llama-stack-mirror/llama_toolchain/distribution/registry.py
2024-08-05 18:04:44 -07:00

124 lines
3.9 KiB
Python

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from functools import lru_cache
from typing import List, Optional
from llama_toolchain.agentic_system.providers import available_agentic_system_providers
from llama_toolchain.inference.providers import available_inference_providers
from llama_toolchain.safety.providers import available_safety_providers
from .datatypes import Api, Distribution, RemoteProviderSpec
# This is currently duplicated from `requirements.txt` with a few minor changes
# dev-dependencies like "ufmt" etc. are nuked. A few specialized dependencies
# are moved to the appropriate distribution.
COMMON_DEPENDENCIES = [
"accelerate",
"black==24.4.2",
"blobfile",
"codeshield",
"fairscale",
"fastapi",
"fire",
"flake8",
"httpx",
"huggingface-hub",
"json-strong-typing",
"llama-models",
"omegaconf",
"pandas",
"Pillow",
"pydantic==1.10.13",
"pydantic_core==2.18.2",
"python-dotenv",
"python-openapi",
"requests",
"tiktoken",
"torch",
"transformers",
"uvicorn",
]
def client_module(api: Api) -> str:
return f"llama_toolchain.{api.value}.client"
def remote(api: Api, port: int) -> RemoteProviderSpec:
return RemoteProviderSpec(
api=api,
provider_id=f"{api.value}-remote",
base_url=f"http://localhost:{port}",
module=client_module(api),
)
@lru_cache()
def available_distributions() -> List[Distribution]:
inference_providers_by_id = {
a.provider_id: a for a in available_inference_providers()
}
safety_providers_by_id = {a.provider_id: a for a in available_safety_providers()}
agentic_system_providers_by_id = {
a.provider_id: a for a in available_agentic_system_providers()
}
return [
Distribution(
name="local-inline",
description="Use code from `llama_toolchain` itself to serve all llama stack APIs",
additional_pip_packages=COMMON_DEPENDENCIES,
provider_specs={
Api.inference: inference_providers_by_id["meta-reference"],
Api.safety: safety_providers_by_id["meta-reference"],
Api.agentic_system: agentic_system_providers_by_id["meta-reference"],
},
),
# NOTE: this hardcodes the ports to which things point to
Distribution(
name="full-remote",
description="Point to remote services for all llama stack APIs",
additional_pip_packages=[
"python-dotenv",
"blobfile",
"codeshield",
"fairscale",
"fastapi",
"fire",
"httpx",
"huggingface-hub",
"json-strong-typing",
"pydantic==1.10.13",
"pydantic_core==2.18.2",
"uvicorn",
],
provider_specs={
Api.inference: remote(Api.inference, 5001),
Api.safety: remote(Api.safety, 5001),
Api.agentic_system: remote(Api.agentic_system, 5001),
},
),
Distribution(
name="local-ollama",
description="Like local-source, but use ollama for running LLM inference",
additional_pip_packages=COMMON_DEPENDENCIES,
provider_specs={
Api.inference: inference_providers_by_id["meta-ollama"],
Api.safety: safety_providers_by_id["meta-reference"],
Api.agentic_system: agentic_system_providers_by_id["meta-reference"],
},
),
]
@lru_cache()
def resolve_distribution(name: str) -> Optional[Distribution]:
for dist in available_distributions():
if dist.name == name:
return dist
return None