chore: import upstream snapshot with attribution

2026-07-13 13:23:58 +08:00
commit 770d92cb1f
694 changed files with 114634 additions and 0 deletions
@@ -0,0 +1,121 @@
+"""Command line entrypoint of configuration generation."""
+
+from pathlib import Path
+from typing import Union
+
+from mlc_llm.interface.gen_config import CONV_TEMPLATES, gen_config
+from mlc_llm.interface.help import HELP
+from mlc_llm.model import MODELS
+from mlc_llm.quantization import QUANTIZATION
+from mlc_llm.support.argparse import ArgumentParser
+from mlc_llm.support.auto_config import detect_config, detect_model_type
+
+
+def main(argv):
+    """Parse command line argumennts and call `mlc_llm.compiler.gen_config`."""
+    parser = ArgumentParser("MLC LLM Configuration Generator")
+
+    def _parse_output(path: Union[str, Path]) -> Path:
+        path = Path(path)
+        if not path.is_dir():
+            path.mkdir(parents=True, exist_ok=True)
+        return path
+
+    parser.add_argument(
+        "config",
+        type=detect_config,
+        help=HELP["config"] + " (required)",
+    )
+    parser.add_argument(
+        "--quantization",
+        type=str,
+        required=True,
+        choices=list(QUANTIZATION.keys()),
+        help=HELP["quantization"] + " (required, choices: %(choices)s)",
+    )
+    parser.add_argument(
+        "--model-type",
+        type=str,
+        default="auto",
+        choices=["auto", *list(MODELS.keys())],
+        help=HELP["model_type"] + ' (default: "%(default)s", choices: %(choices)s)',
+    )
+    parser.add_argument(
+        "--conv-template",
+        type=str,
+        required=True,
+        choices=list(CONV_TEMPLATES),
+        help=HELP["conv_template"] + " (required, choices: %(choices)s)",
+    )
+    parser.add_argument(
+        "--context-window-size",
+        type=int,
+        default=None,
+        help=HELP["context_window_size"] + ' (default: "%(default)s")',
+    )
+    parser.add_argument(
+        "--sliding-window-size",
+        type=int,
+        default=None,
+        help=HELP["sliding_window_size"] + ' (default: "%(default)s")',
+    )
+    parser.add_argument(
+        "--prefill-chunk-size",
+        type=int,
+        default=None,
+        help=HELP["prefill_chunk_size"] + ' (default: "%(default)s")',
+    )
+    parser.add_argument(
+        "--attention-sink-size",
+        type=int,
+        default=None,
+        help=HELP["attention_sink_size"] + ' (default: "%(default)s")',
+    )
+    parser.add_argument(
+        "--tensor-parallel-shards",
+        type=int,
+        default=None,
+        help=HELP["tensor_parallel_shards"] + ' (default: "%(default)s")',
+    )
+    parser.add_argument(
+        "--pipeline-parallel-stages",
+        type=int,
+        default=None,
+        help=HELP["pipeline_parallel_stages"] + ' (default: "%(default)s")',
+    )
+    parser.add_argument(
+        "--disaggregation",
+        type=bool,
+        default=None,
+        help=HELP["disaggregation"] + ' (default: "%(default)s")',
+    )
+    parser.add_argument(
+        "--max-batch-size",
+        type=int,
+        default=128,
+        help=HELP["max_batch_size"] + ' (default: "%(default)s")',
+    )
+    parser.add_argument(
+        "--output",
+        "-o",
+        type=_parse_output,
+        required=True,
+        help=HELP["output_gen_mlc_chat_config"] + " (required)",
+    )
+    parsed = parser.parse_args(argv)
+    model = detect_model_type(parsed.model_type, parsed.config)
+    gen_config(
+        config=parsed.config,
+        model=model,
+        quantization=QUANTIZATION[parsed.quantization],
+        conv_template=parsed.conv_template,
+        context_window_size=parsed.context_window_size,
+        sliding_window_size=parsed.sliding_window_size,
+        prefill_chunk_size=parsed.prefill_chunk_size,
+        attention_sink_size=parsed.attention_sink_size,
+        tensor_parallel_shards=parsed.tensor_parallel_shards,
+        pipeline_parallel_stages=parsed.pipeline_parallel_stages,
+        disaggregation=parsed.disaggregation,
+        max_batch_size=parsed.max_batch_size,
+        output=parsed.output,
+    )