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https://github.com/meta-llama/llama-stack.git
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69b692af91
Add comprehensive OpenTelemetry-based metrics for agent observability: - Workflow completion/failure tracking with duration measurements - Step execution counters for performance monitoring - Tool usage tracking with normalized tool names - Non-blocking telemetry emission with named async tasks - Comprehensive unit and integration test coverage - Graceful handling when telemetry is disabled
42 lines
1.4 KiB
Python
42 lines
1.4 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 llama_stack.providers.datatypes import (
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Api,
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InlineProviderSpec,
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ProviderSpec,
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)
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from llama_stack.providers.utils.kvstore import kvstore_dependencies
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def available_providers() -> list[ProviderSpec]:
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return [
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InlineProviderSpec(
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api=Api.agents,
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provider_type="inline::meta-reference",
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pip_packages=[
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"matplotlib",
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"pillow",
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"pandas",
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"scikit-learn",
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"mcp>=1.8.1",
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]
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+ kvstore_dependencies(), # TODO make this dynamic based on the kvstore config
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module="llama_stack.providers.inline.agents.meta_reference",
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config_class="llama_stack.providers.inline.agents.meta_reference.MetaReferenceAgentsImplConfig",
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api_dependencies=[
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Api.inference,
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Api.safety,
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Api.vector_io,
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Api.vector_dbs,
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Api.tool_runtime,
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Api.tool_groups,
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Api.telemetry,
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],
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description="Meta's reference implementation of an agent system that can use tools, access vector databases, and perform complex reasoning tasks.",
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),
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]
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