diff --git a/README.md b/README.md
index 214b72b8..c02b7750 100644
--- a/README.md
+++ b/README.md
@@ -53,9 +53,7 @@ Choose your path:
 - **Documentation**: https://llamafactory.readthedocs.io/en/latest/
 - **Colab (free)**: https://colab.research.google.com/drive/1eRTPn37ltBbYsISy9Aw2NuI2Aq5CQrD9?usp=sharing
 - **Local machine**: Please refer to [usage](#getting-started)
-- **PAI-DSW (free trial)**: [Llama3 Example](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory) | [Qwen2-VL Example](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_qwen2vl) | [DeepSeek-R1-Distill Example](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_deepseek_r1_distill_7b)
-- **Amazon SageMaker**: [Blog](https://aws.amazon.com/cn/blogs/machine-learning/how-apoidea-group-enhances-visual-information-extraction-from-banking-documents-with-multimodal-models-using-llama-factory-on-amazon-sagemaker-hyperpod/)
-- **Easy Dataset**: [Fine-tune on Synthetic Data](https://buaa-act.feishu.cn/wiki/GVzlwYcRFiR8OLkHbL6cQpYin7g)
+- **PAI-DSW (free trial)**: https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory
 
 > [!NOTE]
 > Except for the above links, all other websites are unauthorized third-party websites. Please carefully use them.
@@ -107,7 +105,7 @@ Choose your path:
 
 - [How Apoidea Group enhances visual information extraction from banking documents with multimodal models using LLaMA-Factory on Amazon SageMaker HyperPod](https://aws.amazon.com/cn/blogs/machine-learning/how-apoidea-group-enhances-visual-information-extraction-from-banking-documents-with-multimodal-models-using-llama-factory-on-amazon-sagemaker-hyperpod/) (English)
 - [Easy Dataset × LLaMA Factory: Enabling LLMs to Efficiently Learn Domain Knowledge](https://buaa-act.feishu.cn/wiki/GVzlwYcRFiR8OLkHbL6cQpYin7g) (English)
-- [LLaMA Factory: Fine-tuning the DeepSeek-R1-Distill-Qwen-7B Model For News Classifier](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_deepseek_r1_distill_7b) (Chinese)
+- [LLaMA Factory: Fine-tuning the DeepSeek-R1-Distill-Qwen-7B Model for News Classifier](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_deepseek_r1_distill_7b) (Chinese)
 
 <details><summary>All Blogs</summary>
 
@@ -918,6 +916,7 @@ If you have a project that should be incorporated, please contact via email or c
 1. **[RAG-Retrieval](https://github.com/NLPJCL/RAG-Retrieval)**: A full pipeline for RAG retrieval model fine-tuning, inference, and distillation. [[blog]](https://zhuanlan.zhihu.com/p/987727357)
 1. **[360-LLaMA-Factory](https://github.com/Qihoo360/360-LLaMA-Factory)**: A modified library that supports long sequence SFT & DPO using ring attention.
 1. **[Sky-T1](https://novasky-ai.github.io/posts/sky-t1/)**: An o1-like model fine-tuned by NovaSky AI with very small cost.
+1. **[WeClone](https://github.com/xming521/WeClone)**: One-stop solution for creating your digital avatar from chat logs.
 
 </details>
 
diff --git a/README_zh.md b/README_zh.md
index 342cdf84..f9029948 100644
--- a/README_zh.md
+++ b/README_zh.md
@@ -55,9 +55,7 @@ https://github.com/user-attachments/assets/43b700c6-a178-41db-b1f8-8190a5d3fcfc
 - **框架文档（昇腾 NPU）**：https://ascend.github.io/docs/sources/llamafactory/
 - **Colab（免费）**：https://colab.research.google.com/drive/1d5KQtbemerlSDSxZIfAaWXhKr30QypiK?usp=sharing
 - **本地机器**：请见[如何使用](#如何使用)
-- **PAI-DSW（免费试用）**：[Llama3 案例](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory) | [Qwen2-VL 案例](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_qwen2vl) | [DeepSeek-R1-Distill 案例](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_deepseek_r1_distill_7b)
-- **Amazon SageMaker**：[博客](https://aws.amazon.com/cn/blogs/china/a-one-stop-code-free-model-fine-tuning-deployment-platform-based-on-sagemaker-and-llama-factory/)
-- **Easy Dataset**：[数据蒸馏微调](https://buaa-act.feishu.cn/wiki/KY9xwTGs1iqHrRkjXBwcZP9WnL9)
+- **PAI-DSW（免费试用）**：https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory
 
