初始化项目，由ModelHub XC社区提供模型

Model: ayh015/myLightningOPD
Source: Original Platform

slime/utils/debug_utils/send_to_sglang.py

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+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import asyncio
+import json
+from typing import Annotated
+
+import typer
+from openai import AsyncOpenAI
+
+from slime.utils.data import read_file
+
+
+# can unify w/ sglang_rollout.py later, e.g. add RM, if needed
+def main(
+    prompt_data: Annotated[str, typer.Option()],
+    url: Annotated[str, typer.Option()] = "http://localhost:30000/v1",
+    input_key: Annotated[str, typer.Option()] = "input",
+    n_samples_per_prompt: Annotated[int, typer.Option()] = 1,
+    rollout_max_response_len: Annotated[int, typer.Option()] = 1024,
+    rollout_temperature: Annotated[float, typer.Option()] = 1.0,
+    rollout_top_p: Annotated[float, typer.Option()] = 1.0,
+):
+    """
+    Minimally send prompts to SGLang using OpenAI endpoints with arguments in the same format as main Slime.
+
+    Example usage:
+    python -m slime.utils.debug_utils.send_to_sglang --prompt-data /root/datasets/aime-2024/aime-2024.jsonl --input-key prompt --n-samples-per-prompt 16 --rollout-max-response-len 32768 --rollout-temperature 0.8 --rollout-top-p 0.7
+    """
+
+    async def _main_async():
+        tasks = [
+            asyncio.create_task(_run_one(row, row_index=row_index, repeat_index=repeat_index))
+            for row_index, row in enumerate(read_file(prompt_data))
+            for repeat_index in range(n_samples_per_prompt)
+        ]
+        outputs = await asyncio.gather(*tasks)
+        for output in outputs:
+            print(json.dumps(output))
+
+    async def _run_one(row, row_index: int, repeat_index: int):
+        resp = await client.chat.completions.create(
+            messages=row[input_key],
+            model="dummy_model",
+            max_tokens=rollout_max_response_len,
+            temperature=rollout_temperature,
+            top_p=rollout_top_p,
+        )
+        return dict(
+            row_index=row_index,
+            repeat_index=repeat_index,
+            **row,
+            response=resp.choices[0].message.content,
+        )
+
+    client = AsyncOpenAI(api_key="dummy_key", base_url=url)
+    asyncio.run(_main_async())
+
+
+if __name__ == "__main__":
+    typer.run(main)