n8n/packages/@n8n/nodes-langchain/utils/logWrapper.ts

463 lines
16 KiB
TypeScript

import { NodeOperationError, NodeConnectionType } from 'n8n-workflow';
import type { ConnectionTypes, IExecuteFunctions, INodeExecutionData } from 'n8n-workflow';
import type { Tool } from '@langchain/core/tools';
import type { BaseMessage } from '@langchain/core/messages';
import type { InputValues, MemoryVariables, OutputValues } from '@langchain/core/memory';
import type { BaseChatMessageHistory } from '@langchain/core/chat_history';
import type { BaseCallbackConfig, Callbacks } from '@langchain/core/callbacks/manager';
import { Embeddings } from '@langchain/core/embeddings';
import { VectorStore } from '@langchain/core/vectorstores';
import type { Document } from '@langchain/core/documents';
import { TextSplitter } from '@langchain/textsplitters';
import type { BaseChatMemory } from '@langchain/community/memory/chat_memory';
import { BaseRetriever } from '@langchain/core/retrievers';
import { BaseOutputParser, OutputParserException } from '@langchain/core/output_parsers';
import { isObject } from 'lodash';
import type { BaseDocumentLoader } from 'langchain/dist/document_loaders/base';
import { N8nJsonLoader } from './N8nJsonLoader';
import { N8nBinaryLoader } from './N8nBinaryLoader';
import { logAiEvent, isToolsInstance, isBaseChatMemory, isBaseChatMessageHistory } from './helpers';
const errorsMap: { [key: string]: { message: string; description: string } } = {
'You exceeded your current quota, please check your plan and billing details.': {
message: 'OpenAI quota exceeded',
description: 'You exceeded your current quota, please check your plan and billing details.',
},
};
export async function callMethodAsync<T>(
this: T,
parameters: {
executeFunctions: IExecuteFunctions;
connectionType: ConnectionTypes;
currentNodeRunIndex: number;
method: (...args: any[]) => Promise<unknown>;
arguments: unknown[];
},
): Promise<unknown> {
try {
return await parameters.method.call(this, ...parameters.arguments);
} catch (e) {
// Langchain checks for OutputParserException to run retry chain
// for auto-fixing the output so skip wrapping in this case
if (e instanceof OutputParserException) throw e;
// Propagate errors from sub-nodes
if (e.functionality === 'configuration-node') throw e;
const connectedNode = parameters.executeFunctions.getNode();
const error = new NodeOperationError(connectedNode, e, {
functionality: 'configuration-node',
});
if (errorsMap[error.message]) {
error.description = errorsMap[error.message].description;
error.message = errorsMap[error.message].message;
}
parameters.executeFunctions.addOutputData(
parameters.connectionType,
parameters.currentNodeRunIndex,
error,
);
if (error.message) {
error.description = error.message;
throw error;
}
throw new NodeOperationError(
connectedNode,
`Error on node "${connectedNode.name}" which is connected via input "${parameters.connectionType}"`,
{ functionality: 'configuration-node' },
);
}
}
export function callMethodSync<T>(
this: T,
parameters: {
executeFunctions: IExecuteFunctions;
connectionType: ConnectionTypes;
currentNodeRunIndex: number;
method: (...args: any[]) => T;
arguments: unknown[];
},
): unknown {
try {
return parameters.method.call(this, ...parameters.arguments);
} catch (e) {
// Propagate errors from sub-nodes
if (e.functionality === 'configuration-node') throw e;
const connectedNode = parameters.executeFunctions.getNode();
const error = new NodeOperationError(connectedNode, e);
parameters.executeFunctions.addOutputData(
parameters.connectionType,
parameters.currentNodeRunIndex,
error,
);
throw new NodeOperationError(
connectedNode,
`Error on node "${connectedNode.name}" which is connected via input "${parameters.connectionType}"`,
{ functionality: 'configuration-node' },
);
}
}
export function logWrapper(
originalInstance:
| Tool
| BaseChatMemory
| BaseChatMessageHistory
| BaseOutputParser
| BaseRetriever
| Embeddings
| Document[]
| Document
| BaseDocumentLoader
| TextSplitter
| VectorStore
| N8nBinaryLoader
| N8nJsonLoader,
executeFunctions: IExecuteFunctions,
) {
return new Proxy(originalInstance, {
get: (target, prop) => {
let connectionType: ConnectionTypes | undefined;
// ========== BaseChatMemory ==========
if (isBaseChatMemory(originalInstance)) {
if (prop === 'loadMemoryVariables' && 'loadMemoryVariables' in target) {
return async (values: InputValues): Promise<MemoryVariables> => {
connectionType = NodeConnectionType.AiMemory;
const { index } = executeFunctions.addInputData(connectionType, [
[{ json: { action: 'loadMemoryVariables', values } }],
]);
const response = (await callMethodAsync.call(target, {
