Move grammar to function call argument

llama_cpp/llama.py

@@ -227,7 +227,6 @@ class Llama:
         tensor_split: Optional[List[float]] = None,
         rope_freq_base: float = 10000.0,
         rope_freq_scale: float = 1.0,
-        grammar: Optional[Union[str, Path]] = None,
         n_gqa: Optional[int] = None,  # (TEMPORARY) must be 8 for llama2 70b
         rms_norm_eps: Optional[float] = None,  # (TEMPORARY)
         mul_mat_q: Optional[bool] = None,  # (TEMPORARY)
@@ -254,7 +253,6 @@ class Llama:
             tensor_split: List of floats to split the model across multiple GPUs. If None, the model is not split.
             rope_freq_base: Base frequency for rope sampling.
             rope_freq_scale: Scale factor for rope sampling.
-            grammar: Path to a BNF grammar file to use for grammar based sampling.
             verbose: Print verbose output to stderr.
 
         Raises:
@@ -383,12 +381,6 @@ class Llama:
         self.scores: npt.NDArray[np.single] = np.ndarray(
             (n_ctx, self._n_vocab), dtype=np.single
         )
-        if grammar is not None:
-            self.grammar = LlamaGrammar.from_file(
-                grammar, verbose=verbose
-            )  # type: Optional[LlamaGrammar]
-        else:
-            self.grammar = None
 
     @property
     def _input_ids(self) -> npt.NDArray[np.intc]:
@@ -527,6 +519,7 @@ class Llama:
         mirostat_eta: llama_cpp.c_float,
         penalize_nl: bool = True,
         logits_processor: Optional[LogitsProcessorList] = None,
+        grammar: Optional[LlamaGrammar] = None,
     ):
         assert self.ctx is not None
         assert self.n_tokens > 0
@@ -574,11 +567,11 @@ class Llama:
         if not penalize_nl:
             candidates.data[self._token_nl].logit = llama_cpp.c_float(nl_logit)
 
-        if self.grammar is not None:
+        if grammar is not None:
             llama_cpp.llama_sample_grammar(
                 ctx=self.ctx,
                 candidates=llama_cpp.ctypes.byref(candidates),  # type: ignore
-                grammar=self.grammar.grammar,
+                grammar=grammar.grammar,
             )
 
         if temp.value == 0.0:
@@ -650,10 +643,10 @@ class Llama:
                 ctx=self.ctx,
                 candidates=llama_cpp.ctypes.byref(candidates),  # type: ignore
             )
-        if self.grammar is not None:
+        if grammar is not None:
             llama_cpp.llama_grammar_accept_token(
                 ctx=self.ctx,
-                grammar=self.grammar.grammar,
+                grammar=grammar.grammar,
                 token=llama_cpp.ctypes.c_int(id),
             )
         return id
@@ -672,6 +665,7 @@ class Llama:
         mirostat_tau: float = 5.0,
         penalize_nl: bool = True,
         logits_processor: Optional[LogitsProcessorList] = None,
+        grammar: Optional[LlamaGrammar] = None,
     ):
         """Sample a token from the model.
 
@@ -705,6 +699,7 @@ class Llama:
             mirostat_eta=llama_cpp.c_float(mirostat_eta),
             penalize_nl=penalize_nl,
             logits_processor=logits_processor,
+            grammar=grammar,
         )
 
     def generate(
@@ -723,6 +718,7 @@ class Llama:
         mirostat_eta: float = 0.1,
         logits_processor: Optional[LogitsProcessorList] = None,
         stopping_criteria: Optional[StoppingCriteriaList] = None,
+        grammar: Optional[LlamaGrammar] = None,
     ) -> Generator[int, Optional[Sequence[int]], None]:
         """Create a generator of tokens from a prompt.
 
@@ -761,8 +757,8 @@ class Llama:
         if reset:
             self.reset()
 
-        if self.grammar is not None:
+        if grammar is not None:
-            self.grammar.reset()
+            grammar.reset()
 
         while True:
             self.eval(tokens)
@@ -778,6 +774,7 @@ class Llama:
                 mirostat_tau=mirostat_tau,
                 mirostat_eta=mirostat_eta,
                 logits_processor=logits_processor,
+                grammar=grammar,
             )
             if stopping_criteria is not None and stopping_criteria(
                 self._input_ids.tolist(), self._scores[-1, :].tolist()
@@ -880,6 +877,7 @@ class Llama:
         model: Optional[str] = None,
         stopping_criteria: Optional[StoppingCriteriaList] = None,
         logits_processor: Optional[LogitsProcessorList] = None,
+        grammar: Optional[LlamaGrammar] = None,
     ) -> Union[Iterator[Completion], Iterator[CompletionChunk]]:
         assert self.ctx is not None
 
@@ -957,6 +955,7 @@ class Llama:
             repeat_penalty=repeat_penalty,
             stopping_criteria=stopping_criteria,
             logits_processor=logits_processor,
+            grammar=grammar,
         ):
             if token == self._token_eos:
                 text = self.detokenize(completion_tokens)
@@ -1301,6 +1300,7 @@ class Llama:
         model: Optional[str] = None,
         stopping_criteria: Optional[StoppingCriteriaList] = None,
         logits_processor: Optional[LogitsProcessorList] = None,
+        grammar: Optional[LlamaGrammar] = None,
     ) -> Union[Completion, Iterator[CompletionChunk]]:
         """Generate text from a prompt.
 
@@ -1345,6 +1345,7 @@ class Llama:
             model=model,
             stopping_criteria=stopping_criteria,
             logits_processor=logits_processor,
+            grammar=grammar
         )
         if stream:
             chunks: Iterator[CompletionChunk] = completion_or_chunks
@@ -1374,6 +1375,7 @@ class Llama:
         model: Optional[str] = None,
         stopping_criteria: Optional[StoppingCriteriaList] = None,
         logits_processor: Optional[LogitsProcessorList] = None,
+        grammar: Optional[LlamaGrammar] = None,
     ) -> Union[Completion, Iterator[CompletionChunk]]:
         """Generate text from a prompt.
 
@@ -1418,6 +1420,7 @@ class Llama:
             model=model,
             stopping_criteria=stopping_criteria,
             logits_processor=logits_processor,
+            grammar=grammar,
         )
 
     def _convert_text_completion_to_chat(
@@ -1498,6 +1501,7 @@ class Llama:
         mirostat_eta: float = 0.1,
         model: Optional[str] = None,
         logits_processor: Optional[LogitsProcessorList] = None,
+        grammar: Optional[LlamaGrammar] = None,
     ) -> Union[ChatCompletion, Iterator[ChatCompletionChunk]]:
         """Generate a chat completion from a list of messages.
 
@@ -1540,6 +1544,7 @@ class Llama:
             mirostat_eta=mirostat_eta,
             model=model,
             logits_processor=logits_processor,
+            grammar=grammar,
         )
         if stream:
             chunks: Iterator[CompletionChunk] = completion_or_chunks  # type: ignore