 > [!NOTE]
 > 除上述链接以外的其他网站均为未经许可的第三方网站，请小心甄别。
@@ -109,12 +107,12 @@ https://github.com/user-attachments/assets/43b700c6-a178-41db-b1f8-8190a5d3fcfc
 
 - [通过亚马逊 SageMaker HyperPod 上的 LLaMA-Factory 增强多模态模型银行文档的视觉信息提取](https://aws.amazon.com/cn/blogs/machine-learning/how-apoidea-group-enhances-visual-information-extraction-from-banking-documents-with-multimodal-models-using-llama-factory-on-amazon-sagemaker-hyperpod/)（英文）
 - [Easy Dataset × LLaMA Factory: 让大模型高效学习领域知识](https://buaa-act.feishu.cn/wiki/KY9xwTGs1iqHrRkjXBwcZP9WnL9)（中文）
-- [LLaMA Factory：微调DeepSeek-R1-Distill-Qwen-7B模型实现新闻标题分类器](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_deepseek_r1_distill_7b)（中文）
+- [LLaMA Factory：微调 DeepSeek-R1-Distill-Qwen-7B 模型实现新闻标题分类器](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_deepseek_r1_distill_7b)（中文）
 
 <details><summary>全部博客</summary>
 
 - [基于 Amazon SageMaker 和 LLaMA-Factory 打造一站式无代码模型微调部署平台 Model Hub](https://aws.amazon.com/cn/blogs/china/a-one-stop-code-free-model-fine-tuning-deployment-platform-based-on-sagemaker-and-llama-factory/)（中文）
-- [LLaMA Factory多模态微调实践：微调Qwen2-VL构建文旅大模型](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_qwen2vl)（中文）
+- [LLaMA Factory 多模态微调实践：微调 Qwen2-VL 构建文旅大模型](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory_qwen2vl)（中文）
 - [LLaMA Factory：微调LLaMA3模型实现角色扮演](https://gallery.pai-ml.com/#/preview/deepLearning/nlp/llama_factory)（中文）
 
 </details>
@@ -920,6 +918,7 @@ swanlab_run_name: test_run # 可选
 1. **[RAG-Retrieval](https://github.com/NLPJCL/RAG-Retrieval)**：一个全链路 RAG 检索模型微调、推理和蒸馏代码库。[[blog]](https://zhuanlan.zhihu.com/p/987727357)
 1. **[360-LLaMA-Factory](https://github.com/Qihoo360/360-LLaMA-Factory)**：一个魔改后的代码库，通过 Ring Attention 支持长序列的 SFT 和 DPO 训练。
 1. **[Sky-T1](https://novasky-ai.github.io/posts/sky-t1/)**：由 NovaSky AI 微调的低成本类 o1 长推理模型。
+1. **[WeClone](https://github.com/xming521/WeClone)**：从聊天记录创造数字分身的一站式解决方案。
 
 </details>
 
diff --git a/src/llamafactory/data/tool_utils.py b/src/llamafactory/data/tool_utils.py
index b2f2798b..37856151 100644
--- a/src/llamafactory/data/tool_utils.py
+++ b/src/llamafactory/data/tool_utils.py
@@ -125,11 +125,7 @@ class DefaultToolUtils(ToolUtils):
     @override
     @staticmethod
     def function_formatter(functions: list["FunctionCall"]) -> str:
-        function_text = ""
-        for name, arguments in functions:
-            function_text += f"Action: {name}\nAction Input: {arguments}\n"
-
-        return function_text
+        return "\n".join([f"Action: {name}\nAction Input: {arguments}" for name, arguments in functions])
 
