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67 lines
2.2 KiB
Python
67 lines
2.2 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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from typing import Any, AsyncGenerator, Dict, List, Tuple
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from llama_stack.distribution.datatypes import Api
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from llama_stack.apis.inference import * # noqa: F403
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from llama_stack.providers.registry.inference import available_providers
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class InferenceRouterImpl(Inference):
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"""Routes to an provider based on the memory bank type"""
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def __init__(
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self,
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inner_impls: List[Tuple[str, Any]],
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deps: List[Api],
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) -> None:
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self.inner_impls = inner_impls
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self.deps = deps
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print("INIT INFERENCE ROUTER!")
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# self.providers = {}
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# for routing_key, provider_impl in inner_impls:
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# self.providers[routing_key] = provider_impl
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async def initialize(self) -> None:
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pass
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async def shutdown(self) -> None:
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pass
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# for p in self.providers.values():
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# await p.shutdown()
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async def chat_completion(
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self,
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model: str,
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messages: List[Message],
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sampling_params: Optional[SamplingParams] = SamplingParams(),
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# zero-shot tool definitions as input to the model
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tools: Optional[List[ToolDefinition]] = list,
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tool_choice: Optional[ToolChoice] = ToolChoice.auto,
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tool_prompt_format: Optional[ToolPromptFormat] = ToolPromptFormat.json,
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stream: Optional[bool] = False,
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logprobs: Optional[LogProbConfig] = None,
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) -> AsyncGenerator:
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print("router chat_completion")
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yield ChatCompletionResponseStreamChunk(
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event=ChatCompletionResponseEvent(
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event_type=ChatCompletionResponseEventType.progress,
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delta="router chat completion",
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)
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)
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# async for chunk in self.providers[model].chat_completion(
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# model=model,
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# messages=messages,
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# sampling_params=sampling_params,
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# tools=tools,
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# tool_choice=tool_choice,
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# tool_prompt_format=tool_prompt_format,
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# stream=stream,
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# logprobs=logprobs,
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# ):
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# yield chunk
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