fix tool formatter, allow parallel function #4362

Former-commit-id: cd75b1fe9d91fb52a9ae6de7435302ff06b4d933

src/llamafactory/api/chat.py

@@ -92,9 +92,11 @@ def _process_request(
             raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid role")
 
         if message.role == Role.ASSISTANT and isinstance(message.tool_calls, list) and len(message.tool_calls):
-            name = message.tool_calls[0].function.name
+            tool_calls = [
-            arguments = message.tool_calls[0].function.arguments
+                {"name": tool_call.function.name, "argument": tool_call.function.arguments}
-            content = json.dumps({"name": name, "argument": arguments}, ensure_ascii=False)
+                for tool_call in message.tool_calls
+            ]
+            content = json.dumps(tool_calls, ensure_ascii=False)
             input_messages.append({"role": ROLE_MAPPING[Role.FUNCTION], "content": content})
         elif isinstance(message.content, list):
             for input_item in message.content:
@@ -118,7 +120,7 @@ def _process_request(
     if isinstance(tool_list, list) and len(tool_list):
         try:
             tools = json.dumps([dictify(tool.function) for tool in tool_list], ensure_ascii=False)
-        except Exception:
+        except json.JSONDecodeError:
             raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid tools")
     else:
         tools = None
@@ -160,17 +162,16 @@ async def create_chat_completion_response(
     choices = []
     for i, response in enumerate(responses):
         if tools:
-            result = chat_model.engine.template.format_tools.extract(response.response_text)
+            result = chat_model.engine.template.extract_tool(response.response_text)
         else:
             result = response.response_text
 
         if isinstance(result, list):
             tool_calls = []
             for tool in result:
-                name, arguments = tool
+                function = Function(name=tool[0], arguments=tool[1])
-                function = Function(name=name, arguments=arguments)
+                tool_calls.append(FunctionCall(id="call_{}".format(uuid.uuid4().hex), function=function))
-                tool_call = FunctionCall(id="call_{}".format(uuid.uuid4().hex), function=function)
+
-                tool_calls.append(tool_call)
             response_message = ChatCompletionMessage(role=Role.ASSISTANT, tool_calls=tool_calls)
             finish_reason = Finish.TOOL
         else:

src/llamafactory/data/formatter.py

@@ -22,29 +22,20 @@ from typing import Any, Dict, List, Literal, Optional, Sequence, Set, Tuple, Uni
 SLOTS = Sequence[Union[str, Set[str], Dict[str, str]]]
 
 
-JSON_FORMAT_PROMPT = (
+DEFAULT_TOOL_PROMPT = (
-    """, in a JSON format representing the kwargs (e.g. ```{"input": "hello world", "num_beams": 5}```)"""
-)
-
-
-TOOL_SYSTEM_PROMPT = (
     "You have access to the following tools:\n{tool_text}"
     "Use the following format if using a tool:\n"
     "```\n"
     "Action: tool name (one of [{tool_names}]).\n"
-    "Action Input: the input to the tool{format_prompt}.\n"
+    "Action Input: the input to the tool, in a JSON format representing the kwargs "
+    """(e.g. ```{{"input": "hello world", "num_beams": 5}}```).\n"""
     "```\n"
 )
 
 
-GLM4_TOOL_SUFFIX_PROMPT = (
-    "在调用上述函数时，请使用 Json 格式表示调用的参数。"
-)
-
 GLM4_TOOL_PROMPT = (
-    "你是一个名为 GLM-4 的人工智能助手。你是基于智谱AI训练的语言模型 GLM-4 模型开发的，你的任务是针对用户的问题和要求提供适当的答复和支持，"
+    "你是一个名为 GLM-4 的人工智能助手。你是基于智谱AI训练的语言模型 GLM-4 模型开发的，"
-    "{tool_text}"
+    "你的任务是针对用户的问题和要求提供适当的答复和支持。{tool_text}"
-    
 )
 
 
@@ -73,32 +64,19 @@ def default_tool_formatter(tools: List[Dict[str, Any]]) -> str:
         )
         tool_names.append(tool["name"])
 
