""Ensure the Together provider does not cache api keys across client requests"""
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config = TogetherImplConfig()
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inference_adapter = TogetherInferenceAdapter(config)
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inference_adapter.__provider_spec__ = MagicMock()
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inference_adapter.__provider_spec__.provider_data_validator = (
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"llama_stack.providers.remote.inference.together.TogetherProviderDataValidator"
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)
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for api_key in ["test1", "test2"]:
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with request_provider_data_context({"x-llamastack-provider-data": json.dumps({"together_api_key": api_key})}):
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together_client = inference_adapter._get_client()
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assert together_client.client.api_key == api_key
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openai_client = inference_adapter._get_openai_client()
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assert openai_client.api_key == api_key
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def test_llama_compat_provider_openai_client_caching():
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"""Ensure the LlamaCompat provider does not cache api keys across client requests"""
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config = LlamaCompatConfig()
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inference_adapter = LlamaCompatInferenceAdapter(config)
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inference_adapter.__provider_spec__ = MagicMock()
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inference_adapter.__provider_spec__.provider_data_validator = (
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"llama_stack.providers.remote.inference.llama_openai_compat.config.LlamaProviderDataValidator"
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)
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for api_key in ["test1", "test2"]:
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with request_provider_data_context({"x-llamastack-provider-data": json.dumps({"llama_api_key": api_key})}):
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assert inference_adapter.client.api_key == api_key
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