diff --git a/packages/components/nodes/agents/ConversationalAgent/ConversationalAgent.ts b/packages/components/nodes/agents/ConversationalAgent/ConversationalAgent.ts index 8a2329b5..cb5d3189 100644 --- a/packages/components/nodes/agents/ConversationalAgent/ConversationalAgent.ts +++ b/packages/components/nodes/agents/ConversationalAgent/ConversationalAgent.ts @@ -2,7 +2,7 @@ import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Inter import { initializeAgentExecutorWithOptions, AgentExecutor, InitializeAgentExecutorOptions } from 'langchain/agents' import { Tool } from 'langchain/tools' import { BaseChatMemory } from 'langchain/memory' -import { getBaseClasses, mapChatHistory } from '../../../src/utils' +import { getBaseClasses } from '../../../src/utils' import { BaseChatModel } from 'langchain/chat_models/base' import { flatten } from 'lodash' import { additionalCallbacks } from '../../../src/handler' @@ -90,18 +90,17 @@ class ConversationalAgent_Agents implements INode { async run(nodeData: INodeData, input: string, options: ICommonObject): Promise { const executor = nodeData.instance as AgentExecutor - const memory = nodeData.inputs?.memory as BaseChatMemory + const memory = nodeData.inputs?.memory + memory.returnMessages = true // Return true for BaseChatModel - if (options && options.chatHistory) { - const chatHistoryClassName = memory.chatHistory.constructor.name - // Only replace when its In-Memory - if (chatHistoryClassName && chatHistoryClassName === 'ChatMessageHistory') { - memory.chatHistory = mapChatHistory(options) - executor.memory = memory - } + /* When incomingInput.history is provided, only force replace chatHistory if its ShortTermMemory + * LongTermMemory will automatically retrieved chatHistory from sessionId + */ + if (options && options.chatHistory && memory.isShortTermMemory) { + await memory.resumeMessages(options.chatHistory) } - ;(executor.memory as any).returnMessages = true // Return true for BaseChatModel + executor.memory = memory const callbacks = await additionalCallbacks(nodeData, options) diff --git a/packages/components/nodes/agents/ConversationalRetrievalAgent/ConversationalRetrievalAgent.ts b/packages/components/nodes/agents/ConversationalRetrievalAgent/ConversationalRetrievalAgent.ts index 643c6a65..ce5b5e18 100644 --- a/packages/components/nodes/agents/ConversationalRetrievalAgent/ConversationalRetrievalAgent.ts +++ b/packages/components/nodes/agents/ConversationalRetrievalAgent/ConversationalRetrievalAgent.ts @@ -1,6 +1,6 @@ import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' import { initializeAgentExecutorWithOptions, AgentExecutor } from 'langchain/agents' -import { getBaseClasses, mapChatHistory } from '../../../src/utils' +import { getBaseClasses } from '../../../src/utils' import { flatten } from 'lodash' import { BaseChatMemory } from 'langchain/memory' import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler' @@ -58,8 +58,8 @@ class ConversationalRetrievalAgent_Agents implements INode { async init(nodeData: INodeData): Promise { const model = nodeData.inputs?.model - const memory = nodeData.inputs?.memory as BaseChatMemory const systemMessage = nodeData.inputs?.systemMessage as string + const memory = nodeData.inputs?.memory as BaseChatMemory let tools = nodeData.inputs?.tools tools = flatten(tools) @@ -78,19 +78,21 @@ class ConversationalRetrievalAgent_Agents implements INode { async run(nodeData: INodeData, input: string, options: ICommonObject): Promise { const executor = nodeData.instance as AgentExecutor + const memory = nodeData.inputs?.memory - if (executor.memory) { - ;(executor.memory as any).memoryKey = 'chat_history' - ;(executor.memory as any).outputKey = 'output' - ;(executor.memory as any).returnMessages = true + memory.memoryKey = 'chat_history' + memory.outputKey = 'output' + memory.returnMessages = true - const chatHistoryClassName = (executor.memory as any).chatHistory.constructor.name - // Only replace when its In-Memory - if (chatHistoryClassName && chatHistoryClassName === 'ChatMessageHistory') { - ;(executor.memory as any).chatHistory = mapChatHistory(options) - } + /* When incomingInput.history is provided, only force replace chatHistory if its ShortTermMemory + * LongTermMemory will automatically retrieved chatHistory from sessionId + */ + if (options && options.chatHistory && memory.isShortTermMemory) { + await memory.resumeMessages(options.chatHistory) } + executor.memory = memory + const loggerHandler = new ConsoleCallbackHandler(options.logger) const callbacks = await additionalCallbacks(nodeData, options) diff --git a/packages/components/nodes/agents/OpenAIAssistant/OpenAIAssistant.ts b/packages/components/nodes/agents/OpenAIAssistant/OpenAIAssistant.ts index 7f2377bd..1a48be50 100644 --- a/packages/components/nodes/agents/OpenAIAssistant/OpenAIAssistant.ts +++ b/packages/components/nodes/agents/OpenAIAssistant/OpenAIAssistant.ts @@ -81,50 +81,8 @@ class OpenAIAssistant_Agents implements INode { } } - async init(): Promise { - return null - } - - //@ts-ignore - memoryMethods = { - async clearSessionMemory(nodeData: INodeData, options: ICommonObject): Promise { - const selectedAssistantId = nodeData.inputs?.selectedAssistant as string - const appDataSource = options.appDataSource as DataSource - const databaseEntities = options.databaseEntities as IDatabaseEntity - let sessionId = nodeData.inputs?.sessionId as string - - const assistant = await appDataSource.getRepository(databaseEntities['Assistant']).findOneBy({ - id: selectedAssistantId - }) - - if (!assistant) { - options.logger.error(`Assistant ${selectedAssistantId} not found`) - return - } - - if (!sessionId && options.chatId) { - const chatmsg = await appDataSource.getRepository(databaseEntities['ChatMessage']).findOneBy({ - chatId: options.chatId - }) - if (!chatmsg) { - options.logger.error(`Chat Message with Chat Id: ${options.chatId} not found`) - return - } - sessionId = chatmsg.sessionId - } - - const credentialData = await getCredentialData(assistant.credential ?? '', options) - const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData) - if (!openAIApiKey) { - options.logger.error(`OpenAI ApiKey not found`) - return - } - - const openai = new OpenAI({ apiKey: openAIApiKey }) - options.logger.info(`Clearing OpenAI Thread ${sessionId}`) - if (sessionId) await openai.beta.threads.del(sessionId) - options.logger.info(`Successfully cleared OpenAI Thread ${sessionId}`) - } + async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { + return new OpenAIAssistant({ nodeData, options }) } async run(nodeData: INodeData, input: string, options: ICommonObject): Promise { @@ -459,4 +417,58 @@ const formatToOpenAIAssistantTool = (tool: any): OpenAI.Beta.AssistantCreatePara } } +interface OpenAIAssistantInput { + nodeData: INodeData + options: ICommonObject +} + +class OpenAIAssistant { + nodeData: INodeData + options: ICommonObject = {} + + constructor(fields: OpenAIAssistantInput) { + this.nodeData = fields.nodeData + this.options = fields.options + } + + async clearChatMessages(): Promise { + const selectedAssistantId = this.nodeData.inputs?.selectedAssistant as string + const appDataSource = this.options.appDataSource as DataSource + const databaseEntities = this.options.databaseEntities as IDatabaseEntity + let sessionId = this.nodeData.inputs?.sessionId as string + + const assistant = await appDataSource.getRepository(databaseEntities['Assistant']).findOneBy({ + id: selectedAssistantId + }) + + if (!assistant) { + this.options.logger.error(`Assistant ${selectedAssistantId} not found`) + return + } + + if (!sessionId && this.options.chatId) { + const chatmsg = await appDataSource.getRepository(databaseEntities['ChatMessage']).findOneBy({ + chatId: this.options.chatId + }) + if (!chatmsg) { + this.options.logger.error(`Chat Message with Chat Id: ${this.options.chatId} not found`) + return + } + sessionId = chatmsg.sessionId + } + + const credentialData = await getCredentialData(assistant.credential ?? '', this.options) + const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, this.nodeData) + if (!openAIApiKey) { + this.options.logger.error(`OpenAI ApiKey not found`) + return + } + + const openai = new OpenAI({ apiKey: openAIApiKey }) + this.options.logger.info(`Clearing OpenAI Thread ${sessionId}`) + if (sessionId) await openai.beta.threads.del(sessionId) + this.options.logger.info(`Successfully cleared OpenAI Thread ${sessionId}`) + } +} + module.exports = { nodeClass: OpenAIAssistant_Agents } diff --git a/packages/components/nodes/agents/OpenAIFunctionAgent/OpenAIFunctionAgent.ts b/packages/components/nodes/agents/OpenAIFunctionAgent/OpenAIFunctionAgent.ts index 96ba7ea3..781292d7 100644 --- a/packages/components/nodes/agents/OpenAIFunctionAgent/OpenAIFunctionAgent.ts +++ b/packages/components/nodes/agents/OpenAIFunctionAgent/OpenAIFunctionAgent.ts @@ -1,6 +1,6 @@ import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' import { initializeAgentExecutorWithOptions, AgentExecutor } from 'langchain/agents' -import { getBaseClasses, mapChatHistory } from '../../../src/utils' +import { getBaseClasses } from '../../../src/utils' import { BaseLanguageModel } from 'langchain/base_language' import { flatten } from 'lodash' import { BaseChatMemory } from 'langchain/memory' @@ -56,8 +56,8 @@ class OpenAIFunctionAgent_Agents implements INode { async init(nodeData: INodeData): Promise { const model = nodeData.inputs?.model as BaseLanguageModel - const memory = nodeData.inputs?.memory as BaseChatMemory const systemMessage = nodeData.inputs?.systemMessage as string + const memory = nodeData.inputs?.memory as BaseChatMemory let tools = nodeData.inputs?.tools tools = flatten(tools) @@ -69,25 +69,23 @@ class OpenAIFunctionAgent_Agents implements INode { prefix: systemMessage ?? `You are a helpful AI assistant.` } }) - if (memory) executor.memory = memory - + executor.memory = memory return executor } async run(nodeData: INodeData, input: string, options: ICommonObject): Promise { const executor = nodeData.instance as AgentExecutor - const memory = nodeData.inputs?.memory as BaseChatMemory + const memory = nodeData.inputs?.memory + memory.returnMessages = true // Return true for BaseChatModel - if (options && options.chatHistory) { - const chatHistoryClassName = memory.chatHistory.constructor.name - // Only replace when its In-Memory - if (chatHistoryClassName && chatHistoryClassName === 'ChatMessageHistory') { - memory.chatHistory = mapChatHistory(options) - executor.memory = memory - } + /* When incomingInput.history is provided, only force replace chatHistory if its ShortTermMemory + * LongTermMemory will automatically retrieved chatHistory from sessionId + */ + if (options && options.chatHistory && memory.isShortTermMemory) { + await memory.resumeMessages(options.chatHistory) } - ;(executor.memory as any).returnMessages = true // Return true for BaseChatModel + executor.memory = memory const loggerHandler = new ConsoleCallbackHandler(options.logger) const callbacks = await additionalCallbacks(nodeData, options) diff --git a/packages/components/nodes/chains/ConversationChain/ConversationChain.ts b/packages/components/nodes/chains/ConversationChain/ConversationChain.ts index 7887ce97..aa9b1a8a 100644 --- a/packages/components/nodes/chains/ConversationChain/ConversationChain.ts +++ b/packages/components/nodes/chains/ConversationChain/ConversationChain.ts @@ -1,6 +1,6 @@ import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' import { ConversationChain } from 'langchain/chains' -import { getBaseClasses, mapChatHistory } from '../../../src/utils' +import { getBaseClasses } from '../../../src/utils' import { ChatPromptTemplate, HumanMessagePromptTemplate, MessagesPlaceholder, SystemMessagePromptTemplate } from 'langchain/prompts' import { BufferMemory } from 'langchain/memory' import { BaseChatModel } from 'langchain/chat_models/base' @@ -105,15 +105,14 @@ class ConversationChain_Chains implements INode { async run(nodeData: INodeData, input: string, options: ICommonObject): Promise { const chain = nodeData.instance as ConversationChain - const memory = nodeData.inputs?.memory as BufferMemory + const memory = nodeData.inputs?.memory memory.returnMessages = true // Return true for BaseChatModel - if (options && options.chatHistory) { - const chatHistoryClassName = memory.chatHistory.constructor.name - // Only replace when its In-Memory - if (chatHistoryClassName && chatHistoryClassName === 'ChatMessageHistory') { - memory.chatHistory = mapChatHistory(options) - } + /* When incomingInput.history is provided, only force replace chatHistory if its ShortTermMemory + * LongTermMemory will automatically retrieved chatHistory from sessionId + */ + if (options && options.chatHistory && memory.isShortTermMemory) { + await memory.resumeMessages(options.chatHistory) } chain.memory = memory diff --git a/packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts b/packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts index 9a8c1b18..d8fb4225 100644 --- a/packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts +++ b/packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts @@ -1,9 +1,9 @@ import { BaseLanguageModel } from 'langchain/base_language' -import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' -import { getBaseClasses, mapChatHistory } from '../../../src/utils' +import { ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface' +import { getBaseClasses } from '../../../src/utils' import { ConversationalRetrievalQAChain, QAChainParams } from 'langchain/chains' import { BaseRetriever } from 'langchain/schema/retriever' -import { BufferMemory, BufferMemoryInput } from 'langchain/memory' +import { BufferMemoryInput, BufferMemory } from 'langchain/memory' import { PromptTemplate } from 'langchain/prompts' import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler' import { @@ -158,7 +158,7 @@ class ConversationalRetrievalQAChain_Chains implements INode { returnMessages: true } if (chainOption === 'refine') fields.outputKey = 'output_text' - obj.memory = new BufferMemory(fields) + obj.memory = new BufferMemoryExtended(fields) } const chain = ConversationalRetrievalQAChain.fromLLM(model, vectorStoreRetriever, obj) @@ -178,12 +178,11 @@ class ConversationalRetrievalQAChain_Chains implements INode { const obj = { question: input } - if (options && options.chatHistory && chain.memory) { - const chatHistoryClassName = (chain.memory as any).chatHistory.constructor.name - // Only replace when its In-Memory - if (chatHistoryClassName && chatHistoryClassName === 'ChatMessageHistory') { - ;(chain.memory as any).chatHistory = mapChatHistory(options) - } + /* When incomingInput.history is provided, only force replace chatHistory if its ShortTermMemory + * LongTermMemory will automatically retrieved chatHistory from sessionId + */ + if (options && options.chatHistory && chain.memory && (chain.memory as any).isShortTermMemory) { + await (chain.memory as any).resumeMessages(options.chatHistory) } const loggerHandler = new ConsoleCallbackHandler(options.logger) @@ -216,4 +215,27 @@ class ConversationalRetrievalQAChain_Chains implements INode { } } +class BufferMemoryExtended extends BufferMemory { + isShortTermMemory = true + + constructor(fields: BufferMemoryInput) { + super(fields) + } + + async clearChatMessages(): Promise { + await this.clear() + } + + async resumeMessages(messages: IMessage[]): Promise { + // Clear existing chatHistory to avoid duplication + if (messages.length) await this.clear() + + // Insert into chatHistory + for (const msg of messages) { + if (msg.type === 'userMessage') await this.chatHistory.addUserMessage(msg.message) + else if (msg.type === 'apiMessage') await this.chatHistory.addAIChatMessage(msg.message) + } + } +} + module.exports = { nodeClass: ConversationalRetrievalQAChain_Chains } diff --git a/packages/components/nodes/chatmodels/AzureChatOpenAI/AzureChatOpenAI_LlamaIndex.ts b/packages/components/nodes/chatmodels/AzureChatOpenAI/AzureChatOpenAI_LlamaIndex.ts new file mode 100644 index 00000000..850c2bc5 --- /dev/null +++ b/packages/components/nodes/chatmodels/AzureChatOpenAI/AzureChatOpenAI_LlamaIndex.ts @@ -0,0 +1,135 @@ +import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' +import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { OpenAI, ALL_AVAILABLE_OPENAI_MODELS } from 'llamaindex' + +interface AzureOpenAIConfig { + apiKey?: string + endpoint?: string + apiVersion?: string + deploymentName?: string +} + +class AzureChatOpenAI_LlamaIndex_ChatModels implements INode { + label: string + name: string + version: number + type: string + icon: string + category: string + description: string + baseClasses: string[] + tags: string[] + credential: INodeParams + inputs: INodeParams[] + + constructor() { + this.label = 'AzureChatOpenAI' + this.name = 'azureChatOpenAI_LlamaIndex' + this.version = 1.0 + this.type = 'AzureChatOpenAI' + this.icon = 'Azure.svg' + this.category = 'Chat Models' + this.description = 'Wrapper around Azure OpenAI Chat LLM with LlamaIndex implementation' + this.baseClasses = [this.type, 'BaseChatModel_LlamaIndex', ...getBaseClasses(OpenAI)] + this.tags = ['LlamaIndex'] + this.credential = { + label: 'Connect Credential', + name: 'credential', + type: 'credential', + credentialNames: ['azureOpenAIApi'] + } + this.inputs = [ + { + label: 'Model Name', + name: 'modelName', + type: 'options', + options: [ + { + label: 'gpt-4', + name: 'gpt-4' + }, + { + label: 'gpt-4-32k', + name: 'gpt-4-32k' + }, + { + label: 'gpt-3.5-turbo', + name: 'gpt-3.5-turbo' + }, + { + label: 'gpt-3.5-turbo-16k', + name: 'gpt-3.5-turbo-16k' + } + ], + default: 'gpt-3.5-turbo-16k', + optional: true + }, + { + label: 'Temperature', + name: 'temperature', + type: 'number', + step: 0.1, + default: 0.9, + optional: true + }, + { + label: 'Max Tokens', + name: 'maxTokens', + type: 'number', + step: 1, + optional: true, + additionalParams: true + }, + { + label: 'Top Probability', + name: 'topP', + type: 'number', + step: 0.1, + optional: true, + additionalParams: true + }, + { + label: 'Timeout', + name: 'timeout', + type: 'number', + step: 1, + optional: true, + additionalParams: true + } + ] + } + + async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { + const modelName = nodeData.inputs?.modelName as keyof typeof ALL_AVAILABLE_OPENAI_MODELS + const temperature = nodeData.inputs?.temperature as string + const maxTokens = nodeData.inputs?.maxTokens as string + const topP = nodeData.inputs?.topP as string + const timeout = nodeData.inputs?.timeout as string + + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const azureOpenAIApiKey = getCredentialParam('azureOpenAIApiKey', credentialData, nodeData) + const azureOpenAIApiInstanceName = getCredentialParam('azureOpenAIApiInstanceName', credentialData, nodeData) + const azureOpenAIApiDeploymentName = getCredentialParam('azureOpenAIApiDeploymentName', credentialData, nodeData) + const azureOpenAIApiVersion = getCredentialParam('azureOpenAIApiVersion', credentialData, nodeData) + + const obj: Partial & { azure?: AzureOpenAIConfig } = { + temperature: parseFloat(temperature), + model: modelName, + azure: { + apiKey: azureOpenAIApiKey, + endpoint: `https://${azureOpenAIApiInstanceName}.openai.azure.com`, + apiVersion: azureOpenAIApiVersion, + deploymentName: azureOpenAIApiDeploymentName + } + } + + if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10) + if (topP) obj.topP = parseFloat(topP) + if (timeout) obj.timeout = parseInt(timeout, 10) + + const model = new OpenAI(obj) + return model + } +} + +module.exports = { nodeClass: AzureChatOpenAI_LlamaIndex_ChatModels } diff --git a/packages/components/nodes/chatmodels/ChatAnthropic/ChatAnthropic.ts b/packages/components/nodes/chatmodels/ChatAnthropic/ChatAnthropic.ts index 358a15d1..8209c04a 100644 --- a/packages/components/nodes/chatmodels/ChatAnthropic/ChatAnthropic.ts +++ b/packages/components/nodes/chatmodels/ChatAnthropic/ChatAnthropic.ts @@ -3,6 +3,7 @@ import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../ import { AnthropicInput, ChatAnthropic } from 'langchain/chat_models/anthropic' import { BaseCache } from 'langchain/schema' import { BaseLLMParams } from 'langchain/llms/base' +import { availableModels } from './utils' class ChatAnthropic_ChatModels implements INode { label: string @@ -42,67 +43,7 @@ class ChatAnthropic_ChatModels implements INode { label: 'Model Name', name: 'modelName', type: 'options', - options: [ - { - label: 'claude-2', - name: 'claude-2', - description: 'Claude 2 latest major version, automatically get updates to the model as they are released' - }, - { - label: 'claude-2.1', - name: 'claude-2.1', - description: 'Claude 2 latest full version' - }, - { - label: 'claude-instant-1', - name: 'claude-instant-1', - description: 'Claude Instant latest major version, automatically get updates to the model as they are released' - }, - { - label: 'claude-v1', - name: 'claude-v1' - }, - { - label: 'claude-v1-100k', - name: 'claude-v1-100k' - }, - { - label: 'claude-v1.0', - name: 'claude-v1.0' - }, - { - label: 'claude-v1.2', - name: 'claude-v1.2' - }, - { - label: 'claude-v1.3', - name: 