-    return TOOL_SYSTEM_PROMPT.format(
+    return DEFAULT_TOOL_PROMPT.format(tool_text=tool_text, tool_names=", ".join(tool_names))
-        tool_text=tool_text, tool_names=", ".join(tool_names), format_prompt=JSON_FORMAT_PROMPT
-    )
-
-
-def glm4_tool_formatter(tools: List[Dict[str, Any]]) -> str:
-    tool_text = ""
-    for tool in tools:
-        tool_name = tool["name"]
-        tool_text += f"\n\n## {tool_name}\n\n{json.dumps(tool, ensure_ascii=False, indent=4)}\n{GLM4_TOOL_SUFFIX_PROMPT}"
-    return GLM4_TOOL_PROMPT.format(tool_text=tool_text)
 
 
 def default_tool_extractor(content: str) -> Union[str, List[Tuple[str, str]]]:
-    regex = re.compile(r"Action:\s*([a-zA-Z0-9_]+)\s*Action Input:\s*({.*?})(?=\nAction:|\Z)", re.DOTALL)
+    regex = re.compile(r"Action:\s*([a-zA-Z0-9_]+)\s*Action Input:\s*(.+?)(?=\s*Action:|$)", re.DOTALL)
-    action_match = re.findall(regex, content)
+    action_match: List[Tuple[str, str]] = re.findall(regex, content)
     if not action_match:
         return content
 
     results = []
-    
     for match in action_match:
-        tool_name, tool_input = match
+        tool_name = match[0].strip()
-        tool_name = tool_name.strip()
+        tool_input = match[1].strip().strip('"').strip("```")
-        tool_input = tool_input.strip().strip('"').strip("```")
-
         try:
             arguments = json.loads(tool_input)
             results.append((tool_name, json.dumps(arguments, ensure_ascii=False)))
@@ -108,18 +86,27 @@ def default_tool_extractor(content: str) -> Union[str, List[Tuple[str, str]]]:
     return results
 
 
+def glm4_tool_formatter(tools: List[Dict[str, Any]]) -> str:
+    tool_text = ""
+    for tool in tools:
+        tool_text += "\n\n## {name}\n\n{body}\n在调用上述函数时，请使用 Json 格式表示调用的参数。".format(
+            name=tool["name"], body=json.dumps(tool, indent=4, ensure_ascii=False)
+        )
+
+    return GLM4_TOOL_PROMPT.format(tool_text=tool_text)
+
+
 def glm4_tool_extractor(content: str) -> Union[str, List[Tuple[str, str]]]:
-    lines = content.strip().split("\n")
+    if "\n" not in content:
-    if len(lines) != 2:
         return content
-    tool_name = lines[0].strip()
+
-    tool_input = lines[1].strip()
+    tool_name, tool_input = content.split("\n", maxsplit=1)
     try:
         arguments = json.loads(tool_input)
     except json.JSONDecodeError:
         return content
-    return [(tool_name, json.dumps(arguments, ensure_ascii=False))]
 
+    return [(tool_name, json.dumps(arguments, ensure_ascii=False))]
 
 
 @dataclass
@@ -193,22 +180,28 @@ class FunctionFormatter(Formatter):
 
     def apply(self, **kwargs) -> SLOTS:
         content = kwargs.pop("content")
+        functions: List[Tuple[str, str]] = []
         try:
-            function = json.loads(content)
+            tool_calls = json.loads(content)
-            name = function["name"]
+            if not isinstance(tool_calls, list):  # parallel function call
-            arguments = json.dumps(function["arguments"], ensure_ascii=False)
+                tool_calls = [tool_calls]
-        except Exception:
+
-            name, arguments = "", ""
+            for tool_call in tool_calls:
+                functions.append((tool_call["name"], json.dumps(tool_call["arguments"], ensure_ascii=False)))
+
+        except json.JSONDecodeError:
+            functions = []
 
         elements = []
-        for slot in self.slots:
+        for name, arguments in functions:
-            if isinstance(slot, str):
+            for slot in self.slots:
-                slot = slot.replace("{{name}}", name).replace("{{arguments}}", arguments)
+                if isinstance(slot, str):
-                elements.append(slot)
+                    slot = slot.replace("{{name}}", name).replace("{{arguments}}", arguments)
-            elif isinstance(slot, (dict, set)):
+                    elements.append(slot)
-                elements.append(slot)
+                elif isinstance(slot, (dict, set)):
-            else:
+                    elements.append(slot)
-                raise RuntimeError("Input must be string, set[str] or dict[str, str], got {}".format(type(slot)))
+                else:
+                    raise RuntimeError("Input must be string, set[str] or dict[str, str], got {}".format(type(slot)))
 
         return elements
 
@@ -216,29 +209,22 @@ class FunctionFormatter(Formatter):
 @dataclass
 class ToolFormatter(Formatter):
     def __post_init__(self):
-        if self.tool_format is None:
+        if self.tool_format == "default":
+            self._tool_formatter = default_tool_formatter
+            self._tool_extractor = default_tool_extractor
+        elif self.tool_format == "glm4":
+            self._tool_formatter = glm4_tool_formatter
+            self._tool_extractor = glm4_tool_extractor
+        else:
             raise ValueError("Tool format was not found.")
 
