Skip to content

Pydantic Function Tool

Pydantic Function Tool.

PydanticFunction

Bases: Protocol

PydanticFunction Protocol.

Source code in src/llm_agents_from_scratch/tools/pydantic_function.py 
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
class PydanticFunction(Protocol):
    """PydanticFunction Protocol."""

    __name__: str
    __doc__: str | None

    def __call__(self, params: BaseModel, *args: Any, **kwargs: Any) -> Any:
        """Callable interface.

        Args:
            params (BaseModel): The function's params as a ~pydantic.BaseModel.
            *args (Any): Additional positional arguments.
            **kwargs (Any): Additional keyword arguments.

        Returns:
            Any: The result of the function call.
        """
        ...  # pragma: no cover

__call__ 

__call__(params, *args, **kwargs)

Callable interface.

Parameters:

Name Type Description Default
params BaseModel

The function's params as a ~pydantic.BaseModel.

 required
*args Any

Additional positional arguments.

 ()
**kwargs Any

Additional keyword arguments.

 {}

Returns:

Name Type Description
Any Any

The result of the function call.
Source code in src/llm_agents_from_scratch/tools/pydantic_function.py 
19
20
21
22
23
24
25
26
27
28
29
30
def __call__(self, params: BaseModel, *args: Any, **kwargs: Any) -> Any:
    """Callable interface.

    Args:
        params (BaseModel): The function's params as a ~pydantic.BaseModel.
        *args (Any): Additional positional arguments.
        **kwargs (Any): Additional keyword arguments.

    Returns:
        Any: The result of the function call.
    """
    ...  # pragma: no cover

AsyncPydanticFunction

Bases: Protocol

Asynchronous PydanticFunction Protocol.

Source code in src/llm_agents_from_scratch/tools/pydantic_function.py 
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
class AsyncPydanticFunction(Protocol):
    """Asynchronous PydanticFunction Protocol."""

    __name__: str
    __doc__: str | None

    async def __call__(
        self,
        params: BaseModel,
        *args: Any,
        **kwargs: Any,
    ) -> Awaitable[Any]:
        """Asynchronous callable interface.

        Args:
            params (BaseModel): The function's params as a ~pydantic.BaseModel.
            *args (Any): Additional positional arguments.
            **kwargs (Any): Additional keyword arguments.

        Returns:
            Awaitable[Any]: The result of the function call.
        """
        ...  # pragma: no cover

__call__ async 

__call__(params, *args, **kwargs)

Asynchronous callable interface.

Parameters:

Name Type Description Default
params BaseModel

The function's params as a ~pydantic.BaseModel.

 required
*args Any

Additional positional arguments.

 ()
**kwargs Any

Additional keyword arguments.

 {}

Returns:

Type Description
Awaitable[Any]

Awaitable[Any]: The result of the function call.
Source code in src/llm_agents_from_scratch/tools/pydantic_function.py 
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
async def __call__(
    self,
    params: BaseModel,
    *args: Any,
    **kwargs: Any,
) -> Awaitable[Any]:
    """Asynchronous callable interface.

    Args:
        params (BaseModel): The function's params as a ~pydantic.BaseModel.
        *args (Any): Additional positional arguments.
        **kwargs (Any): Additional keyword arguments.

    Returns:
        Awaitable[Any]: The result of the function call.
    """
    ...  # pragma: no cover

PydanticFunctionTool

Bases: BaseTool

Pydantic function calling tool.

Turn a Python function that takes in a ~pydantic.BaseModel params object into a tool for an LLM.

Attributes:

Name Type Description
func

PydanticFunction to represent as a tool.
params_mdl

The params BaseModel.
desc

Description of the PydanticFunction.
Source code in src/llm_agents_from_scratch/tools/pydantic_function.py 
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
class PydanticFunctionTool(BaseTool):
    """Pydantic function calling tool.

    Turn a Python function that takes in a ~pydantic.BaseModel params object
    into a tool for an LLM.

    Attributes:
        func: PydanticFunction to represent as a tool.
        params_mdl: The params BaseModel.
        desc: Description of the PydanticFunction.
    """

    def __init__(
        self,
        func: PydanticFunction,
        desc: str | None = None,
    ):
        """Initialize a PydanticFunctionTool.