'claude-v1.3' - }, - { - label: 'claude-v1.3-100k', - name: 'claude-v1.3-100k' - }, - { - label: 'claude-instant-v1', - name: 'claude-instant-v1' - }, - { - label: 'claude-instant-v1-100k', - name: 'claude-instant-v1-100k' - }, - { - label: 'claude-instant-v1.0', - name: 'claude-instant-v1.0' - }, - { - label: 'claude-instant-v1.1', - name: 'claude-instant-v1.1' - }, - { - label: 'claude-instant-v1.1-100k', - name: 'claude-instant-v1.1-100k' - } - ], + options: [...availableModels], default: 'claude-2', optional: true }, diff --git a/packages/components/nodes/chatmodels/ChatAnthropic/ChatAnthropic_LlamaIndex.ts b/packages/components/nodes/chatmodels/ChatAnthropic/ChatAnthropic_LlamaIndex.ts new file mode 100644 index 00000000..b989ef76 --- /dev/null +++ b/packages/components/nodes/chatmodels/ChatAnthropic/ChatAnthropic_LlamaIndex.ts @@ -0,0 +1,94 @@ +import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' +import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { Anthropic } from 'llamaindex' +import { availableModels } from './utils' + +class ChatAnthropic_LlamaIndex_ChatModels implements INode { + label: string + name: string + version: number + type: string + icon: string + category: string + description: string + tags: string[] + baseClasses: string[] + credential: INodeParams + inputs: INodeParams[] + + constructor() { + this.label = 'ChatAnthropic' + this.name = 'chatAnthropic_LlamaIndex' + this.version = 1.0 + this.type = 'ChatAnthropic' + this.icon = 'chatAnthropic.png' + this.category = 'Chat Models' + this.description = 'Wrapper around ChatAnthropic LLM with LlamaIndex implementation' + this.baseClasses = [this.type, 'BaseChatModel_LlamaIndex', ...getBaseClasses(Anthropic)] + this.tags = ['LlamaIndex'] + this.credential = { + label: 'Connect Credential', + name: 'credential', + type: 'credential', + credentialNames: ['anthropicApi'] + } + this.inputs = [ + { + label: 'Model Name', + name: 'modelName', + type: 'options', + options: [...availableModels], + default: 'claude-2', + optional: true + }, + { + label: 'Temperature', + name: 'temperature', + type: 'number', + step: 0.1, + default: 0.9, + optional: true + }, + { + label: 'Max Tokens', + name: 'maxTokensToSample', + type: 'number', + step: 1, + optional: true, + additionalParams: true + }, + { + label: 'Top P', + name: 'topP', + type: 'number', + step: 0.1, + optional: true, + additionalParams: true + } + ] + } + + async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { + const temperature = nodeData.inputs?.temperature as string + const modelName = nodeData.inputs?.modelName as string + const maxTokensToSample = nodeData.inputs?.maxTokensToSample as string + const topP = nodeData.inputs?.topP as string + + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const anthropicApiKey = getCredentialParam('anthropicApiKey', credentialData, nodeData) + + const obj: Partial = { + temperature: parseFloat(temperature), + model: modelName, + apiKey: anthropicApiKey + } + + if (maxTokensToSample) obj.maxTokens = parseInt(maxTokensToSample, 10) + if (topP) obj.topP = parseFloat(topP) + + const model = new Anthropic(obj) + return model + } +} + +module.exports = { nodeClass: ChatAnthropic_LlamaIndex_ChatModels } diff --git a/packages/components/nodes/chatmodels/ChatAnthropic/utils.ts b/packages/components/nodes/chatmodels/ChatAnthropic/utils.ts new file mode 100644 index 00000000..209996a6 --- /dev/null +++ b/packages/components/nodes/chatmodels/ChatAnthropic/utils.ts @@ -0,0 +1,61 @@ +export const availableModels = [ + { + label: 'claude-2', + name: 'claude-2', + description: 'Claude 2 latest major version, automatically get updates to the model as they are released' + }, + { + label: 'claude-2.1', + name: 'claude-2.1', + description: 'Claude 2 latest full version' + }, + { + label: 'claude-instant-1', + name: 'claude-instant-1', + description: 'Claude Instant latest major version, automatically get updates to the model as they are released' + }, + { + label: 'claude-v1', + name: 'claude-v1' + }, + { + label: 'claude-v1-100k', + name: 'claude-v1-100k' + }, + { + label: 'claude-v1.0', + name: 'claude-v1.0' + }, + { + label: 'claude-v1.2', + name: 'claude-v1.2' + }, + { + label: 'claude-v1.3', + name: 'claude-v1.3' + }, + { + label: 'claude-v1.3-100k', + name: 'claude-v1.3-100k' + }, + { + label: 'claude-instant-v1', + name: 'claude-instant-v1' + }, + { + label: 'claude-instant-v1-100k', + name: 'claude-instant-v1-100k' + }, + { + label: 'claude-instant-v1.0', + name: 'claude-instant-v1.0' + }, + { + label: 'claude-instant-v1.1', + name: 'claude-instant-v1.1' + }, + { + label: 'claude-instant-v1.1-100k', + name: 'claude-instant-v1.1-100k' + } +] diff --git a/packages/components/nodes/chatmodels/ChatOpenAI/ChatOpenAI_LlamaIndex.ts b/packages/components/nodes/chatmodels/ChatOpenAI/ChatOpenAI_LlamaIndex.ts new file mode 100644 index 00000000..147bfe3f --- /dev/null +++ b/packages/components/nodes/chatmodels/ChatOpenAI/ChatOpenAI_LlamaIndex.ts @@ -0,0 +1,148 @@ +import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' +import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { OpenAI, ALL_AVAILABLE_OPENAI_MODELS } from 'llamaindex' + +class ChatOpenAI_LlamaIndex_LLMs implements INode { + label: string + name: string + version: number + type: string + icon: string + category: string + description: string + baseClasses: string[] + tags: string[] + credential: INodeParams + inputs: INodeParams[] + + constructor() { + this.label = 'ChatOpenAI' + this.name = 'chatOpenAI_LlamaIndex' + this.version = 1.0 + this.type = 'ChatOpenAI' + this.icon = 'openai.png' + this.category = 'Chat Models' + this.description = 'Wrapper around OpenAI Chat LLM with LlamaIndex implementation' + this.baseClasses = [this.type, 'BaseChatModel_LlamaIndex', ...getBaseClasses(OpenAI)] + this.tags = ['LlamaIndex'] + this.credential = { + label: 'Connect Credential', + name: 'credential', + type: 'credential', + credentialNames: ['openAIApi'] + } + this.inputs = [ + { + label: 'Model Name', + name: 'modelName', + type: 'options', + options: [ + { + label: 'gpt-4', + name: 'gpt-4' + }, + { + label: 'gpt-4-1106-preview', + name: 'gpt-4-1106-preview' + }, + { + label: 'gpt-4-vision-preview', + name: 'gpt-4-vision-preview' + }, + { + label: 'gpt-4-0613', + name: 'gpt-4-0613' + }, + { + label: 'gpt-4-32k', + name: 'gpt-4-32k' + }, + { + label: 'gpt-4-32k-0613', + name: 'gpt-4-32k-0613' + }, + { + label: 'gpt-3.5-turbo', + name: 'gpt-3.5-turbo' + }, + { + label: 'gpt-3.5-turbo-1106', + name: 'gpt-3.5-turbo-1106' + }, + { + label: 'gpt-3.5-turbo-0613', + name: 'gpt-3.5-turbo-0613' + }, + { + label: 'gpt-3.5-turbo-16k', + name: 'gpt-3.5-turbo-16k' + }, + { + label: 'gpt-3.5-turbo-16k-0613', + name: 'gpt-3.5-turbo-16k-0613' + } + ], + default: 'gpt-3.5-turbo', + optional: true + }, + { + label: 'Temperature', + name: 'temperature', + type: 'number', + step: 0.1, + default: 0.9, + optional: true + }, + { + label: 'Max Tokens', + name: 'maxTokens', + type: 'number', + step: 1, + optional: true, + additionalParams: true + }, + { + label: 'Top Probability', + name: 'topP', + type: 'number', + step: 0.1, + optional: true, + additionalParams: true + }, + { + label: 'Timeout', + name: 'timeout', + type: 'number', + step: 1, + optional: true, + additionalParams: true + } + ] + } + + async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { + const temperature = nodeData.inputs?.temperature as string + const modelName = nodeData.inputs?.modelName as keyof typeof ALL_AVAILABLE_OPENAI_MODELS + const maxTokens = nodeData.inputs?.maxTokens as string + const topP = nodeData.inputs?.topP as string + const timeout = nodeData.inputs?.timeout as string + + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData) + + const obj: Partial = { + temperature: parseFloat(temperature), + model: modelName, + apiKey: openAIApiKey + } + + if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10) + if (topP) obj.topP = parseFloat(topP) + if (timeout) obj.timeout = parseInt(timeout, 10) + + const model = new OpenAI(obj) + return model + } +} + +module.exports = { nodeClass: ChatOpenAI_LlamaIndex_LLMs } diff --git a/packages/components/nodes/embeddings/AzureOpenAIEmbedding/AzureOpenAIEmbedding_LlamaIndex.ts b/packages/components/nodes/embeddings/AzureOpenAIEmbedding/AzureOpenAIEmbedding_LlamaIndex.ts new file mode 100644 index 00000000..38e45402 --- /dev/null +++ b/packages/components/nodes/embeddings/AzureOpenAIEmbedding/AzureOpenAIEmbedding_LlamaIndex.ts @@ -0,0 +1,77 @@ +import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' +import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { OpenAIEmbedding } from 'llamaindex' + +interface AzureOpenAIConfig { + apiKey?: string + endpoint?: string + apiVersion?: string + deploymentName?: string +} + +class AzureOpenAIEmbedding_LlamaIndex_Embeddings implements INode { + label: string + name: string + version: number + type: string + icon: string + category: string + description: string + baseClasses: string[] + credential: INodeParams + tags: string[] + inputs: INodeParams[] + + constructor() { + this.label = 'Azure OpenAI Embeddings' + this.name = 'azureOpenAIEmbeddingsLlamaIndex' + this.version = 1.0 + this.type = 'AzureOpenAIEmbeddings' + this.icon = 'Azure.svg' + this.category = 'Embeddings' + this.description = 'Azure OpenAI API embeddings with LlamaIndex implementation' + this.baseClasses = [this.type, 'BaseEmbedding_LlamaIndex', ...getBaseClasses(OpenAIEmbedding)] + this.tags = ['LlamaIndex'] + this.credential = { + label: 'Connect Credential', + name: 'credential', + type: 'credential', + credentialNames: ['azureOpenAIApi'] + } + this.inputs = [ + { + label: 'Timeout', + name: 'timeout', + type: 'number', + optional: true, + additionalParams: true + } + ] + } + + async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { + const timeout = nodeData.inputs?.timeout as string + + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const azureOpenAIApiKey = getCredentialParam('azureOpenAIApiKey', credentialData, nodeData) + const azureOpenAIApiInstanceName = getCredentialParam('azureOpenAIApiInstanceName', credentialData, nodeData) + const azureOpenAIApiDeploymentName = getCredentialParam('azureOpenAIApiDeploymentName', credentialData, nodeData) + const azureOpenAIApiVersion = getCredentialParam('azureOpenAIApiVersion', credentialData, nodeData) + + const obj: Partial & { azure?: AzureOpenAIConfig } = { + azure: { + apiKey: azureOpenAIApiKey, + endpoint: `https://${azureOpenAIApiInstanceName}.openai.azure.com`, + apiVersion: azureOpenAIApiVersion, + deploymentName: azureOpenAIApiDeploymentName + } + } + + if (timeout) obj.timeout = parseInt(timeout, 10) + + const model = new OpenAIEmbedding(obj) + return model + } +} + +module.exports = { nodeClass: AzureOpenAIEmbedding_LlamaIndex_Embeddings } diff --git a/packages/components/nodes/embeddings/OpenAIEmbedding/OpenAIEmbedding_LlamaIndex.ts b/packages/components/nodes/embeddings/OpenAIEmbedding/OpenAIEmbedding_LlamaIndex.ts new file mode 100644 index 00000000..4ff780e3 --- /dev/null +++ b/packages/components/nodes/embeddings/OpenAIEmbedding/OpenAIEmbedding_LlamaIndex.ts @@ -0,0 +1,68 @@ +import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' +import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { OpenAIEmbedding } from 'llamaindex' + +class OpenAIEmbedding_LlamaIndex_Embeddings implements INode { + label: string + name: string + version: number + type: string + icon: string + category: string + description: string + baseClasses: string[] + tags: string[] + credential: INodeParams + inputs: INodeParams[] + + constructor() { + this.label = 'OpenAI Embedding' + this.name = 'openAIEmbedding_LlamaIndex' + this.version = 1.0 + this.type = 'OpenAIEmbedding' + this.icon = 'openai.png' + this.category = 'Embeddings' + this.description = 'OpenAI Embedding with LlamaIndex implementation' + this.baseClasses = [this.type, 'BaseEmbedding_LlamaIndex', ...getBaseClasses(OpenAIEmbedding)] + this.tags = ['LlamaIndex'] + this.credential = { + label: 'Connect Credential', + name: 'credential', + type: 'credential', + credentialNames: ['openAIApi'] + } + this.inputs = [ + { + label: 'Timeout', + name: 'timeout', + type: 'number', + optional: true, + additionalParams: true + }, + { + label: 'BasePath', + name: 'basepath', + type: 'string', + optional: true, + additionalParams: true + } + ] + } + + async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { + const timeout = nodeData.inputs?.timeout as string + + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData) + + const obj: Partial = { + apiKey: openAIApiKey + } + if (timeout) obj.timeout = parseInt(timeout, 10) + + const model = new OpenAIEmbedding(obj) + return model + } +} + +module.exports = { nodeClass: OpenAIEmbedding_LlamaIndex_Embeddings } diff --git a/packages/components/nodes/engine/ChatEngine/ContextChatEngine.ts b/packages/components/nodes/engine/ChatEngine/ContextChatEngine.ts new file mode 100644 index 00000000..dd77601a --- /dev/null +++ b/packages/components/nodes/engine/ChatEngine/ContextChatEngine.ts @@ -0,0 +1,178 @@ +import { ICommonObject, IMessage, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' +import { ContextChatEngine, ChatMessage } from 'llamaindex' + +class ContextChatEngine_LlamaIndex implements INode { + label: string + name: string + version: number + description: string + type: string + icon: string + category: string + baseClasses: string[] + tags: string[] + inputs: INodeParams[] + outputs: INodeOutputsValue[] + + constructor() { + this.label = 'Context Chat Engine' + this.name = 'contextChatEngine' + this.version = 1.0 + this.type = 'ContextChatEngine' + this.icon = 'context-chat-engine.png' + this.category = 'Engine' + this.description = 'Answer question based on retrieved documents (context) with built-in memory to remember conversation' + this.baseClasses = [this.type] + this.tags = ['LlamaIndex'] + this.inputs = [ + { + label: 'Chat Model', + name: 'model', + type: 'BaseChatModel_LlamaIndex' + }, + { + label: 'Vector Store Retriever', + name: 'vectorStoreRetriever', + type: 'VectorIndexRetriever' + }, + { + label: 'Memory', + name: 'memory', + type: 'BaseChatMemory' + }, + { + label: 'System Message', + name: 'systemMessagePrompt', + type: 'string', + rows: 4, + optional: true, + placeholder: + 'I want you to act as a document that I am having a conversation with. Your name is "AI Assistant". You will provide me with answers from the given info. If the answer is not included, say exactly "Hmm, I am not sure." and stop after that. Refuse to answer any question not about the info. Never break character.' + } + ] + } + + async init(nodeData: INodeData): Promise { + const model = nodeData.inputs?.model + const vectorStoreRetriever = nodeData.inputs?.vectorStoreRetriever + const memory = nodeData.inputs?.memory + + const chatEngine = new ContextChatEngine({ chatModel: model, retriever: vectorStoreRetriever }) + ;(chatEngine as any).memory = memory + return chatEngine + } + + async run(nodeData: INodeData, input: string, options: ICommonObject): Promise { + const chatEngine = nodeData.instance as ContextChatEngine + const systemMessagePrompt = nodeData.inputs?.systemMessagePrompt as string + const memory = nodeData.inputs?.memory + + const chatHistory = [] as ChatMessage[] + + let sessionId = '' + if (memory) { + if (memory.isSessionIdUsingChatMessageId) sessionId = options.chatId + else sessionId = nodeData.inputs?.sessionId + } + + if (systemMessagePrompt) { + chatHistory.push({ + content: systemMessagePrompt, + role: 'user' + }) + } + + /* When incomingInput.history is provided, only force replace chatHistory if its ShortTermMemory + * LongTermMemory will automatically retrieved chatHistory from sessionId + */ + if (options && options.chatHistory && memory.isShortTermMemory) { + await memory.resumeMessages(options.chatHistory) + } + + const msgs: IMessage[] = await memory.getChatMessages(sessionId) + for (const message of msgs) { + if (message.type === 'apiMessage') { + chatHistory.push({ + content: message.message, + role: 'assistant' + }) + } else if (message.type === 'userMessage') { + chatHistory.push({ + content: message.message, + role: 'user' + }) + } + } + + if (options.socketIO && options.socketIOClientId) { + let response = '' + const stream = await chatEngine.chat(input, chatHistory, true) + let isStart = true + const onNextPromise = () => { + return new Promise((resolve, reject) => { + const onNext = async () => { + try { + const { value, done } = await stream.next() + if (!done) { + if (isStart) { + options.socketIO.to(options.socketIOClientId).emit('start') + isStart = false + } + options.socketIO.to(options.socketIOClientId).emit('token', value) + response += value + onNext() + } else { + resolve(response) + } + } catch (error) { + reject(error) + } + } + onNext() + }) + } + + try { + const result = await onNextPromise() + if (memory) { + await memory.addChatMessages( + [ + { + text: input, + type: 'userMessage' + }, + { + text: result, + type: 'apiMessage' + } + ], + sessionId + ) + } + return result as string + } catch (error) { + throw new Error(error) + } + } else { + const response = await chatEngine.chat(input, chatHistory) + if (memory) { + await memory.addChatMessages( + [ + { + text: input, + type: 'userMessage' + }, + { + text: response?.response, + type: 'apiMessage' + } + ], + sessionId + ) + } + return response?.response + } + } +} + +module.exports = { nodeClass: ContextChatEngine_LlamaIndex } diff --git a/packages/components/nodes/engine/ChatEngine/SimpleChatEngine.ts b/packages/components/nodes/engine/ChatEngine/SimpleChatEngine.ts new file mode 100644 index 00000000..9ae9c2f1 --- /dev/null +++ b/packages/components/nodes/engine/ChatEngine/SimpleChatEngine.ts @@ -0,0 +1,171 @@ +import { ICommonObject, IMessage, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' +import { ChatMessage, SimpleChatEngine } from 'llamaindex' + +class SimpleChatEngine_LlamaIndex implements INode { + label: string + name: string + version: number + description: string + type: string + icon: string + category: string + baseClasses: string[] + tags: string[] + inputs: INodeParams[] + outputs: INodeOutputsValue[] + + constructor() { + this.label = 'Simple Chat Engine' + this.name = 'simpleChatEngine' + this.version = 1.0 + this.type = 'SimpleChatEngine' + this.icon = 'chat-engine.png' + this.category = 'Engine' + this.description = 'Simple engine to handle back and forth conversations' + this.baseClasses = [this.type] + this.tags = ['LlamaIndex'] + this.inputs = [ + { + label: 'Chat Model', + name: 'model', + type: 'BaseChatModel_LlamaIndex' + }, + { + label: 'Memory', + name: 'memory', + type: 'BaseChatMemory' + }, + { + label: 'System Message', + name: 'systemMessagePrompt', + type: 'string', + rows: 4, + optional: true, + placeholder: 'You are a helpful assistant' + } + ] + } + + async init(nodeData: INodeData): Promise { + const model = nodeData.inputs?.model + const memory = nodeData.inputs?.memory + + const chatEngine = new SimpleChatEngine({ llm: model }) + ;(chatEngine as any).memory = memory + return chatEngine + } + + async run(nodeData: INodeData, input: string, options: ICommonObject): Promise { + const chatEngine = nodeData.instance as SimpleChatEngine + const systemMessagePrompt = nodeData.inputs?.systemMessagePrompt as string + const memory = nodeData.inputs?.memory + + const chatHistory = [] as ChatMessage[] + + let sessionId = '' + if (memory) { + if (memory.isSessionIdUsingChatMessageId) sessionId = options.chatId + else sessionId = nodeData.inputs?.sessionId + } + + if (systemMessagePrompt) { + chatHistory.push({ + content: systemMessagePrompt, + role: 'user' + }) + } + + /* When incomingInput.history is provided, only force replace chatHistory if its ShortTermMemory + * LongTermMemory will automatically retrieved chatHistory from sessionId + */ + if (options && options.chatHistory && memory.isShortTermMemory) { + await memory.resumeMessages(options.chatHistory) + } + + const msgs: IMessage[] = await memory.getChatMessages(sessionId) + for (const message of msgs) { + if (message.type === 'apiMessage') { + chatHistory.push({ + content: message.message, + role: 'assistant' + }) + } else if (message.type === 'userMessage') { + chatHistory.push({ + content: message.message, + role: 'user' + }) + } + } + + if (options.socketIO && options.socketIOClientId) { + let response = '' + const stream = await chatEngine.chat(input, chatHistory, true) + let isStart = true + const onNextPromise = () => { + return new Promise((resolve, reject) => { + const onNext = async () => { + try { + const { value, done } = await stream.next() + if (!done) { + if (isStart) { + options.socketIO.to(options.socketIOClientId).emit('start') + isStart = false + } + options.socketIO.to(options.socketIOClientId).emit('token', value) + response += value + onNext() + } else { + resolve(response) + } + } catch (error) { + reject(error) + } + } + onNext() + }) + } + + try { + const result = await onNextPromise() + if (memory) { + await memory.addChatMessages( + [ + { + text: input, + type: 'userMessage' + }, + { + text: result, + type: 'apiMessage' + } + ], + sessionId + ) + } + return result as string + } catch (error) { + throw new Error(error) + } + } else { + const response = await chatEngine.chat(input, chatHistory) + if (memory) { + await memory.addChatMessages( + [ + { + text: input, + type: 'userMessage' + }, + { + text: response?.response, + type: 'apiMessage' + } + ], + sessionId + ) + } + return response?.response + } + } +} + +module.exports = { nodeClass: SimpleChatEngine_LlamaIndex } diff --git a/packages/components/nodes/engine/ChatEngine/chat-engine.png b/packages/components/nodes/engine/ChatEngine/chat-engine.png new file mode 100644 index 00000000..d614b888 Binary files /dev/null and b/packages/components/nodes/engine/ChatEngine/chat-engine.png differ diff --git a/packages/components/nodes/engine/ChatEngine/context-chat-engine.png b/packages/components/nodes/engine/ChatEngine/context-chat-engine.png new file mode 100644 index 00000000..ef4adc13 Binary files /dev/null and b/packages/components/nodes/engine/ChatEngine/context-chat-engine.png differ diff --git a/packages/components/nodes/engine/QueryEngine/QueryEngine.ts b/packages/components/nodes/engine/QueryEngine/QueryEngine.ts new file mode 100644 index 00000000..7059c260 --- /dev/null +++ b/packages/components/nodes/engine/QueryEngine/QueryEngine.ts @@ -0,0 +1,126 @@ +import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' +import { + RetrieverQueryEngine, + BaseNode, + Metadata, + ResponseSynthesizer, + CompactAndRefine, + TreeSummarize, + Refine, + SimpleResponseBuilder +} from 'llamaindex' + +class QueryEngine_LlamaIndex implements INode { + label: string + name: string + version: number + description: string + type: string + icon: string + category: string + baseClasses: string[] + tags: string[] + inputs: INodeParams[] + outputs: INodeOutputsValue[] + + constructor() { + this.label = 'Query Engine' + this.name = 'queryEngine' + this.version = 1.0 + this.type = 'QueryEngine' + this.icon = 'query-engine.png' + this.category = 'Engine' + this.description = 'Simple query engine built to answer question over your data, without memory' + this.baseClasses = [this.type] + this.tags = ['LlamaIndex'] + this.inputs = [ + { + label: 'Vector Store Retriever', + name: 'vectorStoreRetriever', + type: 'VectorIndexRetriever' + }, + { + label: 'Response Synthesizer', + name: 'responseSynthesizer', + type: 'ResponseSynthesizer', + description: + 'ResponseSynthesizer is responsible for sending the query, nodes, and prompt templates to the LLM to generate a response. See more', + optional: true + }, + { + label: 'Return Source Documents', + name: 'returnSourceDocuments', + type: 'boolean', + optional: true + } + ] + } + + async init(nodeData: INodeData): Promise { + const vectorStoreRetriever = nodeData.inputs?.vectorStoreRetriever + const responseSynthesizerObj = nodeData.inputs?.responseSynthesizer + + if (responseSynthesizerObj) { + if (responseSynthesizerObj.type === 'TreeSummarize') { + const responseSynthesizer = new ResponseSynthesizer({ + responseBuilder: new TreeSummarize(vectorStoreRetriever.serviceContext, responseSynthesizerObj.textQAPromptTemplate), + serviceContext: vectorStoreRetriever.serviceContext + }) + return new RetrieverQueryEngine(vectorStoreRetriever, responseSynthesizer) + } else if (responseSynthesizerObj.type === 'CompactAndRefine') { + const responseSynthesizer = new ResponseSynthesizer({ + responseBuilder: new CompactAndRefine( + vectorStoreRetriever.serviceContext, + responseSynthesizerObj.textQAPromptTemplate, + responseSynthesizerObj.refinePromptTemplate + ), + serviceContext: vectorStoreRetriever.serviceContext + }) + return new RetrieverQueryEngine(vectorStoreRetriever, responseSynthesizer) + } else if (responseSynthesizerObj.type === 'Refine') { + const responseSynthesizer = new ResponseSynthesizer({ + responseBuilder: new Refine( + vectorStoreRetriever.serviceContext, + responseSynthesizerObj.textQAPromptTemplate, + responseSynthesizerObj.refinePromptTemplate + ), + serviceContext: vectorStoreRetriever.serviceContext + }) + return new RetrieverQueryEngine(vectorStoreRetriever, responseSynthesizer) + } else if (responseSynthesizerObj.type === 'SimpleResponseBuilder') { + const responseSynthesizer = new ResponseSynthesizer({ + responseBuilder: new SimpleResponseBuilder(vectorStoreRetriever.serviceContext), + serviceContext: vectorStoreRetriever.serviceContext + }) + return new RetrieverQueryEngine(vectorStoreRetriever, responseSynthesizer) + } + } + + const queryEngine = new RetrieverQueryEngine(vectorStoreRetriever) + return queryEngine + } + + async run(nodeData: INodeData, input: string): Promise { + const queryEngine = nodeData.instance as RetrieverQueryEngine + const returnSourceDocuments = nodeData.inputs?.returnSourceDocuments as boolean + + const response = await queryEngine.query(input) + if (returnSourceDocuments && response.sourceNodes?.length) + return { text: response?.response, sourceDocuments: reformatSourceDocuments(response.sourceNodes) } + + return response?.response + } +} + +const reformatSourceDocuments = (sourceNodes: BaseNode[]) => { + const sourceDocuments = [] + for (const node of sourceNodes) { + sourceDocuments.push({ + pageContent: (node as any).text, + metadata: node.metadata + }) + } + return sourceDocuments +} + +module.exports = { nodeClass: QueryEngine_LlamaIndex } diff --git a/packages/components/nodes/engine/QueryEngine/query-engine.png b/packages/components/nodes/engine/QueryEngine/query-engine.png new file mode 100644 index 00000000..68efdbe0 Binary files /dev/null and b/packages/components/nodes/engine/QueryEngine/query-engine.png differ diff --git a/packages/components/nodes/memory/BufferMemory/BufferMemory.ts b/packages/components/nodes/memory/BufferMemory/BufferMemory.ts index 7793d96d..5310f88d 100644 --- a/packages/components/nodes/memory/BufferMemory/BufferMemory.ts +++ b/packages/components/nodes/memory/BufferMemory/BufferMemory.ts @@ -1,6 +1,6 @@ -import { INode, INodeData, INodeParams } from '../../../src/Interface' -import { getBaseClasses } from '../../../src/utils' -import { BufferMemory } from 'langchain/memory' +import { IMessage, INode, INodeData, INodeParams, MessageType } from '../../../src/Interface' +import { convertBaseMessagetoIMessage, getBaseClasses } from '../../../src/utils' +import { BufferMemory, BufferMemoryInput } from 'langchain/memory' class BufferMemory_Memory implements INode { label: string @@ -41,7 +41,7 @@ class BufferMemory_Memory implements INode { async init(nodeData: INodeData): Promise { const memoryKey = nodeData.inputs?.memoryKey as string const inputKey = nodeData.inputs?.inputKey as string - return new BufferMemory({ + return new BufferMemoryExtended({ returnMessages: true, memoryKey, inputKey @@ -49,4 +49,43 @@ class BufferMemory_Memory implements INode { } } +class BufferMemoryExtended extends BufferMemory { + isShortTermMemory = true + + constructor(fields: BufferMemoryInput) { + super(fields) + } + + async getChatMessages(): Promise { + const memoryResult = await this.loadMemoryVariables({}) + const baseMessages = memoryResult[this.memoryKey ?? 'chat_history'] + return convertBaseMessagetoIMessage(baseMessages) + } + + async addChatMessages(msgArray: { text: string; type: MessageType }[]): Promise { + const input = msgArray.find((msg) => msg.type === 'userMessage') + const output = msgArray.find((msg) => msg.type === 'apiMessage') + + const inputValues = { [this.inputKey ?? 'input']: input?.text } + const outputValues = { output: output?.text } + + await this.saveContext(inputValues, outputValues) + } + + async clearChatMessages(): Promise { + await this.clear() + } + + async resumeMessages(messages: IMessage[]): Promise { + // Clear existing chatHistory to avoid duplication + if (messages.length) await this.clear() + + // Insert into chatHistory + for (const msg of messages) { + if (msg.type === 'userMessage') await this.chatHistory.addUserMessage(msg.message) + else if (msg.type === 'apiMessage') await this.chatHistory.addAIChatMessage(msg.message) + } + } +} + module.exports = { nodeClass: BufferMemory_Memory } diff --git a/packages/components/nodes/memory/BufferWindowMemory/BufferWindowMemory.ts b/packages/components/nodes/memory/BufferWindowMemory/BufferWindowMemory.ts index 84e607e5..9915d48d 100644 --- a/packages/components/nodes/memory/BufferWindowMemory/BufferWindowMemory.ts +++ b/packages/components/nodes/memory/BufferWindowMemory/BufferWindowMemory.ts @@ -1,5 +1,5 @@ -import { INode, INodeData, INodeParams } from '../../../src/Interface' -import { getBaseClasses } from '../../../src/utils' +import { IMessage, INode, INodeData, INodeParams, MessageType } from '../../../src/Interface' +import { convertBaseMessagetoIMessage, getBaseClasses } from '../../../src/utils' import { BufferWindowMemory, BufferWindowMemoryInput } from 'langchain/memory' class BufferWindowMemory_Memory implements INode { @@ -57,7 +57,46 @@ class BufferWindowMemory_Memory implements INode { k: parseInt(k, 10) } - return new BufferWindowMemory(obj) + return new BufferWindowMemoryExtended(obj) + } +} + +class BufferWindowMemoryExtended extends BufferWindowMemory { + isShortTermMemory = true + + constructor(fields: BufferWindowMemoryInput) { + super(fields) + } + + async getChatMessages(): Promise { + const memoryResult = await this.loadMemoryVariables({}) + const baseMessages = memoryResult[this.memoryKey ?? 'chat_history'] + return convertBaseMessagetoIMessage(baseMessages) + } + + async addChatMessages(msgArray: { text: string; type: MessageType }[]): Promise { + const input = msgArray.find((msg) => msg.type === 'userMessage') + const output = msgArray.find((msg) => msg.type === 'apiMessage') + + const inputValues = { [this.inputKey ?? 'input']: input?.text } + const outputValues = { output: output?.text } + + await this.saveContext(inputValues, outputValues) + } + + async clearChatMessages(): Promise { + await this.clear() + } + + async resumeMessages(messages: IMessage[]): Promise { + // Clear existing chatHistory to avoid duplication + if (messages.length) await this.clear() + + // Insert into chatHistory + for (const msg of messages) { + if (msg.type === 'userMessage') await this.chatHistory.addUserMessage(msg.message) + else if (msg.type === 'apiMessage') await this.chatHistory.addAIChatMessage(msg.message) + } } } diff --git a/packages/components/nodes/memory/ConversationSummaryMemory/ConversationSummaryMemory.ts b/packages/components/nodes/memory/ConversationSummaryMemory/ConversationSummaryMemory.ts index 332d73aa..e88beb13 100644 --- a/packages/components/nodes/memory/ConversationSummaryMemory/ConversationSummaryMemory.ts +++ b/packages/components/nodes/memory/ConversationSummaryMemory/ConversationSummaryMemory.ts @@ -1,5 +1,5 @@ -import { INode, INodeData, INodeParams } from '../../../src/Interface' -import { getBaseClasses } from '../../../src/utils' +import { IMessage, INode, INodeData, INodeParams, MessageType } from '../../../src/Interface' +import { convertBaseMessagetoIMessage, getBaseClasses } from '../../../src/utils' import { ConversationSummaryMemory, ConversationSummaryMemoryInput } from 'langchain/memory' import { BaseLanguageModel } from 'langchain/base_language' @@ -56,7 +56,50 @@ class ConversationSummaryMemory_Memory implements INode { inputKey } - return new ConversationSummaryMemory(obj) + return new ConversationSummaryMemoryExtended(obj) + } +} + +class ConversationSummaryMemoryExtended extends ConversationSummaryMemory { + isShortTermMemory = true + + constructor(fields: ConversationSummaryMemoryInput) { + super(fields) + } + + async getChatMessages(): Promise { + const memoryResult = await this.loadMemoryVariables({}) + const baseMessages = memoryResult[this.memoryKey ?? 'chat_history'] + return convertBaseMessagetoIMessage(baseMessages) + } + + async addChatMessages(msgArray: { text: string; type: MessageType }[]): Promise { + const input = msgArray.find((msg) => msg.type === 'userMessage') + const output = msgArray.find((msg) => msg.type === 'apiMessage') + + const inputValues = { [this.inputKey ?? 'input']: input?.text } + const outputValues = { output: output?.text } + + await this.saveContext(inputValues, outputValues) + } + + async clearChatMessages(): Promise { + await this.clear() + } + + async resumeMessages(messages: IMessage[]): Promise { + // Clear existing chatHistory to avoid duplication + if (messages.length) await this.clear() + + // Insert into chatHistory + for (const msg of messages) { + if (msg.type === 'userMessage') await this.chatHistory.addUserMessage(msg.message) + else if (msg.type === 'apiMessage') await this.chatHistory.addAIChatMessage(msg.message) + } + + // Replace buffer + const chatMessages = await this.chatHistory.getMessages() + this.buffer = await this.predictNewSummary(chatMessages.slice(-2), this.buffer) } } diff --git a/packages/components/nodes/memory/DynamoDb/DynamoDb.ts b/packages/components/nodes/memory/DynamoDb/DynamoDb.ts index 8ca6cf9e..a1c44554 100644 --- a/packages/components/nodes/memory/DynamoDb/DynamoDb.ts +++ b/packages/components/nodes/memory/DynamoDb/DynamoDb.ts @@ -1,15 +1,19 @@ import { - ICommonObject, - INode, - INodeData, - INodeParams, - getBaseClasses, - getCredentialData, - getCredentialParam, - serializeChatHistory -} from '../../../src' + DynamoDBClient, + DynamoDBClientConfig, + GetItemCommand, + GetItemCommandInput, + UpdateItemCommand, + UpdateItemCommandInput, + DeleteItemCommand, + DeleteItemCommandInput, + AttributeValue +} from '@aws-sdk/client-dynamodb' import { DynamoDBChatMessageHistory } from 'langchain/stores/message/dynamodb' import { BufferMemory, BufferMemoryInput } from 'langchain/memory' +import { mapStoredMessageToChatMessage, AIMessage, HumanMessage, StoredMessage } from 'langchain/schema' +import { convertBaseMessagetoIMessage, getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { ICommonObject, IMessage, INode, INodeData, INodeParams, MessageType } from '../../../src/Interface' class DynamoDb_Memory implements INode { label: string @@ -60,7 +64,8 @@ class DynamoDb_Memory implements INode { label: 'Session ID', name: 'sessionId', type: 'string', - description: 'If not specified, the first CHAT_MESSAGE_ID will be used as sessionId', + description: + 'If not specified, a random id will be used. Learn more', default: '', additionalParams: true, optional: true @@ -78,73 +83,205 @@ class DynamoDb_Memory implements INode { async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { return initalizeDynamoDB(nodeData, options) } - - //@ts-ignore - memoryMethods = { - async clearSessionMemory(nodeData: INodeData, options: ICommonObject): Promise { - const dynamodbMemory = await initalizeDynamoDB(nodeData, options) - const sessionId = nodeData.inputs?.sessionId as string - const chatId = options?.chatId as string - options.logger.info(`Clearing DynamoDb memory session ${sessionId ? sessionId : chatId}`) - await dynamodbMemory.clear() - options.logger.info(`Successfully cleared DynamoDb memory session ${sessionId ? sessionId : chatId}`) - }, - async getChatMessages(nodeData: INodeData, options: ICommonObject): Promise { - const memoryKey = nodeData.inputs?.memoryKey as string - const dynamodbMemory = await initalizeDynamoDB(nodeData, options) - const key = memoryKey ?? 'chat_history' - const memoryResult = await dynamodbMemory.loadMemoryVariables({}) - return serializeChatHistory(memoryResult[key]) - } - } } const initalizeDynamoDB = async (nodeData: INodeData, options: ICommonObject): Promise => { const tableName = nodeData.inputs?.tableName as string const partitionKey = nodeData.inputs?.partitionKey as string - const sessionId = nodeData.inputs?.sessionId as string const region = nodeData.inputs?.region as string const memoryKey = nodeData.inputs?.memoryKey as string const chatId = options.chatId let isSessionIdUsingChatMessageId = false - if (!sessionId && chatId) isSessionIdUsingChatMessageId = true + let sessionId = '' + + if (!nodeData.inputs?.sessionId && chatId) { + isSessionIdUsingChatMessageId = true + sessionId = chatId + } else { + sessionId = nodeData.inputs?.sessionId + } const credentialData = await getCredentialData(nodeData.credential ?? '', options) const accessKeyId = getCredentialParam('accessKey', credentialData, nodeData) const secretAccessKey = getCredentialParam('secretAccessKey', credentialData, nodeData) + const config: DynamoDBClientConfig = { + region, + credentials: { + accessKeyId, + secretAccessKey + } + } + + const client = new DynamoDBClient(config ?? {}) + const dynamoDb = new DynamoDBChatMessageHistory({ tableName, partitionKey, sessionId: sessionId ? sessionId : chatId, - config: { - region, - credentials: { - accessKeyId, - secretAccessKey - } - } + config }) const memory = new BufferMemoryExtended({ memoryKey: memoryKey ?? 'chat_history', chatHistory: dynamoDb, - isSessionIdUsingChatMessageId + isSessionIdUsingChatMessageId, + sessionId, + dynamodbClient: client }) return memory } interface BufferMemoryExtendedInput { isSessionIdUsingChatMessageId: boolean + dynamodbClient: DynamoDBClient + sessionId: string +} + +interface DynamoDBSerializedChatMessage { + M: { + type: { + S: string + } + text: { + S: string + } + role?: { + S: string + } + } } class BufferMemoryExtended extends BufferMemory { - isSessionIdUsingChatMessageId? = false + isSessionIdUsingChatMessageId = false + sessionId = '' + dynamodbClient: DynamoDBClient - constructor(fields: BufferMemoryInput & Partial) { + constructor(fields: BufferMemoryInput & BufferMemoryExtendedInput) { super(fields) this.isSessionIdUsingChatMessageId = fields.isSessionIdUsingChatMessageId + this.sessionId = fields.sessionId + this.dynamodbClient = fields.dynamodbClient + } + + overrideDynamoKey(overrideSessionId = '') { + const existingDynamoKey = (this as any).dynamoKey + const partitionKey = (this as any).partitionKey + + let newDynamoKey: Record = {} + + if (Object.keys(existingDynamoKey).includes(partitionKey)) { + newDynamoKey[partitionKey] = { S: overrideSessionId } + } + + return Object.keys(newDynamoKey).length ? newDynamoKey : existingDynamoKey + } + + async addNewMessage( + messages: StoredMessage[], + client: DynamoDBClient, + tableName = '', + dynamoKey: Record = {}, + messageAttributeName = 'messages' + ) { + const params: UpdateItemCommandInput = { + TableName: tableName, + Key: dynamoKey, + ExpressionAttributeNames: { + '#m': messageAttributeName + }, + ExpressionAttributeValues: { + ':empty_list': { + L: [] + }, + ':m': { + L: messages.map((message) => { + const dynamoSerializedMessage: DynamoDBSerializedChatMessage = { + M: { + type: { + S: message.type + }, + text: { + S: message.data.content + } + } + } + if (message.data.role) { + dynamoSerializedMessage.M.role = { S: message.data.role } + } + return dynamoSerializedMessage + }) + } + }, + UpdateExpression: 'SET #m = list_append(if_not_exists(#m, :empty_list), :m)' + } + + await client.send(new UpdateItemCommand(params)) + } + + async getChatMessages(overrideSessionId = ''): Promise { + if (!this.dynamodbClient) return [] + + const dynamoKey = overrideSessionId ? this.overrideDynamoKey(overrideSessionId) : (this as any).dynamoKey + const tableName = (this as any).tableName + const messageAttributeName = (this as any).messageAttributeName + + const params: GetItemCommandInput = { + TableName: tableName, + Key: dynamoKey + } + + const response = await this.dynamodbClient.send(new GetItemCommand(params)) + const items = response.Item ? response.Item[messageAttributeName]?.L ?? [] : [] + const messages = items + .map((item) => ({ + type: item.M?.type.S, + data: { + role: item.M?.role?.S, + content: item.M?.text.S + } + })) + .filter((x): x is StoredMessage => x.type !== undefined && x.data.content !