executeFunctions,
connectionType,
currentNodeRunIndex: index,
method: target[prop],
arguments: [values],
})) as MemoryVariables;
const chatHistory = (response?.chat_history as BaseMessage[]) ?? response;
executeFunctions.addOutputData(connectionType, index, [
[{ json: { action: 'loadMemoryVariables', chatHistory } }],
]);
return response;
};
} else if (prop === 'saveContext' && 'saveContext' in target) {
return async (input: InputValues, output: OutputValues): Promise<MemoryVariables> => {
connectionType = NodeConnectionType.AiMemory;
const { index } = executeFunctions.addInputData(connectionType, [
[{ json: { action: 'saveContext', input, output } }],
]);
const response = (await callMethodAsync.call(target, {
executeFunctions,
connectionType,
currentNodeRunIndex: index,
method: target[prop],
arguments: [input, output],
})) as MemoryVariables;
const chatHistory = await target.chatHistory.getMessages();
executeFunctions.addOutputData(connectionType, index, [
[{ json: { action: 'saveContext', chatHistory } }],
]);
return response;
};
}
}
// ========== BaseChatMessageHistory ==========
if (isBaseChatMessageHistory(originalInstance)) {
if (prop === 'getMessages' && 'getMessages' in target) {
return async (): Promise<BaseMessage[]> => {
connectionType = NodeConnectionType.AiMemory;
const { index } = executeFunctions.addInputData(connectionType, [
[{ json: { action: 'getMessages' } }],
]);
const response = (await callMethodAsync.call(target, {
executeFunctions,
connectionType,
currentNodeRunIndex: index,
method: target[prop],
arguments: [],
})) as BaseMessage[];
const payload = { action: 'getMessages', response };
executeFunctions.addOutputData(connectionType, index, [[{ json: payload }]]);
void logAiEvent(executeFunctions, 'n8n.ai.memory.get.messages', { response });
return response;
};
} else if (prop === 'addMessage' && 'addMessage' in target) {
return async (message: BaseMessage): Promise<void> => {
connectionType = NodeConnectionType.AiMemory;
const payload = { action: 'addMessage', message };
const { index } = executeFunctions.addInputData(connectionType, [[{ json: payload }]]);
await callMethodAsync.call(target, {
executeFunctions,
connectionType,
currentNodeRunIndex: index,
method: target[prop],
arguments: [message],
});
void logAiEvent(executeFunctions, 'n8n.ai.memory.added.message', { message });
executeFunctions.addOutputData(connectionType, index, [[{ json: payload }]]);
};
}
}
// ========== BaseOutputParser ==========
if (originalInstance instanceof BaseOutputParser) {
if (prop === 'parse' && 'parse' in target) {
return async (text: string | Record<string, unknown>): Promise<unknown> => {
connectionType = NodeConnectionType.AiOutputParser;
const stringifiedText = isObject(text) ? JSON.stringify(text) : text;
const { index } = executeFunctions.addInputData(connectionType, [
[{ json: { action: 'parse', text: stringifiedText } }],
]);
try {
const response = (await callMethodAsync.call(target, {
executeFunctions,
connectionType,
currentNodeRunIndex: index,
method: target[prop],
arguments: [stringifiedText],
})) as object;
void logAiEvent(executeFunctions, 'n8n.ai.output.parser.parsed', { text, response });
executeFunctions.addOutputData(connectionType, index, [
[{ json: { action: 'parse', response } }],
]);
return response;
} catch (error) {
void logAiEvent(executeFunctions, 'n8n.ai.output.parser.parsed', {
text,
response: error.message ?? error,
});
executeFunctions.addOutputData(connectionType, index, [
[{ json: { action: 'parse', response: error.message ?? error } }],
]);
throw error;
}
};
}
}
// ========== BaseRetriever ==========
if (originalInstance instanceof BaseRetriever) {
if (prop === 'getRelevantDocuments' && 'getRelevantDocuments' in target) {
return async (
query: string,
config?: Callbacks | BaseCallbackConfig,
): Promise<Document[]> => {
connectionType = NodeConnectionType.AiRetriever;
const { index } = executeFunctions.addInputData(connectionType, [
[{ json: { query, config } }],
]);
const response = (await callMethodAsync.call(target, {
executeFunctions,
connectionType,
currentNodeRunIndex: index,
method: target[prop],
arguments: [query, config],
})) as Array<Document<Record<string, any>>>;
void logAiEvent(executeFunctions, 'n8n.ai.retriever.get.relevant.documents', { query });
executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
return response;
};
}
}
// ========== Embeddings ==========
if (originalInstance instanceof Embeddings) {
// Docs -> Embeddings
if (prop === 'embedDocuments' && 'embedDocuments' in target) {
return async (documents: string[]): Promise<number[][]> => {
connectionType = NodeConnectionType.AiEmbedding;
