diff --git a/src/llamafactory/v1/core/utils/rendering.py b/src/llamafactory/v1/core/utils/rendering.py
index cbe8383c4..2cb22bfd6 100644
--- a/src/llamafactory/v1/core/utils/rendering.py
+++ b/src/llamafactory/v1/core/utils/rendering.py
@@ -91,7 +91,11 @@ class Renderer:
self.processor = processor
def render_messages(
- self, messages: list[Message], tools: str | None = None, is_generate: bool = False
+ self,
+ messages: list[Message],
+ tools: str | None = None,
+ is_generate: bool = False,
+ enable_thinking: bool = False,
) -> ModelInput:
"""Apply template to messages and convert them to model input.
@@ -99,6 +103,7 @@ class Renderer:
messages (list[Message]): The messages to render.
tools (str | None, optional): The tools to use. Defaults to None.
is_generate (bool, optional): Whether to render for generation. Defaults to False.
+ enable_thinking (bool, optional): Whether to enable thinking mode for generation. Defaults to False.
Returns:
ModelInput: The rendered model input.
@@ -108,7 +113,9 @@ class Renderer:
else:
from ...plugins.model_plugins.rendering import RenderingPlugin
- return RenderingPlugin(self.template).render_messages(self.processor, messages, tools, is_generate)
+ return RenderingPlugin(self.template).render_messages(
+ self.processor, messages, tools, is_generate, enable_thinking
+ )
def parse_message(self, generated_text: str) -> Message:
"""Parse a message in the template format.
diff --git a/src/llamafactory/v1/plugins/model_plugins/rendering.py b/src/llamafactory/v1/plugins/model_plugins/rendering.py
index 8ca8b43fc..566c83f50 100644
--- a/src/llamafactory/v1/plugins/model_plugins/rendering.py
+++ b/src/llamafactory/v1/plugins/model_plugins/rendering.py
@@ -12,224 +12,45 @@
# See the License for the specific language governing permissions and
# limitations under the License.
-import json
-import re
+import importlib
-from ...utils.constants import IGNORE_INDEX
-from ...utils.helper import get_tokenizer
+from ...utils import logging
from ...utils.plugin import BasePlugin
-from ...utils.types import Message, ModelInput, Processor, ToolCall
+from ...utils.types import Message, ModelInput, Processor
+
+
+logger = logging.get_logger(__name__)
class RenderingPlugin(BasePlugin):
+ _attempted_template_imports: set[str] = set()
+
+ def _ensure_template_imported(self) -> None:
+ if self.name is None or self.name in self._attempted_template_imports:
+ return
+
+ full_module_name = f"{__package__}.templates.{self.name}"
+ self._attempted_template_imports.add(self.name)
+ try:
+ importlib.import_module(full_module_name)
+ except Exception as exc:
+ logger.warning(f"[Template Registry] Failed to import {full_module_name}: {exc}")
+
+ def __getitem__(self, method_name: str):
+ self._ensure_template_imported()
+ return super().__getitem__(method_name)
+
def render_messages(
self,
processor: Processor,
messages: list[Message],
tools: str | None = None,
is_generate: bool = False,
+ enable_thinking: bool = False,
) -> ModelInput:
"""Render messages in the template format."""
- return self["render_messages"](processor, messages, tools, is_generate)
+ return self["render_messages"](processor, messages, tools, is_generate, enable_thinking)
def parse_messages(self, generated_text: str) -> Message:
"""Parse messages in the template format."""
return self["parse_messages"](generated_text)
-
-
-def _update_model_input(
- processor: Processor,
- input_ids: list[int],
- labels: list[int],
- loss_weights: list[int],
- temp_str: str,
- temp_weight: float,
-) -> str:
- """Update model input with temporary string."""