     @override
     @staticmethod
@@ -210,24 +206,23 @@ class Llama3ToolUtils(ToolUtils):
     @override
     @staticmethod
     def function_formatter(functions: list["FunctionCall"]) -> str:
-        if len(functions) > 1:
-            raise ValueError("Llama-3 does not support parallel functions.")
-
-        return f'{{"name": "{functions[0].name}", "parameters": {functions[0].arguments}}}'
+        function_objects = [{"name": name, "parameters": json.loads(arguments)} for name, arguments in functions]
+        return json.dumps(function_objects[0] if len(function_objects) == 1 else function_objects, ensure_ascii=False)
 
     @override
     @staticmethod
     def tool_extractor(content: str) -> Union[str, list["FunctionCall"]]:
         try:
-            tool = json.loads(content.strip())
+            tools = json.loads(content.strip())
         except json.JSONDecodeError:
             return content
 
-        if "name" not in tool or "parameters" not in tool:
+        tools = [tools] if not isinstance(tools, list) else tools
+        try:
+            return [FunctionCall(tool["name"], json.dumps(tool["parameters"], ensure_ascii=False)) for tool in tools]
+        except KeyError:
             return content
 
-        return [FunctionCall(tool["name"], json.dumps(tool["parameters"], ensure_ascii=False))]
-
 
 class MistralToolUtils(ToolUtils):
     r"""Mistral v0.3 tool using template."""
@@ -244,11 +239,9 @@ class MistralToolUtils(ToolUtils):
     @override
     @staticmethod
     def function_formatter(functions: list["FunctionCall"]) -> str:
-        function_texts = []
-        for name, arguments in functions:
-            function_texts.append(f'{{"name": "{name}", "arguments": {arguments}}}')
-
-        return "[" + ", ".join(function_texts) + "]"
+        return json.dumps(
+            [{"name": name, "arguments": json.loads(arguments)} for name, arguments in functions], ensure_ascii=False
+        )
 
     @override
     @staticmethod
@@ -258,17 +251,11 @@ class MistralToolUtils(ToolUtils):
         except json.JSONDecodeError:
             return content
 
-        if not isinstance(tools, list):
-            tools = [tools]
-
-        results = []
-        for tool in tools:
-            if "name" not in tool or "arguments" not in tool:
-                return content
-
-            results.append(FunctionCall(tool["name"], json.dumps(tool["arguments"], ensure_ascii=False)))
-
-        return results
+        tools = [tools] if not isinstance(tools, list) else tools
+        try:
+            return [FunctionCall(tool["name"], json.dumps(tool["arguments"], ensure_ascii=False)) for tool in tools]
+        except KeyError:
+            return content
 
 
 class QwenToolUtils(ToolUtils):
@@ -287,13 +274,11 @@ class QwenToolUtils(ToolUtils):
     @override
     @staticmethod
     def function_formatter(functions: list["FunctionCall"]) -> str:
-        function_texts = []
-        for name, arguments in functions:
-            function_texts.append(
-                "<tool_call>\n" + f'{{"name": "{name}", "arguments": {arguments}}}' + "\n</tool_call>"
-            )
-
-        return "\n".join(function_texts)
+        function_texts = [
+            json.dumps({"name": name, "arguments": json.loads(arguments)}, ensure_ascii=False)
+            for name, arguments in functions
+        ]
+        return "\n".join([f"<tool_call>\n{text}\n</tool_call>" for text in function_texts])
 
     @override
     @staticmethod
diff --git a/tests/data/test_formatter.py b/tests/data/test_formatter.py
index 7e08465a..00b8c649 100644
--- a/tests/data/test_formatter.py
+++ b/tests/data/test_formatter.py
@@ -50,7 +50,7 @@ def test_function_formatter():
     formatter = FunctionFormatter(slots=["{{content}}", "</s>"], tool_format="default")
     tool_calls = json.dumps(FUNCTION)
     assert formatter.apply(content=tool_calls) == [
-        """Action: tool_name\nAction Input: {"foo": "bar", "size": 10}\n""",
+        """Action: tool_name\nAction Input: {"foo": "bar", "size": 10}""",
         "</s>",
     ]
 