     def apply(self, **kwargs) -> SLOTS:
         content = kwargs.pop("content")
         try:
             tools = json.loads(content)
-            if not len(tools):
+            return [self._tool_formatter(tools) if len(tools) != 0 else ""]
-                return [""]
+        except json.JSONDecodeError:
-
-            if self.tool_format == "default":
-                return [default_tool_formatter(tools)]
-            elif self.tool_format == "glm4":
-                return [glm4_tool_formatter(tools)]
-            else:
-                raise NotImplementedError
-        except Exception:
             return [""]
 
     def extract(self, content: str) -> Union[str, List[Tuple[str, str]]]:
-        if self.tool_format == "default":
+        return self._tool_extractor(content)
-            return default_tool_extractor(content)
-        elif self.tool_format == "glm4":
-            return glm4_tool_extractor(content)
-        else:
-            raise NotImplementedError

src/llamafactory/data/template.py

@@ -79,6 +79,12 @@ class Template:
         """
         return self._encode(tokenizer, messages, system, tools, cutoff_len, reserved_label_len)
 
+    def extract_tool(self, content: str) -> Union[str, List[Tuple[str, str]]]:
+        r"""
+        Extracts tool message.
+        """
+        return self.format_tools.extract(content)
+
     def _encode(
         self,
         tokenizer: "PreTrainedTokenizer",
@@ -100,7 +106,8 @@ class Template:
             if i == 0 and (system or tools or self.force_system):
                 tool_text = self.format_tools.apply(content=tools)[0] if tools else ""
                 elements += self.format_system.apply(content=(system + tool_text))
-            elif i > 0 and i % 2 == 0:
+
+            if i > 0 and i % 2 == 0:
                 elements += self.format_separator.apply()
 
             if message["role"] == Role.USER.value:
@@ -191,7 +198,8 @@ class Llama2Template(Template):
             if i == 0 and (system or tools or self.force_system):
                 tool_text = self.format_tools.apply(content=tools)[0] if tools else ""
                 system_text = self.format_system.apply(content=(system + tool_text))[0]
-            elif i > 0 and i % 2 == 0:
+
+            if i > 0 and i % 2 == 0:
                 elements += self.format_separator.apply()
 
             if message["role"] == Role.USER.value:
@@ -259,7 +267,9 @@ def _register_template(
     template_class = Llama2Template if name.startswith("llama2") else Template
     default_user_formatter = StringFormatter(slots=["{{content}}"])
     default_assistant_formatter = StringFormatter(slots=["{{content}}"] + eos_slots)
-    default_function_formatter = FunctionFormatter(slots=["Action: {{name}}\nAction Input: {{arguments}}"] + eos_slots)
+    default_function_formatter = FunctionFormatter(
+        slots=["Action: {{name}}\nAction Input: {{arguments}}\n"] + eos_slots
+    )
     default_tool_formatter = ToolFormatter(tool_format="default")
     default_separator_formatter = EmptyFormatter()
     TEMPLATES[name] = template_class(

src/llamafactory/webui/chatter.py

@@ -140,16 +140,15 @@ class WebChatModel(ChatModel):
         ):
             response += new_text
             if tools:
-                result = self.engine.template.format_tools.extract(response)
+                result = self.engine.template.extract_tool(response)
             else:
                 result = response
 
