[Feature] Pydantic validation for speculative.py (#27156)

Signed-off-by: Navya Srivastava <navya.srivastava1707@gmail.com>
Co-authored-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

vllm/config/speculative.py

@@ -5,7 +5,7 @@ import ast
 import hashlib
 from typing import TYPE_CHECKING, Any, Literal
 
-from pydantic import SkipValidation, model_validator
+from pydantic import Field, SkipValidation, model_validator
 from pydantic.dataclasses import dataclass
 from typing_extensions import Self
 
@@ -62,7 +62,7 @@ class SpeculativeConfig:
     enforce_eager: bool | None = None
     """Override the default enforce_eager from model_config"""
     # General speculative decoding control
-    num_speculative_tokens: SkipValidation[int] = None  # type: ignore
+    num_speculative_tokens: int = Field(default=None, gt=0)
     """The number of speculative tokens, if provided. It will default to the
     number in the draft model config if present, otherwise, it is required."""
     model: str | None = None
@@ -76,7 +76,7 @@ class SpeculativeConfig:
 
     If using `ngram` method, the related configuration `prompt_lookup_max` and
     `prompt_lookup_min` should be considered."""
-    draft_tensor_parallel_size: int | None = None
+    draft_tensor_parallel_size: int | None = Field(default=None, ge=1)
     """The degree of the tensor parallelism for the draft model. Can only be 1
     or the same as the target model's tensor parallel size."""
     disable_logprobs: bool = True
@@ -89,7 +89,7 @@ class SpeculativeConfig:
     """Quantization method that was used to quantize the draft model weights.
     If `None`, we assume the model weights are not quantized. Note that it only
     takes effect when using the draft model-based speculative method."""
-    max_model_len: int | None = None
+    max_model_len: int | None = Field(default=None, ge=1)
     """The maximum model length of the draft model. Used when testing the
     ability to skip speculation for some sequences."""
     revision: str | None = None
@@ -102,7 +102,7 @@ class SpeculativeConfig:
     will use the default version."""
 
     # Advanced control
-    disable_by_batch_size: int | None = None
+    disable_by_batch_size: int | None = Field(default=None, ge=2)
     """Disable speculative decoding for new incoming requests when the number
     of enqueued requests is larger than this value, if provided."""
     disable_padded_drafter_batch: bool = False
@@ -112,10 +112,10 @@ class SpeculativeConfig:
     only affects the EAGLE method of speculation."""
 
     # Ngram proposer configuration
-    prompt_lookup_max: int | None = None
+    prompt_lookup_max: int | None = Field(default=None, ge=1)
     """Maximum size of ngram token window when using Ngram proposer, required
     when method is set to ngram."""
-    prompt_lookup_min: int | None = None
+    prompt_lookup_min: int | None = Field(default=None, ge=1)
     """Minimum size of ngram token window when using Ngram proposer, if
     provided. Defaults to 1."""
 
@@ -232,9 +232,8 @@ class SpeculativeConfig:
 
         if self.model is None and self.num_speculative_tokens is not None:
             if self.method == "mtp":
-                assert self.target_model_config is not None, (
+                if self.target_model_config is None:
-                    "target_model_config must be present for mtp"
+                    raise ValueError("target_model_config must be present for mtp")
-                )
                 if self.target_model_config.hf_text_config.model_type == "deepseek_v32":
                     # FIXME(luccafong): cudgraph with v32 MTP is not supported,
                     # remove this when the issue is fixed.
@@ -268,21 +267,21 @@ class SpeculativeConfig:
                 self.prompt_lookup_min = 5
                 self.prompt_lookup_max = 5
             elif self.prompt_lookup_min is None:
-                assert self.prompt_lookup_max is not None
+                if self.prompt_lookup_max is None:
+                    raise ValueError(
+                        "Either prompt_lookup_max or prompt_lookup_min must be "
+                        "provided when using the ngram method."
+                    )
                 self.prompt_lookup_min = self.prompt_lookup_max
             elif self.prompt_lookup_max is None:
-                assert self.prompt_lookup_min is not None
+                if self.prompt_lookup_min is None:
+                    raise ValueError(
+                        "Either prompt_lookup_max or prompt_lookup_min must be "
+                        "provided when using the ngram method."
+                    )
                 self.prompt_lookup_max = self.prompt_lookup_min
 
             # Validate values
-            if self.prompt_lookup_min < 1:
-                raise ValueError(
-                    f"prompt_lookup_min={self.prompt_lookup_min} must be > 0"
-                )
-            if self.prompt_lookup_max < 1:
-                raise ValueError(
-                    f"prompt_lookup_max={self.prompt_lookup_max} must be > 0"
-                )
             if self.prompt_lookup_min > self.prompt_lookup_max:
                 raise ValueError(
                     f"prompt_lookup_min={self.prompt_lookup_min} must "
@@ -446,6 +445,7 @@ class SpeculativeConfig:
                         self.target_parallel_config, self.draft_tensor_parallel_size
                     )
                 )
+        return self
 
     @staticmethod
     def _maybe_override_draft_max_model_len(