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fix(AI Agent Node): Fix output parsing and empty tool input handling in AI Agent node (#10970)

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oleg 2024-09-30 10:09:39 +02:00 committed by GitHub
parent 0ca9c076ca
commit 3a65bdc1f5
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1 changed files with 65 additions and 22 deletions
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87
packages/@n8n/nodes-langchain/nodes/agents/Agent/agents/ToolsAgent/execute.ts
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@ -1,27 +1,28 @@
import { BINARY_ENCODING, NodeConnectionType, NodeOperationError } from 'n8n-workflow';
import type { IExecuteFunctions, INodeExecutionData } from 'n8n-workflow';
import type { AgentAction, AgentFinish } from 'langchain/agents';
import { AgentExecutor, createToolCallingAgent } from 'langchain/agents';
import type { BaseChatMemory } from '@langchain/community/memory/chat_memory';
import { HumanMessage } from '@langchain/core/messages';
import type { BaseMessage } from '@langchain/core/messages';
import type { BaseOutputParser, StructuredOutputParser } from '@langchain/core/output_parsers';
import type { BaseMessagePromptTemplateLike } from '@langchain/core/prompts';
import { ChatPromptTemplate } from '@langchain/core/prompts';
import { omit } from 'lodash';
import { RunnableSequence } from '@langchain/core/runnables';
import type { Tool } from '@langchain/core/tools';
import { DynamicStructuredTool } from '@langchain/core/tools';
import type { AgentAction, AgentFinish } from 'langchain/agents';
import { AgentExecutor, createToolCallingAgent } from 'langchain/agents';
import { OutputFixingParser } from 'langchain/output_parsers';
import { omit } from 'lodash';
import { BINARY_ENCODING, jsonParse, NodeConnectionType, NodeOperationError } from 'n8n-workflow';
import type { IExecuteFunctions, INodeExecutionData } from 'n8n-workflow';
import type { ZodObject } from 'zod';
import { z } from 'zod';
import type { BaseOutputParser, StructuredOutputParser } from '@langchain/core/output_parsers';
import { OutputFixingParser } from 'langchain/output_parsers';
import { HumanMessage } from '@langchain/core/messages';
import { RunnableSequence } from '@langchain/core/runnables';
import { SYSTEM_MESSAGE } from './prompt';
import {
isChatInstance,
getPromptInputByType,
getOptionalOutputParsers,
getConnectedTools,
} from '../../../../../utils/helpers';
import { SYSTEM_MESSAGE } from './prompt';
function getOutputParserSchema(outputParser: BaseOutputParser): ZodObject<any, any, any, any> {
const parserType = outputParser.lc_namespace[outputParser.lc_namespace.length - 1];
@ -74,6 +75,39 @@ async function extractBinaryMessages(ctx: IExecuteFunctions) {
content: [...binaryMessages],
});
}
/**
* Fixes empty content messages in agent steps.
*
* This function is necessary when using RunnableSequence.from in LangChain.
* If a tool doesn't have any arguments, LangChain returns input: '' (empty string).
* This can throw an error for some providers (like Anthropic) which expect the input to always be an object.
* This function replaces empty string inputs with empty objects to prevent such errors.
*
* @param steps - The agent steps to fix
* @returns The fixed agent steps
*/
function fixEmptyContentMessage(steps: AgentFinish | AgentAction[]) {
if (!Array.isArray(steps)) return steps;
steps.forEach((step) => {
if ('messageLog' in step && step.messageLog !== undefined) {
if (Array.isArray(step.messageLog)) {
step.messageLog.forEach((message: BaseMessage) => {
if ('content' in message && Array.isArray(message.content)) {
// eslint-disable-next-line @typescript-eslint/no-unsafe-member-access
(message.content as Array<{ input?: string | object }>).forEach((content) => {
if (content.input === '') {
content.input = {};
}
});
}
});
}
}
});
return steps;
}
export async function toolsAgentExecute(this: IExecuteFunctions): Promise<INodeExecutionData[][]> {
this.logger.debug('Executing Tools Agent');
@ -156,6 +190,14 @@ export async function toolsAgentExecute(this: IExecuteFunctions): Promise<INodeE
// If the steps do not contain multiple outputs, return them as is
return agentFinishSteps;
}
// If memory is connected we need to stringify the returnValues so that it can be saved in the memory as a string
function handleParsedStepOutput(output: Record<string, unknown>) {
return {
returnValues: memory ? { output: JSON.stringify(output) } : output,
log: 'Final response formatted',
};
}
async function agentStepsParser(
steps: AgentFinish | AgentAction[],
): Promise<AgentFinish | AgentAction[]> {
@ -168,24 +210,18 @@ export async function toolsAgentExecute(this: IExecuteFunctions): Promise<INodeE
unknown
>;
return {
returnValues,
log: 'Final response formatted',
};
return handleParsedStepOutput(returnValues);
}
}
// If the steps are an AgentFinish and the outputParser is defined it must mean that the LLM didn't use `format_final_response` tool so we will parse the output manually
// If the steps are an AgentFinish and the outputParser is defined it must mean that the LLM didn't use `format_final_response` tool so we will try to parse the output manually
if (outputParser && typeof steps === 'object' && (steps as AgentFinish).returnValues) {
const finalResponse = (steps as AgentFinish).returnValues;
const returnValues = (await outputParser.parse(finalResponse as unknown as string)) as Record<
string,
unknown
>;
return {
returnValues,
log: 'Final response formatted',
};
return handleParsedStepOutput(returnValues);
}
return handleAgentFinishOutput(steps);
}
@ -233,7 +269,7 @@ export async function toolsAgentExecute(this: IExecuteFunctions): Promise<INodeE
});
agent.streamRunnable = false;
const runnableAgent = RunnableSequence.from([agent, agentStepsParser]);
const runnableAgent = RunnableSequence.from([agent, agentStepsParser, fixEmptyContentMessage]);
const executor = AgentExecutor.fromAgentAndTools({
agent: runnableAgent,
@ -273,6 +309,13 @@ export async function toolsAgentExecute(this: IExecuteFunctions): Promise<INodeE
'IMPORTANT: Always call `format_final_response` to format your final response!',
});
if (memory && outputParser) {
const parsedOutput = jsonParse<{ output: Record<string, unknown> }>(
response.output as string,
);
response.output = parsedOutput?.output ?? parsedOutput;
}
returnData.push({
json: omit(
response,