35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
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 | class FunctionTool(AsyncBaseTool):
"""Function Tool.
A tool that takes in a function.
"""
def __init__(
self,
fn: Optional[Callable[..., Any]] = None,
metadata: Optional[ToolMetadata] = None,
async_fn: Optional[AsyncCallable] = None,
) -> None:
if fn is None and async_fn is None:
raise ValueError("fn or async_fn must be provided.")
if fn is not None:
self._fn = fn
elif async_fn is not None:
self._fn = async_to_sync(async_fn)
if async_fn is not None:
self._async_fn = async_fn
elif fn is not None:
self._async_fn = sync_to_async(self._fn)
if metadata is None:
raise ValueError("metadata must be provided.")
self._metadata = metadata
@classmethod
def from_defaults(
cls,
fn: Optional[Callable[..., Any]] = None,
name: Optional[str] = None,
description: Optional[str] = None,
return_direct: bool = False,
fn_schema: Optional[Type[BaseModel]] = None,
async_fn: Optional[AsyncCallable] = None,
tool_metadata: Optional[ToolMetadata] = None,
) -> "FunctionTool":
if tool_metadata is None:
fn_to_parse = fn or async_fn
assert fn_to_parse is not None, "fn or async_fn must be provided."
name = name or fn_to_parse.__name__
docstring = fn_to_parse.__doc__
description = description or f"{name}{signature(fn_to_parse)}\n{docstring}"
if fn_schema is None:
fn_schema = create_schema_from_function(
f"{name}", fn_to_parse, additional_fields=None
)
tool_metadata = ToolMetadata(
name=name,
description=description,
fn_schema=fn_schema,
return_direct=return_direct,
)
return cls(fn=fn, metadata=tool_metadata, async_fn=async_fn)
@property
def metadata(self) -> ToolMetadata:
"""Metadata."""
return self._metadata
@property
def fn(self) -> Callable[..., Any]:
"""Function."""
return self._fn
@property
def async_fn(self) -> AsyncCallable:
"""Async function."""
return self._async_fn
def call(self, *args: Any, **kwargs: Any) -> ToolOutput:
"""Call."""
tool_output = self._fn(*args, **kwargs)
return ToolOutput(
content=str(tool_output),
tool_name=self.metadata.name,
raw_input={"args": args, "kwargs": kwargs},
raw_output=tool_output,
)
async def acall(self, *args: Any, **kwargs: Any) -> ToolOutput:
"""Call."""
tool_output = await self._async_fn(*args, **kwargs)
return ToolOutput(
content=str(tool_output),
tool_name=self.metadata.name,
raw_input={"args": args, "kwargs": kwargs},
raw_output=tool_output,
)
def to_langchain_tool(
self,
**langchain_tool_kwargs: Any,
) -> "Tool":
"""To langchain tool."""
from llama_index.core.bridge.langchain import Tool
langchain_tool_kwargs = self._process_langchain_tool_kwargs(
langchain_tool_kwargs
)
return Tool.from_function(
func=self.fn,
coroutine=self.async_fn,
**langchain_tool_kwargs,
)
def to_langchain_structured_tool(
self,
**langchain_tool_kwargs: Any,
) -> "StructuredTool":
"""To langchain structured tool."""
from llama_index.core.bridge.langchain import StructuredTool
langchain_tool_kwargs = self._process_langchain_tool_kwargs(
langchain_tool_kwargs
)
return StructuredTool.from_function(
func=self.fn,
coroutine=self.async_fn,
**langchain_tool_kwargs,
)
|