== undefined) + const baseMessages = messages.map(mapStoredMessageToChatMessage) + return convertBaseMessagetoIMessage(baseMessages) + } + + async addChatMessages(msgArray: { text: string; type: MessageType }[], overrideSessionId = ''): Promise { + if (!this.dynamodbClient) return + + const dynamoKey = overrideSessionId ? this.overrideDynamoKey(overrideSessionId) : (this as any).dynamoKey + const tableName = (this as any).tableName + const messageAttributeName = (this as any).messageAttributeName + + const input = msgArray.find((msg) => msg.type === 'userMessage') + const output = msgArray.find((msg) => msg.type === 'apiMessage') + + if (input) { + const newInputMessage = new HumanMessage(input.text) + const messageToAdd = [newInputMessage].map((msg) => msg.toDict()) + await this.addNewMessage(messageToAdd, this.dynamodbClient, tableName, dynamoKey, messageAttributeName) + } + + if (output) { + const newOutputMessage = new AIMessage(output.text) + const messageToAdd = [newOutputMessage].map((msg) => msg.toDict()) + await this.addNewMessage(messageToAdd, this.dynamodbClient, tableName, dynamoKey, messageAttributeName) + } + } + + async clearChatMessages(overrideSessionId = ''): Promise { + if (!this.dynamodbClient) return + + const dynamoKey = overrideSessionId ? this.overrideDynamoKey(overrideSessionId) : (this as any).dynamoKey + const tableName = (this as any).tableName + + const params: DeleteItemCommandInput = { + TableName: tableName, + Key: dynamoKey + } + await this.dynamodbClient.send(new DeleteItemCommand(params)) + await this.clear() } } diff --git a/packages/components/nodes/memory/MongoDBMemory/MongoDBMemory.ts b/packages/components/nodes/memory/MongoDBMemory/MongoDBMemory.ts index 76cb7e31..8bebcfad 100644 --- a/packages/components/nodes/memory/MongoDBMemory/MongoDBMemory.ts +++ b/packages/components/nodes/memory/MongoDBMemory/MongoDBMemory.ts @@ -1,17 +1,9 @@ -import { - getBaseClasses, - getCredentialData, - getCredentialParam, - ICommonObject, - INode, - INodeData, - INodeParams, - serializeChatHistory -} from '../../../src' +import { MongoClient, Collection, Document } from 'mongodb' import { MongoDBChatMessageHistory } from 'langchain/stores/message/mongodb' import { BufferMemory, BufferMemoryInput } from 'langchain/memory' -import { BaseMessage, mapStoredMessageToChatMessage } from 'langchain/schema' -import { MongoClient } from 'mongodb' +import { BaseMessage, mapStoredMessageToChatMessage, AIMessage, HumanMessage } from 'langchain/schema' +import { convertBaseMessagetoIMessage, getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { ICommonObject, IMessage, INode, INodeData, INodeParams, MessageType } from '../../../src/Interface' class MongoDB_Memory implements INode { label: string @@ -57,7 +49,8 @@ class MongoDB_Memory implements INode { label: 'Session Id', name: 'sessionId', type: 'string', - description: 'If not specified, the first CHAT_MESSAGE_ID will be used as sessionId', + description: + 'If not specified, a random id will be used. Learn more', default: '', additionalParams: true, optional: true @@ -75,44 +68,33 @@ class MongoDB_Memory implements INode { async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { return initializeMongoDB(nodeData, options) } - - //@ts-ignore - memoryMethods = { - async clearSessionMemory(nodeData: INodeData, options: ICommonObject): Promise { - const mongodbMemory = await initializeMongoDB(nodeData, options) - const sessionId = nodeData.inputs?.sessionId as string - const chatId = options?.chatId as string - options.logger.info(`Clearing MongoDB memory session ${sessionId ? sessionId : chatId}`) - await mongodbMemory.clear() - options.logger.info(`Successfully cleared MongoDB memory session ${sessionId ? sessionId : chatId}`) - }, - async getChatMessages(nodeData: INodeData, options: ICommonObject): Promise { - const memoryKey = nodeData.inputs?.memoryKey as string - const mongodbMemory = await initializeMongoDB(nodeData, options) - const key = memoryKey ?? 'chat_history' - const memoryResult = await mongodbMemory.loadMemoryVariables({}) - return serializeChatHistory(memoryResult[key]) - } - } } const initializeMongoDB = async (nodeData: INodeData, options: ICommonObject): Promise => { const databaseName = nodeData.inputs?.databaseName as string const collectionName = nodeData.inputs?.collectionName as string - const sessionId = nodeData.inputs?.sessionId as string const memoryKey = nodeData.inputs?.memoryKey as string const chatId = options?.chatId as string let isSessionIdUsingChatMessageId = false - if (!sessionId && chatId) isSessionIdUsingChatMessageId = true + let sessionId = '' + + if (!nodeData.inputs?.sessionId && chatId) { + isSessionIdUsingChatMessageId = true + sessionId = chatId + } else { + sessionId = nodeData.inputs?.sessionId + } const credentialData = await getCredentialData(nodeData.credential ?? '', options) let mongoDBConnectUrl = getCredentialParam('mongoDBConnectUrl', credentialData, nodeData) const client = new MongoClient(mongoDBConnectUrl) await client.connect() + const collection = client.db(databaseName).collection(collectionName) + /**** Methods below are needed to override the original implementations ****/ const mongoDBChatMessageHistory = new MongoDBChatMessageHistory({ collection, sessionId: sessionId ? sessionId : chatId @@ -140,24 +122,83 @@ const initializeMongoDB = async (nodeData: INodeData, options: ICommonObject): P mongoDBChatMessageHistory.clear = async (): Promise => { await collection.deleteOne({ sessionId: (mongoDBChatMessageHistory as any).sessionId }) } + /**** End of override functions ****/ return new BufferMemoryExtended({ memoryKey: memoryKey ?? 'chat_history', chatHistory: mongoDBChatMessageHistory, - isSessionIdUsingChatMessageId + isSessionIdUsingChatMessageId, + sessionId, + collection }) } interface BufferMemoryExtendedInput { isSessionIdUsingChatMessageId: boolean + collection: Collection + sessionId: string } class BufferMemoryExtended extends BufferMemory { - isSessionIdUsingChatMessageId? = false + isSessionIdUsingChatMessageId = false + sessionId = '' + collection: Collection - constructor(fields: BufferMemoryInput & Partial) { + constructor(fields: BufferMemoryInput & BufferMemoryExtendedInput) { super(fields) this.isSessionIdUsingChatMessageId = fields.isSessionIdUsingChatMessageId + this.sessionId = fields.sessionId + this.collection = fields.collection + } + + async getChatMessages(overrideSessionId = ''): Promise { + if (!this.collection) return [] + + const id = overrideSessionId ?? this.sessionId + const document = await this.collection.findOne({ sessionId: id }) + const messages = document?.messages || [] + const baseMessages = messages.map(mapStoredMessageToChatMessage) + return convertBaseMessagetoIMessage(baseMessages) + } + + async addChatMessages(msgArray: { text: string; type: MessageType }[], overrideSessionId = ''): Promise { + if (!this.collection) return + + const id = overrideSessionId ?? this.sessionId + const input = msgArray.find((msg) => msg.type === 'userMessage') + const output = msgArray.find((msg) => msg.type === 'apiMessage') + + if (input) { + const newInputMessage = new HumanMessage(input.text) + const messageToAdd = [newInputMessage].map((msg) => msg.toDict()) + await this.collection.updateOne( + { sessionId: id }, + { + $push: { messages: { $each: messageToAdd } } + }, + { upsert: true } + ) + } + + if (output) { + const newOutputMessage = new AIMessage(output.text) + const messageToAdd = [newOutputMessage].map((msg) => msg.toDict()) + await this.collection.updateOne( + { sessionId: id }, + { + $push: { messages: { $each: messageToAdd } } + }, + { upsert: true } + ) + } + } + + async clearChatMessages(overrideSessionId = ''): Promise { + if (!this.collection) return + + const id = overrideSessionId ?? this.sessionId + await this.collection.deleteOne({ sessionId: id }) + await this.clear() } } diff --git a/packages/components/nodes/memory/MotorheadMemory/MotorheadMemory.ts b/packages/components/nodes/memory/MotorheadMemory/MotorheadMemory.ts index 9cdbcd5c..6dd94944 100644 --- a/packages/components/nodes/memory/MotorheadMemory/MotorheadMemory.ts +++ b/packages/components/nodes/memory/MotorheadMemory/MotorheadMemory.ts @@ -1,9 +1,9 @@ -import { INode, INodeData, INodeParams } from '../../../src/Interface' -import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { IMessage, INode, INodeData, INodeParams, MessageType } from '../../../src/Interface' +import { convertBaseMessagetoIMessage, getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' import { ICommonObject } from '../../../src' import { MotorheadMemory, MotorheadMemoryInput } from 'langchain/memory' import fetch from 'node-fetch' -import { getBufferString } from 'langchain/memory' +import { InputValues, MemoryVariables, OutputValues } from 'langchain/memory' class MotorMemory_Memory implements INode { label: string @@ -46,7 +46,8 @@ class MotorMemory_Memory implements INode { label: 'Session Id', name: 'sessionId', type: 'string', - description: 'If not specified, the first CHAT_MESSAGE_ID will be used as sessionId', + description: + 'If not specified, a random id will be used. Learn more', default: '', additionalParams: true, optional: true @@ -64,35 +65,22 @@ class MotorMemory_Memory implements INode { async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { return initalizeMotorhead(nodeData, options) } - - //@ts-ignore - memoryMethods = { - async clearSessionMemory(nodeData: INodeData, options: ICommonObject): Promise { - const motorhead = await initalizeMotorhead(nodeData, options) - const sessionId = nodeData.inputs?.sessionId as string - const chatId = options?.chatId as string - options.logger.info(`Clearing Motorhead memory session ${sessionId ? sessionId : chatId}`) - await motorhead.clear() - options.logger.info(`Successfully cleared Motorhead memory session ${sessionId ? sessionId : chatId}`) - }, - async getChatMessages(nodeData: INodeData, options: ICommonObject): Promise { - const memoryKey = nodeData.inputs?.memoryKey as string - const motorhead = await initalizeMotorhead(nodeData, options) - const key = memoryKey ?? 'chat_history' - const memoryResult = await motorhead.loadMemoryVariables({}) - return getBufferString(memoryResult[key]) - } - } } const initalizeMotorhead = async (nodeData: INodeData, options: ICommonObject): Promise => { const memoryKey = nodeData.inputs?.memoryKey as string const baseURL = nodeData.inputs?.baseURL as string - const sessionId = nodeData.inputs?.sessionId as string const chatId = options?.chatId as string let isSessionIdUsingChatMessageId = false - if (!sessionId && chatId) isSessionIdUsingChatMessageId = true + let sessionId = '' + + if (!nodeData.inputs?.sessionId && chatId) { + isSessionIdUsingChatMessageId = true + sessionId = chatId + } else { + sessionId = nodeData.inputs?.sessionId + } const credentialData = await getCredentialData(nodeData.credential ?? '', options) const apiKey = getCredentialParam('apiKey', credentialData, nodeData) @@ -100,8 +88,9 @@ const initalizeMotorhead = async (nodeData: INodeData, options: ICommonObject): let obj: MotorheadMemoryInput & Partial = { returnMessages: true, - sessionId: sessionId ? sessionId : chatId, - memoryKey + sessionId, + memoryKey, + isSessionIdUsingChatMessageId } if (baseURL) { @@ -117,8 +106,6 @@ const initalizeMotorhead = async (nodeData: INodeData, options: ICommonObject): } } - if (isSessionIdUsingChatMessageId) obj.isSessionIdUsingChatMessageId = true - const motorheadMemory = new MotorheadMemoryExtended(obj) // Get messages from sessionId @@ -139,7 +126,24 @@ class MotorheadMemoryExtended extends MotorheadMemory { this.isSessionIdUsingChatMessageId = fields.isSessionIdUsingChatMessageId } - async clear(): Promise { + async loadMemoryVariables(values: InputValues, overrideSessionId = ''): Promise { + if (overrideSessionId) { + super.sessionId = overrideSessionId + } + return super.loadMemoryVariables({ values }) + } + + async saveContext(inputValues: InputValues, outputValues: OutputValues, overrideSessionId = ''): Promise { + if (overrideSessionId) { + super.sessionId = overrideSessionId + } + return super.saveContext(inputValues, outputValues) + } + + async clear(overrideSessionId = ''): Promise { + if (overrideSessionId) { + super.sessionId = overrideSessionId + } try { await this.caller.call(fetch, `${this.url}/sessions/${this.sessionId}/memory`, { //@ts-ignore @@ -155,6 +159,28 @@ class MotorheadMemoryExtended extends MotorheadMemory { await this.chatHistory.clear() await super.clear() } + + async getChatMessages(overrideSessionId = ''): Promise { + const id = overrideSessionId ?? this.sessionId + const memoryVariables = await this.loadMemoryVariables({}, id) + const baseMessages = memoryVariables[this.memoryKey] + return convertBaseMessagetoIMessage(baseMessages) + } + + async addChatMessages(msgArray: { text: string; type: MessageType }[], overrideSessionId = ''): Promise { + const id = overrideSessionId ?? this.sessionId + const input = msgArray.find((msg) => msg.type === 'userMessage') + const output = msgArray.find((msg) => msg.type === 'apiMessage') + const inputValues = { [this.inputKey ?? 'input']: input?.text } + const outputValues = { output: output?.text } + + await this.saveContext(inputValues, outputValues, id) + } + + async clearChatMessages(overrideSessionId = ''): Promise { + const id = overrideSessionId ?? this.sessionId + await this.clear(id) + } } module.exports = { nodeClass: MotorMemory_Memory } diff --git a/packages/components/nodes/memory/RedisBackedChatMemory/RedisBackedChatMemory.ts b/packages/components/nodes/memory/RedisBackedChatMemory/RedisBackedChatMemory.ts index 7fe447ad..4692088b 100644 --- a/packages/components/nodes/memory/RedisBackedChatMemory/RedisBackedChatMemory.ts +++ b/packages/components/nodes/memory/RedisBackedChatMemory/RedisBackedChatMemory.ts @@ -1,9 +1,9 @@ -import { INode, INodeData, INodeParams, ICommonObject } from '../../../src/Interface' -import { getBaseClasses, getCredentialData, getCredentialParam, serializeChatHistory } from '../../../src/utils' +import { Redis } from 'ioredis' import { BufferMemory, BufferMemoryInput } from 'langchain/memory' import { RedisChatMessageHistory, RedisChatMessageHistoryInput } from 'langchain/stores/message/ioredis' -import { mapStoredMessageToChatMessage, BaseMessage } from 'langchain/schema' -import { Redis } from 'ioredis' +import { mapStoredMessageToChatMessage, BaseMessage, AIMessage, HumanMessage } from 'langchain/schema' +import { INode, INodeData, INodeParams, ICommonObject, MessageType, IMessage } from '../../../src/Interface' +import { convertBaseMessagetoIMessage, getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' class RedisBackedChatMemory_Memory implements INode { label: string @@ -38,7 +38,8 @@ class RedisBackedChatMemory_Memory implements INode { label: 'Session Id', name: 'sessionId', type: 'string', - description: 'If not specified, the first CHAT_MESSAGE_ID will be used as sessionId', + description: + 'If not specified, a random id will be used. Learn more', default: '', additionalParams: true, optional: true @@ -64,40 +65,28 @@ class RedisBackedChatMemory_Memory implements INode { async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { return await initalizeRedis(nodeData, options) } - - //@ts-ignore - memoryMethods = { - async clearSessionMemory(nodeData: INodeData, options: ICommonObject): Promise { - const redis = await initalizeRedis(nodeData, options) - const sessionId = nodeData.inputs?.sessionId as string - const chatId = options?.chatId as string - options.logger.info(`Clearing Redis memory session ${sessionId ? sessionId : chatId}`) - await redis.clear() - options.logger.info(`Successfully cleared Redis memory session ${sessionId ? sessionId : chatId}`) - }, - async getChatMessages(nodeData: INodeData, options: ICommonObject): Promise { - const memoryKey = nodeData.inputs?.memoryKey as string - const redis = await initalizeRedis(nodeData, options) - const key = memoryKey ?? 'chat_history' - const memoryResult = await redis.loadMemoryVariables({}) - return serializeChatHistory(memoryResult[key]) - } - } } const initalizeRedis = async (nodeData: INodeData, options: ICommonObject): Promise => { - const sessionId = nodeData.inputs?.sessionId as string const sessionTTL = nodeData.inputs?.sessionTTL as number const memoryKey = nodeData.inputs?.memoryKey as string const chatId = options?.chatId as string let isSessionIdUsingChatMessageId = false - if (!sessionId && chatId) isSessionIdUsingChatMessageId = true + let sessionId = '' + + if (!nodeData.inputs?.sessionId && chatId) { + isSessionIdUsingChatMessageId = true + sessionId = chatId + } else { + sessionId = nodeData.inputs?.sessionId + } const credentialData = await getCredentialData(nodeData.credential ?? '', options) const redisUrl = getCredentialParam('redisUrl', credentialData, nodeData) let client: Redis + if (!redisUrl || redisUrl === '') { const username = getCredentialParam('redisCacheUser', credentialData, nodeData) const password = getCredentialParam('redisCachePwd', credentialData, nodeData) @@ -115,7 +104,7 @@ const initalizeRedis = async (nodeData: INodeData, options: ICommonObject): Prom } let obj: RedisChatMessageHistoryInput = { - sessionId: sessionId ? sessionId : chatId, + sessionId, client } @@ -128,6 +117,7 @@ const initalizeRedis = async (nodeData: INodeData, options: ICommonObject): Prom const redisChatMessageHistory = new RedisChatMessageHistory(obj) + /**** Methods below are needed to override the original implementations ****/ redisChatMessageHistory.getMessages = async (): Promise => { const rawStoredMessages = await client.lrange((redisChatMessageHistory as any).sessionId, 0, -1) const orderedMessages = rawStoredMessages.reverse().map((message) => JSON.parse(message)) @@ -145,25 +135,73 @@ const initalizeRedis = async (nodeData: INodeData, options: ICommonObject): Prom redisChatMessageHistory.clear = async (): Promise => { await client.del((redisChatMessageHistory as any).sessionId) } + /**** End of override functions ****/ const memory = new BufferMemoryExtended({ memoryKey: memoryKey ?? 'chat_history', chatHistory: redisChatMessageHistory, - isSessionIdUsingChatMessageId + isSessionIdUsingChatMessageId, + sessionId, + redisClient: client }) + return memory } interface BufferMemoryExtendedInput { isSessionIdUsingChatMessageId: boolean + redisClient: Redis + sessionId: string } class BufferMemoryExtended extends BufferMemory { - isSessionIdUsingChatMessageId? = false + isSessionIdUsingChatMessageId = false + sessionId = '' + redisClient: Redis - constructor(fields: BufferMemoryInput & Partial) { + constructor(fields: BufferMemoryInput & BufferMemoryExtendedInput) { super(fields) this.isSessionIdUsingChatMessageId = fields.isSessionIdUsingChatMessageId + this.sessionId = fields.sessionId + this.redisClient = fields.redisClient + } + + async getChatMessages(overrideSessionId = ''): Promise { + if (!this.redisClient) return [] + + const id = overrideSessionId ?? this.sessionId + const rawStoredMessages = await this.redisClient.lrange(id, 0, -1) + const orderedMessages = rawStoredMessages.reverse().map((message) => JSON.parse(message)) + const baseMessages = orderedMessages.map(mapStoredMessageToChatMessage) + return convertBaseMessagetoIMessage(baseMessages) + } + + async addChatMessages(msgArray: { text: string; type: MessageType }[], overrideSessionId = ''): Promise { + if (!this.redisClient) return + + const id = overrideSessionId ?? this.sessionId + const input = msgArray.find((msg) => msg.type === 'userMessage') + const output = msgArray.find((msg) => msg.type === 'apiMessage') + + if (input) { + const newInputMessage = new HumanMessage(input.text) + const messageToAdd = [newInputMessage].map((msg) => msg.toDict()) + await this.redisClient.lpush(id, JSON.stringify(messageToAdd[0])) + } + + if (output) { + const newOutputMessage = new AIMessage(output.text) + const messageToAdd = [newOutputMessage].map((msg) => msg.toDict()) + await this.redisClient.lpush(id, JSON.stringify(messageToAdd[0])) + } + } + + async clearChatMessages(overrideSessionId = ''): Promise { + if (!this.redisClient) return + + const id = overrideSessionId ?? this.sessionId + await this.redisClient.del(id) + await this.clear() } } diff --git a/packages/components/nodes/memory/UpstashRedisBackedChatMemory/UpstashRedisBackedChatMemory.ts b/packages/components/nodes/memory/UpstashRedisBackedChatMemory/UpstashRedisBackedChatMemory.ts index 8bca0440..327f0f32 100644 --- a/packages/components/nodes/memory/UpstashRedisBackedChatMemory/UpstashRedisBackedChatMemory.ts +++ b/packages/components/nodes/memory/UpstashRedisBackedChatMemory/UpstashRedisBackedChatMemory.ts @@ -1,8 +1,10 @@ -import { INode, INodeData, INodeParams } from '../../../src/Interface' -import { getBaseClasses, getCredentialData, getCredentialParam, serializeChatHistory } from '../../../src/utils' -import { ICommonObject } from '../../../src' +import { Redis } from '@upstash/redis' import { BufferMemory, BufferMemoryInput } from 'langchain/memory' import { UpstashRedisChatMessageHistory } from 'langchain/stores/message/upstash_redis' +import { mapStoredMessageToChatMessage, AIMessage, HumanMessage, StoredMessage } from 'langchain/schema' +import { IMessage, INode, INodeData, INodeParams, MessageType } from '../../../src/Interface' +import { convertBaseMessagetoIMessage, getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { ICommonObject } from '../../../src/Interface' class UpstashRedisBackedChatMemory_Memory implements INode { label: string @@ -43,7 +45,8 @@ class UpstashRedisBackedChatMemory_Memory implements INode { label: 'Session Id', name: 'sessionId', type: 'string', - description: 'If not specified, the first CHAT_MESSAGE_ID will be used as sessionId', + description: + 'If not specified, a random id will be used. Learn more', default: '', additionalParams: true, optional: true @@ -62,51 +65,43 @@ class UpstashRedisBackedChatMemory_Memory implements INode { async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { return initalizeUpstashRedis(nodeData, options) } - - //@ts-ignore - memoryMethods = { - async clearSessionMemory(nodeData: INodeData, options: ICommonObject): Promise { - const redis = await initalizeUpstashRedis(nodeData, options) - const sessionId = nodeData.inputs?.sessionId as string - const chatId = options?.chatId as string - options.logger.info(`Clearing Upstash Redis memory session ${sessionId ? sessionId : chatId}`) - await redis.clear() - options.logger.info(`Successfully cleared Upstash Redis memory session ${sessionId ? sessionId : chatId}`) - }, - async getChatMessages(nodeData: INodeData, options: ICommonObject): Promise { - const redis = await initalizeUpstashRedis(nodeData, options) - const key = 'chat_history' - const memoryResult = await redis.loadMemoryVariables({}) - return serializeChatHistory(memoryResult[key]) - } - } } const initalizeUpstashRedis = async (nodeData: INodeData, options: ICommonObject): Promise => { const baseURL = nodeData.inputs?.baseURL as string - const sessionId = nodeData.inputs?.sessionId as string const sessionTTL = nodeData.inputs?.sessionTTL as string const chatId = options?.chatId as string let isSessionIdUsingChatMessageId = false - if (!sessionId && chatId) isSessionIdUsingChatMessageId = true + let sessionId = '' + + if (!nodeData.inputs?.sessionId && chatId) { + isSessionIdUsingChatMessageId = true + sessionId = chatId + } else { + sessionId = nodeData.inputs?.sessionId + } const credentialData = await getCredentialData(nodeData.credential ?? '', options) const upstashRestToken = getCredentialParam('upstashRestToken', credentialData, nodeData) + const client = new Redis({ + url: baseURL, + token: upstashRestToken + }) + const redisChatMessageHistory = new UpstashRedisChatMessageHistory({ sessionId: sessionId ? sessionId : chatId, sessionTTL: sessionTTL ? parseInt(sessionTTL, 10) : undefined, - config: { - url: baseURL, - token: upstashRestToken - } + client }) const memory = new BufferMemoryExtended({ memoryKey: 'chat_history', chatHistory: redisChatMessageHistory, - isSessionIdUsingChatMessageId + isSessionIdUsingChatMessageId, + sessionId, + redisClient: client }) return memory @@ -114,14 +109,59 @@ const initalizeUpstashRedis = async (nodeData: INodeData, options: ICommonObject interface BufferMemoryExtendedInput { isSessionIdUsingChatMessageId: boolean + redisClient: Redis + sessionId: string } class BufferMemoryExtended extends BufferMemory { - isSessionIdUsingChatMessageId? = false + isSessionIdUsingChatMessageId = false + sessionId = '' + redisClient: Redis - constructor(fields: BufferMemoryInput & Partial) { + constructor(fields: BufferMemoryInput & BufferMemoryExtendedInput) { super(fields) this.isSessionIdUsingChatMessageId = fields.isSessionIdUsingChatMessageId + this.sessionId = fields.sessionId + this.redisClient = fields.redisClient + } + + async getChatMessages(overrideSessionId = ''): Promise { + if (!this.redisClient) return [] + + const id = overrideSessionId ?? this.sessionId + const rawStoredMessages: StoredMessage[] = await this.redisClient.lrange(id, 0, -1) + const orderedMessages = rawStoredMessages.reverse() + const previousMessages = orderedMessages.filter((x): x is StoredMessage => x.type !