mirror of
https://github.com/n8n-io/n8n.git
synced 2024-11-10 14:44:05 -08:00
7501ad8f3c
Co-authored-by: Oleg Ivaniv <me@olegivaniv.com>
547 lines
18 KiB
TypeScript
547 lines
18 KiB
TypeScript
import {
|
|
NodeOperationError,
|
|
type ConnectionTypes,
|
|
type IExecuteFunctions,
|
|
type INodeExecutionData,
|
|
NodeConnectionType,
|
|
jsonStringify,
|
|
} from 'n8n-workflow';
|
|
|
|
import { Tool } from 'langchain/tools';
|
|
import type { BaseMessage, ChatResult, InputValues } from 'langchain/schema';
|
|
import { BaseChatMessageHistory } from 'langchain/schema';
|
|
import { BaseChatModel } from 'langchain/chat_models/base';
|
|
import type { CallbackManagerForLLMRun } from 'langchain/callbacks';
|
|
|
|
import { Embeddings } from 'langchain/embeddings/base';
|
|
import { VectorStore } from 'langchain/vectorstores/base';
|
|
import type { Document } from 'langchain/document';
|
|
import { TextSplitter } from 'langchain/text_splitter';
|
|
import type { BaseDocumentLoader } from 'langchain/document_loaders/base';
|
|
import type { BaseCallbackConfig, Callbacks } from 'langchain/dist/callbacks/manager';
|
|
import { BaseLLM } from 'langchain/llms/base';
|
|
import { BaseChatMemory } from 'langchain/memory';
|
|
import type { MemoryVariables } from 'langchain/dist/memory/base';
|
|
import { BaseRetriever } from 'langchain/schema/retriever';
|
|
import type { FormatInstructionsOptions } from 'langchain/schema/output_parser';
|
|
import { BaseOutputParser } from 'langchain/schema/output_parser';
|
|
import { isObject } from 'lodash';
|
|
import { N8nJsonLoader } from './N8nJsonLoader';
|
|
import { N8nBinaryLoader } from './N8nBinaryLoader';
|
|
import { isChatInstance } 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) {
|
|
// 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
|
|
| BaseChatModel
|
|
| BaseChatMemory
|
|
| BaseLLM
|
|
| 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 (originalInstance instanceof BaseChatMemory) {
|
|
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;
|
|
|
|
executeFunctions.addOutputData(connectionType, index, [
|
|
[{ json: { action: 'loadMemoryVariables', response } }],
|
|
]);
|
|
return response;
|
|
};
|
|
} else if (
|
|
prop === 'outputKey' &&
|
|
'outputKey' in target &&
|
|
target.constructor.name === 'BufferWindowMemory'
|
|
) {
|
|
connectionType = NodeConnectionType.AiMemory;
|
|
const { index } = executeFunctions.addInputData(connectionType, [
|
|
[{ json: { action: 'chatHistory' } }],
|
|
]);
|
|
const response = target[prop];
|
|
|
|
target.chatHistory
|
|
.getMessages()
|
|
.then((messages) => {
|
|
executeFunctions.addOutputData(NodeConnectionType.AiMemory, index, [
|
|
[{ json: { action: 'chatHistory', chatHistory: messages } }],
|
|
]);
|
|
})
|
|
.catch((error: Error) => {
|
|
executeFunctions.addOutputData(NodeConnectionType.AiMemory, index, [
|
|
[{ json: { action: 'chatHistory', error } }],
|
|
]);
|
|
});
|
|
return response;
|
|
}
|
|
}
|
|
|
|
// ========== BaseChatMessageHistory ==========
|
|
if (originalInstance instanceof BaseChatMessageHistory) {
|
|
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 executeFunctions.logAiEvent(
|
|
'n8n.ai.memory.get.messages',
|
|
jsonStringify({ 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 executeFunctions.logAiEvent(
|
|
'n8n.ai.memory.added.message',
|
|
jsonStringify({ message }),
|
|
);
|
|
executeFunctions.addOutputData(connectionType, index, [[{ json: payload }]]);
|
|
};
|
|
}
|
|
}
|
|
|
|
// ========== BaseChatModel ==========
|
|
if (originalInstance instanceof BaseLLM || isChatInstance(originalInstance)) {
|
|
if (prop === '_generate' && '_generate' in target) {
|
|
return async (
|
|
messages: BaseMessage[] & string[],
|
|
options: any,
|
|