- if not temp_str:
- return ""
-
- tokenizer = get_tokenizer(processor)
- temp_ids = tokenizer.encode(temp_str, add_special_tokens=False)
- input_ids.extend(temp_ids)
- loss_weights.extend([temp_weight] * len(temp_ids))
- if temp_weight > 1e-6:
- labels.extend(temp_ids)
- else:
- labels.extend([IGNORE_INDEX] * len(temp_ids))
-
- return ""
-
-
-@RenderingPlugin("qwen3_nothink").register("render_messages")
-def render_qwen3_nothink_messages(
- processor: Processor,
- messages: list[Message],
- tools: str | None = None,
- is_generate: bool = False,
-) -> ModelInput:
- """Render messages in the Qwen3 nothink template format.
-
- See https://huggingface.co/spaces/huggingfacejs/chat-template-playground?modelId=Qwen/Qwen3-4B-Instruct-2507
- """
- input_ids, labels, loss_weights = [], [], []
- temp_str, temp_weight = "", 0.0
- if tools:
- temp_str += "<|im_start|>system\n"
- if messages[0]["role"] == "system":
- for content in messages[0]["content"]:
- if content["type"] == "text":
- temp_str += content["value"]
- else:
- raise ValueError(f"Unsupported content type: {content['type']}")
-
- temp_str += "\n\n"
- temp_weight = messages[0].get("loss_weight", 0.0)
-
- temp_str += (
- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\n"
- "You are provided with function signatures within XML tags:\n"
- )
- try:
- tools = json.loads(tools)
- except json.JSONDecodeError:
- raise ValueError(f"Invalid tools format: {str(tools)}.")
-
- if not isinstance(tools, list):
- tools = [tools]
-
- for tool in tools:
- temp_str += "\n" + json.dumps(tool, ensure_ascii=False)
-
- temp_str += (
- "\n\n\nFor each function call, return a json object with function name "
- 'and arguments within XML tags:\n\n{"name": '
- ', "arguments": }\n<|im_end|>\n'
- )
- elif messages[0]["role"] == "system":
- temp_str += "<|im_start|>system\n"
- for content in messages[0]["content"]:
- if content["type"] == "text":
- temp_str += content["value"]
- else:
- raise ValueError(f"Unsupported content type: {content['type']}")
-
- temp_str += "<|im_end|>\n"
- temp_weight = messages[0].get("loss_weight", 0.0)
-
- temp_str = _update_model_input(processor, input_ids, labels, loss_weights, temp_str, temp_weight)
-
- for turn_idx, message in enumerate(messages):
- if message["role"] == "user" or (message["role"] == "system" and turn_idx != 0):
- temp_str += "<|im_start|>" + message["role"] + "\n"
- for content in message["content"]:
- if content["type"] == "text":
- temp_str += content["value"]
- else:
- raise ValueError(f"Unsupported content type: {content['type']}")
-
- temp_str += "<|im_end|>\n"
- temp_weight = message.get("loss_weight", 0.0)
- elif message["role"] == "assistant":
- temp_str += "<|im_start|>" + message["role"] + "\n"
- for val_idx, content in enumerate(message["content"]):
- if content["type"] == "text":
- temp_str += content["value"]
- elif content["type"] == "reasoning":
- temp_str += "\n" + content["value"] + "\n\n\n" # avoid using special tokens
- elif content["type"] == "tool_call":
- if val_idx != 0 and message["content"][val_idx - 1]["type"] in ["text", "tool_call"]:
- temp_str += "\n"
-
- try:
- tool_call: ToolCall = json.loads(content["value"])
- except json.JSONDecodeError:
- raise ValueError(f"Invalid tool call format: {content['value']}.")