== undefined && x.data.content !== undefined) + const baseMessages = previousMessages.map(mapStoredMessageToChatMessage) + return convertBaseMessagetoIMessage(baseMessages) + } + + async addChatMessages(msgArray: { text: string; type: MessageType }[], overrideSessionId = ''): Promise { + if (!this.redisClient) return + + const id = overrideSessionId ?? this.sessionId + const input = msgArray.find((msg) => msg.type === 'userMessage') + const output = msgArray.find((msg) => msg.type === 'apiMessage') + + if (input) { + const newInputMessage = new HumanMessage(input.text) + const messageToAdd = [newInputMessage].map((msg) => msg.toDict()) + await this.redisClient.lpush(id, JSON.stringify(messageToAdd[0])) + } + + if (output) { + const newOutputMessage = new AIMessage(output.text) + const messageToAdd = [newOutputMessage].map((msg) => msg.toDict()) + await this.redisClient.lpush(id, JSON.stringify(messageToAdd[0])) + } + } + + async clearChatMessages(overrideSessionId = ''): Promise { + if (!this.redisClient) return + + const id = overrideSessionId ?? this.sessionId + await this.redisClient.del(id) + await this.clear() } } diff --git a/packages/components/nodes/memory/ZepMemory/ZepMemory.ts b/packages/components/nodes/memory/ZepMemory/ZepMemory.ts index ced871a1..ac0ac896 100644 --- a/packages/components/nodes/memory/ZepMemory/ZepMemory.ts +++ b/packages/components/nodes/memory/ZepMemory/ZepMemory.ts @@ -1,9 +1,8 @@ -import { SystemMessage } from 'langchain/schema' -import { INode, INodeData, INodeParams } from '../../../src/Interface' -import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { IMessage, INode, INodeData, INodeParams, MessageType } from '../../../src/Interface' +import { convertBaseMessagetoIMessage, getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' import { ZepMemory, ZepMemoryInput } from 'langchain/memory/zep' import { ICommonObject } from '../../../src' -import { getBufferString } from 'langchain/memory' +import { InputValues, MemoryVariables, OutputValues } from 'langchain/memory' class ZepMemory_Memory implements INode { label: string @@ -20,7 +19,7 @@ class ZepMemory_Memory implements INode { constructor() { this.label = 'Zep Memory' this.name = 'ZepMemory' - this.version = 1.0 + this.version = 2.0 this.type = 'ZepMemory' this.icon = 'zep.png' this.category = 'Memory' @@ -41,17 +40,12 @@ class ZepMemory_Memory implements INode { type: 'string', default: 'http://127.0.0.1:8000' }, - { - label: 'Auto Summary', - name: 'autoSummary', - type: 'boolean', - default: true - }, { label: 'Session Id', name: 'sessionId', type: 'string', - description: 'If not specified, the first CHAT_MESSAGE_ID will be used as sessionId', + description: + 'If not specified, a random id will be used. Learn more', default: '', additionalParams: true, optional: true @@ -61,13 +55,7 @@ class ZepMemory_Memory implements INode { name: 'k', type: 'number', default: '10', - description: 'Window of size k to surface the last k back-and-forth to use as memory.' - }, - { - label: 'Auto Summary Template', - name: 'autoSummaryTemplate', - type: 'string', - default: 'This is the summary of the following conversation:\n{summary}', + description: 'Window of size k to surface the last k back-and-forth to use as memory.', additionalParams: true }, { @@ -109,57 +97,7 @@ class ZepMemory_Memory implements INode { } async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { - const autoSummaryTemplate = nodeData.inputs?.autoSummaryTemplate as string - const autoSummary = nodeData.inputs?.autoSummary as boolean - - const k = nodeData.inputs?.k as string - - let zep = await initalizeZep(nodeData, options) - - // hack to support summary - let tmpFunc = zep.loadMemoryVariables - zep.loadMemoryVariables = async (values) => { - let data = await tmpFunc.bind(zep, values)() - if (autoSummary && zep.returnMessages && data[zep.memoryKey] && data[zep.memoryKey].length) { - const zepClient = await zep.zepClientPromise - const memory = await zepClient.memory.getMemory(zep.sessionId, parseInt(k, 10) ?? 10) - if (memory?.summary) { - let summary = autoSummaryTemplate.replace(/{summary}/g, memory.summary.content) - // eslint-disable-next-line no-console - console.log('[ZepMemory] auto summary:', summary) - data[zep.memoryKey].unshift(new SystemMessage(summary)) - } - } - // for langchain zep memory compatibility, or we will get "Missing value for input variable chat_history" - if (data instanceof Array) { - data = { - [zep.memoryKey]: data - } - } - return data - } - return zep - } - - //@ts-ignore - memoryMethods = { - async clearSessionMemory(nodeData: INodeData, options: ICommonObject): Promise { - const zep = await initalizeZep(nodeData, options) - const sessionId = nodeData.inputs?.sessionId as string - const chatId = options?.chatId as string - options.logger.info(`Clearing Zep memory session ${sessionId ? sessionId : chatId}`) - await zep.clear() - options.logger.info(`Successfully cleared Zep memory session ${sessionId ? sessionId : chatId}`) - }, - async getChatMessages(nodeData: INodeData, options: ICommonObject): Promise { - const memoryKey = nodeData.inputs?.memoryKey as string - const aiPrefix = nodeData.inputs?.aiPrefix as string - const humanPrefix = nodeData.inputs?.humanPrefix as string - const zep = await initalizeZep(nodeData, options) - const key = memoryKey ?? 'chat_history' - const memoryResult = await zep.loadMemoryVariables({}) - return getBufferString(memoryResult[key], humanPrefix, aiPrefix) - } + return await initalizeZep(nodeData, options) } } @@ -169,40 +107,94 @@ const initalizeZep = async (nodeData: INodeData, options: ICommonObject): Promis const humanPrefix = nodeData.inputs?.humanPrefix as string const memoryKey = nodeData.inputs?.memoryKey as string const inputKey = nodeData.inputs?.inputKey as string - const sessionId = nodeData.inputs?.sessionId as string + const k = nodeData.inputs?.k as string const chatId = options?.chatId as string let isSessionIdUsingChatMessageId = false - if (!sessionId && chatId) isSessionIdUsingChatMessageId = true + let sessionId = '' + + if (!nodeData.inputs?.sessionId && chatId) { + isSessionIdUsingChatMessageId = true + sessionId = chatId + } else { + sessionId = nodeData.inputs?.sessionId + } const credentialData = await getCredentialData(nodeData.credential ?? '', options) const apiKey = getCredentialParam('apiKey', credentialData, nodeData) - const obj: ZepMemoryInput & Partial = { + const obj: ZepMemoryInput & ZepMemoryExtendedInput = { baseURL, - sessionId: sessionId ? sessionId : chatId, aiPrefix, humanPrefix, returnMessages: true, memoryKey, - inputKey + inputKey, + sessionId, + isSessionIdUsingChatMessageId, + k: k ? parseInt(k, 10) : undefined } if (apiKey) obj.apiKey = apiKey - if (isSessionIdUsingChatMessageId) obj.isSessionIdUsingChatMessageId = true return new ZepMemoryExtended(obj) } interface ZepMemoryExtendedInput { isSessionIdUsingChatMessageId: boolean + k?: number } class ZepMemoryExtended extends ZepMemory { - isSessionIdUsingChatMessageId? = false + isSessionIdUsingChatMessageId = false + lastN?: number - constructor(fields: ZepMemoryInput & Partial) { + constructor(fields: ZepMemoryInput & ZepMemoryExtendedInput) { super(fields) this.isSessionIdUsingChatMessageId = fields.isSessionIdUsingChatMessageId + this.lastN = fields.k + } + + async loadMemoryVariables(values: InputValues, overrideSessionId = ''): Promise { + if (overrideSessionId) { + super.sessionId = overrideSessionId + } + return super.loadMemoryVariables({ ...values, lastN: this.lastN }) + } + + async saveContext(inputValues: InputValues, outputValues: OutputValues, overrideSessionId = ''): Promise { + if (overrideSessionId) { + super.sessionId = overrideSessionId + } + return super.saveContext(inputValues, outputValues) + } + + async clear(overrideSessionId = ''): Promise { + if (overrideSessionId) { + super.sessionId = overrideSessionId + } + return super.clear() + } + + async getChatMessages(overrideSessionId = ''): Promise { + const id = overrideSessionId ?? this.sessionId + const memoryVariables = await this.loadMemoryVariables({}, id) + const baseMessages = memoryVariables[this.memoryKey] + return convertBaseMessagetoIMessage(baseMessages) + } + + async addChatMessages(msgArray: { text: string; type: MessageType }[], overrideSessionId = ''): Promise { + const id = overrideSessionId ?? this.sessionId + const input = msgArray.find((msg) => msg.type === 'userMessage') + const output = msgArray.find((msg) => msg.type === 'apiMessage') + const inputValues = { [this.inputKey ?? 'input']: input?.text } + const outputValues = { output: output?.text } + + await this.saveContext(inputValues, outputValues, id) + } + + async clearChatMessages(overrideSessionId = ''): Promise { + const id = overrideSessionId ?? this.sessionId + await this.clear(id) } } diff --git a/packages/components/nodes/responsesynthesizer/CompactRefine/CompactRefine.ts b/packages/components/nodes/responsesynthesizer/CompactRefine/CompactRefine.ts new file mode 100644 index 00000000..db998e1f --- /dev/null +++ b/packages/components/nodes/responsesynthesizer/CompactRefine/CompactRefine.ts @@ -0,0 +1,75 @@ +import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' +import { ResponseSynthesizerClass } from '../base' + +class CompactRefine_LlamaIndex implements INode { + label: string + name: string + version: number + description: string + type: string + icon: string + category: string + baseClasses: string[] + tags: string[] + inputs: INodeParams[] + outputs: INodeOutputsValue[] + + constructor() { + this.label = 'Compact and Refine' + this.name = 'compactrefineLlamaIndex' + this.version = 1.0 + this.type = 'CompactRefine' + this.icon = 'compactrefine.svg' + this.category = 'Response Synthesizer' + this.description = + 'CompactRefine is a slight variation of Refine that first compacts the text chunks into the smallest possible number of chunks.' + this.baseClasses = [this.type, 'ResponseSynthesizer'] + this.tags = ['LlamaIndex'] + this.inputs = [ + { + label: 'Refine Prompt', + name: 'refinePrompt', + type: 'string', + rows: 4, + default: `The original query is as follows: {query} +We have provided an existing answer: {existingAnswer} +We have the opportunity to refine the existing answer (only if needed) with some more context below. +------------ +{context} +------------ +Given the new context, refine the original answer to better answer the query. If the context isn't useful, return the original answer. +Refined Answer:`, + warning: `Prompt can contains no variables, or up to 3 variables. Variables must be {existingAnswer}, {context} and {query}`, + optional: true + }, + { + label: 'Text QA Prompt', + name: 'textQAPrompt', + type: 'string', + rows: 4, + default: `Context information is below. +--------------------- +{context} +--------------------- +Given the context information and not prior knowledge, answer the query. +Query: {query} +Answer:`, + warning: `Prompt can contains no variables, or up to 2 variables. Variables must be {context} and {query}`, + optional: true + } + ] + } + + async init(nodeData: INodeData): Promise { + const refinePrompt = nodeData.inputs?.refinePrompt as string + const textQAPrompt = nodeData.inputs?.textQAPrompt as string + + const refinePromptTemplate = ({ context = '', existingAnswer = '', query = '' }) => + refinePrompt.replace('{existingAnswer}', existingAnswer).replace('{context}', context).replace('{query}', query) + const textQAPromptTemplate = ({ context = '', query = '' }) => textQAPrompt.replace('{context}', context).replace('{query}', query) + + return new ResponseSynthesizerClass({ textQAPromptTemplate, refinePromptTemplate, type: 'CompactAndRefine' }) + } +} + +module.exports = { nodeClass: CompactRefine_LlamaIndex } diff --git a/packages/components/nodes/responsesynthesizer/CompactRefine/compactrefine.svg b/packages/components/nodes/responsesynthesizer/CompactRefine/compactrefine.svg new file mode 100644 index 00000000..9ea95529 --- /dev/null +++ b/packages/components/nodes/responsesynthesizer/CompactRefine/compactrefine.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/packages/components/nodes/responsesynthesizer/Refine/Refine.ts b/packages/components/nodes/responsesynthesizer/Refine/Refine.ts new file mode 100644 index 00000000..267bc208 --- /dev/null +++ b/packages/components/nodes/responsesynthesizer/Refine/Refine.ts @@ -0,0 +1,75 @@ +import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' +import { ResponseSynthesizerClass } from '../base' + +class Refine_LlamaIndex implements INode { + label: string + name: string + version: number + description: string + type: string + icon: string + category: string + baseClasses: string[] + tags: string[] + inputs: INodeParams[] + outputs: INodeOutputsValue[] + + constructor() { + this.label = 'Refine' + this.name = 'refineLlamaIndex' + this.version = 1.0 + this.type = 'Refine' + this.icon = 'refine.svg' + this.category = 'Response Synthesizer' + this.description = + 'Create and refine an answer by sequentially going through each retrieved text chunk. This makes a separate LLM call per Node. Good for more detailed answers.' + this.baseClasses = [this.type, 'ResponseSynthesizer'] + this.tags = ['LlamaIndex'] + this.inputs = [ + { + label: 'Refine Prompt', + name: 'refinePrompt', + type: 'string', + rows: 4, + default: `The original query is as follows: {query} +We have provided an existing answer: {existingAnswer} +We have the opportunity to refine the existing answer (only if needed) with some more context below. +------------ +{context} +------------ +Given the new context, refine the original answer to better answer the query. If the context isn't useful, return the original answer. +Refined Answer:`, + warning: `Prompt can contains no variables, or up to 3 variables. Variables must be {existingAnswer}, {context} and {query}`, + optional: true + }, + { + label: 'Text QA Prompt', + name: 'textQAPrompt', + type: 'string', + rows: 4, + default: `Context information is below. +--------------------- +{context} +--------------------- +Given the context information and not prior knowledge, answer the query. +Query: {query} +Answer:`, + warning: `Prompt can contains no variables, or up to 2 variables. Variables must be {context} and {query}`, + optional: true + } + ] + } + + async init(nodeData: INodeData): Promise { + const refinePrompt = nodeData.inputs?.refinePrompt as string + const textQAPrompt = nodeData.inputs?.textQAPrompt as string + + const refinePromptTemplate = ({ context = '', existingAnswer = '', query = '' }) => + refinePrompt.replace('{existingAnswer}', existingAnswer).replace('{context}', context).replace('{query}', query) + const textQAPromptTemplate = ({ context = '', query = '' }) => textQAPrompt.replace('{context}', context).replace('{query}', query) + + return new ResponseSynthesizerClass({ textQAPromptTemplate, refinePromptTemplate, type: 'Refine' }) + } +} + +module.exports = { nodeClass: Refine_LlamaIndex } diff --git a/packages/components/nodes/responsesynthesizer/Refine/refine.svg b/packages/components/nodes/responsesynthesizer/Refine/refine.svg new file mode 100644 index 00000000..1170c584 --- /dev/null +++ b/packages/components/nodes/responsesynthesizer/Refine/refine.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/packages/components/nodes/responsesynthesizer/SimpleResponseBuilder/SimpleResponseBuilder.ts b/packages/components/nodes/responsesynthesizer/SimpleResponseBuilder/SimpleResponseBuilder.ts new file mode 100644 index 00000000..cb880020 --- /dev/null +++ b/packages/components/nodes/responsesynthesizer/SimpleResponseBuilder/SimpleResponseBuilder.ts @@ -0,0 +1,35 @@ +import { INode, INodeOutputsValue, INodeParams } from '../../../src/Interface' +import { ResponseSynthesizerClass } from '../base' + +class SimpleResponseBuilder_LlamaIndex implements INode { + label: string + name: string + version: number + description: string + type: string + icon: string + category: string + baseClasses: string[] + tags: string[] + inputs: INodeParams[] + outputs: INodeOutputsValue[] + + constructor() { + this.label = 'Simple Response Builder' + this.name = 'simpleResponseBuilderLlamaIndex' + this.version = 1.0 + this.type = 'SimpleResponseBuilder' + this.icon = 'simplerb.svg' + this.category = 'Response Synthesizer' + this.description = `Apply a query to a collection of text chunks, gathering the responses in an array, and return a combined string of all responses. Useful for individual queries on each text chunk.` + this.baseClasses = [this.type, 'ResponseSynthesizer'] + this.tags = ['LlamaIndex'] + this.inputs = [] + } + + async init(): Promise { + return new ResponseSynthesizerClass({ type: 'SimpleResponseBuilder' }) + } +} + +module.exports = { nodeClass: SimpleResponseBuilder_LlamaIndex } diff --git a/packages/components/nodes/responsesynthesizer/SimpleResponseBuilder/simplerb.svg b/packages/components/nodes/responsesynthesizer/SimpleResponseBuilder/simplerb.svg new file mode 100644 index 00000000..6f04fdc9 --- /dev/null +++ b/packages/components/nodes/responsesynthesizer/SimpleResponseBuilder/simplerb.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/packages/components/nodes/responsesynthesizer/TreeSummarize/TreeSummarize.ts b/packages/components/nodes/responsesynthesizer/TreeSummarize/TreeSummarize.ts new file mode 100644 index 00000000..44872786 --- /dev/null +++ b/packages/components/nodes/responsesynthesizer/TreeSummarize/TreeSummarize.ts @@ -0,0 +1,56 @@ +import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' +import { ResponseSynthesizerClass } from '../base' + +class TreeSummarize_LlamaIndex implements INode { + label: string + name: string + version: number + description: string + type: string + icon: string + category: string + baseClasses: string[] + tags: string[] + inputs: INodeParams[] + outputs: INodeOutputsValue[] + + constructor() { + this.label = 'TreeSummarize' + this.name = 'treeSummarizeLlamaIndex' + this.version = 1.0 + this.type = 'TreeSummarize' + this.icon = 'treesummarize.svg' + this.category = 'Response Synthesizer' + this.description = + 'Given a set of text chunks and the query, recursively construct a tree and return the root node as the response. Good for summarization purposes.' + this.baseClasses = [this.type, 'ResponseSynthesizer'] + this.tags = ['LlamaIndex'] + this.inputs = [ + { + label: 'Prompt', + name: 'prompt', + type: 'string', + rows: 4, + default: `Context information from multiple sources is below. +--------------------- +{context} +--------------------- +Given the information from multiple sources and not prior knowledge, answer the query. +Query: {query} +Answer:`, + warning: `Prompt can contains no variables, or up to 2 variables. Variables must be {context} and {query}`, + optional: true + } + ] + } + + async init(nodeData: INodeData): Promise { + const prompt = nodeData.inputs?.prompt as string + + const textQAPromptTemplate = ({ context = '', query = '' }) => prompt.replace('{context}', context).replace('{query}', query) + + return new ResponseSynthesizerClass({ textQAPromptTemplate, type: 'TreeSummarize' }) + } +} + +module.exports = { nodeClass: TreeSummarize_LlamaIndex } diff --git a/packages/components/nodes/responsesynthesizer/TreeSummarize/treesummarize.svg b/packages/components/nodes/responsesynthesizer/TreeSummarize/treesummarize.svg new file mode 100644 index 00000000..f81a3a53 --- /dev/null +++ b/packages/components/nodes/responsesynthesizer/TreeSummarize/treesummarize.