        Args:
            func (PydanticFunction): The Pydantic function to expose as a tool
                to the LLM.
            desc (str | None, optional): Description of the function.
                Defaults to None.
        """
        self.func = func
        self._desc = desc
        self.params_mdl = _validate_pydantic_function(func)

    @property
    def name(self) -> str:
        """Name of function tool."""
        return self.func.__name__

    @property
    def description(self) -> str:
        """Description of what this function tool does."""
        return (
            self._desc or self.func.__doc__ or f"Tool for {self.func.__name__}"
        )

    @property
    def parameters_json_schema(self) -> dict[str, Any]:
        """JSON schema for tool parameters."""
        return self.params_mdl.model_json_schema()

    def __call__(
        self,
        tool_call: ToolCall,
        *args: Any,
        **kwargs: Any,
    ) -> ToolCallResult:
        """Execute the function tool with a ToolCall.

        Args:
            tool_call (ToolCall): The ToolCall to execute.
            *args (Any): Additional positional arguments.
            **kwargs (Any): Additional keyword arguments.

        Returns:
            ToolCallResult: The result of the tool call execution.
        """
        try:
            params = self.params_mdl.model_validate(tool_call.arguments)
            # execute the function
            res = self.func(params)
            content = str(res)
            error = False
        except Exception as e:
            error_details = {
                "error_type": e.__class__.__name__,
                "message": f"Internal error while executing tool: {str(e)}",
            }
            content = json.dumps(error_details)
            error = True

        return ToolCallResult(
            tool_call_id=tool_call.id_,
            content=content,
            error=error,
        )

name property 

name

Name of function tool.

description property 

description

Description of what this function tool does.

parameters_json_schema property 

parameters_json_schema

JSON schema for tool parameters.

__init__ 

__init__(func, desc=None)

Initialize a PydanticFunctionTool.

Parameters:

Name Type Description Default
func PydanticFunction

The Pydantic function to expose as a tool to the LLM.

 required
desc str | None

Description of the function. Defaults to None.

 None
Source code in src/llm_agents_from_scratch/tools/pydantic_function.py 
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
def __init__(
    self,
    func: PydanticFunction,
    desc: str | None = None,
):
    """Initialize a PydanticFunctionTool.

    Args:
        func (PydanticFunction): The Pydantic function to expose as a tool
            to the LLM.
        desc (str | None, optional): Description of the function.
            Defaults to None.
    """
    self.func = func
    self._desc = desc
    self.params_mdl = _validate_pydantic_function(func)

__call__ 

__call__(tool_call, *args, **kwargs)

Execute the function tool with a ToolCall.

Parameters:

Name Type Description Default
tool_call ToolCall

The ToolCall to execute.

 required
*args Any

Additional positional arguments.

 ()
**kwargs Any

Additional keyword arguments.

 {}

Returns:

Name Type Description
ToolCallResult ToolCallResult

The result of the tool call execution.
Source code in src/llm_agents_from_scratch/tools/pydantic_function.py 
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
def __call__(
    self,
    tool_call: ToolCall,
    *args: Any,
    **kwargs: Any,
) -> ToolCallResult:
    """Execute the function tool with a ToolCall.

    Args:
        tool_call (ToolCall): The ToolCall to execute.
        *args (Any): Additional positional arguments.
        **kwargs (Any): Additional keyword arguments.

    Returns:
        ToolCallResult: The result of the tool call execution.
    """
    try:
        params = self.params_mdl.model_validate(tool_call.arguments)
        # execute the function
        res = self.func(params)
        content = str(res)
        error = False
    except Exception as e:
        error_details = {
            "error_type": e.__class__.__name__,
            "message": f"Internal error while executing tool: {str(e)}",
        }
        content = json.dumps(error_details)
        error = True

    return ToolCallResult(
        tool_call_id=tool_call.id_,
        content=content,
        error=error,
    )

AsyncPydanticFunctionTool

Bases: AsyncBaseTool

Async Pydantic function calling tool.

Turn an async Python function that takes in a ~pydantic.BaseModel params object into a tool for an LLM.

Attributes:

Name Type Description
func

AsyncPydanticFunction to represent as a tool.
params_mdl

The params BaseModel.
desc

Description of the PydanticFunction.
Source code in src/llm_agents_from_scratch/tools/pydantic_function.py 
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
class AsyncPydanticFunctionTool(AsyncBaseTool):
    """Async Pydantic function calling tool.