-
- temp_str += (
- '\n{"name": "'
- + tool_call["name"]
- + '", "arguments": '
- + json.dumps(tool_call["arguments"], ensure_ascii=False)
- + "}\n"
- )
-
- else:
- raise ValueError(f"Unsupported content type: {content['type']}")
-
- temp_str += "<|im_end|>\n"
- temp_weight = message.get("loss_weight", 1.0)
- elif message["role"] == "tool":
- if turn_idx == 0 or messages[turn_idx - 1]["role"] != "tool":
- temp_str += "<|im_start|>user"
-
- temp_str += "\n\n"
- for content in message["content"]:
- if content["type"] == "text":
- temp_str += content["value"]
- else:
- raise ValueError(f"Unsupported content type: {content['type']}")
-
- temp_str += "\n"
- if turn_idx == len(messages) - 1 or messages[turn_idx + 1]["role"] != "tool":
- temp_str += "<|im_end|>\n"
-
- temp_weight = message.get("loss_weight", 0.0)
-
- temp_str = _update_model_input(processor, input_ids, labels, loss_weights, temp_str, temp_weight)
-
- if is_generate:
- temp_str += "<|im_start|>assistant\n"
- temp_weight = 0.0
-
- temp_str = _update_model_input(processor, input_ids, labels, loss_weights, temp_str, temp_weight)
-
- attention_mask = [1] * len(input_ids)
- return ModelInput(
- input_ids=input_ids,
- attention_mask=attention_mask,
- labels=labels,
- loss_weights=loss_weights,
- )
-
-
-@RenderingPlugin("qwen3_nothink").register("parse_message")
-def parse_qwen3_nothink_message(generated_text: str) -> Message:
- """Parse a message in the Qwen3 nothink template format. Supports interleaved reasoning and tool calls.
-
- Args:
- generated_text (str): The generated text in the Qwen3 nothink template format.
-
- Returns:
- Message: The parsed message.
- """
- pattern = re.compile(r"<(thinking|tool_call)>\s*(.*?)\s*\s*", re.DOTALL)
- content = []
- last_end = 0
- for match in pattern.finditer(generated_text):
- start, end = match.span()
- if start > last_end:
- text = generated_text[last_end:start].strip()
- if text:
- content.append({"type": "text", "value": text})
-
- tag_type = match.group(1)
- tag_value = match.group(2).strip()
- if tag_type == "thinking":
- content.append({"type": "reasoning", "value": tag_value.strip()})
- elif tag_type == "tool_call":
- try:
- json.loads(tag_value.strip())
- except json.JSONDecodeError:
- raise ValueError(f"Invalid tool call format: {tag_value.strip()}.")
-
- content.append({"type": "tool_call", "value": tag_value.strip()})
-
- last_end = end
-
- if last_end < len(generated_text):
- text = generated_text[last_end:].strip()
- if text:
- content.append({"type": "text", "value": text})
-
- return Message(role="assistant", content=content)
diff --git a/src/llamafactory/v1/plugins/model_plugins/templates/__init__.py b/src/llamafactory/v1/plugins/model_plugins/templates/__init__.py
new file mode 100644
index 000000000..ec0d62554
--- /dev/null
+++ b/src/llamafactory/v1/plugins/model_plugins/templates/__init__.py
@@ -0,0 +1,13 @@
+# Copyright 2025 the LlamaFactory team.
+#
+# 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.
diff --git a/src/llamafactory/v1/plugins/model_plugins/templates/qwen3.py b/src/llamafactory/v1/plugins/model_plugins/templates/qwen3.py
new file mode 100644
index 000000000..e9f479941
--- /dev/null
+++ b/src/llamafactory/v1/plugins/model_plugins/templates/qwen3.py
@@ -0,0 +1,259 @@
+# Copyright 2025 the LlamaFactory team.
+#
+# 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.
+
+import json
+import re
+
+from ....utils.constants import IGNORE_INDEX
+from ....utils.helper import get_tokenizer
+from ....utils.types import Message, ModelInput, Processor, ToolCall
+from ..rendering import RenderingPlugin
+
+
+def _update_model_input(
+ processor: Processor,
+ input_ids: list[int],
+ labels: list[int],
+ loss_weights: list[int],
+ temp_str: str,
+ temp_weight: float,
+) -> str:
+ """Update model input with temporary string."""
+ if not temp_str:
+ return ""
+
+ tokenizer = get_tokenizer(processor)
+ temp_ids = tokenizer.encode(temp_str, add_special_tokens=False)
+ input_ids.extend(temp_ids)
+ loss_weights.extend([temp_weight] * len(temp_ids))
+ if temp_weight > 1e-6:
+ labels.extend(temp_ids)
+ else:
+ labels.extend([IGNORE_INDEX] * len(temp_ids))
+
+ return ""
+
+
+def _concat_text_content(message: Message) -> str:
+ """Concatenate text fields in a message."""
