evals new rebase

llama_stack/apis/evals/client.py

@@ -0,0 +1,85 @@
+# 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 json
+
+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,
+        task: str,
+        dataset: Optional[str] = None,
+        eval_task_config: Optional[EvaluateTaskConfig] = None,
+    ) -> EvaluateResponse:
+        async with httpx.AsyncClient() as client:
+            response = await client.post(
+                f"{self.base_url}/evals/run",
+                json={
+                    "model": model,
+                    "task": task,
+                    "dataset": dataset,
+                    "eval_task_config": (
+                        json.loads(eval_task_config.json())
+                        if eval_task_config
+                        else None
+                    ),
+                },
+                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(
+        model="Llama3.1-8B-Instruct",
+        dataset="mmlu-simple-eval-en",
+        task="mmlu",
+        eval_task_config=EvaluateTaskConfig(
+            n_samples=2,
+        ),
+    )
+    cprint(f"evaluate response={response}", "green")
+
+    # Eleuther Eval Task
+    # response = await client.run_evals(
+    #     model="Llama3.1-8B-Instruct",
+    #     task="meta_mmlu_pro_instruct",
+    #     # task="meta_ifeval",
+    #     eval_task_config=EvaluateTaskConfig(
+    #         n_samples=2,
+    #     )
+    # )
+    # cprint(response.metrics["metrics_table"], "red")
+
+
+def main(host: str, port: int):
+    asyncio.run(run_main(host, port))
+
+
+if __name__ == "__main__":
+    fire.Fire(main)