@@ -60,7 +60,7 @@ def test_multi_function_formatter():
     tool_calls = json.dumps([FUNCTION] * 2)
     assert formatter.apply(content=tool_calls) == [
         """Action: tool_name\nAction Input: {"foo": "bar", "size": 10}\n"""
-        """Action: tool_name\nAction Input: {"foo": "bar", "size": 10}\n""",
+        """Action: tool_name\nAction Input: {"foo": "bar", "size": 10}""",
         "</s>",
     ]
 
@@ -85,7 +85,7 @@ def test_default_tool_formatter():
 
 def test_default_tool_extractor():
     formatter = ToolFormatter(tool_format="default")
-    result = """Action: test_tool\nAction Input: {"foo": "bar", "size": 10}\n"""
+    result = """Action: test_tool\nAction Input: {"foo": "bar", "size": 10}"""
     assert formatter.extract(result) == [("test_tool", """{"foo": "bar", "size": 10}""")]
 
 
@@ -93,7 +93,7 @@ def test_default_multi_tool_extractor():
     formatter = ToolFormatter(tool_format="default")
     result = (
         """Action: test_tool\nAction Input: {"foo": "bar", "size": 10}\n"""
-        """Action: another_tool\nAction Input: {"foo": "job", "size": 2}\n"""
+        """Action: another_tool\nAction Input: {"foo": "job", "size": 2}"""
     )
     assert formatter.extract(result) == [
         ("test_tool", """{"foo": "bar", "size": 10}"""),
@@ -125,12 +125,22 @@ def test_glm4_tool_extractor():
 
 def test_llama3_function_formatter():
     formatter = FunctionFormatter(slots=["{{content}}<|eot_id|>"], tool_format="llama3")
-    tool_calls = json.dumps({"name": "tool_name", "arguments": {"foo": "bar", "size": 10}})
+    tool_calls = json.dumps(FUNCTION)
     assert formatter.apply(content=tool_calls) == [
         """{"name": "tool_name", "parameters": {"foo": "bar", "size": 10}}<|eot_id|>"""
     ]
 
 
+def test_llama3_multi_function_formatter():
+    formatter = FunctionFormatter(slots=["{{content}}<|eot_id|>"], tool_format="llama3")
+    tool_calls = json.dumps([FUNCTION] * 2)
+    assert formatter.apply(content=tool_calls) == [
+        """[{"name": "tool_name", "parameters": {"foo": "bar", "size": 10}}, """
+        """{"name": "tool_name", "parameters": {"foo": "bar", "size": 10}}]"""
+        """<|eot_id|>"""
+    ]
+
+
 def test_llama3_tool_formatter():
     formatter = ToolFormatter(tool_format="llama3")
     date = datetime.now().strftime("%d %b %Y")
@@ -150,6 +160,18 @@ def test_llama3_tool_extractor():
     assert formatter.extract(result) == [("test_tool", """{"foo": "bar", "size": 10}""")]
 
 
+def test_llama3_multi_tool_extractor():
+    formatter = ToolFormatter(tool_format="llama3")
+    result = (
+        """[{"name": "test_tool", "parameters": {"foo": "bar", "size": 10}}, """
+        """{"name": "another_tool", "parameters": {"foo": "job", "size": 2}}]"""
+    )
+    assert formatter.extract(result) == [
+        ("test_tool", """{"foo": "bar", "size": 10}"""),
+        ("another_tool", """{"foo": "job", "size": 2}"""),
+    ]
+
+
 def test_mistral_function_formatter():
     formatter = FunctionFormatter(slots=["[TOOL_CALLS] {{content}}", "</s>"], tool_format="mistral")
     tool_calls = json.dumps(FUNCTION)