mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-12-08 19:10:56 +00:00
67 lines
1.7 KiB
Python
67 lines
1.7 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.
|
|
|
|
import asyncio
|
|
|
|
import fire
|
|
import httpx
|
|
from termcolor import cprint
|
|
|
|
from .evals import * # noqa: F403
|
|
|
|
|
|
class EvaluationClient(Evals):
|
|
def __init__(self, base_url: str):
|
|
self.base_url = base_url
|
|
|
|
async def initialize(self) -> None:
|
|
pass
|
|
|
|
async def shutdown(self) -> None:
|
|
pass
|
|
|
|
async def run_evals(self, model: str, dataset: str, task: str) -> EvaluateResponse:
|
|
async with httpx.AsyncClient() as client:
|
|
response = await client.post(
|
|
f"{self.base_url}/evals/run",
|
|
json={
|
|
"model": model,
|
|
"dataset": dataset,
|
|
"task": task,
|
|
},
|
|
headers={"Content-Type": "application/json"},
|
|
timeout=3600,
|
|
)
|
|
response.raise_for_status()
|
|
return EvaluateResponse(**response.json())
|
|
|
|
|
|
async def run_main(host: str, port: int):
|
|
client = EvaluationClient(f"http://{host}:{port}")
|
|
|
|
# CustomDataset
|
|
# response = await client.run_evals(
|
|
# "Llama3.1-8B-Instruct",
|
|
# "mmlu-simple-eval-en",
|
|
# "mmlu",
|
|
# )
|
|
# cprint(f"evaluate response={response}", "green")
|
|
|
|
# Eleuther Eval
|
|
response = await client.run_evals(
|
|
"Llama3.1-8B-Instruct",
|
|
"PLACEHOLDER_DATASET_NAME",
|
|
"mmlu",
|
|
)
|
|
cprint(response.metrics["metrics_table"], "red")
|
|
|
|
|
|
def main(host: str, port: int):
|
|
asyncio.run(run_main(host, port))
|
|
|
|
|
|
if __name__ == "__main__":
|
|
fire.Fire(main)
|