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748606195b
* remove configure * build msg * wip * build->run * delete prints * docs * fix docs, kill configure * precommit * update fireworks build * docs * clean up build * comments * fix * test * remove baking build.yaml into docker * fix msg, urls * configure msg
48 lines
1.6 KiB
Python
48 lines
1.6 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 Optional
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from llama_models.schema_utils import json_schema_type
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from pydantic import BaseModel, Field
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@json_schema_type
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class TGIImplConfig(BaseModel):
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host: str = "localhost"
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port: int = 8080
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protocol: str = "http"
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@property
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def url(self) -> str:
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return f"{self.protocol}://{self.host}:{self.port}"
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api_token: Optional[str] = Field(
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default=None,
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description="A bearer token if your TGI endpoint is protected.",
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)
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@json_schema_type
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class InferenceEndpointImplConfig(BaseModel):
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endpoint_name: str = Field(
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description="The name of the Hugging Face Inference Endpoint in the format of '{namespace}/{endpoint_name}' (e.g. 'my-cool-org/meta-llama-3-1-8b-instruct-rce'). Namespace is optional and will default to the user account if not provided.",
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)
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api_token: Optional[str] = Field(
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default=None,
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description="Your Hugging Face user access token (will default to locally saved token if not provided)",
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)
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@json_schema_type
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class InferenceAPIImplConfig(BaseModel):
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huggingface_repo: str = Field(
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description="The model ID of the model on the Hugging Face Hub (e.g. 'meta-llama/Meta-Llama-3.1-70B-Instruct')",
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)
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api_token: Optional[str] = Field(
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default=None,
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description="Your Hugging Face user access token (will default to locally saved token if not provided)",
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)
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