const { index } = executeFunctions.addInputData(connectionType, [
[{ json: { documents } }],
]);
const response = (await callMethodAsync.call(target, {
executeFunctions,
connectionType,
currentNodeRunIndex: index,
method: target[prop],
arguments: [documents],
})) as number[][];
void logAiEvent(executeFunctions, 'n8n.ai.embeddings.embedded.document');
executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
return response;
};
}
// Query -> Embeddings
if (prop === 'embedQuery' && 'embedQuery' in target) {
return async (query: string): Promise<number[]> => {
connectionType = NodeConnectionType.AiEmbedding;
const { index } = executeFunctions.addInputData(connectionType, [
[{ json: { query } }],
]);
const response = (await callMethodAsync.call(target, {
executeFunctions,
connectionType,
currentNodeRunIndex: index,
method: target[prop],
arguments: [query],
})) as number[];
void logAiEvent(executeFunctions, 'n8n.ai.embeddings.embedded.query');
executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
return response;
};
}
}
// ========== N8n Loaders Process All ==========
if (
originalInstance instanceof N8nJsonLoader ||
originalInstance instanceof N8nBinaryLoader
) {
// Process All
if (prop === 'processAll' && 'processAll' in target) {
return async (items: INodeExecutionData[]): Promise<number[]> => {
connectionType = NodeConnectionType.AiDocument;
const { index } = executeFunctions.addInputData(connectionType, [items]);
const response = (await callMethodAsync.call(target, {
executeFunctions,
connectionType,
currentNodeRunIndex: index,
method: target[prop],
arguments: [items],
})) as number[];
executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
return response;
};
}
// Process Each
if (prop === 'processItem' && 'processItem' in target) {
return async (item: INodeExecutionData, itemIndex: number): Promise<number[]> => {
connectionType = NodeConnectionType.AiDocument;
const { index } = executeFunctions.addInputData(connectionType, [[item]]);
const response = (await callMethodAsync.call(target, {
executeFunctions,
connectionType,
currentNodeRunIndex: index,
method: target[prop],
arguments: [item, itemIndex],
})) as number[];
void logAiEvent(executeFunctions, 'n8n.ai.document.processed');
executeFunctions.addOutputData(connectionType, index, [
[{ json: { response }, pairedItem: { item: itemIndex } }],
]);
return response;
};
}
}
// ========== TextSplitter ==========
if (originalInstance instanceof TextSplitter) {
if (prop === 'splitText' && 'splitText' in target) {
return async (text: string): Promise<string[]> => {
connectionType = NodeConnectionType.AiTextSplitter;
const { index } = executeFunctions.addInputData(connectionType, [
[{ json: { textSplitter: text } }],
]);
const response = (await callMethodAsync.call(target, {
executeFunctions,
connectionType,
currentNodeRunIndex: index,
method: target[prop],
arguments: [text],
})) as string[];
void logAiEvent(executeFunctions, 'n8n.ai.text.splitter.split');
executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
return response;
};
}
}
// ========== Tool ==========
if (isToolsInstance(originalInstance)) {
if (prop === '_call' && '_call' in target) {
return async (query: string): Promise<string> => {
connectionType = NodeConnectionType.AiTool;
const { index } = executeFunctions.addInputData(connectionType, [
[{ json: { query } }],
]);
const response = (await callMethodAsync.call(target, {
executeFunctions,
connectionType,
currentNodeRunIndex: index,
method: target[prop],
arguments: [query],
})) as string;
void logAiEvent(executeFunctions, 'n8n.ai.tool.called', { query, response });
executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
return response;
};
}
}
// ========== VectorStore ==========
if (originalInstance instanceof VectorStore) {
if (prop === 'similaritySearch' && 'similaritySearch' in target) {
return async (
query: string,
k?: number,
// @ts-ignore
filter?: BiquadFilterType | undefined,
_callbacks?: Callbacks | undefined,
): Promise<Document[]> => {
connectionType = NodeConnectionType.AiVectorStore;
const { index } = executeFunctions.addInputData(connectionType, [
[{ json: { query, k, filter } }],
]);
const response = (await callMethodAsync.call(target, {
executeFunctions,
connectionType,
currentNodeRunIndex: index,
method: target[prop],
arguments: [query, k, filter, _callbacks],
})) as Array<Document<Record<string, any>>>;
void logAiEvent(executeFunctions, 'n8n.ai.vector.store.searched', { query });
executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
return response;
};
}
}
// eslint-disable-next-line @typescript-eslint/no-unsafe-return
return (target as any)[prop];
},
});
}