+ message_text = ""
+ for content in message["content"]:
+ if content["type"] == "text":
+ message_text += content["value"]
+ else:
+ raise ValueError(f"Unsupported content type: {content['type']}")
+
+ return message_text
+
+
+def _get_last_query_index(messages: list[Message]) -> int:
+ """Find the last user query index, excluding wrapped tool responses."""
+ last_query_index = len(messages) - 1
+ for idx in range(len(messages) - 1, -1, -1):
+ message = messages[idx]
+ if message["role"] != "user":
+ continue
+
+ user_text = ""
+ is_plain_text = True
+ for content in message["content"]:
+ if content["type"] != "text":
+ is_plain_text = False
+ break
+ user_text += content["value"]
+
+ if not is_plain_text:
+ continue
+
+ if not (user_text.startswith("") and user_text.endswith("")):
+ last_query_index = idx
+ break
+
+ return last_query_index
+
+
+def _split_assistant_content(message: Message) -> tuple[str, str, list[ToolCall]]:
+ """Split assistant message into text, reasoning and tool calls."""
+ text_content = ""
+ reasoning_content = ""
+ tool_calls: list[ToolCall] = []
+
+ for content in message["content"]:
+ if content["type"] == "text":
+ text_content += content["value"]
+ elif content["type"] == "reasoning":
+ reasoning_content += content["value"]
+ elif content["type"] == "tool_call":
+ try:
+ tool_call: ToolCall = json.loads(content["value"])
+ except json.JSONDecodeError:
+ raise ValueError(f"Invalid tool call format: {content['value']}.")
+
+ tool_calls.append(tool_call)
+ else:
+ raise ValueError(f"Unsupported content type: {content['type']}")
+
+ return text_content, reasoning_content, tool_calls
+
+
+@RenderingPlugin("qwen3").register("render_messages")
+def render_qwen3_messages(
+ processor: Processor,
+ messages: list[Message],
+ tools: str | None = None,
+ is_generate: bool = False,
+ enable_thinking: bool = False,
+) -> ModelInput:
+ """Render messages in the Qwen3 template format.
+
+ See https://huggingface.co/spaces/huggingfacejs/chat-template-playground?modelId=Qwen/Qwen3-8B
+ """
+ input_ids, labels, loss_weights = [], [], []
+ temp_str, temp_weight = "", 0.0
+ if tools:
+ temp_str += "<|im_start|>system\n"
+ if messages[0]["role"] == "system":
+ temp_str += _concat_text_content(messages[0]) + "\n\n"
+ temp_weight = messages[0].get("loss_weight", 0.0)
+
+ temp_str += (
+ "# Tools\n\nYou may call one or more functions to assist with the user query.\n\n"
+ "You are provided with function signatures within XML tags:\n"
+ )
+ try:
+ tools = json.loads(tools)
+ except json.JSONDecodeError:
+ raise ValueError(f"Invalid tools format: {str(tools)}.")
