API + Model: Add support for JSON schema constraints

Add the ability to constrain the return value of a model to be JSON.
Built using the JSON schema standard to define the properties of what
the model should return.

This feature should be more accurate than using GBNF/EBNF to yield
the same results due to the use of lmformatenforcer.

GBNF/EBNF will be added in a different commit/branch.

Signed-off-by: kingbri <bdashore3@proton.me>

backends/exllamav2/grammar.py

@@ -0,0 +1,61 @@
+from common.logger import init_logger
+from exllamav2 import ExLlamaV2, ExLlamaV2Tokenizer
+from exllamav2.generator import ExLlamaV2Sampler
+
+# Temporary, remove once the exllama version is bumped
+try:
+    from exllamav2.generator.filters import ExLlamaV2PrefixFilter
+
+    _exllama_filter_available = True
+except ImportError:
+    _exllama_filter_available = False
+
+try:
+    from lmformatenforcer import JsonSchemaParser
+    from lmformatenforcer.integrations.exllamav2 import ExLlamaV2TokenEnforcerFilter
+
+    _lmformatenforcer_available = True
+except ImportError:
+    _lmformatenforcer_available = False
+
+
+logger = init_logger(__name__)
+
+
+class ExLlamaV2Grammar:
+    """ExLlamaV2 class for various grammar filters/parsers."""
+
+    def add_json_schema_filter(
+        self,
+        json_schema: dict,
+        gen_settings: ExLlamaV2Sampler.Settings,
+        model: ExLlamaV2,
+        tokenizer: ExLlamaV2Tokenizer,
+    ):
+        """Adds an ExllamaV2 filter based on a JSON schema."""
+
+        # Check if the required dependencies can be imported
+        if not _exllama_filter_available:
+            logger.warning(
+                "ExllamaV2PrefixFilter is not available "
+                "in the currently installed ExllamaV2 version."
+            )
+
+            return
+
+        if not _lmformatenforcer_available:
+            logger.error(
+                "lmformatenforcer must be installed to parse a json schema.\n"
+                "Please run the following command: pip install lm-format-enforcer"
+            )
+
+            return
+
+        # Create the parser
+        schema_parser = JsonSchemaParser(json_schema)
+        lmfilter = ExLlamaV2TokenEnforcerFilter(schema_parser, tokenizer)
+        prefix_filter = ExLlamaV2PrefixFilter(model, tokenizer, "{")
+
+        # Append the filters
+        gen_settings.filters += [lmfilter, prefix_filter]
+        gen_settings.filter_prefer_eos = True

backends/exllamav2/model.py

@@ -16,6 +16,7 @@ from exllamav2 import (
 from exllamav2.generator import ExLlamaV2StreamingGenerator, ExLlamaV2Sampler
 from typing import List, Optional, Union
 
+from backends.exllamav2.grammar import ExLlamaV2Grammar
 from common.gen_logging import log_generation_params, log_prompt, log_response
 from common.templating import (
     PromptTemplate,
@@ -758,6 +759,16 @@ class ExllamaV2Container:
                         "in the model's vocab. Skipping."
                     )
 
+        # Initialize grammar handler
+        grammar_handler = ExLlamaV2Grammar()
+
+        # Add JSON schema filter if it exists
+        json_schema = unwrap(kwargs.get("json_schema"))
+        if json_schema:
+            grammar_handler.add_json_schema_filter(
+                json_schema, gen_settings, self.model, self.tokenizer
+            )
+
         # Ban the EOS token if specified. If not, append to stop conditions
         # as well.
         # Set this below logging to avoid polluting the stop strings array

common/sampling.py

@@ -118,6 +118,10 @@ class BaseSamplerRequest(BaseModel):
         default_factory=lambda: get_default_sampler_value("negative_prompt")
     )
 
+    json_schema: Optional[object] = Field(
+        default_factory=lambda: get_default_sampler_value("json_schema"),
+    )
+
     # Aliased variables
     typical: Optional[float] = Field(
         default_factory=lambda: get_default_sampler_value("typical", 1.0),
@@ -261,6 +265,7 @@ class BaseSamplerRequest(BaseModel):
             "mirostat_eta": self.mirostat_eta,
             "cfg_scale": self.cfg_scale,
             "negative_prompt": self.negative_prompt,
+            "json_schema": self.json_schema,
         }
 
         return {**gen_params, **kwargs}