feat(providers): Groq now uses LiteLLM openai-compat (#1303)

Groq has never supported raw completions anyhow. So this makes it easier
to switch it to LiteLLM. All our test suite passes.

I also updated all the openai-compat providers so they work with api
keys passed from headers. `provider_data`

## Test Plan

```bash
LLAMA_STACK_CONFIG=groq \
   pytest -s -v tests/client-sdk/inference/test_text_inference.py \
   --inference-model=groq/llama-3.3-70b-versatile --vision-inference-model=""
```

Also tested (openai, anthropic, gemini) providers. No regressions.

llama_stack/providers/remote/inference/groq/groq.py

@@ -4,130 +4,26 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import warnings
-from typing import AsyncIterator, List, Optional, Union
-
-import groq
-from groq import Groq
-
-from llama_stack.apis.inference import (
-    ChatCompletionRequest,
-    ChatCompletionResponse,
-    ChatCompletionResponseStreamChunk,
-    CompletionResponse,
-    CompletionResponseStreamChunk,
-    EmbeddingsResponse,
-    EmbeddingTaskType,
-    Inference,
-    InterleavedContent,
-    InterleavedContentItem,
-    LogProbConfig,
-    Message,
-    ResponseFormat,
-    TextTruncation,
-    ToolChoice,
-    ToolConfig,
-)
-from llama_stack.distribution.request_headers import NeedsRequestProviderData
-from llama_stack.models.llama.datatypes import SamplingParams, ToolDefinition, ToolPromptFormat
 from llama_stack.providers.remote.inference.groq.config import GroqConfig
-from llama_stack.providers.utils.inference.model_registry import (
-    ModelRegistryHelper,
-)
+from llama_stack.providers.utils.inference.litellm_openai_mixin import LiteLLMOpenAIMixin
 
-from .groq_utils import (
-    convert_chat_completion_request,
-    convert_chat_completion_response,
-    convert_chat_completion_response_stream,
-)
-from .models import _MODEL_ENTRIES
+from .models import MODEL_ENTRIES
 
 
-class GroqInferenceAdapter(Inference, ModelRegistryHelper, NeedsRequestProviderData):
+class GroqInferenceAdapter(LiteLLMOpenAIMixin):
     _config: GroqConfig
 
     def __init__(self, config: GroqConfig):
-        ModelRegistryHelper.__init__(self, model_entries=_MODEL_ENTRIES)
-        self._config = config
-
-    def completion(
-        self,
-        model_id: str,
-        content: InterleavedContent,
-        sampling_params: Optional[SamplingParams] = SamplingParams(),
-        response_format: Optional[ResponseFormat] = None,
-        stream: Optional[bool] = False,
-        logprobs: Optional[LogProbConfig] = None,
-    ) -> Union[CompletionResponse, AsyncIterator[CompletionResponseStreamChunk]]:
-        # Groq doesn't support non-chat completion as of time of writing
-        raise NotImplementedError()
-
-    async def chat_completion(
-        self,
-        model_id: str,
-        messages: List[Message],
-        sampling_params: Optional[SamplingParams] = SamplingParams(),
-        response_format: Optional[ResponseFormat] = None,
-        tools: Optional[List[ToolDefinition]] = None,
-        tool_choice: Optional[ToolChoice] = ToolChoice.auto,
-        tool_prompt_format: Optional[ToolPromptFormat] = None,
-        stream: Optional[bool] = False,
-        logprobs: Optional[LogProbConfig] = None,
-        tool_config: Optional[ToolConfig] = None,
-    ) -> Union[ChatCompletionResponse, AsyncIterator[ChatCompletionResponseStreamChunk]]:
-        model_id = self.get_provider_model_id(model_id)
-        if model_id == "llama-3.2-3b-preview":
-            warnings.warn(
-                "Groq only contains a preview version for llama-3.2-3b-instruct. "
-                "Preview models aren't recommended for production use. "
-                "They can be discontinued on short notice."
-                "More details: https://console.groq.com/docs/models"
-            )
-
-        request = convert_chat_completion_request(
-            request=ChatCompletionRequest(
-                model=model_id,
-                messages=messages,
-                sampling_params=sampling_params,
-                response_format=response_format,
-                tools=tools,
-                stream=stream,
-                logprobs=logprobs,
-                tool_config=tool_config,
-            )
+        LiteLLMOpenAIMixin.__init__(
+            self,
+            model_entries=MODEL_ENTRIES,
+            api_key_from_config=config.api_key,
+            provider_data_api_key_field="groq_api_key",
         )
+        self.config = config
 
-        try:
-            response = self._get_client().chat.completions.create(**request)
-        except groq.BadRequestError as e:
-            if e.body.get("error", {}).get("code") == "tool_use_failed":
-                # For smaller models, Groq may fail to call a tool even when the request is well formed
-                raise ValueError("Groq failed to call a tool", e.body.get("error", {})) from e
-            else:
-                raise e
+    async def initialize(self):
+        await super().initialize()
 
-        if stream:
-            return convert_chat_completion_response_stream(response)
-        else:
-            return convert_chat_completion_response(response)
-
-    async def embeddings(
-        self,
-        model_id: str,
-        contents: List[str] | List[InterleavedContentItem],
-        text_truncation: Optional[TextTruncation] = TextTruncation.none,
-        output_dimension: Optional[int] = None,
-        task_type: Optional[EmbeddingTaskType] = None,
-    ) -> EmbeddingsResponse:
-        raise NotImplementedError()
-
-    def _get_client(self) -> Groq:
-        if self._config.api_key is not None:
-            return Groq(api_key=self._config.api_key)
-        else:
-            provider_data = self.get_request_provider_data()
-            if provider_data is None or not provider_data.groq_api_key:
-                raise ValueError(
-                    'Pass Groq API Key in the header X-LlamaStack-Provider-Data as { "groq_api_key": "<your api key>" }'
-                )
-            return Groq(api_key=provider_data.groq_api_key)
+    async def shutdown(self):
+        await super().shutdown()