forked from phoenix-oss/llama-stack-mirror
191cd28831
* Simplified Telemetry API and tying it to logger * small update which adds a METRIC type * move span events one level down into structured log events --------- Co-authored-by: Ashwin Bharambe <ashwin@meta.com>
76 lines
2.7 KiB
Python
76 lines
2.7 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 functools import lru_cache
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from typing import List, Optional
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from .datatypes import * # noqa: F403
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@lru_cache()
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def available_distribution_specs() -> List[DistributionSpec]:
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return [
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DistributionSpec(
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distribution_type="local",
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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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Api.inference: "meta-reference",
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Api.memory: "meta-reference-faiss",
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Api.safety: "meta-reference",
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Api.agentic_system: "meta-reference",
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Api.telemetry: "console",
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},
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),
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DistributionSpec(
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distribution_type="remote",
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description="Point to remote services for all llama stack APIs",
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providers={
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**{x: "remote" for x in Api},
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Api.telemetry: "console",
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},
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),
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DistributionSpec(
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distribution_type="local-ollama",
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description="Like local, but use ollama for running LLM inference",
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providers={
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Api.inference: remote_provider_type("ollama"),
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Api.safety: "meta-reference",
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Api.agentic_system: "meta-reference",
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Api.memory: "meta-reference-faiss",
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Api.telemetry: "console",
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},
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),
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DistributionSpec(
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distribution_type="local-plus-fireworks-inference",
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description="Use Fireworks.ai for running LLM inference",
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providers={
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Api.inference: remote_provider_type("fireworks"),
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Api.safety: "meta-reference",
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Api.agentic_system: "meta-reference",
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Api.memory: "meta-reference-faiss",
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Api.telemetry: "console",
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},
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),
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DistributionSpec(
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distribution_type="local-plus-together-inference",
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description="Use Together.ai for running LLM inference",
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providers={
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Api.inference: remote_provider_type("together"),
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Api.safety: "meta-reference",
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Api.agentic_system: "meta-reference",
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Api.memory: "meta-reference-faiss",
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Api.telemetry: "console",
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},
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),
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]
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@lru_cache()
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def resolve_distribution_spec(distribution_type: str) -> Optional[DistributionSpec]:
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for spec in available_distribution_specs():
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if spec.distribution_type == distribution_type:
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return spec
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return None
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