Support FP8 E4M3 KV Cache (#2786)

Co-authored-by: root <bjmsong@126.com>

python/sglang/srt/server_args.py

@@ -32,6 +32,7 @@ from sglang.srt.utils import (
     is_hip,
     is_ipv6,
     is_port_available,
+    nullable_str,
 )
 
 logger = logging.getLogger(__name__)
@@ -47,6 +48,7 @@ class ServerArgs:
     trust_remote_code: bool = True
     dtype: str = "auto"
     kv_cache_dtype: str = "auto"
+    quantization_param_path: nullable_str = None
     quantization: Optional[str] = None
     context_length: Optional[int] = None
     device: str = "cuda"
@@ -350,8 +352,17 @@ class ServerArgs:
             "--kv-cache-dtype",
             type=str,
             default=ServerArgs.kv_cache_dtype,
-            choices=["auto", "fp8_e5m2"],
-            help='Data type for kv cache storage. "auto" will use model data type. "fp8_e5m2" is supported for CUDA 11.8+.',
+            choices=["auto", "fp8_e5m2", "fp8_e4m3"],
+            help='Data type for kv cache storage. "auto" will use model data type. "fp8_e5m2" and "fp8_e4m3" is supported for CUDA 11.8+.',
+        )
+        parser.add_argument(
+            "--quantization-param-path",
+            type=nullable_str,
+            default=None,
+            help="Path to the JSON file containing the KV cache "
+            "scaling factors. This should generally be supplied, when "
+            "KV cache dtype is FP8. Otherwise, KV cache scaling factors "
+            "default to 1.0, which may cause accuracy issues. ",
         )
         parser.add_argument(
             "--quantization",