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12 | 12 | "In the context of AI agents, tools are designed to be executed by agents in\n", |
13 | 13 | "response to model-generated function calls.\n", |
14 | 14 | "\n", |
15 | | - "AutoGen provides the {py:mod}`autogen_core.components.tools` module with a suite of built-in\n", |
| 15 | + "AutoGen provides the {py:mod}`autogen_core.tools` module with a suite of built-in\n", |
16 | 16 | "tools and utilities for creating and running custom tools." |
17 | 17 | ] |
18 | 18 | }, |
|
22 | 22 | "source": [ |
23 | 23 | "## Built-in Tools\n", |
24 | 24 | "\n", |
25 | | - "One of the built-in tools is the {py:class}`~autogen_core.components.tools.PythonCodeExecutionTool`,\n", |
| 25 | + "One of the built-in tools is the {py:class}`~autogen_core.tools.PythonCodeExecutionTool`,\n", |
26 | 26 | "which allows agents to execute Python code snippets.\n", |
27 | 27 | "\n", |
28 | 28 | "Here is how you create the tool and use it." |
|
44 | 44 | ], |
45 | 45 | "source": [ |
46 | 46 | "from autogen_core import CancellationToken\n", |
47 | | - "from autogen_core.components.tools import PythonCodeExecutionTool\n", |
| 47 | + "from autogen_core.tools import PythonCodeExecutionTool\n", |
48 | 48 | "from autogen_ext.code_executors.docker import DockerCommandLineCodeExecutor\n", |
49 | 49 | "\n", |
50 | 50 | "# Create the tool.\n", |
|
73 | 73 | "The {py:class}`~autogen_ext.code_executors.docker.DockerCommandLineCodeExecutor`\n", |
74 | 74 | "class is a built-in code executor that runs Python code snippets in a subprocess\n", |
75 | 75 | "in the command line environment of a docker container.\n", |
76 | | - "The {py:class}`~autogen_core.components.tools.PythonCodeExecutionTool` class wraps the code executor\n", |
| 76 | + "The {py:class}`~autogen_core.tools.PythonCodeExecutionTool` class wraps the code executor\n", |
77 | 77 | "and provides a simple interface to execute Python code snippets.\n", |
78 | 78 | "\n", |
79 | 79 | "Other built-in tools will be added in the future." |
|
87 | 87 | "\n", |
88 | 88 | "A tool can also be a simple Python function that performs a specific action.\n", |
89 | 89 | "To create a custom function tool, you just need to create a Python function\n", |
90 | | - "and use the {py:class}`~autogen_core.components.tools.FunctionTool` class to wrap it.\n", |
| 90 | + "and use the {py:class}`~autogen_core.tools.FunctionTool` class to wrap it.\n", |
91 | 91 | "\n", |
92 | | - "The {py:class}`~autogen_core.components.tools.FunctionTool` class uses descriptions and type annotations\n", |
| 92 | + "The {py:class}`~autogen_core.tools.FunctionTool` class uses descriptions and type annotations\n", |
93 | 93 | "to inform the LLM when and how to use a given function. The description provides context\n", |
94 | 94 | "about the function’s purpose and intended use cases, while type annotations inform the LLM about\n", |
95 | 95 | "the expected parameters and return type.\n", |
|
114 | 114 | "import random\n", |
115 | 115 | "\n", |
116 | 116 | "from autogen_core import CancellationToken\n", |
117 | | - "from autogen_core.components.tools import FunctionTool\n", |
| 117 | + "from autogen_core.tools import FunctionTool\n", |
118 | 118 | "from typing_extensions import Annotated\n", |
119 | 119 | "\n", |
120 | 120 | "\n", |
|
140 | 140 | "source": [ |
141 | 141 | "## Tool-Equipped Agent\n", |
142 | 142 | "\n", |
143 | | - "To use tools with an agent, you can use {py:class}`~autogen_core.components.tool_agent.ToolAgent`,\n", |
| 143 | + "To use tools with an agent, you can use {py:class}`~autogen_core.tool_agent.ToolAgent`,\n", |
144 | 144 | "by using it in a composition pattern.\n", |
145 | | - "Here is an example tool-use agent that uses {py:class}`~autogen_core.components.tool_agent.ToolAgent`\n", |
| 145 | + "Here is an example tool-use agent that uses {py:class}`~autogen_core.tool_agent.ToolAgent`\n", |
146 | 146 | "as an inner agent for executing tools." |
147 | 147 | ] |
148 | 148 | }, |
|
163 | 163 | " SingleThreadedAgentRuntime,\n", |
164 | 164 | " message_handler,\n", |
165 | 165 | ")\n", |
166 | | - "from autogen_core.components.tools import FunctionTool, Tool, ToolSchema\n", |
167 | 166 | "from autogen_core.models import (\n", |
168 | 167 | " ChatCompletionClient,\n", |
169 | 168 | " LLMMessage,\n", |
170 | 169 | " SystemMessage,\n", |
171 | 170 | " UserMessage,\n", |
172 | 171 | ")\n", |
173 | 172 | "from autogen_core.tool_agent import ToolAgent, tool_agent_caller_loop\n", |
| 173 | + "from autogen_core.tools import FunctionTool, Tool, ToolSchema\n", |
174 | 174 | "from autogen_ext.models import OpenAIChatCompletionClient\n", |
175 | 175 | "\n", |
176 | 176 | "\n", |
|
209 | 209 | "cell_type": "markdown", |
210 | 210 | "metadata": {}, |
211 | 211 | "source": [ |
212 | | - "The `ToolUseAgent` class uses a convenience function {py:meth}`~autogen_core.components.tool_agent.tool_agent_caller_loop`, \n", |
| 212 | + "The `ToolUseAgent` class uses a convenience function {py:meth}`~autogen_core.tool_agent.tool_agent_caller_loop`, \n", |
213 | 213 | "to handle the interaction between the model and the tool agent.\n", |
214 | 214 | "The core idea can be described using a simple control flow graph:\n", |
215 | 215 | "\n", |
|
218 | 218 | "The `ToolUseAgent`'s `handle_user_message` handler handles messages from the user,\n", |
219 | 219 | "and determines whether the model has generated a tool call.\n", |
220 | 220 | "If the model has generated tool calls, then the handler sends a function call\n", |
221 | | - "message to the {py:class}`~autogen_core.components.tool_agent.ToolAgent` agent\n", |
| 221 | + "message to the {py:class}`~autogen_core.tool_agent.ToolAgent` agent\n", |
222 | 222 | "to execute the tools,\n", |
223 | 223 | "and then queries the model again with the results of the tool calls.\n", |
224 | 224 | "This process continues until the model stops generating tool calls,\n", |
|
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