API + Model: Add support for regex pattern constraints

Adds the ability to constrain generation via regex pattern using lm-format-enforcer.

backends/exllamav2/grammar.py

@@ -97,6 +97,49 @@ class ExLlamaV2Grammar:
         gen_settings.filters.extend([lmfilter, prefix_filter])
         gen_settings.filter_prefer_eos = True
 
+    def add_regex_filter(
+        self,
+        pattern: str,
+        gen_settings: ExLlamaV2Sampler.Settings,
+        tokenizer: ExLlamaV2Tokenizer,
+    ):
+        """Adds an ExllamaV2 filter based on regular expressions."""
+
+        # Import optional dependencies
+        try:
+            from lmformatenforcer import RegexParser
+            from lmformatenforcer.integrations.exllamav2 import (
+                ExLlamaV2TokenEnforcerFilter,
+            )
+        except ImportError:
+            logger.error(
+                "Skipping regex parsing because "
+                "lm-format-enforcer is not installed.\n"
+                "Please run the following command in your environment "
+                "to reinstall dependencies:\n"
+                "pip install -U ."
+            )
+
+            return
+
+        # Create the parser
+        try:
+            pattern_parser = RegexParser(pattern)
+        except Exception:
+            traceback.print_exc()
+            logger.error(
+                "Skipping because the regex pattern couldn't be parsed. "
+                "Please read the above error for more information."
+            )
+
+            return
+
+        lmfilter = ExLlamaV2TokenEnforcerFilter(pattern_parser, tokenizer)
+
+        # Append the filters
+        gen_settings.filters.extend([lmfilter])
+        gen_settings.filter_prefer_eos = True
+
     def add_ebnf_filter(
         self,
         ebnf_string: str,

backends/exllamav2/model.py

@@ -850,6 +850,13 @@ class ExllamaV2Container:
                 json_schema, gen_settings, self.model, self.tokenizer
             )
 
+        # Add regex filter if it exists
+        regex_pattern = unwrap(kwargs.get("regex_pattern"))
+        if regex_pattern:
+            grammar_handler.add_regex_filter(
+                regex_pattern, gen_settings, self.tokenizer
+            )
+
         # Add EBNF filter if it exists
         grammar_string = unwrap(kwargs.get("grammar_string"))
         if grammar_string:

common/sampling.py

@@ -138,6 +138,10 @@ class BaseSamplerRequest(BaseModel):
         default_factory=lambda: get_default_sampler_value("json_schema"),
     )
 
+    regex_pattern: Optional[str] = Field(
+        default_factory=lambda: get_default_sampler_value("regex_pattern"),
+    )
+
     grammar_string: Optional[str] = Field(
         default_factory=lambda: get_default_sampler_value("grammar_string"),
     )
@@ -312,6 +316,7 @@ class BaseSamplerRequest(BaseModel):
             "cfg_scale": self.cfg_scale,
             "negative_prompt": self.negative_prompt,
             "json_schema": self.json_schema,
+            "regex_pattern": self.regex_pattern,
             "grammar_string": self.grammar_string,
             "speculative_ngram": self.speculative_ngram,
         }