diff --git a/src/openllm/_schema.py b/src/openllm/_schema.py
index f0bc5e7e..2934cc6a 100644
--- a/src/openllm/_schema.py
+++ b/src/openllm/_schema.py
@@ -16,7 +16,6 @@ Schema definition for OpenLLM. This can be use for client interaction.
 """
 from __future__ import annotations
 
-import string
 import typing as t
 
 import inflection
@@ -25,56 +24,6 @@ import pydantic
 import openllm
 
 
-class PromptFormatter(string.Formatter):
-    def vformat(self, format_string: str, args: t.Sequence[t.Any], kwargs: t.Mapping[str, t.Any]) -> str:
-        if len(args) > 0:
-            raise ValueError("Positional arguments are not supported")
-        return super().vformat(format_string, args, kwargs)
-
-    def check_unused_args(
-        self, used_args: set[int | str], args: t.Sequence[t.Any], kwargs: t.Mapping[str, t.Any]
-    ) -> None:
-        """Check if extra params is passed."""
-        extras = set(kwargs).difference(used_args)
-        if extras:
-            raise KeyError(f"Extra params passed: {extras}")
-
-    def extract_template_variables(self, template: str) -> t.Sequence[str]:
-        """Extract template variables from a template string."""
-        return [field[1] for field in self.parse(template) if field[1] is not None]
-
-
-# TODO: Support jinja2 template, go template and possible other prompt template engine.
-_default_formatter = PromptFormatter()
-
-
-class PromptTemplate(pydantic.BaseModel):
-    template: str
-    input_variables: t.Sequence[str]
-
-    model_config = {"extra": "forbid"}
-
-    def to_str(self, **kwargs: str) -> str:
-        """Generate a prompt from the template and input variables"""
-        if not kwargs:
-            raise ValueError("Keyword arguments are required")
-        if not all(k in kwargs for k in self.input_variables):
-            raise ValueError(f"Missing required input variables: {self.input_variables}")
-        return _default_formatter.format(self.template, **kwargs)
-
-    @classmethod
-    def from_template(cls, template: str) -> PromptTemplate:
-        input_variables = _default_formatter.extract_template_variables(template)
-        return cls(template=template, input_variables=input_variables)
-
-    @classmethod
-    def from_default(cls, model: str) -> PromptTemplate:
-        template = getattr(openllm.utils.get_lazy_module(model), "DEFAULT_PROMPT_TEMPLATE")
-        if template is None:
-            raise ValueError(f"Model {model} does not have a default prompt template.")
-        return cls.from_template(template)
-
-
 class GenerationInput(pydantic.BaseModel):
     model_config = {"extra": "forbid"}
 
diff --git a/src/openllm_client/__init__.py b/src/openllm_client/__init__.py
index 89359b7c..959dc5ed 100644
--- a/src/openllm_client/__init__.py
+++ b/src/openllm_client/__init__.py
@@ -23,7 +23,7 @@ from __future__ import annotations
 import logging
 import typing as t
 
-import bentoml
+from ._prompt import PromptTemplate as PromptTemplate
 
 logger = logging.getLogger(__name__)
 
diff --git a/src/openllm_client/_prompt.py b/src/openllm_client/_prompt.py
new file mode 100644
index 00000000..828893fa
--- /dev/null
+++ b/src/openllm_client/_prompt.py
@@ -0,0 +1,71 @@
+# Copyright 2023 BentoML Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+import string
+import typing as t
+
+import pydantic
+
+import openllm
+
+
+class PromptFormatter(string.Formatter):
+    def vformat(self, format_string: str, args: t.Sequence[t.Any], kwargs: t.Mapping[str, t.Any]) -> str:
+        if len(args) > 0:
+            raise ValueError("Positional arguments are not supported")
+        return super().vformat(format_string, args, kwargs)
+
+    def check_unused_args(
+        self, used_args: set[int | str], args: t.Sequence[t.Any], kwargs: t.Mapping[str, t.Any]
+    ) -> None:
+        """Check if extra params is passed."""
+        extras = set(kwargs).difference(used_args)
+        if extras:
+            raise KeyError(f"Extra params passed: {extras}")
+
+    def extract_template_variables(self, template: str) -> t.Sequence[str]:
+        """Extract template variables from a template string."""
+        return [field[1] for field in self.parse(template) if field[1] is not None]
+
+
+# TODO: Support jinja2 template, go template and possible other prompt template engine.
+_default_formatter = PromptFormatter()
+
+
+class PromptTemplate(pydantic.BaseModel):
+    template: str
+    input_variables: t.Sequence[str]
+
+    model_config = {"extra": "forbid"}
+
+    def to_str(self, **kwargs: str) -> str:
+        """Generate a prompt from the template and input variables"""
+        if not kwargs:
+            raise ValueError("Keyword arguments are required")
+        if not all(k in kwargs for k in self.input_variables):
+            raise ValueError(f"Missing required input variables: {self.input_variables}")
+        return _default_formatter.format(self.template, **kwargs)
+
+    @classmethod
+    def from_template(cls, template: str) -> PromptTemplate:
+        input_variables = _default_formatter.extract_template_variables(template)
+        return cls(template=template, input_variables=input_variables)
+
+    @classmethod
+    def from_default(cls, model: str) -> PromptTemplate:
+        template = getattr(openllm.utils.get_lazy_module(model), "DEFAULT_PROMPT_TEMPLATE")
+        if template is None:
+            raise ValueError(f"Model {model} does not have a default prompt template.")
+        return cls.from_template(template)