+
+ if not isinstance(tools, list):
+ tools = [tools]
+
+ for tool in tools:
+ temp_str += "\n" + json.dumps(tool, ensure_ascii=False)
+
+ temp_str += (
+ "\n\n\nFor each function call, return a json object with function name "
+ 'and arguments within XML tags:\n\n{"name": '
+ ', "arguments": }\n<|im_end|>\n'
+ )
+ elif messages[0]["role"] == "system":
+ temp_str += "<|im_start|>system\n" + _concat_text_content(messages[0]) + "<|im_end|>\n"
+ temp_weight = messages[0].get("loss_weight", 0.0)
+
+ temp_str = _update_model_input(processor, input_ids, labels, loss_weights, temp_str, temp_weight)
+ last_query_index = _get_last_query_index(messages)
+
+ for turn_idx, message in enumerate(messages):
+ if message["role"] == "user" or (message["role"] == "system" and turn_idx != 0):
+ temp_str += "<|im_start|>" + message["role"] + "\n" + _concat_text_content(message) + "<|im_end|>\n"
+ temp_weight = message.get("loss_weight", 0.0)
+ elif message["role"] == "assistant":
+ temp_str += "<|im_start|>" + message["role"] + "\n"
+
+ text_content, reasoning_content, tool_calls = _split_assistant_content(message)
+ if turn_idx > last_query_index and (turn_idx == len(messages) - 1 or reasoning_content):
+ temp_str += "\n" + reasoning_content.strip("\n") + "\n\n\n" + text_content.lstrip("\n")
+ else:
+ temp_str += text_content
+
+ for tool_call_idx, tool_call in enumerate(tool_calls):
+ if (tool_call_idx == 0 and text_content) or tool_call_idx > 0:
+ temp_str += "\n"
+
+ arguments = tool_call.get("arguments")
+ if isinstance(arguments, str):
+ arguments_str = arguments
+ else:
+ arguments_str = json.dumps(arguments, ensure_ascii=False)
+
+ temp_str += (
+ '\n{"name": "'
+ + tool_call["name"]
+ + '", "arguments": '
+ + arguments_str
+ + "}\n"
+ )
+
+ temp_str += "<|im_end|>\n"
+ temp_weight = message.get("loss_weight", 1.0)
+ elif message["role"] == "tool":
+ if turn_idx == 0 or messages[turn_idx - 1]["role"] != "tool":
+ temp_str += "<|im_start|>user"
+
+ temp_str += "\n\n" + _concat_text_content(message) + "\n"
+ if turn_idx == len(messages) - 1 or messages[turn_idx + 1]["role"] != "tool":
+ temp_str += "<|im_end|>\n"
+
+ temp_weight = message.get("loss_weight", 0.0)
+
+ temp_str = _update_model_input(processor, input_ids, labels, loss_weights, temp_str, temp_weight)
+
+ if is_generate:
+ temp_str += "<|im_start|>assistant\n"
+ temp_weight = 0.0
+ if enable_thinking is False:
+ temp_str += "\n\n\n\n"
+
+ temp_str = _update_model_input(processor, input_ids, labels, loss_weights, temp_str, temp_weight)
+
+ attention_mask = [1] * len(input_ids)
+ return ModelInput(
+ input_ids=input_ids,
+ attention_mask=attention_mask,
+ labels=labels,
+ loss_weights=loss_weights,
+ )
+
+
+@RenderingPlugin("qwen3").register("parse_message")
+def parse_qwen3_message(generated_text: str) -> Message:
+ """Parse a message in the Qwen3 template format. Supports interleaved reasoning and tool calls.
+
+ Args:
+ generated_text (str): The generated text in the Qwen3 template format.
+
+ Returns:
+ Message: The parsed message.
+ """
+ pattern = re.compile(r"<(think|tool_call)>\s*(.*?)\s*\s*", re.DOTALL)
+ content = []
+ last_end = 0
+
+ for match in pattern.finditer(generated_text):
+ start, end = match.span()
+ if start > last_end:
+ text = generated_text[last_end:start].strip()
+ if text:
+ content.append({"type": "text", "value": text})
+
+ tag_type = match.group(1)
+ tag_value = match.group(2).strip()
+ if tag_type == "think":
+ content.append({"type": "reasoning", "value": tag_value.strip()})
+ elif tag_type == "tool_call":
+ try:
+ json.loads(tag_value.strip())
+ except json.JSONDecodeError:
+ raise ValueError(f"Invalid tool call format: {tag_value.strip()}.")
+
+ content.append({"type": "tool_call", "value": tag_value.strip()})
+
+ last_end = end
+
+ if last_end < len(generated_text):
+ text = generated_text[last_end:].strip()
+ if text:
+ content.append({"type": "text", "value": text})
+
+ return Message(role="assistant", content=content)
diff --git a/src/llamafactory/v1/plugins/model_plugins/templates/qwen3_nothink.py b/src/llamafactory/v1/plugins/model_plugins/templates/qwen3_nothink.py
new file mode 100644
index 000000000..244835e0f
--- /dev/null
+++ b/src/llamafactory/v1/plugins/model_plugins/templates/qwen3_nothink.py
@@ -0,0 +1,209 @@
+# Copyright 2025 the LlamaFactory team.