runManager?: CallbackManagerForLLMRun,
|
|
): Promise<ChatResult> => {
|
|
connectionType = NodeConnectionType.AiLanguageModel;
|
|
const { index } = executeFunctions.addInputData(connectionType, [
|
|
[{ json: { messages, options } }],
|
|
]);
|
|
try {
|
|
const response = (await callMethodAsync.call(target, {
|
|
executeFunctions,
|
|
connectionType,
|
|
currentNodeRunIndex: index,
|
|
method: target[prop],
|
|
arguments: [
|
|
messages,
|
|
{ ...options, signal: executeFunctions.getExecutionCancelSignal() },
|
|
runManager,
|
|
],
|
|
})) as ChatResult;
|
|
|
|
void executeFunctions.logAiEvent(
|
|
'n8n.ai.llm.generated',
|
|
jsonStringify({
|
|
messages:
|
|
typeof messages === 'string'
|
|
? messages
|
|
: messages.map((message) => message.toJSON()),
|
|
options,
|
|
response,
|
|
}),
|
|
);
|
|
executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
|
|
return response;
|
|
} catch (error) {
|
|
// Mute AbortError as they are expected
|
|
if (error?.name === 'AbortError') return { generations: [] };
|
|
throw error;
|
|
}
|
|
};
|
|
}
|
|
}
|
|
|
|
// ========== BaseOutputParser ==========
|
|
if (originalInstance instanceof BaseOutputParser) {
|
|
if (prop === 'getFormatInstructions' && 'getFormatInstructions' in target) {
|
|
return (options?: FormatInstructionsOptions): string => {
|
|
connectionType = NodeConnectionType.AiOutputParser;
|
|
const { index } = executeFunctions.addInputData(connectionType, [
|
|
[{ json: { action: 'getFormatInstructions' } }],
|
|
]);
|
|
|
|
// @ts-ignore
|
|
const response = callMethodSync.call(target, {
|
|
executeFunctions,
|
|
connectionType,
|
|
currentNodeRunIndex: index,
|
|
method: target[prop],
|
|
arguments: [options],
|
|
}) as string;
|
|
|
|
executeFunctions.addOutputData(connectionType, index, [
|
|
[{ json: { action: 'getFormatInstructions', response } }],
|
|
]);
|
|
void executeFunctions.logAiEvent(
|
|
'n8n.ai.output.parser.get.instructions',
|
|
jsonStringify({ response }),
|
|
);
|
|
return response;
|
|
};
|
|
} else 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 } }],
|
|
]);
|
|
|
|
const response = (await callMethodAsync.call(target, {
|
|
executeFunctions,
|
|
connectionType,
|
|
currentNodeRunIndex: index,
|
|
method: target[prop],
|
|
arguments: [stringifiedText],
|
|
})) as object;
|
|
|
|
void executeFunctions.logAiEvent(
|
|
'n8n.ai.output.parser.parsed',
|
|
jsonStringify({ text, response }),
|
|
);
|
|
executeFunctions.addOutputData(connectionType, index, [
|
|
[{ json: { action: 'parse', response } }],
|
|
]);
|
|
return response;
|
|
};
|
|
}
|
|
}
|
|
|
|
// ========== 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 executeFunctions.logAiEvent(
|
|
'n8n.ai.retriever.get.relevant.documents',
|
|
jsonStringify({ 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 executeFunctions.logAiEvent('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 executeFunctions.logAiEvent('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 executeFunctions.logAiEvent('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 executeFunctions.logAiEvent('n8n.ai.text.splitter.split');
|
|
executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
|
|
return response;
|
|
};
|
|
}
|
|
}
|
|
|
|
// ========== Tool ==========
|
|
if (originalInstance instanceof Tool) {
|
|
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 executeFunctions.logAiEvent(
|
|
'n8n.ai.tool.called',
|
|
jsonStringify({ 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 executeFunctions.logAiEvent(
|
|
'n8n.ai.vector.store.searched',
|
|
jsonStringify({ query }),
|
|
);
|
|
executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
|
|
|
|
return response;
|
|
};
|
|
}
|
|
}
|
|
|
|
return (target as any)[prop];
|
|
},
|
|
});
|
|
}
|