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/packages/components/nodes/responsesynthesizer/base.ts b/packages/components/nodes/responsesynthesizer/base.ts new file mode 100644 index 00000000..68fd7f1a --- /dev/null +++ b/packages/components/nodes/responsesynthesizer/base.ts @@ -0,0 +1,11 @@ +export class ResponseSynthesizerClass { + type: string + textQAPromptTemplate?: any + refinePromptTemplate?: any + + constructor(params: { type: string; textQAPromptTemplate?: any; refinePromptTemplate?: any }) { + this.type = params.type + this.textQAPromptTemplate = params.textQAPromptTemplate + this.refinePromptTemplate = params.refinePromptTemplate + } +} diff --git a/packages/components/nodes/vectorstores/Pinecone/Pinecone_LlamaIndex.ts b/packages/components/nodes/vectorstores/Pinecone/Pinecone_LlamaIndex.ts new file mode 100644 index 00000000..683e6f25 --- /dev/null +++ b/packages/components/nodes/vectorstores/Pinecone/Pinecone_LlamaIndex.ts @@ -0,0 +1,366 @@ +import { + BaseNode, + Document, + Metadata, + VectorStore, + VectorStoreQuery, + VectorStoreQueryResult, + serviceContextFromDefaults, + storageContextFromDefaults, + VectorStoreIndex, + BaseEmbedding +} from 'llamaindex' +import { FetchResponse, Index, Pinecone, ScoredPineconeRecord } from '@pinecone-database/pinecone' +import { flatten } from 'lodash' +import { Document as LCDocument } from 'langchain/document' +import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' +import { flattenObject, getCredentialData, getCredentialParam } from '../../../src/utils' + +class PineconeLlamaIndex_VectorStores implements INode { + label: string + name: string + version: number + description: string + type: string + icon: string + category: string + tags: string[] + baseClasses: string[] + inputs: INodeParams[] + credential: INodeParams + + constructor() { + this.label = 'Pinecone' + this.name = 'pineconeLlamaIndex' + this.version = 1.0 + this.type = 'Pinecone' + this.icon = 'pinecone.png' + this.category = 'Vector Stores' + this.description = `Upsert embedded data and perform similarity search upon query using Pinecone, a leading fully managed hosted vector database` + this.baseClasses = [this.type, 'VectorIndexRetriever'] + this.tags = ['LlamaIndex'] + this.credential = { + label: 'Connect Credential', + name: 'credential', + type: 'credential', + credentialNames: ['pineconeApi'] + } + this.inputs = [ + { + label: 'Document', + name: 'document', + type: 'Document', + list: true, + optional: true + }, + { + label: 'Chat Model', + name: 'model', + type: 'BaseChatModel_LlamaIndex' + }, + { + label: 'Embeddings', + name: 'embeddings', + type: 'BaseEmbedding_LlamaIndex' + }, + { + label: 'Pinecone Index', + name: 'pineconeIndex', + type: 'string' + }, + { + label: 'Pinecone Namespace', + name: 'pineconeNamespace', + type: 'string', + placeholder: 'my-first-namespace', + additionalParams: true, + optional: true + }, + { + label: 'Pinecone Metadata Filter', + name: 'pineconeMetadataFilter', + type: 'json', + optional: true, + additionalParams: true + }, + { + label: 'Top K', + name: 'topK', + description: 'Number of top results to fetch. Default to 4', + placeholder: '4', + type: 'number', + additionalParams: true, + optional: true + } + ] + } + + //@ts-ignore + vectorStoreMethods = { + async upsert(nodeData: INodeData, options: ICommonObject): Promise { + const indexName = nodeData.inputs?.pineconeIndex as string + const pineconeNamespace = nodeData.inputs?.pineconeNamespace as string + const docs = nodeData.inputs?.document as LCDocument[] + const embeddings = nodeData.inputs?.embeddings as BaseEmbedding + const model = nodeData.inputs?.model + + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const pineconeApiKey = getCredentialParam('pineconeApiKey', credentialData, nodeData) + const pineconeEnv = getCredentialParam('pineconeEnv', credentialData, nodeData) + + const pcvs = new PineconeVectorStore({ + indexName, + apiKey: pineconeApiKey, + environment: pineconeEnv, + namespace: pineconeNamespace + }) + + const flattenDocs = docs && docs.length ? flatten(docs) : [] + const finalDocs = [] + for (let i = 0; i < flattenDocs.length; i += 1) { + if (flattenDocs[i] && flattenDocs[i].pageContent) { + finalDocs.push(new LCDocument(flattenDocs[i])) + } + } + + const llamadocs: Document[] = [] + for (const doc of finalDocs) { + llamadocs.push(new Document({ text: doc.pageContent, metadata: doc.metadata })) + } + + const serviceContext = serviceContextFromDefaults({ llm: model, embedModel: embeddings }) + const storageContext = await storageContextFromDefaults({ vectorStore: pcvs }) + + try { + await VectorStoreIndex.fromDocuments(llamadocs, { serviceContext, storageContext }) + } catch (e) { + throw new Error(e) + } + } + } + + async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { + const indexName = nodeData.inputs?.pineconeIndex as string + const pineconeNamespace = nodeData.inputs?.pineconeNamespace as string + const pineconeMetadataFilter = nodeData.inputs?.pineconeMetadataFilter + const embeddings = nodeData.inputs?.embeddings as BaseEmbedding + const model = nodeData.inputs?.model + const topK = nodeData.inputs?.topK as string + const k = topK ? parseFloat(topK) : 4 + + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const pineconeApiKey = getCredentialParam('pineconeApiKey', credentialData, nodeData) + const pineconeEnv = getCredentialParam('pineconeEnv', credentialData, nodeData) + + const obj: PineconeParams = { + indexName, + apiKey: pineconeApiKey, + environment: pineconeEnv + } + + if (pineconeNamespace) obj.namespace = pineconeNamespace + if (pineconeMetadataFilter) { + const metadatafilter = typeof pineconeMetadataFilter === 'object' ? pineconeMetadataFilter : JSON.parse(pineconeMetadataFilter) + obj.queryFilter = metadatafilter + } + + const pcvs = new PineconeVectorStore(obj) + + const serviceContext = serviceContextFromDefaults({ llm: model, embedModel: embeddings }) + const storageContext = await storageContextFromDefaults({ vectorStore: pcvs }) + + const index = await VectorStoreIndex.init({ + nodes: [], + storageContext, + serviceContext + }) + + const retriever = index.asRetriever() + retriever.similarityTopK = k + ;(retriever as any).serviceContext = serviceContext + + return retriever + } +} + +type PineconeParams = { + indexName: string + apiKey: string + environment: string + namespace?: string + chunkSize?: number + queryFilter?: object +} + +class PineconeVectorStore implements VectorStore { + storesText: boolean = true + db?: Pinecone + indexName: string + apiKey: string + environment: string + chunkSize: number + namespace?: string + queryFilter?: object + + constructor(params: PineconeParams) { + this.indexName = params?.indexName + this.apiKey = params?.apiKey + this.environment = params?.environment + this.namespace = params?.namespace ?? '' + this.chunkSize = params?.chunkSize ?? Number.parseInt(process.env.PINECONE_CHUNK_SIZE ?? '100') + this.queryFilter = params?.queryFilter ?? {} + } + + private async getDb(): Promise { + if (!this.db) { + this.db = new Pinecone({ + apiKey: this.apiKey, + environment: this.environment + }) + } + return Promise.resolve(this.db) + } + + client() { + return this.getDb() + } + + async index() { + const db: Pinecone = await this.getDb() + return db.Index(this.indexName) + } + + async clearIndex() { + const db: Pinecone = await this.getDb() + return await db.index(this.indexName).deleteAll() + } + + async add(embeddingResults: BaseNode[]): Promise { + if (embeddingResults.length == 0) { + return Promise.resolve([]) + } + + const idx: Index = await this.index() + const nodes = embeddingResults.map(this.nodeToRecord) + + for (let i = 0; i < nodes.length; i += this.chunkSize) { + const chunk = nodes.slice(i, i + this.chunkSize) + const result = await this.saveChunk(idx, chunk) + if (!result) { + return Promise.reject() + } + } + return Promise.resolve([]) + } + + protected async saveChunk(idx: Index, chunk: any) { + try { + const namespace = idx.namespace(this.namespace ?? '') + await namespace.upsert(chunk) + return true + } catch (err) { + return false + } + } + + async delete(refDocId: string): Promise { + const idx = await this.index() + const namespace = idx.namespace(this.namespace ?? '') + return namespace.deleteOne(refDocId) + } + + async query(query: VectorStoreQuery): Promise { + const queryOptions: any = { + vector: query.queryEmbedding, + topK: query.similarityTopK, + filter: this.queryFilter + } + + const idx = await this.index() + const namespace = idx.namespace(this.namespace ?? '') + const results = await namespace.query(queryOptions) + + const idList = results.matches.map((row) => row.id) + const records: FetchResponse = await namespace.fetch(idList) + const rows = Object.values(records.records) + + const nodes = rows.map((row) => { + return new Document({ + id_: row.id, + text: this.textFromResultRow(row), + metadata: this.metaWithoutText(row.metadata), + embedding: row.values + }) + }) + + const result = { + nodes: nodes, + similarities: results.matches.map((row) => row.score || 999), + ids: results.matches.map((row) => row.id) + } + + return Promise.resolve(result) + } + + /** + * Required by VectorStore interface. Currently ignored. + */ + persist(): Promise { + return Promise.resolve() + } + + textFromResultRow(row: ScoredPineconeRecord): string { + return row.metadata?.text ?? '' + } + + metaWithoutText(meta: Metadata): any { + return Object.keys(meta) + .filter((key) => key != 'text') + .reduce((acc: any, key: string) => { + acc[key] = meta[key] + return acc + }, {}) + } + + nodeToRecord(node: BaseNode) { + let id: any = node.id_.length ? node.id_ : null + return { + id: id, + values: node.getEmbedding(), + metadata: { + ...cleanupMetadata(node.metadata), + text: (node as any).text + } + } + } +} + +const cleanupMetadata = (nodeMetadata: ICommonObject) => { + // Pinecone doesn't support nested objects, so we flatten them + const documentMetadata: any = { ...nodeMetadata } + // preserve string arrays which are allowed + const stringArrays: Record = {} + for (const key of Object.keys(documentMetadata)) { + if (Array.isArray(documentMetadata[key]) && documentMetadata[key].every((el: any) => typeof el === 'string')) { + stringArrays[key] = documentMetadata[key] + delete documentMetadata[key] + } + } + const metadata: { + [key: string]: string | number | boolean | string[] | null + } = { + ...flattenObject(documentMetadata), + ...stringArrays + } + // Pinecone doesn't support null values, so we remove them + for (const key of Object.keys(metadata)) { + if (metadata[key] == null) { + delete metadata[key] + } else if (typeof metadata[key] === 'object' && Object.keys(metadata[key] as unknown as object).length === 0) { + delete metadata[key] + } + } + return metadata +} + +module.exports = { nodeClass: PineconeLlamaIndex_VectorStores } diff --git a/packages/components/nodes/vectorstores/SimpleStore/SimpleStore.ts b/packages/components/nodes/vectorstores/SimpleStore/SimpleStore.ts new file mode 100644 index 00000000..eeef6f69 --- /dev/null +++ b/packages/components/nodes/vectorstores/SimpleStore/SimpleStore.ts @@ -0,0 +1,124 @@ +import path from 'path' +import { flatten } from 'lodash' +import { storageContextFromDefaults, serviceContextFromDefaults, VectorStoreIndex, Document } from 'llamaindex' +import { Document as LCDocument } from 'langchain/document' +import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' +import { getUserHome } from '../../../src' + +class SimpleStoreUpsert_LlamaIndex_VectorStores implements INode { + label: string + name: string + version: number + description: string + type: string + icon: string + category: string + baseClasses: string[] + tags: string[] + inputs: INodeParams[] + outputs: INodeOutputsValue[] + + constructor() { + this.label = 'SimpleStore' + this.name = 'simpleStoreLlamaIndex' + this.version = 1.0 + this.type = 'SimpleVectorStore' + this.icon = 'simplevs.svg' + this.category = 'Vector Stores' + this.description = 'Upsert embedded data to local path and perform similarity search' + this.baseClasses = [this.type, 'VectorIndexRetriever'] + this.tags = ['LlamaIndex'] + this.inputs = [ + { + label: 'Document', + name: 'document', + type: 'Document', + list: true, + optional: true + }, + { + label: 'Chat Model', + name: 'model', + type: 'BaseChatModel_LlamaIndex' + }, + { + label: 'Embeddings', + name: 'embeddings', + type: 'BaseEmbedding_LlamaIndex' + }, + { + label: 'Base Path to store', + name: 'basePath', + description: + 'Path to store persist embeddings indexes with persistence. If not specified, default to same path where database is stored', + type: 'string', + optional: true + }, + { + label: 'Top K', + name: 'topK', + description: 'Number of top results to fetch. Default to 4', + placeholder: '4', + type: 'number', + optional: true + } + ] + } + + //@ts-ignore + vectorStoreMethods = { + async upsert(nodeData: INodeData): Promise { + const basePath = nodeData.inputs?.basePath as string + const docs = nodeData.inputs?.document as LCDocument[] + const embeddings = nodeData.inputs?.embeddings + const model = nodeData.inputs?.model + + let filePath = '' + if (!basePath) filePath = path.join(getUserHome(), '.flowise', 'llamaindex') + else filePath = basePath + + const flattenDocs = docs && docs.length ? flatten(docs) : [] + const finalDocs = [] + for (let i = 0; i < flattenDocs.length; i += 1) { + finalDocs.push(new LCDocument(flattenDocs[i])) + } + + const llamadocs: Document[] = [] + for (const doc of finalDocs) { + llamadocs.push(new Document({ text: doc.pageContent, metadata: doc.metadata })) + } + + const serviceContext = serviceContextFromDefaults({ llm: model, embedModel: embeddings }) + const storageContext = await storageContextFromDefaults({ persistDir: filePath }) + + try { + await VectorStoreIndex.fromDocuments(llamadocs, { serviceContext, storageContext }) + } catch (e) { + throw new Error(e) + } + } + } + + async init(nodeData: INodeData): Promise { + const basePath = nodeData.inputs?.basePath as string + const embeddings = nodeData.inputs?.embeddings + const model = nodeData.inputs?.model + const topK = nodeData.inputs?.topK as string + const k = topK ? parseFloat(topK) : 4 + + let filePath = '' + if (!basePath) filePath = path.join(getUserHome(), '.flowise', 'llamaindex') + else filePath = basePath + + const serviceContext = serviceContextFromDefaults({ llm: model, embedModel: embeddings }) + const storageContext = await storageContextFromDefaults({ persistDir: filePath }) + + const index = await VectorStoreIndex.init({ storageContext, serviceContext }) + const retriever = index.asRetriever() + retriever.similarityTopK = k + + return retriever + } +} + +module.exports = { nodeClass: SimpleStoreUpsert_LlamaIndex_VectorStores } diff --git a/packages/components/nodes/vectorstores/SimpleStore/simplevs.svg b/packages/components/nodes/vectorstores/SimpleStore/simplevs.svg new file mode 100644 index 00000000..52c74432 --- /dev/null +++ b/packages/components/nodes/vectorstores/SimpleStore/simplevs.svg @@ -0,0 +1,6 @@ + + + + + + \ No newline at end of file diff --git a/packages/components/package.json b/packages/components/package.json index bea9a7a0..d1485b37 100644 --- a/packages/components/package.json +++ b/packages/components/package.json @@ -21,7 +21,7 @@ "@aws-sdk/client-s3": "^3.427.0", "@dqbd/tiktoken": "^1.0.7", "@elastic/elasticsearch": "^8.9.0", - "@getzep/zep-js": "^0.6.3", + "@getzep/zep-js": "^0.9.0", "@gomomento/sdk": "^1.51.1", "@gomomento/sdk-core": "^1.51.1", "@google-ai/generativelanguage": "^0.2.1", @@ -54,6 +54,7 @@ "langfuse-langchain": "^1.0.31", "langsmith": "^0.0.32", "linkifyjs": "^4.1.1", + "llamaindex": "^0.0.30", "llmonitor": "^0.5.5", "mammoth": "^1.5.1", "moment": "^2.29.3", diff --git a/packages/components/src/Interface.ts b/packages/components/src/Interface.ts index 6752f944..53d72cb4 100644 --- a/packages/components/src/Interface.ts +++ b/packages/components/src/Interface.ts @@ -91,6 +91,7 @@ export interface INodeProperties { version: number category: string baseClasses: string[] + tags?: string[] description?: string filePath?: string badge?: string @@ -107,10 +108,6 @@ export interface INode extends INodeProperties { search: (nodeData: INodeData, options?: ICommonObject) => Promise delete: (nodeData: INodeData, options?: ICommonObject) => Promise } - memoryMethods?: { - clearSessionMemory: (nodeData: INodeData, options?: ICommonObject) => Promise - getChatMessages: (nodeData: INodeData, options?: ICommonObject) => Promise - } init?(nodeData: INodeData, input: string, options?: ICommonObject): Promise run?(nodeData: INodeData, input: string, options?: ICommonObject): Promise } diff --git a/packages/components/src/utils.ts b/packages/components/src/utils.ts index 404f7c75..ceeb402a 100644 --- a/packages/components/src/utils.ts +++ b/packages/components/src/utils.ts @@ -8,7 +8,7 @@ import { DataSource } from 'typeorm' import { ICommonObject, IDatabaseEntity, IMessage, INodeData } from './Interface' import { AES, enc } from 'crypto-js' import { ChatMessageHistory } from 'langchain/memory' -import { AIMessage, HumanMessage } from 'langchain/schema' +import { AIMessage, HumanMessage, BaseMessage } from 'langchain/schema' export const numberOrExpressionRegex = '^(\\d+\\.?\\d*|{{.*}})$' //return true if string consists only numbers OR expression {{}} export const notEmptyRegex = '(.|\\s)*\\S(.