+#
+# 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.
+
+import json
+import re
+
+from ....utils.constants import IGNORE_INDEX
+from ....utils.helper import get_tokenizer
+from ....utils.types import Message, ModelInput, Processor, ToolCall
+from ..rendering import RenderingPlugin
+
+
+def _update_model_input(
+ processor: Processor,
+ input_ids: list[int],
+ labels: list[int],
+ loss_weights: list[int],
+ temp_str: str,
+ temp_weight: float,
+) -> str:
+ """Update model input with temporary string."""
+ if not temp_str:
+ return ""
+
+ tokenizer = get_tokenizer(processor)
+ temp_ids = tokenizer.encode(temp_str, add_special_tokens=False)
+ input_ids.extend(temp_ids)
+ loss_weights.extend([temp_weight] * len(temp_ids))
+ if temp_weight > 1e-6:
+ labels.extend(temp_ids)
+ else:
+ labels.extend([IGNORE_INDEX] * len(temp_ids))
+
+ return ""
+
+
+def _concat_text_content(message: Message) -> str:
+ """Concatenate text fields in a message."""
+ message_text = ""
+ for content in message["content"]:
+ if content["type"] == "text":
+ message_text += content["value"]
+ else:
+ raise ValueError(f"Unsupported content type: {content['type']}")
+
+ return message_text
+
+
+@RenderingPlugin("qwen3_nothink").register("render_messages")
+def render_qwen3_nothink_messages(
+ processor: Processor,
+ messages: list[Message],
+ tools: str | None = None,
+ is_generate: bool = False,
+ enable_thinking: bool = False,
+) -> ModelInput:
+ """Render messages in the Qwen3 nothink template format.
+
+ See https://huggingface.co/spaces/huggingfacejs/chat-template-playground?modelId=Qwen/Qwen3-4B-Instruct-2507
+ """
+ input_ids, labels, loss_weights = [], [], []
+ temp_str, temp_weight = "", 0.0
+ if tools:
+ temp_str += "<|im_start|>system\n"
+ if messages[0]["role"] == "system":
+ temp_str += _concat_text_content(messages[0]) + "\n\n"
+ temp_weight = messages[0].get("loss_weight", 0.0)
+
+ temp_str += (
+ "# Tools\n\nYou may call one or more functions to assist with the user query.\n\n"
+ "You are provided with function signatures within XML tags:\n"
+ )
+
+ try:
+ tools = json.loads(tools)
+ except json.JSONDecodeError:
+ raise ValueError(f"Invalid tools format: {str(tools)}.")
+
+ if not isinstance(tools, list):
+ tools = [tools]
+
+ for tool in tools:
+ temp_str += "\n" + json.dumps(tool, ensure_ascii=False)
+
+ temp_str += (
+ "\n\n\nFor each function call, return a json object with function name "
+ 'and arguments within XML tags:\n\n{"name": '
+ ', "arguments": }\n<|im_end|>\n'
+ )
+ elif messages[0]["role"] == "system":
+ temp_str += "<|im_start|>system\n" + _concat_text_content(messages[0]) + "<|im_end|>\n"
+ temp_weight = messages[0].get("loss_weight", 0.0)
+
+ temp_str = _update_model_input(processor, input_ids, labels, loss_weights, temp_str, temp_weight)
+
+ for turn_idx, message in enumerate(messages):
+ if message["role"] == "user" or (message["role"] == "system" and turn_idx != 0):
+ temp_str += "<|im_start|>" + message["role"] + "\n" + _concat_text_content(message) + "<|im_end|>\n"
+ temp_weight = message.get("loss_weight", 0.0)
+ elif message["role"] == "assistant":
+ temp_str += "<|im_start|>" + message["role"] + "\n"
+ for val_idx, content in enumerate(message["content"]):
+ if content["type"] == "text":
+ temp_str += content["value"]
+ elif content["type"] == "reasoning":
+ temp_str += "\n" + content["value"] + "\n\n\n" # avoid using special tokens
+ elif content["type"] == "tool_call":
+ if val_idx != 0 and message["content"][val_idx - 1]["type"] in ["text", "tool_call"]:
+ temp_str += "\n"
+
+ try:
+ tool_call: ToolCall = json.loads(content["value"])
+ except json.JSONDecodeError:
+ raise ValueError(f"Invalid tool call format: {content['value']}.")
