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Add Groq provider - chat completions
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153
llama_stack/providers/remote/inference/groq/groq_utils.py
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153
llama_stack/providers/remote/inference/groq/groq_utils.py
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# 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 warnings
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from typing import AsyncGenerator, Literal
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from groq import Stream
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from groq.types.chat.chat_completion import ChatCompletion
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from groq.types.chat.chat_completion_assistant_message_param import (
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ChatCompletionAssistantMessageParam,
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)
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from groq.types.chat.chat_completion_chunk import ChatCompletionChunk
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from groq.types.chat.chat_completion_message_param import ChatCompletionMessageParam
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from groq.types.chat.chat_completion_system_message_param import (
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ChatCompletionSystemMessageParam,
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)
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from groq.types.chat.chat_completion_user_message_param import (
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ChatCompletionUserMessageParam,
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)
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from groq.types.chat.completion_create_params import CompletionCreateParams
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from llama_stack.apis.inference import (
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ChatCompletionRequest,
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ChatCompletionResponse,
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ChatCompletionResponseEvent,
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ChatCompletionResponseEventType,
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ChatCompletionResponseStreamChunk,
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CompletionMessage,
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Message,
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StopReason,
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)
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def convert_chat_completion_request(
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request: ChatCompletionRequest,
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) -> CompletionCreateParams:
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"""
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Convert a ChatCompletionRequest to a Groq API-compatible dictionary.
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Warns client if request contains unsupported features.
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"""
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if request.logprobs:
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# Groq doesn't support logprobs at the time of writing
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warnings.warn("logprobs are not supported yet")
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if request.response_format:
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# Groq's JSON mode is beta at the time of writing
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warnings.warn("response_format is not supported yet")
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if request.sampling_params.repetition_penalty != 1.0:
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# groq supports frequency_penalty, but frequency_penalty and sampling_params.repetition_penalty
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# seem to have different semantics
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# frequency_penalty defaults to 0 is a float between -2.0 and 2.0
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# repetition_penalty defaults to 1 and is often set somewhere between 1.0 and 2.0
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# so we exclude it for now
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warnings.warn("repetition_penalty is not supported")
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if request.tools:
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warnings.warn("tools are not supported yet")
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return CompletionCreateParams(
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model=request.model,
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messages=[_convert_message(message) for message in request.messages],
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logprobs=None,
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frequency_penalty=None,
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stream=request.stream,
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max_tokens=request.sampling_params.max_tokens or None,
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temperature=request.sampling_params.temperature,
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top_p=request.sampling_params.top_p,
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)
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def _convert_message(message: Message) -> ChatCompletionMessageParam:
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if message.role == "system":
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return ChatCompletionSystemMessageParam(role="system", content=message.content)
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elif message.role == "user":
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return ChatCompletionUserMessageParam(role="user", content=message.content)
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elif message.role == "assistant":
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return ChatCompletionAssistantMessageParam(
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role="assistant", content=message.content
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)
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else:
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raise ValueError(f"Invalid message role: {message.role}")
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def convert_chat_completion_response(
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response: ChatCompletion,
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) -> ChatCompletionResponse:
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# groq only supports n=1 at time of writing, so there is only one choice
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choice = response.choices[0]
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return ChatCompletionResponse(
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completion_message=CompletionMessage(
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content=choice.message.content,
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stop_reason=_map_finish_reason_to_stop_reason(choice.finish_reason),
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),
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)
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def _map_finish_reason_to_stop_reason(
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finish_reason: Literal["stop", "length", "tool_calls"]
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) -> StopReason:
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"""
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Convert a Groq chat completion finish_reason to a StopReason.
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finish_reason: Literal["stop", "length", "tool_calls"]
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- stop -> model hit a natural stop point or a provided stop sequence
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- length -> maximum number of tokens specified in the request was reached
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- tool_calls -> model called a tool
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"""
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if finish_reason == "stop":
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return StopReason.end_of_turn
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elif finish_reason == "length":
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return StopReason.out_of_tokens
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elif finish_reason == "tool_calls":
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raise NotImplementedError("tool_calls is not supported yet")
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else:
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raise ValueError(f"Invalid finish reason: {finish_reason}")
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async def convert_chat_completion_response_stream(
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stream: Stream[ChatCompletionChunk],
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) -> AsyncGenerator[ChatCompletionResponseStreamChunk, None]:
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event_type = ChatCompletionResponseEventType.start
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for chunk in stream:
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choice = chunk.choices[0]
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# We assume there's only one finish_reason for the entire stream.
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# We collect the last finish_reason
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if choice.finish_reason:
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stop_reason = _map_finish_reason_to_stop_reason(choice.finish_reason)
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yield ChatCompletionResponseStreamChunk(
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event=ChatCompletionResponseEvent(
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event_type=event_type,
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delta=choice.delta.content or "",
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logprobs=None,
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)
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)
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event_type = ChatCompletionResponseEventType.progress
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yield ChatCompletionResponseStreamChunk(
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event=ChatCompletionResponseEvent(
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event_type=ChatCompletionResponseEventType.complete,
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delta="",
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logprobs=None,
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stop_reason=stop_reason,
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)
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)
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