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delete distribution registry
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description: Like local, but use ollama for running LLM inference
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providers:
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inference: remote::ollama
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safety: meta-reference
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agentic_system: meta-reference
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memory: meta-reference-faiss
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telemetry: console
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description: Use Fireworks.ai for running LLM inference
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providers:
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inference: remote::fireworks
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safety: meta-reference
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agentic_system: meta-reference
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memory: meta-reference-faiss
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telemetry: console
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description: Use TGI (local or with Hugging Face Inference Endpoints for running LLM inference. When using HF Inference Endpoints, you must provide the name of the endpoint).
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providers:
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inference: remote::tgi
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safety: meta-reference
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agentic_system: meta-reference
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memory: meta-reference-faiss
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description: Use Together.ai for running LLM inference
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providers:
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inference: remote::together
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safety: meta-reference
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agentic_system: meta-reference
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memory: meta-reference-faiss
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telemetry: console
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description: Use code from `llama_toolchain` itself to serve all llama stack APIs
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providers:
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inference: meta-reference
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memory: meta-reference-faiss
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safety: meta-reference
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agentic_system: meta-reference
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telemetry: console
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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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from functools import lru_cache
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from pathlib import Path
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from typing import List, Optional
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from .datatypes import * # noqa: F403
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import yaml
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@lru_cache()
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def available_distribution_specs() -> List[DistributionSpec]:
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distribution_specs = []
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for p in Path("llama_toolchain/configs/distributions/distribution_registry").rglob(
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"*.yaml"
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):
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with open(p, "r") as f:
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distribution_specs.append(DistributionSpec(**yaml.safe_load(f)))
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return distribution_specs
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