OpenAIToolsAgent class

Note: This class is deprecated. Use ToolsAgent (from the langchain package instead). It works with the same API as this class, but can be used with any provider that supports tool calling. You can run dart fix --apply to automatically update your code.

An Agent driven by OpenAI's Tools powered API.

Example:

final llm = ChatOpenAI(
  apiKey: openaiApiKey,
  model: 'gpt-4-turbo',
  temperature: 0,
);
final tools = [CalculatorTool()];
final agent = ToolsAgent.fromLLMAndTools(llm: llm, tools: tools);
final executor = AgentExecutor(agent: agent);
final res = await executor.run('What is 40 raised to the 0.43 power? ');

You can easily add memory to the agent using the memory parameter from the OpenAIToolsAgent.fromLLMAndTools constructor. Make sure you enable BaseChatMemory.returnMessages on your memory, as the agent works with ChatMessages. The default prompt template already takes care of adding the history to the prompt. For example:

final memory = ConversationBufferMemory(returnMessages: true);
final agent = OpenAIToolsAgent.fromLLMAndTools(
  llm: llm,
  tools: tools,
  memory: memory,
);

If you need to use your own llmChain make sure your prompt template includes:

MessagePlaceholder(variableName: agentInputKey): the input to the agent.
If you are using memory:
- MessagesPlaceholder(variableName: '{memoryKey}'): the history of chat messages.
If you are not using memory:
- MessagesPlaceholder(variableName: BaseActionAgent.agentScratchpadInputKey): the intermediary work of the agent (if you are using memory, the agent uses the memory to store the intermediary work). Example:

ChatPromptTemplate.fromTemplates([
  (ChatMessageType.system, 'You are a helpful AI assistant'),
  (ChatMessageType.messagesPlaceholder, 'history'),
  (ChatMessageType.messagePlaceholder, 'input'),
]);

You can use OpenAIToolsAgent.createPrompt to build the prompt template if you only need to customize the system message or add some extra messages.

Annotations

@Deprecated('Use ToolsAgent instead')

Constructors

OpenAIToolsAgent.new({required LLMChain<ChatOpenAI, ChatOpenAIOptions, BaseChatMemory> llmChain, required List<Tool<Object, ToolOptions, Object>> tools})
OpenAIToolsAgent.fromLLMAndTools({required ChatOpenAI llm, required List<Tool<Object, ToolOptions, Object>> tools, BaseChatMemory? memory, SystemChatMessagePromptTemplate systemChatMessage = _systemChatMessagePromptTemplate, List<ChatMessagePromptTemplate>? extraPromptMessages}): Construct an OpenAIToolsAgent from an llm and tools.
factory

Properties

agentType → String: Returns the type of agent.
no setter
hashCode → int: The hash code for this object.
no setterinherited
inputKeys → Set<String>: Returns the input keys.
no setter
llmChain → LLMChain<ChatOpenAI, ChatOpenAIOptions, BaseChatMemory>: Chain to use to call the LLM.
final
returnValues → Set<String>: Returns values of the agent.
no setterinherited
runtimeType → Type: A representation of the runtime type of the object.
no setterinherited
tools → List<Tool<Object, ToolOptions, Object>>: The tools this agent can use.
finalinherited

Methods

noSuchMethod(Invocation invocation) → dynamic: Invoked when a nonexistent method or property is accessed.
inherited
plan(AgentPlanInput input) → Future<List<BaseAgentAction>>: Given the input and previous steps, returns the next action to take.
returnStoppedResponse(AgentEarlyStoppingMethod earlyStoppingMethod, List<AgentStep> intermediateSteps) → AgentFinish: Return response when agent has been stopped due to max iterations.
inherited
toString() → String: A string representation of this object.
inherited

Operators

operator ==(Object other) → bool: The equality operator.
inherited

Static Methods

createPrompt({SystemChatMessagePromptTemplate systemChatMessage = _systemChatMessagePromptTemplate, List<ChatMessagePromptTemplate>? extraPromptMessages, BaseChatMemory? memory}) → BasePromptTemplate: Creates prompt for this agent.

Constants

agentInputKey → const String: The key for the input to the agent.