-            if isinstance(result, tuple):
+            if isinstance(result, list):
-                name, arguments = result
+                tool_calls = [{"name": tool[0], "arguments": json.loads(tool[1])} for tool in result]
-                arguments = json.loads(arguments)
+                tool_calls = json.dumps(tool_calls, indent=4, ensure_ascii=False)
-                tool_call = json.dumps({"name": name, "arguments": arguments}, ensure_ascii=False)
+                output_messages = messages + [{"role": Role.FUNCTION.value, "content": tool_calls}]
-                output_messages = messages + [{"role": Role.FUNCTION.value, "content": tool_call}]
+                bot_text = "```json\n" + tool_calls + "\n```"
-                bot_text = "```json\n" + tool_call + "\n```"
             else:
                 output_messages = messages + [{"role": Role.ASSISTANT.value, "content": result}]
                 bot_text = result

tests/data/test_formatter.py

@@ -0,0 +1,125 @@
+# Copyright 2024 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
+
+from llamafactory.data.formatter import EmptyFormatter, FunctionFormatter, StringFormatter, ToolFormatter
+
+
+def test_empty_formatter():
+    formatter = EmptyFormatter(slots=["\n"])
+    assert formatter.apply() == ["\n"]
+
+
+def test_string_formatter():
+    formatter = StringFormatter(slots=["<s>", "Human: {{content}}\nAssistant:"])
+    assert formatter.apply(content="Hi") == ["<s>", "Human: Hi\nAssistant:"]
+
+
+def test_function_formatter():
+    formatter = FunctionFormatter(slots=["Action: {{name}}\nAction Input: {{arguments}}\n"])
+    tool_calls = json.dumps({"name": "tool_name", "arguments": {"foo": "bar", "size": 10}})
+    assert formatter.apply(content=tool_calls) == [
+        """Action: tool_name\nAction Input: {\"foo\": \"bar\", \"size\": 10}\n"""
+    ]
+
+
+def test_multi_function_formatter():
+    formatter = FunctionFormatter(slots=["Action: {{name}}\nAction Input: {{arguments}}\n"])
+    tool_calls = json.dumps([{"name": "tool_name", "arguments": {"foo": "bar", "size": 10}}] * 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""",
+    ]
+
+
+def test_default_tool_formatter():
+    formatter = ToolFormatter(tool_format="default")
+    tools = [
+        {
+            "name": "test_tool",
+            "description": "tool_desc",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "foo": {"type": "string", "description": "foo_desc"},
+                    "bar": {"type": "number", "description": "bar_desc"},
+                },
+                "required": ["foo"],
+            },
+        }
+    ]
+    assert formatter.apply(content=json.dumps(tools)) == [
+        "You have access to the following tools:\n"
+        "> Tool Name: test_tool\n"
+        "Tool Description: tool_desc\n"
+        "Tool Args:\n"
+        "  - foo (string, required): foo_desc\n"
+        "  - bar (number): bar_desc\n\n"
+        "Use the following format if using a tool:\n"
+        "```\n"
+        "Action: tool name (one of [test_tool]).\n"
+        "Action Input: the input to the tool, in a JSON format representing the kwargs "
+        """(e.g. ```{"input": "hello world", "num_beams": 5}```).\n"""
+        "```\n"
+    ]
+
+
+def test_default_tool_extractor():
+    formatter = ToolFormatter(tool_format="default")
+    result = """Action: test_tool\nAction Input: {"foo": "bar", "size": 10}\n"""
+    assert formatter.extract(result) == [("test_tool", """{"foo": "bar", "size": 10}""")]
+
+
+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"""
+    )
+    assert formatter.extract(result) == [
+        ("test_tool", """{"foo": "bar", "size": 10}"""),
+        ("another_tool", """{"foo": "job", "size": 2}"""),
+    ]
+
+
+def test_glm4_tool_formatter():
+    formatter = ToolFormatter(tool_format="glm4")
+    tools = [
+        {
+            "name": "test_tool",
+            "description": "tool_desc",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "foo": {"type": "string", "description": "foo_desc"},
+                    "bar": {"type": "number", "description": "bar_desc"},
+                },
+                "required": ["foo"],
+            },
+        }
+    ]
+    assert formatter.apply(content=json.dumps(tools)) == [
+        "你是一个名为 GLM-4 的人工智能助手。你是基于智谱AI训练的语言模型 GLM-4 模型开发的，"
+        "你的任务是针对用户的问题和要求提供适当的答复和支持。"
+        "\n\n## test_tool\n\n{}\n在调用上述函数时，请使用 Json 格式表示调用的参数。".format(
+            json.dumps(tools[0], indent=4)
+        )
+    ]
+
+
+def test_glm4_tool_extractor():
+    formatter = ToolFormatter(tool_format="glm4")
+    result = """test_tool\n{"foo": "bar", "size": 10}\n"""
+    assert formatter.extract(result) == [("test_tool", """{"foo": "bar", "size": 10}""")]