diff --git a/outlines/generate/api.py b/outlines/generate/api.py
index dea3108d5..ad01377c0 100644
--- a/outlines/generate/api.py
+++ b/outlines/generate/api.py
@@ -1,6 +1,6 @@
 import datetime
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any, Iterator, List, Optional, Union, cast
+from typing import TYPE_CHECKING, Any, Iterator, List, Optional, Union
 
 from outlines.generate.generator import sequence_generator
 from outlines.samplers import BeamSearchSampler, GreedySampler, MultinomialSampler
@@ -534,9 +534,8 @@ def stream(
 class VisionSequenceGeneratorAdapter(SequenceGeneratorAdapter):
     def __call__(  # type: ignore
         self,
-        prompts: Union[str, List[str], List[dict], List[List[dict]]],
+        prompts: Union[str, List[str]],
         media: Union[str, Any],
-        apply_chat_template: bool = False,
         max_tokens: Optional[int] = None,
         stop_at: Optional[Union[str, List[str]]] = None,
         seed: Optional[int] = None,
@@ -547,17 +546,6 @@ def __call__(  # type: ignore
 
         Media: A URI to construct media or media object itself. Used as AutoProcessor argument.
         """
-        if apply_chat_template:
-            # Transform the huggingface conversation object into the string that this
-            #   model expects.
-            # https://huggingface.co/docs/transformers/main/en/chat_templating
-            prompts = (
-                [self.model.processor.apply_chat_template(p) for p in prompts]
-                if isinstance(prompts[0], list)
-                else self.model.processor.apply_chat_template(prompts)
-            )
-        prompts = cast(Union[str, List[str]], prompts)
-
         prompts, media = self._validate_prompt_media_types(prompts, media)
 
         generation_params = self.prepare_generation_parameters(
@@ -577,26 +565,14 @@ def __call__(  # type: ignore
 
     def stream(  # type: ignore
         self,
-        prompts: Union[str, List[str], List[dict], List[List[dict]]],
+        prompts: Union[str, List[str]],
         media: List[Union[str, Any, List[Union[str, Any]]]],
-        apply_chat_template: bool = False,
         max_tokens: Optional[int] = None,
         stop_at: Optional[Union[str, List[str]]] = None,
         seed: Optional[int] = None,
         **model_specific_params,
     ):
         """Return a text generator from a prompt or a list of prompts."""
-        if apply_chat_template:
-            # Transform the huggingface conversation object into the string that this
-            #   model expects.
-            # https://huggingface.co/docs/transformers/main/en/chat_templating
-            prompts = (
-                [self.model.processor.apply_chat_template(p) for p in prompts]
-                if isinstance(prompts[0], list)
-                else self.model.processor.apply_chat_template(prompts)
-            )
-        prompts = cast(Union[str, List[str]], prompts)
-
         prompts, media = self._validate_prompt_media_types(prompts, media)
         generation_params = self.prepare_generation_parameters(
             max_tokens, stop_at, seed