refactor: migrate scripts from argparse to click, add YAML config support

- Replace argparse with click in all scripts (train, server, generate,
  preprocess, benchmark)
- Add --config YAML support to train.py with CLI flag override
- Add --dry-run mode to validate config before training
- Add type annotations throughout benchmark.py
- Unify docstring format across all commands
- Remove redundant deps httpx, requests, pyyaml, rich from pyproject.toml
- Net -346 lines while adding YAML config support

scripts/tools/server.py

@@ -1,72 +1,58 @@
-import argparse
 from pathlib import Path
 
+import click
 import torch
 
 from astrai.inference import run_server
 
+_DTYPES = ["bfloat16", "float16", "float32"]
 
-def main():
-    parser = argparse.ArgumentParser(description="Start AstrAI inference HTTP server")
-    parser.add_argument(
-        "--host", default="0.0.0.0", help="Host address (default: 0.0.0.0)"
-    )
-    parser.add_argument(
-        "--port", type=int, default=8000, help="Port number (default: 8000)"
-    )
-    parser.add_argument(
-        "--reload", action="store_true", help="Enable auto-reload for development"
-    )
-    parser.add_argument(
-        "--param_path",
-        type=Path,
-        default=None,
-        help="Path to model parameters (default: project_root/params)",
-    )
-    parser.add_argument(
-        "--device",
-        type=str,
-        default="cuda",
-        help="Device to load model on (default: cuda)",
-    )
-    parser.add_argument(
-        "--dtype",
-        type=str,
-        default="bfloat16",
-        choices=["bfloat16", "float16", "float32"],
-        help="Data type for model weights (default: bfloat16)",
-    )
-    parser.add_argument(
-        "--max_batch_size",
-        type=int,
-        default=16,
-        help="Maximum batch size for continuous batching (default: 16)",
-    )
-    args = parser.parse_args()
 
-    # Convert dtype string to torch dtype
+@click.command(name="serve", help="Launch inference server (OpenAI-compatible API).")
+@click.option("--host", default="0.0.0.0", help="Host address.")
+@click.option("--port", type=int, default=8000, help="Port number.")
+@click.option("--reload", is_flag=True, help="Enable auto-reload for development.")
+@click.option(
+    "--param_path",
+    type=click.Path(exists=True),
+    default=None,
+    help="Path to model parameters.",
+)
+@click.option("--device", default="cuda", help="Device to load model on.")
+@click.option(
+    "--dtype",
+    type=click.Choice(_DTYPES),
+    default="bfloat16",
+    help="Data type for model weights.",
+)
+@click.option(
+    "--max_batch_size",
+    type=int,
+    default=16,
+    help="Maximum batch size for continuous batching.",
+)
+def server_command(host, port, reload, param_path, device, dtype, max_batch_size):
+    """Launch inference server (OpenAI-compatible API)."""
     dtype_map = {
         "bfloat16": torch.bfloat16,
         "float16": torch.float16,
         "float32": torch.float32,
     }
-    dtype = dtype_map[args.dtype]
-
     project_root = Path(__file__).parent.parent.parent
-    param_path = args.param_path or (project_root / "params")
-    print(f"Starting AstrAI inference server on http://{args.host}:{args.port}")
-    print(f"Model parameters expected at: {param_path}")
-    print(f"Device: {args.device}, Dtype: {args.dtype}")
+    param_path = param_path or str(project_root / "params")
+
+    click.echo(f"Starting server on http://{host}:{port}")
+    click.echo(f"Model: {param_path}  |  Device: {device}  |  Dtype: {dtype}")
     run_server(
-        host=args.host,
-        port=args.port,
-        reload=args.reload,
-        device=args.device,
-        dtype=dtype,
-        param_path=param_path,
-        max_batch_size=args.max_batch_size,
+        host=host,
+        port=port,
+        reload=reload,
+        device=device,
+        dtype=dtype_map[dtype],
+        param_path=Path(param_path),
+        max_batch_size=max_batch_size,
     )
 
 
 if __name__ == "__main__":
-    main()
+    server_command()