tool_message
langroid/agent/tool_message.py
Structured messages to an agent, typically from an LLM, to be handled by an agent. The messages could represent, for example: - information or data given to the agent - request for information or data from the agent - request to run a method of the agent
ToolMessage
¶
Bases: ABC
, BaseModel
Abstract Class for a class that defines the structure of a "Tool" message from an LLM. Depending on context, "tools" are also referred to as "plugins", or "function calls" (in the context of OpenAI LLMs). Essentially, they are a way for the LLM to express its intent to run a special function or method. Currently these "tools" are handled by methods of the agent.
Attributes:
Name | Type | Description |
---|---|---|
request |
str
|
name of agent method to map to. |
purpose |
str
|
purpose of agent method, expressed in general terms. (This is used when auto-generating the tool instruction to the LLM) |
result |
str
|
example of result of agent method. |
examples()
classmethod
¶
usage_example()
classmethod
¶
Instruction to the LLM showing an example of how to use the message. Returns: str: example of how to use the message
Source code in langroid/agent/tool_message.py
default_value(f)
classmethod
¶
Returns the default value of the given field, for the message-class Args: f (str): field name
Returns:
Name | Type | Description |
---|---|---|
Any |
Any
|
default value of the field, or None if not set or if the field does not exist. |
Source code in langroid/agent/tool_message.py
json_instructions(tool=False)
classmethod
¶
Default Instructions to the LLM showing how to use the tool/function-call. Works for GPT4 but override this for weaker LLMs if needed.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
tool |
bool
|
instructions for Langroid-native tool use? (e.g. for non-OpenAI LLM) (or else it would be for OpenAI Function calls) |
False
|
Returns: str: instructions on how to use the message
Source code in langroid/agent/tool_message.py
json_group_instructions()
staticmethod
¶
Template for instructions for a group of tools. Works with GPT4 but override this for weaker LLMs if needed.
Source code in langroid/agent/tool_message.py
llm_function_schema(request=False, defaults=True)
classmethod
¶
Clean up the schema of the Pydantic class (which can recursively contain other Pydantic classes), to create a version compatible with OpenAI Function-call API.
Adapted from this excellent library: https://github.com/jxnl/instructor/blob/main/instructor/function_calls.py
Parameters:
Name | Type | Description | Default |
---|---|---|---|
request |
bool
|
whether to include the "request" field in the schema. (we set this to True when using Langroid-native TOOLs as opposed to OpenAI Function calls) |
False
|
defaults |
bool
|
whether to include fields with default values in the schema, in the "properties" section. |
True
|
Returns:
Name | Type | Description |
---|---|---|
LLMFunctionSpec |
LLMFunctionSpec
|
the schema as an LLMFunctionSpec |
Source code in langroid/agent/tool_message.py
simple_schema()
classmethod
¶
Return a simplified schema for the message, with only the request and required fields. Returns: Dict[str, Any]: simplified schema