mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-06-27 18:50:41 +00:00
cb2a9784ab
Fixes multiple issues 1. llama stack build of dependencies was breaking with incompatible numpy / pandas when importing datasets Moved the notebook to start a local server instead of using library as a client. This way the setup is cleaner since its all contained and by using `uv run --with` we can test both the server setup process too in CI and release time. 2. The change to [1] surfaced some other issues - running `llama stack run` was defaulting to conda env name - provider data was not being managed properly - Some notebook cells (telemetry for evals) were not updated with latest changes Fixed all the issues and update the notebook. ### Test 1. Manually run it all in local env 2. `pytest -v -s --nbval-lax docs/getting_started.ipynb`
37 lines
1.2 KiB
Python
37 lines
1.2 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 contextvars import ContextVar
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from typing import AsyncGenerator, List, TypeVar
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T = TypeVar("T")
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def preserve_contexts_async_generator(
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gen: AsyncGenerator[T, None], context_vars: List[ContextVar]
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) -> AsyncGenerator[T, None]:
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"""
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Wraps an async generator to preserve context variables across iterations.
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This is needed because we start a new asyncio event loop for each streaming request,
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and we need to preserve the context across the event loop boundary.
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"""
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# Capture initial context values
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initial_context_values = {context_var.name: context_var.get() for context_var in context_vars}
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async def wrapper() -> AsyncGenerator[T, None]:
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while True:
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try:
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# Restore context values before any await
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for context_var in context_vars:
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context_var.set(initial_context_values[context_var.name])
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item = await gen.__anext__()
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yield item
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except StopAsyncIteration:
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break
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return wrapper()
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