    Turn an async Python function that takes in a ~pydantic.BaseModel params
    object into a tool for an LLM.

    Attributes:
        func: AsyncPydanticFunction to represent as a tool.
        params_mdl: The params BaseModel.
        desc: Description of the PydanticFunction.
    """

    def __init__(
        self,
        func: AsyncPydanticFunction,
        desc: str | None = None,
    ):
        """Initialize an AsyncPydanticFunctionTool.

        Args:
            func (AsyncPydanticFunction): The async Pydantic function to expose
                as a tool to the LLM.
            desc (str | None, optional): Description of the function.
                Defaults to None.
        """
        self.func = func
        self._desc = desc
        self.params_mdl = _validate_pydantic_function(func)

    @property
    def name(self) -> str:
        """Name of function tool."""
        return self.func.__name__

    @property
    def description(self) -> str:
        """Description of what this function tool does."""
        return (
            self._desc or self.func.__doc__ or f"Tool for {self.func.__name__}"
        )

    @property
    def parameters_json_schema(self) -> dict[str, Any]:
        """JSON schema for tool parameters."""
        return self.params_mdl.model_json_schema()

    async def __call__(
        self,
        tool_call: ToolCall,
        *args: Any,
        **kwargs: Any,
    ) -> ToolCallResult:
        """Execute the function tool with a ToolCall.

        Args:
            tool_call (ToolCall): The ToolCall to execute.
            *args (Any): Additional positional arguments.
            **kwargs (Any): Additional keyword arguments.

        Returns:
            ToolCallResult: The result of the tool call execution.
        """
        try:
            params = self.params_mdl.model_validate(tool_call.arguments)
            # execute the function
            res = await self.func(params)
            content = str(res)
            error = False
        except Exception as e:
            error_details = {
                "error_type": e.__class__.__name__,
                "message": f"Internal error while executing tool: {str(e)}",
            }
            content = json.dumps(error_details)
            error = True

        return ToolCallResult(
            tool_call_id=tool_call.id_,
            content=content,
            error=error,
        )

name property 

name

Name of function tool.

description property 

description

Description of what this function tool does.

parameters_json_schema property 

parameters_json_schema

JSON schema for tool parameters.

__init__ 

__init__(func, desc=None)

Initialize an AsyncPydanticFunctionTool.

Parameters:

Name Type Description Default
func AsyncPydanticFunction

The async Pydantic function to expose as a tool to the LLM.

 required
desc str | None

Description of the function. Defaults to None.

 None
Source code in src/llm_agents_from_scratch/tools/pydantic_function.py 
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
def __init__(
    self,
    func: AsyncPydanticFunction,
    desc: str | None = None,
):
    """Initialize an AsyncPydanticFunctionTool.

    Args:
        func (AsyncPydanticFunction): The async Pydantic function to expose
            as a tool to the LLM.
        desc (str | None, optional): Description of the function.
            Defaults to None.
    """
    self.func = func
    self._desc = desc
    self.params_mdl = _validate_pydantic_function(func)

__call__ async 

__call__(tool_call, *args, **kwargs)

Execute the function tool with a ToolCall.

Parameters:

Name Type Description Default
tool_call ToolCall

The ToolCall to execute.

 required
*args Any

Additional positional arguments.

 ()
**kwargs Any

Additional keyword arguments.

 {}

Returns:

Name Type Description
ToolCallResult ToolCallResult

The result of the tool call execution.
Source code in src/llm_agents_from_scratch/tools/pydantic_function.py 
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
async def __call__(
    self,
    tool_call: ToolCall,
    *args: Any,
    **kwargs: Any,
) -> ToolCallResult:
    """Execute the function tool with a ToolCall.

    Args:
        tool_call (ToolCall): The ToolCall to execute.
        *args (Any): Additional positional arguments.
        **kwargs (Any): Additional keyword arguments.

    Returns:
        ToolCallResult: The result of the tool call execution.
    """
    try:
        params = self.params_mdl.model_validate(tool_call.arguments)
        # execute the function
        res = await self.func(params)
        content = str(res)
        error = False
    except Exception as e:
        error_details = {
            "error_type": e.__class__.__name__,
            "message": f"Internal error while executing tool: {str(e)}",
        }
        content = json.dumps(error_details)
        error = True

    return ToolCallResult(
        tool_call_id=tool_call.id_,
        content=content,
        error=error,
    )