+
+ temp_str += (
+ '\n{"name": "'
+ + tool_call["name"]
+ + '", "arguments": '
+ + json.dumps(tool_call["arguments"], ensure_ascii=False)
+ + "}\n"
+ )
+
+ else:
+ raise ValueError(f"Unsupported content type: {content['type']}")
+
+ temp_str += "<|im_end|>\n"
+ temp_weight = message.get("loss_weight", 1.0)
+ elif message["role"] == "tool":
+ if turn_idx == 0 or messages[turn_idx - 1]["role"] != "tool":
+ temp_str += "<|im_start|>user"
+
+ temp_str += "\n\n" + _concat_text_content(message) + "\n"
+ if turn_idx == len(messages) - 1 or messages[turn_idx + 1]["role"] != "tool":
+ temp_str += "<|im_end|>\n"
+
+ temp_weight = message.get("loss_weight", 0.0)
+
+ temp_str = _update_model_input(processor, input_ids, labels, loss_weights, temp_str, temp_weight)
+
+ if is_generate:
+ temp_str += "<|im_start|>assistant\n"
+ temp_weight = 0.0
+ if enable_thinking:
+ raise ValueError("The qwen3_nothink template does not support thinking mode.")
+
+ temp_str = _update_model_input(processor, input_ids, labels, loss_weights, temp_str, temp_weight)
+
+ attention_mask = [1] * len(input_ids)
+ return ModelInput(
+ input_ids=input_ids,
+ attention_mask=attention_mask,
+ labels=labels,
+ loss_weights=loss_weights,
+ )
+
+
+@RenderingPlugin("qwen3_nothink").register("parse_message")
+def parse_qwen3_nothink_message(generated_text: str) -> Message:
+ """Parse a message in the Qwen3 nothink template format. Supports interleaved reasoning and tool calls.
+
+ Args:
+ generated_text (str): The generated text in the Qwen3 nothink template format.
+
+ Returns:
+ Message: The parsed message.
+ """
+ pattern = re.compile(r"<(thinking|tool_call)>\s*(.*?)\s*\s*", re.DOTALL)
+ content = []
+ last_end = 0
+
+ for match in pattern.finditer(generated_text):
+ start, end = match.span()
+ if start > last_end:
+ text = generated_text[last_end:start].strip()
+ if text:
+ content.append({"type": "text", "value": text})
+
+ tag_type = match.group(1)
+ tag_value = match.group(2).strip()
+ if tag_type == "thinking":
+ content.append({"type": "reasoning", "value": tag_value.strip()})
+ elif tag_type == "tool_call":
+ try:
+ json.loads(tag_value.strip())
+ except json.JSONDecodeError:
+ raise ValueError(f"Invalid tool call format: {tag_value.strip()}.")
+
+ content.append({"type": "tool_call", "value": tag_value.strip()})
+
+ last_end = end
+
+ if last_end < len(generated_text):
+ text = generated_text[last_end:].strip()
+ if text:
+ content.append({"type": "text", "value": text})
+
+ return Message(role="assistant", content=content)
diff --git a/src/llamafactory/v1/utils/types.py b/src/llamafactory/v1/utils/types.py
index 2f3906968..b1f7d52cf 100644
--- a/src/llamafactory/v1/utils/types.py
+++ b/src/llamafactory/v1/utils/types.py
@@ -85,7 +85,7 @@ class DistributedConfig(TypedDict, total=False):
class Content(TypedDict):
- type: Literal["text", "reasoning", "tool_call", "image_url"]
+ type: Literal["text", "reasoning", "tool_call", "image_url", "video_url", "audio_url"]
"""Type of the content."""
value: str
"""Value of the content."""