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Update CLI reference and add typing
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3 changed files with 6 additions and 6 deletions
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@ -285,10 +285,10 @@ llama stack list-distributions
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| | "agentic_system": "meta-reference", | |
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| | "memory": "meta-reference-faiss" | |
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| | } | |
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+--------------------------------+---------------------------------------+-------------------------------------------------------------------------------------------+
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| local-plus-tgi-inference | { | Use TGI (local or with <a href="https://huggingface.co/inference-endpoints/dedicated"> |
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| | "inference": "remote::tgi", | Hugging Face Inference Endpoints</a>) for running LLM inference |
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| | "safety": "meta-reference", | |
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|--------------------------------|---------------------------------------|-------------------------------------------------------------------------------------------|
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| local-plus-tgi-inference | { | Use TGI (local or with [Hugging Face Inference Endpoints](https://huggingface.co/ |
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| | "inference": "remote::tgi", | inference-endpoints/dedicated)) for running LLM inference. When using HF Inference |
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| | "safety": "meta-reference", | Endpoints, please provide hf_namespace (username or organization name) and endpoint name. |
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| | "agentic_system": "meta-reference", | |
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| | "memory": "meta-reference-faiss" | |
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| | } | |
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@ -7,7 +7,7 @@
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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, field_validator
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from pydantic import BaseModel, Field
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@json_schema_type
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@ -41,7 +41,7 @@ class LocalTGIAdapter(Inference):
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def client(self) -> InferenceClient:
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return InferenceClient(model=self.config.url, token=self.config.api_token)
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def _get_endpoint_info(self):
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def _get_endpoint_info(self) -> Dict[str, Any]:
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return {**self.client.get_endpoint_info(), "inference_url": self.config.url}
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async def initialize(self) -> None:
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