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* API Keys passed from Client instead of distro configuration * delete distribution registry * Rename the "package" word away * Introduce a "Router" layer for providers Some providers need to be factorized and considered as thin routing layers on top of other providers. Consider two examples: - The inference API should be a routing layer over inference providers, routed using the "model" key - The memory banks API is another instance where various memory bank types will be provided by independent providers (e.g., a vector store is served by Chroma while a keyvalue memory can be served by Redis or PGVector) This commit introduces a generalized routing layer for this purpose. * update `apis_to_serve` * llama_toolchain -> llama_stack * Codemod from llama_toolchain -> llama_stack - added providers/registry - cleaned up api/ subdirectories and moved impls away - restructured api/api.py - from llama_stack.apis.<api> import foo should work now - update imports to do llama_stack.apis.<api> - update many other imports - added __init__, fixed some registry imports - updated registry imports - create_agentic_system -> create_agent - AgenticSystem -> Agent * Moved some stuff out of common/; re-generated OpenAPI spec * llama-toolchain -> llama-stack (hyphens) * add control plane API * add redis adapter + sqlite provider * move core -> distribution * Some more toolchain -> stack changes * small naming shenanigans * Removing custom tool and agent utilities and moving them client side * Move control plane to distribution server for now * Remove control plane from API list * no codeshield dependency randomly plzzzzz * Add "fire" as a dependency * add back event loggers * stack configure fixes * use brave instead of bing in the example client * add init file so it gets packaged * add init files so it gets packaged * Update MANIFEST * bug fix --------- Co-authored-by: Hardik Shah <hjshah@fb.com> Co-authored-by: Xi Yan <xiyan@meta.com> Co-authored-by: Ashwin Bharambe <ashwin@meta.com>
87 lines
2.8 KiB
Python
87 lines
2.8 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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# 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 found in the
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# LICENSE file in the root directory of this source tree.
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from datetime import datetime
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from pathlib import Path
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import fire
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import yaml
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from llama_models import schema_utils
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# We do some monkey-patching to ensure our definitions only use the minimal
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# (json_schema_type, webmethod) definitions from the llama_models package. For
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# generation though, we need the full definitions and implementations from the
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# (json-strong-typing) package.
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from strong_typing.schema import json_schema_type
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from .pyopenapi.options import Options
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from .pyopenapi.specification import Info, Server
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from .pyopenapi.utility import Specification
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schema_utils.json_schema_type = json_schema_type
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from llama_stack.apis.stack import LlamaStack
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# TODO: this should be fixed in the generator itself so it reads appropriate annotations
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STREAMING_ENDPOINTS = [
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"/agentic_system/turn/create",
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"/inference/chat_completion",
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]
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def patch_sse_stream_responses(spec: Specification):
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for path, path_item in spec.document.paths.items():
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if path in STREAMING_ENDPOINTS:
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content = path_item.post.responses["200"].content.pop("application/json")
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path_item.post.responses["200"].content["text/event-stream"] = content
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def main(output_dir: str):
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output_dir = Path(output_dir)
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if not output_dir.exists():
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raise ValueError(f"Directory {output_dir} does not exist")
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now = str(datetime.now())
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print(
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"Converting the spec to YAML (openapi.yaml) and HTML (openapi.html) at " + now
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)
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print("")
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spec = Specification(
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LlamaStack,
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Options(
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server=Server(url="http://any-hosted-llama-stack.com"),
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info=Info(
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title="[DRAFT] Llama Stack Specification",
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version="0.0.1",
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description="""This is the specification of the llama stack that provides
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a set of endpoints and their corresponding interfaces that are tailored to
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best leverage Llama Models. The specification is still in draft and subject to change.
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Generated at """
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+ now,
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),
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),
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)
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patch_sse_stream_responses(spec)
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with open(output_dir / "llama-stack-spec.yaml", "w", encoding="utf-8") as fp:
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yaml.dump(spec.get_json(), fp, allow_unicode=True)
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with open(output_dir / "llama-stack-spec.html", "w") as fp:
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spec.write_html(fp, pretty_print=True)
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if __name__ == "__main__":
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fire.Fire(main)
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