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https://github.com/meta-llama/llama-stack.git
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e830814399
* Add distribution CLI scaffolding * More progress towards `llama distribution install` * getting closer to a distro definition, distro install + configure works * Distribution server now functioning * read existing configuration, save enums properly * Remove inference uvicorn server entrypoint and llama inference CLI command * updated dependency and client model name * Improved exception handling * local imports for faster cli * undo a typo, add a passthrough distribution * implement full-passthrough in the server * add safety adapters, configuration handling, server + clients * cleanup, moving stuff to common, nuke utils * Add a Path() wrapper at the earliest place * fixes * Bring agentic system api to toolchain Add adapter dependencies and resolve adapters using a topological sort * refactor to reduce size of `agentic_system` * move straggler files and fix some important existing bugs * ApiSurface -> Api * refactor a method out * Adapter -> Provider * Make each inference provider into its own subdirectory * installation fixes * Rename Distribution -> DistributionSpec, simplify RemoteProviders * dict key instead of attr * update inference config to take model and not model_dir * Fix passthrough streaming, send headers properly not part of body :facepalm * update safety to use model sku ids and not model dirs * Update cli_reference.md * minor fixes * add DistributionConfig, fix a bug in model download * Make install + start scripts do proper configuration automatically * Update CLI_reference * Nuke fp8_requirements, fold fbgemm into common requirements * Update README, add newline between API surface configurations * Refactor download functionality out of the Command so can be reused * Add `llama model download` alias for `llama download` * Show message about checksum file so users can check themselves * Simpler intro statements * get ollama working * Reduce a bunch of dependencies from toolchain Some improvements to the distribution install script * Avoid using `conda run` since it buffers everything * update dependencies and rely on LLAMA_TOOLCHAIN_DIR for dev purposes * add validation for configuration input * resort imports * make optional subclasses default to yes for configuration * Remove additional_pip_packages; move deps to providers * for inline make 8b model the default * Add scripts to MANIFEST * allow installing from test.pypi.org * Fix #2 to help with testing packages * Must install llama-models at that same version first * fix PIP_ARGS --------- Co-authored-by: Hardik Shah <hjshah@fb.com> Co-authored-by: Hardik Shah <hjshah@meta.com>
59 lines
1.7 KiB
Python
59 lines
1.7 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 typing import List
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from llama_toolchain.agentic_system.meta_reference.safety import ShieldRunnerMixin
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from llama_toolchain.inference.api import Message
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from llama_toolchain.safety.api.datatypes import ShieldDefinition
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from llama_toolchain.safety.api.endpoints import Safety
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from .builtin import BaseTool
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class SafeTool(BaseTool, ShieldRunnerMixin):
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"""A tool that makes other tools safety enabled"""
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def __init__(
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self,
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tool: BaseTool,
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safety_api: Safety,
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input_shields: List[ShieldDefinition] = None,
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output_shields: List[ShieldDefinition] = None,
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):
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self._tool = tool
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ShieldRunnerMixin.__init__(
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self, safety_api, input_shields=input_shields, output_shields=output_shields
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)
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def get_name(self) -> str:
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# return the name of the wrapped tool
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return self._tool.get_name()
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async def run(self, messages: List[Message]) -> List[Message]:
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if self.input_shields:
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await self.run_shields(messages, self.input_shields)
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# run the underlying tool
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res = await self._tool.run(messages)
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if self.output_shields:
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await self.run_shields(messages, self.output_shields)
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return res
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def with_safety(
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tool: BaseTool,
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safety_api: Safety,
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input_shields: List[ShieldDefinition] = None,
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output_shields: List[ShieldDefinition] = None,
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) -> SafeTool:
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return SafeTool(
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tool,
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safety_api,
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input_shields=input_shields,
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output_shields=output_shields,
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)
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