|\\s)*' //return true if string is not empty or blank @@ -587,3 +587,54 @@ export const convertSchemaToZod = (schema: string | object): ICommonObject => { throw new Error(e) } } + +/** + * Flatten nested object + * @param {ICommonObject} obj + * @param {string} parentKey + * @returns {ICommonObject} + */ +export const flattenObject = (obj: ICommonObject, parentKey?: string) => { + let result: any = {} + + Object.keys(obj).forEach((key) => { + const value = obj[key] + const _key = parentKey ? parentKey + '.' + key : key + if (typeof value === 'object') { + result = { ...result, ...flattenObject(value, _key) } + } else { + result[_key] = value + } + }) + + return result +} + +/** + * Convert BaseMessage to IMessage + * @param {ICommonObject} obj + * @param {string} parentKey + * @returns {ICommonObject} + */ +export const convertBaseMessagetoIMessage = (messages: BaseMessage[]): IMessage[] => { + const formatmessages: IMessage[] = [] + for (const m of messages) { + if (m._getType() === 'human') { + formatmessages.push({ + message: m.content as string, + type: 'userMessage' + }) + } else if (m._getType() === 'ai') { + formatmessages.push({ + message: m.content as string, + type: 'apiMessage' + }) + } else if (m._getType() === 'system') { + formatmessages.push({ + message: m.content as string, + type: 'apiMessage' + }) + } + } + return formatmessages +} diff --git a/packages/server/marketplaces/chatflows/Context Chat Engine.json b/packages/server/marketplaces/chatflows/Context Chat Engine.json new file mode 100644 index 00000000..971aeea5 --- /dev/null +++ b/packages/server/marketplaces/chatflows/Context Chat Engine.json @@ -0,0 +1,855 @@ +{ + "description": "Answer question based on retrieved documents (context) with built-in memory to remember conversation using LlamaIndex", + "badge": "NEW", + "nodes": [ + { + "width": 300, + "height": 438, + "id": "textFile_0", + "position": { + "x": 221.215421786192, + "y": 94.91489477412404 + }, + "type": "customNode", + "data": { + "id": "textFile_0", + "label": "Text File", + "version": 3, + "name": "textFile", + "type": "Document", + "baseClasses": ["Document"], + "category": "Document Loaders", + "description": "Load data from text files", + "inputParams": [ + { + "label": "Txt File", + "name": "txtFile", + "type": "file", + "fileType": ".txt, .html, .aspx, .asp, .cpp, .c, .cs, .css, .go, .h, .java, .js, .less, .ts, .php, .proto, .python, .py, .rst, .ruby, .rb, .rs, .scala, .sc, .scss, .sol, .sql, .swift, .markdown, .md, .tex, .ltx, .vb, .xml", + "id": "textFile_0-input-txtFile-file" + }, + { + "label": "Metadata", + "name": "metadata", + "type": "json", + "optional": true, + "additionalParams": true, + "id": "textFile_0-input-metadata-json" + } + ], + "inputAnchors": [ + { + "label": "Text Splitter", + "name": "textSplitter", + "type": "TextSplitter", + "optional": true, + "id": "textFile_0-input-textSplitter-TextSplitter" + } + ], + "inputs": { + "textSplitter": "{{recursiveCharacterTextSplitter_0.data.instance}}", + "metadata": "" + }, + "outputAnchors": [ + { + "name": "output", + "label": "Output", + "type": "options", + "options": [ + { + "id": "textFile_0-output-document-Document", + "name": "document", + "label": "Document", + "type": "Document" + }, + { + "id": "textFile_0-output-text-string|json", + "name": "text", + "label": "Text", + "type": "string | json" + } + ], + "default": "document" + } + ], + "outputs": { + "output": "document" + }, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 221.215421786192, + "y": 94.91489477412404 + }, + "dragging": false + }, + { + "width": 300, + "height": 429, + "id": "recursiveCharacterTextSplitter_0", + "position": { + "x": -203.4868320229876, + "y": 101.32475976329766 + }, + "type": "customNode", + "data": { + "id": "recursiveCharacterTextSplitter_0", + "label": "Recursive Character Text Splitter", + "version": 2, + "name": "recursiveCharacterTextSplitter", + "type": "RecursiveCharacterTextSplitter", + "baseClasses": ["RecursiveCharacterTextSplitter", "TextSplitter", "BaseDocumentTransformer", "Runnable"], + "category": "Text Splitters", + "description": "Split documents recursively by different characters - starting with \"\\n\\n\", then \"\\n\", then \" \"", + "inputParams": [ + { + "label": "Chunk Size", + "name": "chunkSize", + "type": "number", + "default": 1000, + "optional": true, + "id": "recursiveCharacterTextSplitter_0-input-chunkSize-number" + }, + { + "label": "Chunk Overlap", + "name": "chunkOverlap", + "type": "number", + "optional": true, + "id": "recursiveCharacterTextSplitter_0-input-chunkOverlap-number" + }, + { + "label": "Custom Separators", + "name": "separators", + "type": "string", + "rows": 4, + "description": "Array of custom separators to determine when to split the text, will override the default separators", + "placeholder": "[\"|\", \"##\", \">\", \"-\"]", + "additionalParams": true, + "optional": true, + "id": "recursiveCharacterTextSplitter_0-input-separators-string" + } + ], + "inputAnchors": [], + "inputs": { + "chunkSize": 1000, + "chunkOverlap": "", + "separators": "" + }, + "outputAnchors": [ + { + "id": "recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter|BaseDocumentTransformer|Runnable", + "name": "recursiveCharacterTextSplitter", + "label": "RecursiveCharacterTextSplitter", + "type": "RecursiveCharacterTextSplitter | TextSplitter | BaseDocumentTransformer | Runnable" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": -203.4868320229876, + "y": 101.32475976329766 + }, + "dragging": false + }, + { + "width": 300, + "height": 334, + "id": "openAIEmbedding_LlamaIndex_0", + "position": { + "x": 176.27434578083106, + "y": 953.3664298122493 + }, + "type": "customNode", + "data": { + "id": "openAIEmbedding_LlamaIndex_0", + "label": "OpenAI Embedding", + "version": 1, + "name": "openAIEmbedding_LlamaIndex", + "type": "OpenAIEmbedding", + "baseClasses": ["OpenAIEmbedding", "BaseEmbedding_LlamaIndex", "BaseEmbedding"], + "tags": ["LlamaIndex"], + "category": "Embeddings", + "description": "OpenAI Embedding with LlamaIndex implementation", + "inputParams": [ + { + "label": "Connect Credential", + "name": "credential", + "type": "credential", + "credentialNames": ["openAIApi"], + "id": "openAIEmbedding_LlamaIndex_0-input-credential-credential" + }, + { + "label": "Timeout", + "name": "timeout", + "type": "number", + "optional": true, + "additionalParams": true, + "id": "openAIEmbedding_LlamaIndex_0-input-timeout-number" + }, + { + "label": "BasePath", + "name": "basepath", + "type": "string", + "optional": true, + "additionalParams": true, + "id": "openAIEmbedding_LlamaIndex_0-input-basepath-string" + } + ], + "inputAnchors": [], + "inputs": { + "timeout": "", + "basepath": "" + }, + "outputAnchors": [ + { + "id": "openAIEmbedding_LlamaIndex_0-output-openAIEmbedding_LlamaIndex-OpenAIEmbedding|BaseEmbedding_LlamaIndex|BaseEmbedding", + "name": "openAIEmbedding_LlamaIndex", + "label": "OpenAIEmbedding", + "type": "OpenAIEmbedding | BaseEmbedding_LlamaIndex | BaseEmbedding" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 176.27434578083106, + "y": 953.3664298122493 + }, + "dragging": false + }, + { + "width": 300, + "height": 585, + "id": "pineconeLlamaIndex_0", + "position": { + "x": 609.3087433345761, + "y": 488.2141798951578 + }, + "type": "customNode", + "data": { + "id": "pineconeLlamaIndex_0", + "label": "Pinecone", + "version": 1, + "name": "pineconeLlamaIndex", + "type": "Pinecone", + "baseClasses": ["Pinecone", "VectorIndexRetriever"], + "tags": ["LlamaIndex"], + "category": "Vector Stores", + "description": "Upsert embedded data and perform similarity search upon query using Pinecone, a leading fully managed hosted vector database", + "inputParams": [ + { + "label": "Connect Credential", + "name": "credential", + "type": "credential", + "credentialNames": ["pineconeApi"], + "id": "pineconeLlamaIndex_0-input-credential-credential" + }, + { + "label": "Pinecone Index", + "name": "pineconeIndex", + "type": "string", + "id": "pineconeLlamaIndex_0-input-pineconeIndex-string" + }, + { + "label": "Pinecone Namespace", + "name": "pineconeNamespace", + "type": "string", + "placeholder": "my-first-namespace", + "additionalParams": true, + "optional": true, + "id": "pineconeLlamaIndex_0-input-pineconeNamespace-string" + }, + { + "label": "Pinecone Metadata Filter", + "name": "pineconeMetadataFilter", + "type": "json", + "optional": true, + "additionalParams": true, + "id": "pineconeLlamaIndex_0-input-pineconeMetadataFilter-json" + }, + { + "label": "Top K", + "name": "topK", + "description": "Number of top results to fetch. Default to 4", + "placeholder": "4", + "type": "number", + "additionalParams": true, + "optional": true, + "id": "pineconeLlamaIndex_0-input-topK-number" + } + ], + "inputAnchors": [ + { + "label": "Document", + "name": "document", + "type": "Document", + "list": true, + "optional": true, + "id": "pineconeLlamaIndex_0-input-document-Document" + }, + { + "label": "Chat Model", + "name": "model", + "type": "BaseChatModel_LlamaIndex", + "id": "pineconeLlamaIndex_0-input-model-BaseChatModel_LlamaIndex" + }, + { + "label": "Embeddings", + "name": "embeddings", + "type": "BaseEmbedding_LlamaIndex", + "id": "pineconeLlamaIndex_0-input-embeddings-BaseEmbedding_LlamaIndex" + } + ], + "inputs": { + "document": ["{{textFile_0.data.instance}}"], + "model": "{{chatOpenAI_LlamaIndex_1.data.instance}}", + "embeddings": "{{openAIEmbedding_LlamaIndex_0.data.instance}}", + "pineconeIndex": "", + "pineconeNamespace": "", + "pineconeMetadataFilter": "", + "topK": "" + }, + "outputAnchors": [ + { + "id": "pineconeLlamaIndex_0-output-pineconeLlamaIndex-Pinecone|VectorIndexRetriever", + "name": "pineconeLlamaIndex", + "label": "Pinecone", + "type": "Pinecone | VectorIndexRetriever" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 609.3087433345761, + "y": 488.2141798951578 + }, + "dragging": false + }, + { + "width": 300, + "height": 529, + "id": "chatOpenAI_LlamaIndex_1", + "position": { + "x": -195.15244974578656, + "y": 584.9467028201428 + }, + "type": "customNode", + "data": { + "id": "chatOpenAI_LlamaIndex_1", + "label": "ChatOpenAI", + "version": 1, + "name": "chatOpenAI_LlamaIndex", + "type": "ChatOpenAI", + "baseClasses": ["ChatOpenAI", "BaseChatModel_LlamaIndex"], + "tags": ["LlamaIndex"], + "category": "Chat Models", + "description": "Wrapper around OpenAI Chat LLM with LlamaIndex implementation", + "inputParams": [ + { + "label": "Connect Credential", + "name": "credential", + "type": "credential", + "credentialNames": ["openAIApi"], + "id": "chatOpenAI_LlamaIndex_1-input-credential-credential" + }, + { + "label": "Model Name", + "name": "modelName", + "type": "options", + "options": [ + { + "label": "gpt-4", + "name": "gpt-4" + }, + { + "label": "gpt-4-1106-preview", + "name": "gpt-4-1106-preview" + }, + { + "label": "gpt-4-vision-preview", + "name": "gpt-4-vision-preview" + }, + { + "label": "gpt-4-0613", + "name": "gpt-4-0613" + }, + { + "label": "gpt-4-32k", + "name": "gpt-4-32k" + }, + { + "label": "gpt-4-32k-0613", + "name": "gpt-4-32k-0613" + }, + { + "label": "gpt-3.5-turbo", + "name": "gpt-3.5-turbo" + }, + { + "label": "gpt-3.5-turbo-1106", + "name": "gpt-3.5-turbo-1106" + }, + { + "label": "gpt-3.5-turbo-0613", + "name": "gpt-3.5-turbo-0613" + }, + { + "label": "gpt-3.5-turbo-16k", + "name": "gpt-3.5-turbo-16k" + }, + { + "label": "gpt-3.5-turbo-16k-0613", + "name": "gpt-3.5-turbo-16k-0613" + } + ], + "default": "gpt-3.5-turbo", + "optional": true, + "id": "chatOpenAI_LlamaIndex_1-input-modelName-options" + }, + { + "label": "Temperature", + "name": "temperature", + "type": "number", + "step": 0.1, + "default": 0.9, + "optional": true, + "id": "chatOpenAI_LlamaIndex_1-input-temperature-number" + }, + { + "label": "Max Tokens", + "name": "maxTokens", + "type": "number", + "step": 1, + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_LlamaIndex_1-input-maxTokens-number" + }, + { + "label": "Top Probability", + "name": "topP", + "type": "number", + "step": 0.1, + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_LlamaIndex_1-input-topP-number" + }, + { + "label": "Timeout", + "name": "timeout", + "type": "number", + "step": 1, + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_LlamaIndex_1-input-timeout-number" + } + ], + "inputAnchors": [], + "inputs": { + "modelName": "gpt-3.5-turbo-16k", + "temperature": 0.9, + "maxTokens": "", + "topP": "", + "timeout": "" + }, + "outputAnchors": [ + { + "id": "chatOpenAI_LlamaIndex_1-output-chatOpenAI_LlamaIndex-ChatOpenAI|BaseChatModel_LlamaIndex", + "name": "chatOpenAI_LlamaIndex", + "label": "ChatOpenAI", + "type": "ChatOpenAI | BaseChatModel_LlamaIndex" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": -195.15244974578656, + "y": 584.9467028201428 + }, + "dragging": false + }, + { + "width": 300, + "height": 513, + "id": "contextChatEngine_0", + "position": { + "x": 1550.2553933740128, + "y": 270.7914631777829 + }, + "type": "customNode", + "data": { + "id": "contextChatEngine_0", + "label": "Context Chat Engine", + "version": 1, + "name": "contextChatEngine", + "type": "ContextChatEngine", + "baseClasses": ["ContextChatEngine"], + "tags": ["LlamaIndex"], + "category": "Engine", + "description": "Answer question based on retrieved documents (context) with built-in memory to remember conversation", + "inputParams": [ + { + "label": "System Message", + "name": "systemMessagePrompt", + "type": "string", + "rows": 4, + "optional": true, + "placeholder": "I want you to act as a document that I am having a conversation with. Your name is \"AI Assistant\". You will provide me with answers from the given info. If the answer is not included, say exactly \"Hmm, I am not sure.\" and stop after that. Refuse to answer any question not about the info. Never break character.", + "id": "contextChatEngine_0-input-systemMessagePrompt-string" + } + ], + "inputAnchors": [ + { + "label": "Chat Model", + "name": "model", + "type": "BaseChatModel_LlamaIndex", + "id": "contextChatEngine_0-input-model-BaseChatModel_LlamaIndex" + }, + { + "label": "Vector Store Retriever", + "name": "vectorStoreRetriever", + "type": "VectorIndexRetriever", + "id": "contextChatEngine_0-input-vectorStoreRetriever-VectorIndexRetriever" + }, + { + "label": "Memory", + "name": "memory", + "type": "BaseChatMemory", + "id": "contextChatEngine_0-input-memory-BaseChatMemory" + } + ], + "inputs": { + "model": "{{chatOpenAI_LlamaIndex_2.data.instance}}", + "vectorStoreRetriever": "{{pineconeLlamaIndex_0.data.instance}}", + "memory": "{{RedisBackedChatMemory_0.data.instance}}", + "systemMessagePrompt": "" + }, + "outputAnchors": [ + { + "id": "contextChatEngine_0-output-contextChatEngine-ContextChatEngine", + "name": "contextChatEngine", + "label": "ContextChatEngine", + "type": "ContextChatEngine" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 1550.2553933740128, + "y": 270.7914631777829 + }, + "dragging": false + }, + { + "width": 300, + "height": 329, + "id": "RedisBackedChatMemory_0", + "position": { + "x": 1081.252815805786, + "y": 990.1701092562037 + }, + "type": "customNode", + "data": { + "id": "RedisBackedChatMemory_0", + "label": "Redis-Backed Chat Memory", + "version": 2, + "name": "RedisBackedChatMemory", + "type": "RedisBackedChatMemory", + "baseClasses": ["RedisBackedChatMemory", "BaseChatMemory", "BaseMemory"], + "category": "Memory", + "description": "Summarizes the conversation and stores the memory in Redis server", + "inputParams": [ + { + "label": "Connect Credential", + "name": "credential", + "type": "credential", + "optional": true, + "credentialNames": ["redisCacheApi", "redisCacheUrlApi"], + "id": "RedisBackedChatMemory_0-input-credential-credential" + }, + { + "label": "Session Id", + "name": "sessionId", + "type": "string", + "description": "If not specified, a random id will be used. Learn more", + "default": "", + "additionalParams": true, + "optional": true, + "id": "RedisBackedChatMemory_0-input-sessionId-string" + }, + { + "label": "Session Timeouts", + "name": "sessionTTL", + "type": "number", + "description": "Omit this parameter to make sessions never expire", + "additionalParams": true, + "optional": true, + "id": "RedisBackedChatMemory_0-input-sessionTTL-number" + }, + { + "label": "Memory Key", + "name": "memoryKey", + "type": "string", + "default": "chat_history", + "additionalParams": true, + "id": "RedisBackedChatMemory_0-input-memoryKey-string" + } + ], + "inputAnchors": [], + "inputs": { + "sessionId": "", + "sessionTTL": "", + "memoryKey": "chat_history" + }, + "outputAnchors": [ + { + "id": "RedisBackedChatMemory_0-output-RedisBackedChatMemory-RedisBackedChatMemory|BaseChatMemory|BaseMemory", + "name": "RedisBackedChatMemory", + "label": "RedisBackedChatMemory", + "type": "RedisBackedChatMemory | BaseChatMemory | BaseMemory" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "dragging": false, + "positionAbsolute": { + "x": 1081.252815805786, + "y": 990.1701092562037 + } + }, + { + "width": 300, + "height": 529, + "id": "chatOpenAI_LlamaIndex_2", + "position": { + "x": 1015.1605888108386, + "y": -38.31143117572401 + }, + "type": "customNode", + "data": { + "id": "chatOpenAI_LlamaIndex_2", + "label": "ChatOpenAI", + "version": 1, + "name": "chatOpenAI_LlamaIndex", + "type": "ChatOpenAI", + "baseClasses": ["ChatOpenAI", "BaseChatModel_LlamaIndex"], + "tags": ["LlamaIndex"], + "category": "Chat Models", + "description": "Wrapper around OpenAI Chat LLM with LlamaIndex implementation", + "inputParams": [ + { + "label": "Connect Credential", + "name": "credential", + "type": "credential", + "credentialNames": ["openAIApi"], + "id": "chatOpenAI_LlamaIndex_2-input-credential-credential" + }, + { + "label": "Model Name", + "name": "modelName", + "type": "options", + "options": [ + { + "label": "gpt-4", + "name": "gpt-4" + }, + { + "label": "gpt-4-1106-preview", + "name": "gpt-4-1106-preview" + }, + { + "label": "gpt-4-vision-preview", + "name": "gpt-4-vision-preview" + }, + { + "label": "gpt-4-0613", + "name": "gpt-4-0613" + }, + { + "label": "gpt-4-32k", + "name": "gpt-4-32k" + }, + { + "label": "gpt-4-32k-0613", + "name": "gpt-4-32k-0613" + }, + { + "label": "gpt-3.5-turbo", + "name": "gpt-3.5-turbo" + }, + { + "label": "gpt-3.5-turbo-1106", + "name": "gpt-3.5-turbo-1106" + }, + { + "label": "gpt-3.5-turbo-0613", + "name": "gpt-3.5-turbo-0613" + }, + { + "label": "gpt-3.5-turbo-16k", + "name": "gpt-3.5-turbo-16k" + }, + { + "label": "gpt-3.5-turbo-16k-0613", + "name": "gpt-3.5-turbo-16k-0613" + } + ], + "default": "gpt-3.5-turbo", + "optional": true, + "id": "chatOpenAI_LlamaIndex_2-input-modelName-options" + }, + { + "label": "Temperature", + "name": "temperature", + "type": "number", + "step": 0.1, + "default": 0.9, + "optional": true, + "id": "chatOpenAI_LlamaIndex_2-input-temperature-number" + }, + { + "label": "Max Tokens", + "name": "maxTokens", + "type": "number", + "step": 1, + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_LlamaIndex_2-input-maxTokens-number" + }, + { + "label": "Top Probability", + "name": "topP", + "type": "number", + "step": 0.1, + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_LlamaIndex_2-input-topP-number" + }, + { + "label": "Timeout", + "name": "timeout", + "type": "number", + "step": 1, + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_LlamaIndex_2-input-timeout-number" + } + ], + "inputAnchors": [], + "inputs": { + "modelName": "gpt-3.5-turbo", + "temperature": 0.9, + "maxTokens": "", + "topP": "", + "timeout": "" + }, + "outputAnchors": [ + { + "id": "chatOpenAI_LlamaIndex_2-output-chatOpenAI_LlamaIndex-ChatOpenAI|BaseChatModel_LlamaIndex", + "name": "chatOpenAI_LlamaIndex", + "label": "ChatOpenAI", + "type": "ChatOpenAI | BaseChatModel_LlamaIndex" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 1015.1605888108386, + "y": -38.31143117572401 + }, + "dragging": false + } + ], + "edges": [ + { + "source": "recursiveCharacterTextSplitter_0", + "sourceHandle": "recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter|BaseDocumentTransformer|Runnable", + "target": "textFile_0", + "targetHandle": "textFile_0-input-textSplitter-TextSplitter", + "type": "buttonedge", + "id": "recursiveCharacterTextSplitter_0-recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter|BaseDocumentTransformer|Runnable-textFile_0-textFile_0-input-textSplitter-TextSplitter", + "data": { + "label": "" + } + }, + { + "source": "textFile_0", + "sourceHandle": "textFile_0-output-document-Document", + "target": "pineconeLlamaIndex_0", + "targetHandle": 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"targetHandle": "pineconeLlamaIndex_0-input-embeddings-BaseEmbedding_LlamaIndex", + "type": "buttonedge", + "id": "openAIEmbedding_LlamaIndex_0-openAIEmbedding_LlamaIndex_0-output-openAIEmbedding_LlamaIndex-OpenAIEmbedding|BaseEmbedding_LlamaIndex|BaseEmbedding-pineconeLlamaIndex_0-pineconeLlamaIndex_0-input-embeddings-BaseEmbedding_LlamaIndex", + "data": { + "label": "" + } + }, + { + "source": "pineconeLlamaIndex_0", + "sourceHandle": "pineconeLlamaIndex_0-output-pineconeLlamaIndex-Pinecone|VectorIndexRetriever", + "target": "contextChatEngine_0", + "targetHandle": "contextChatEngine_0-input-vectorStoreRetriever-VectorIndexRetriever", + "type": "buttonedge", + "id": "pineconeLlamaIndex_0-pineconeLlamaIndex_0-output-pineconeLlamaIndex-Pinecone|VectorIndexRetriever-contextChatEngine_0-contextChatEngine_0-input-vectorStoreRetriever-VectorIndexRetriever", + "data": { + "label": "" + } + }, + { + "source": "RedisBackedChatMemory_0", + "sourceHandle": "RedisBackedChatMemory_0-output-RedisBackedChatMemory-RedisBackedChatMemory|BaseChatMemory|BaseMemory", + "target": "contextChatEngine_0", + "targetHandle": "contextChatEngine_0-input-memory-BaseChatMemory", + "type": "buttonedge", + "id": "RedisBackedChatMemory_0-RedisBackedChatMemory_0-output-RedisBackedChatMemory-RedisBackedChatMemory|BaseChatMemory|BaseMemory-contextChatEngine_0-contextChatEngine_0-input-memory-BaseChatMemory", + "data": { + "label": "" + } + }, + { + "source": "chatOpenAI_LlamaIndex_2", + "sourceHandle": "chatOpenAI_LlamaIndex_2-output-chatOpenAI_LlamaIndex-ChatOpenAI|BaseChatModel_LlamaIndex", + "target": "contextChatEngine_0", + "targetHandle": "contextChatEngine_0-input-model-BaseChatModel_LlamaIndex", + "type": "buttonedge", + "id": "chatOpenAI_LlamaIndex_2-chatOpenAI_LlamaIndex_2-output-chatOpenAI_LlamaIndex-ChatOpenAI|BaseChatModel_LlamaIndex-contextChatEngine_0-contextChatEngine_0-input-model-BaseChatModel_LlamaIndex", + "data": { + "label": "" + } + } + ] +} diff --git a/packages/server/marketplaces/chatflows/Long Term Memory.json b/packages/server/marketplaces/chatflows/Long Term Memory.json index c508b480..2973594f 100644 --- a/packages/server/marketplaces/chatflows/Long Term Memory.json +++ b/packages/server/marketplaces/chatflows/Long Term Memory.json @@ -205,7 +205,7 @@ "data": { "id": "ZepMemory_0", "label": "Zep Memory", - "version": 1, + "version": 2, "name": "ZepMemory", "type": "ZepMemory", "baseClasses": ["ZepMemory", "BaseChatMemory", "BaseMemory"], @@ -228,13 +228,6 @@ "default": "http://127.0.0.1:8000", "id": "ZepMemory_0-input-baseURL-string" }, - { - "label": "Auto Summary", - "name": "autoSummary", - "type": "boolean", - "default": true, - "id": "ZepMemory_0-input-autoSummary-boolean" - }, { "label": "Session Id", "name": "sessionId", @@ -252,15 +245,8 @@ "default": "10", "step": 1, "description": "Window of size k to surface the last k back-and-forths to use as memory.", - "id": "ZepMemory_0-input-k-number" - }, - { - "label": "Auto Summary Template", - "name": "autoSummaryTemplate", - "type": "string", - "default": "This is the summary of the following conversation:\n{summary}", "additionalParams": true, - "id": "ZepMemory_0-input-autoSummaryTemplate-string" + "id": "ZepMemory_0-input-k-number" }, { "label": "AI Prefix", @@ -306,10 +292,8 @@ "inputAnchors": [], "inputs": { "baseURL": "http://127.0.0.1:8000", - "autoSummary": true, "sessionId": "", "k": "10", - "autoSummaryTemplate": "This is the summary of the following conversation:\n{summary}", "aiPrefix": "ai", "humanPrefix": "human", "memoryKey": "chat_history", diff --git a/packages/server/marketplaces/chatflows/Query Engine.json b/packages/server/marketplaces/chatflows/Query Engine.json new file mode 100644 index 00000000..921ff1d6 --- /dev/null +++ b/packages/server/marketplaces/chatflows/Query Engine.json @@ -0,0 +1,509 @@ +{ + "description": "Stateless query engine designed to answer question over your data using LlamaIndex", + "badge": "NEW", + "nodes": [ + { + "width": 300, + "height": 382, + "id": "queryEngine_0", + "position": { + "x": 1407.9610494306783, + "y": 241.12144405808692 + }, + "type": "customNode", + "data": { + "id": "queryEngine_0", + "label": "Query Engine", + "version": 1, + "name": "queryEngine", + "type": "QueryEngine", + "baseClasses": ["QueryEngine"], + "tags": ["LlamaIndex"], + "category": "Engine", + "description": "Simple query engine built to answer question over your data, without memory", + "inputParams": [ + { + "label": "Return Source Documents", + "name": "returnSourceDocuments", + "type": "boolean", + "optional": true, + "id": "queryEngine_0-input-returnSourceDocuments-boolean" + } + ], + "inputAnchors": [ + { + "label": "Vector Store Retriever", + "name": "vectorStoreRetriever", + "type": "VectorIndexRetriever", + "id": "queryEngine_0-input-vectorStoreRetriever-VectorIndexRetriever" + }, + { + "label": "Response Synthesizer", + "name": "responseSynthesizer", + "type": "ResponseSynthesizer", + "description": "ResponseSynthesizer is responsible for sending the query, nodes, and prompt templates to the LLM to generate a response. See more", + "optional": true, + "id": "queryEngine_0-input-responseSynthesizer-ResponseSynthesizer" + } + ], + "inputs": { + "vectorStoreRetriever": "{{pineconeLlamaIndex_0.data.instance}}", + "responseSynthesizer": "{{compactrefineLlamaIndex_0.data.instance}}", + "returnSourceDocuments": true + }, + "outputAnchors": [ + { + "id": "queryEngine_0-output-queryEngine-QueryEngine", + "name": "queryEngine", + "label": "QueryEngine", + "type": "QueryEngine" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 1407.9610494306783, + "y": 241.12144405808692 + }, + "dragging": false + }, + { + "width": 300, + "height": 585, + "id": "pineconeLlamaIndex_0", + "position": { + "x": 977.3886641397302, + "y": -261.2253031641797 + }, + "type": "customNode", + "data": { + "id": "pineconeLlamaIndex_0", + "label": "Pinecone", + "version": 1, + "name": "pineconeLlamaIndex", + "type": "Pinecone", + "baseClasses": ["Pinecone", "VectorIndexRetriever"], + "tags": ["LlamaIndex"], + "category": "Vector Stores", + "description": "Upsert embedded data and perform similarity search upon query using Pinecone, a leading fully managed hosted vector database", + "inputParams": [ + { + "label": "Connect Credential", + "name": "credential", + "type": "credential", + "credentialNames": ["pineconeApi"], + "id": "pineconeLlamaIndex_0-input-credential-credential" + }, + { + "label": "Pinecone Index", + "name": "pineconeIndex", + "type": "string", + "id": "pineconeLlamaIndex_0-input-pineconeIndex-string" + }, + { + "label": "Pinecone Namespace", + "name": "pineconeNamespace", + "type": "string", + "placeholder": "my-first-namespace", + "additionalParams": true, + "optional": true, + "id": "pineconeLlamaIndex_0-input-pineconeNamespace-string" + }, + { + "label": "Pinecone Metadata Filter", + "name": "pineconeMetadataFilter", + "type": "json", + "optional": true, + "additionalParams": true, + "id": "pineconeLlamaIndex_0-input-pineconeMetadataFilter-json" + }, + { + "label": "Top K", + "name": "topK", + "description": "Number of top results to fetch. 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Variables must be {context} and {query}", + "optional": true, + "id": "compactrefineLlamaIndex_0-input-textQAPrompt-string" + } + ], + "inputAnchors": [], + "inputs": { + "refinePrompt": "The original query is as follows: {query}\nWe have provided an existing answer: {existingAnswer}\nWe have the opportunity to refine the existing answer (only if needed) with some more context below.\n------------\n{context}\n------------\nGiven the new context, refine the original answer to better answer the query. 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"openAIEmbedding_LlamaIndex_0-openAIEmbedding_LlamaIndex_0-output-openAIEmbedding_LlamaIndex-OpenAIEmbedding|BaseEmbedding_LlamaIndex|BaseEmbedding-pineconeLlamaIndex_0-pineconeLlamaIndex_0-input-embeddings-BaseEmbedding_LlamaIndex", + "data": { + "label": "" + } + }, + { + "source": "compactrefineLlamaIndex_0", + "sourceHandle": "compactrefineLlamaIndex_0-output-compactrefineLlamaIndex-CompactRefine|ResponseSynthesizer", + "target": "queryEngine_0", + "targetHandle": "queryEngine_0-input-responseSynthesizer-ResponseSynthesizer", + "type": "buttonedge", + "id": "compactrefineLlamaIndex_0-compactrefineLlamaIndex_0-output-compactrefineLlamaIndex-CompactRefine|ResponseSynthesizer-queryEngine_0-queryEngine_0-input-responseSynthesizer-ResponseSynthesizer", + "data": { + "label": "" + } + }, + { + "source": "chatAnthropic_LlamaIndex_0", + "sourceHandle": "chatAnthropic_LlamaIndex_0-output-chatAnthropic_LlamaIndex-ChatAnthropic|BaseChatModel_LlamaIndex", + "target": "pineconeLlamaIndex_0", + "targetHandle": "pineconeLlamaIndex_0-input-model-BaseChatModel_LlamaIndex", + "type": "buttonedge", + "id": "chatAnthropic_LlamaIndex_0-chatAnthropic_LlamaIndex_0-output-chatAnthropic_LlamaIndex-ChatAnthropic|BaseChatModel_LlamaIndex-pineconeLlamaIndex_0-pineconeLlamaIndex_0-input-model-BaseChatModel_LlamaIndex", + "data": { + "label": "" + } + } + ] +} diff --git a/packages/server/marketplaces/chatflows/Simple Chat Engine.json b/packages/server/marketplaces/chatflows/Simple Chat Engine.json new file mode 100644 index 00000000..b3854a51 --- /dev/null +++ b/packages/server/marketplaces/chatflows/Simple Chat Engine.json @@ -0,0 +1,270 @@ +{ + "description": "Simple chat engine to handle back and forth conversations using LlamaIndex", + "badge": "NEW", + "nodes": [ + { + "width": 300, + "height": 462, + "id": "simpleChatEngine_0", + "position": { + "x": 1210.127368000538, + "y": 324.98110560103896 + }, + "type": "customNode", + "data": { + "id": "simpleChatEngine_0", + "label": "Simple Chat Engine", + "version": 1, + "name": "simpleChatEngine", + "type": "SimpleChatEngine", + "baseClasses": ["SimpleChatEngine"], + "tags": ["LlamaIndex"], + "category": "Engine", + "description": "Simple engine to handle back and forth conversations", + "inputParams": [ + { + "label": "System Message", + "name": "systemMessagePrompt", + "type": "string", + "rows": 4, + "optional": true, + "placeholder": "You are a helpful assistant", + "id": "simpleChatEngine_0-input-systemMessagePrompt-string" + } + ], + "inputAnchors": [ + { + "label": "Chat Model", + "name": "model", + "type": "BaseChatModel_LlamaIndex", + "id": "simpleChatEngine_0-input-model-BaseChatModel_LlamaIndex" + }, + { + "label": "Memory", + "name": "memory", + "type": "BaseChatMemory", + "id": "simpleChatEngine_0-input-memory-BaseChatMemory" + } + ], + "inputs": { + "model": "{{azureChatOpenAI_LlamaIndex_0.data.instance}}", + "memory": "{{bufferMemory_0.data.instance}}", + "systemMessagePrompt": "You are a helpful assistant." + }, + "outputAnchors": [ + { + "id": "simpleChatEngine_0-output-simpleChatEngine-SimpleChatEngine", + "name": "simpleChatEngine", + "label": "SimpleChatEngine", + "type": "SimpleChatEngine" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "dragging": false, + "positionAbsolute": { + "x": 1210.127368000538, + "y": 324.98110560103896 + } + }, + { + "width": 300, + "height": 376, + "id": "bufferMemory_0", + "position": { + "x": 393.9823478014782, + "y": 415.7414943210391 + }, + "type": "customNode", + "data": { + "id": "bufferMemory_0", + "label": "Buffer Memory", + "version": 1, + "name": "bufferMemory", + "type": "BufferMemory", + "baseClasses": ["BufferMemory", "BaseChatMemory", "BaseMemory"], + "category": "Memory", + "description": "Remembers previous conversational back and forths directly", + "inputParams": [ + { + "label": "Memory Key", + "name": "memoryKey", + "type": "string", + "default": "chat_history", + "id": "bufferMemory_0-input-memoryKey-string" + }, + { + "label": "Input Key", + "name": "inputKey", + "type": "string", + "default": "input", + "id": "bufferMemory_0-input-inputKey-string" + } + ], + "inputAnchors": [], + "inputs": { + "memoryKey": "chat_history", + "inputKey": "input" + }, + "outputAnchors": [ + { + "id": "bufferMemory_0-output-bufferMemory-BufferMemory|BaseChatMemory|BaseMemory", + "name": "bufferMemory", + "label": "BufferMemory", + "type": "BufferMemory | BaseChatMemory | BaseMemory" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 393.9823478014782, + "y": 415.7414943210391 + }, + "dragging": false + }, + { + "width": 300, + "height": 529, + "id": "azureChatOpenAI_LlamaIndex_0", + "position": { + "x": 746.5530862509605, + "y": -54.107978373323306 + }, + "type": "customNode", + "data": { + "id": "azureChatOpenAI_LlamaIndex_0", + "label": "AzureChatOpenAI", + "version": 1, + "name": "azureChatOpenAI_LlamaIndex", + "type": "AzureChatOpenAI", + "baseClasses": ["AzureChatOpenAI", "BaseChatModel_LlamaIndex"], + "tags": ["LlamaIndex"], + "category": "Chat Models", + "description": "Wrapper around Azure OpenAI Chat LLM with LlamaIndex implementation", + "inputParams": [ + { + "label": "Connect Credential", + "name": "credential", + "type": "credential", + "credentialNames": ["azureOpenAIApi"], + "id": "azureChatOpenAI_LlamaIndex_0-input-credential-credential" + }, + { + "label": "Model Name", + "name": "modelName", + "type": "options", + "options": [ + { + "label": "gpt-4", + "name": "gpt-4" + }, + { + "label": "gpt-4-32k", + "name": "gpt-4-32k" + }, + { + "label": "gpt-3.5-turbo", + "name": "gpt-3.5-turbo" + }, + { + "label": "gpt-3.5-turbo-16k", + "name": "gpt-3.5-turbo-16k" + } + ], + "default": "gpt-3.5-turbo-16k", + "optional": true, + "id": "azureChatOpenAI_LlamaIndex_0-input-modelName-options" + }, + { + "label": "Temperature", + "name": "temperature", + "type": "number", + "step": 0.1, + "default": 0.9, + "optional": true, + "id": "azureChatOpenAI_LlamaIndex_0-input-temperature-number" + }, + { + "label": "Max Tokens", + "name": "maxTokens", + "type": "number", + "step": 1, + "optional": true, + "additionalParams": true, + "id": "azureChatOpenAI_LlamaIndex_0-input-maxTokens-number" + }, + { + "label": "Top Probability", + "name": "topP", + "type": "number", + "step": 0.1, + "optional": true, + "additionalParams": true, + "id": "azureChatOpenAI_LlamaIndex_0-input-topP-number" + }, + { + "label": "Timeout", + "name": "timeout", + "type": "number", + "step": 1, + "optional": true, + "additionalParams": true, + "id": "azureChatOpenAI_LlamaIndex_0-input-timeout-number" + } + ], + "inputAnchors": [], + "inputs": { + "modelName": "gpt-3.5-turbo-16k", + "temperature": 0.9, + "maxTokens": "", + "topP": "", + "timeout": "" + }, + "outputAnchors": [ + { + "id": "azureChatOpenAI_LlamaIndex_0-output-azureChatOpenAI_LlamaIndex-AzureChatOpenAI|BaseChatModel_LlamaIndex", + "name": "azureChatOpenAI_LlamaIndex", + "label": "AzureChatOpenAI", + "type": "AzureChatOpenAI | BaseChatModel_LlamaIndex" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 746.5530862509605, + "y": -54.107978373323306 + }, + "dragging": false + } + ], + "edges": [ + { + "source": "bufferMemory_0", + "sourceHandle": "bufferMemory_0-output-bufferMemory-BufferMemory|BaseChatMemory|BaseMemory", + "target": "simpleChatEngine_0", + "targetHandle": "simpleChatEngine_0-input-memory-BaseChatMemory", + "type": "buttonedge", + "id": "bufferMemory_0-bufferMemory_0-output-bufferMemory-BufferMemory|BaseChatMemory|BaseMemory-simpleChatEngine_0-simpleChatEngine_0-input-memory-BaseChatMemory", + "data": { + "label": "" + } + }, + { + "source": "azureChatOpenAI_LlamaIndex_0", + "sourceHandle": "azureChatOpenAI_LlamaIndex_0-output-azureChatOpenAI_LlamaIndex-AzureChatOpenAI|BaseChatModel_LlamaIndex", + "target": "simpleChatEngine_0", + "targetHandle": "simpleChatEngine_0-input-model-BaseChatModel_LlamaIndex", + "type": "buttonedge", + "id": "azureChatOpenAI_LlamaIndex_0-azureChatOpenAI_LlamaIndex_0-output-azureChatOpenAI_LlamaIndex-AzureChatOpenAI|BaseChatModel_LlamaIndex-simpleChatEngine_0-simpleChatEngine_0-input-model-BaseChatModel_LlamaIndex", + "data": { + "label": "" + } + } + ] +} diff --git a/packages/server/marketplaces/chatflows/WebPage QnA.json b/packages/server/marketplaces/chatflows/WebPage QnA.json index 9b1119b9..be077f97 100644 --- a/packages/server/marketplaces/chatflows/WebPage QnA.json +++ b/packages/server/marketplaces/chatflows/WebPage QnA.json @@ -589,7 +589,7 @@ "label": "Session Id", "name": "sessionId", "type": "string", - "description": "If not specified, the first CHAT_MESSAGE_ID will be used as sessionId", + "description": "If not specified, a random id will be used. Learn more", "default": "", "additionalParams": true, "optional": true, diff --git a/packages/server/src/index.ts b/packages/server/src/index.ts index d87d2c0a..78cc4260 100644 --- a/packages/server/src/index.ts +++ b/packages/server/src/index.ts @@ -37,13 +37,12 @@ import { databaseEntities, transformToCredentialEntity, decryptCredentialData, - clearAllSessionMemory, replaceInputsWithConfig, getEncryptionKey, - checkMemorySessionId, - clearSessionMemoryFromViewMessageDialog, + replaceMemorySessionId, getUserHome, - replaceChatHistory + replaceChatHistory, + clearSessionMemory } from './utils' import { cloneDeep, omit, uniqWith, isEqual } from 'lodash' import { getDataSource } from './DataSource' @@ -387,7 +386,12 @@ export class App { const endingNodeData = nodes.find((nd) => nd.id === endingNodeId)?.data if (!endingNodeData) return res.status(500).send(`Ending node ${endingNodeId} data not found`) - if (endingNodeData && endingNodeData.category !== 'Chains' && endingNodeData.category !== 'Agents') { + if ( + endingNodeData && + endingNodeData.category !== 'Chains' && + endingNodeData.category !== 'Agents' && + endingNodeData.category !== 'Engine' + ) { return res.status(500).send(`Ending node must be either a Chain or Agent`) } @@ -472,18 +476,15 @@ export class App { const parsedFlowData: IReactFlowObject = JSON.parse(flowData) const nodes = parsedFlowData.nodes - if (isClearFromViewMessageDialog) { - await clearSessionMemoryFromViewMessageDialog( - nodes, - this.nodesPool.componentNodes, - chatId, - this.AppDataSource, - sessionId, - memoryType - ) - } else { - await clearAllSessionMemory(nodes, this.nodesPool.componentNodes, chatId, this.AppDataSource, sessionId) - } + await clearSessionMemory( + nodes, + this.nodesPool.componentNodes, + chatId, + this.AppDataSource, + sessionId, + memoryType, + isClearFromViewMessageDialog + ) const deleteOptions: FindOptionsWhere = { chatflowid, chatId } if (memoryType) deleteOptions.memoryType = memoryType @@ -1377,7 +1378,13 @@ export class App { const endingNodeData = nodes.find((nd) => nd.id === endingNodeId)?.data if (!endingNodeData) return res.status(500).send(`Ending node ${endingNodeId} data not found`) - if (endingNodeData && endingNodeData.category !== 'Chains' && endingNodeData.category !== 'Agents' && !isUpsert) { + if ( + endingNodeData && + endingNodeData.category !== 'Chains' && + endingNodeData.category !== 'Agents' && + endingNodeData.category !== 'Engine' && + !isUpsert + ) { return res.status(500).send(`Ending node must be either a Chain or Agent`) } @@ -1396,7 +1403,9 @@ export class App { isStreamValid = isFlowValidForStream(nodes, endingNodeData) - let chatHistory: IMessage[] | string = incomingInput.history + let chatHistory: IMessage[] = incomingInput.history + + // If chatHistory is empty, and sessionId/chatId is present, replace it if ( endingNodeData.inputs?.memory && !incomingInput.history && @@ -1437,8 +1446,10 @@ export class App { const nodeToExecute = reactFlowNodes.find((node: IReactFlowNode) => node.id === endingNodeId) if (!nodeToExecute) return res.status(404).send(`Node ${endingNodeId} not found`) - if (incomingInput.overrideConfig) + if (incomingInput.overrideConfig) { nodeToExecute.data = replaceInputsWithConfig(nodeToExecute.data, incomingInput.overrideConfig) + } + const reactFlowNodeData: INodeData = resolveVariables( nodeToExecute.data, reactFlowNodes, @@ -1458,19 +1469,11 @@ export class App { logger.debug(`[server]: Running ${nodeToExecuteData.label} (${nodeToExecuteData.id})`) let sessionId = undefined - if (nodeToExecuteData.instance) sessionId = checkMemorySessionId(nodeToExecuteData.instance, chatId) - - const memoryNode = this.findMemoryLabel(nodes, edges) - const memoryType = memoryNode?.data.label - - let chatHistory: IMessage[] | string = incomingInput.history - if (memoryNode && !incomingInput.history && (incomingInput.chatId || incomingInput.overrideConfig?.sessionId)) { - chatHistory = await replaceChatHistory(memoryNode, incomingInput, this.AppDataSource, databaseEntities, logger) - } + if (nodeToExecuteData.instance) sessionId = replaceMemorySessionId(nodeToExecuteData.instance, chatId) let result = isStreamValid ? await nodeInstance.run(nodeToExecuteData, incomingInput.question, { - chatHistory, + chatHistory: incomingInput.history, socketIO, socketIOClientId: incomingInput.socketIOClientId, logger, @@ -1480,7 +1483,7 @@ export class App { chatId }) : await nodeInstance.run(nodeToExecuteData, incomingInput.question, { - chatHistory, + chatHistory: incomingInput.history, logger, appDataSource: this.AppDataSource, databaseEntities, @@ -1495,6 +1498,9 @@ export class App { sessionId = result.assistant.threadId } + const memoryNode = this.findMemoryLabel(nodes, edges) + const memoryType = memoryNode?.data.label + const userMessage: Omit = { role: 'userMessage', content: incomingInput.question, diff --git a/packages/server/src/utils/index.ts b/packages/server/src/utils/index.ts index 0b1e62d2..0b37b608 100644 --- a/packages/server/src/utils/index.ts +++ b/packages/server/src/utils/index.ts @@ -217,7 +217,7 @@ export const buildLangchain = async ( depthQueue: IDepthQueue, componentNodes: IComponentNodes, question: string, - chatHistory: IMessage[] | string, + chatHistory: IMessage[], chatId: string, chatflowid: string, appDataSource: DataSource, @@ -324,22 +324,30 @@ export const buildLangchain = async ( } /** - * Clear all session memories on the canvas + * Clear session memories * @param {IReactFlowNode[]} reactFlowNodes * @param {IComponentNodes} componentNodes * @param {string} chatId * @param {DataSource} appDataSource * @param {string} sessionId + * @param {string} memoryType + * @param {string} isClearFromViewMessageDialog */ -export const clearAllSessionMemory = async ( +export const clearSessionMemory = async ( reactFlowNodes: IReactFlowNode[], componentNodes: IComponentNodes, chatId: string, appDataSource: DataSource, - sessionId?: string + sessionId?: string, + memoryType?: string, + isClearFromViewMessageDialog?: string ) => { for (const node of reactFlowNodes) { if (node.data.category !== 'Memory' && node.data.type !== 'OpenAIAssistant') continue + + // Only clear specific session memory from View Message Dialog UI + if (isClearFromViewMessageDialog && memoryType && node.data.label !== memoryType) continue + const nodeInstanceFilePath = componentNodes[node.data.name].filePath as string const nodeModule = await import(nodeInstanceFilePath) const newNodeInstance = new nodeModule.nodeClass() @@ -348,42 +356,10 @@ export const clearAllSessionMemory = async ( node.data.inputs.sessionId = sessionId } - if (newNodeInstance.memoryMethods && newNodeInstance.memoryMethods.clearSessionMemory) { - await newNodeInstance.memoryMethods.clearSessionMemory(node.data, { chatId, appDataSource, databaseEntities, logger }) - } - } -} + const initializedInstance = await newNodeInstance.init(node.data, '', { chatId, appDataSource, databaseEntities, logger }) -/** - * Clear specific session memory from View Message Dialog UI - * @param {IReactFlowNode[]} reactFlowNodes - * @param {IComponentNodes} componentNodes - * @param {string} chatId - * @param {DataSource} appDataSource - * @param {string} sessionId - * @param {string} memoryType - */ -export const clearSessionMemoryFromViewMessageDialog = async ( - reactFlowNodes: IReactFlowNode[], - componentNodes: IComponentNodes, - chatId: string, - appDataSource: DataSource, - sessionId?: string, - memoryType?: string -) => { - if (!sessionId) return - for (const node of reactFlowNodes) { - if (node.data.category !== 'Memory' && node.data.type !== 'OpenAIAssistant') continue - if (memoryType && node.data.label !== memoryType) continue - const nodeInstanceFilePath = componentNodes[node.data.name].filePath as string - const nodeModule = await import(nodeInstanceFilePath) - const newNodeInstance = new nodeModule.nodeClass() - - if (sessionId && node.data.inputs) node.data.inputs.sessionId = sessionId - - if (newNodeInstance.memoryMethods && newNodeInstance.memoryMethods.clearSessionMemory) { - await newNodeInstance.memoryMethods.clearSessionMemory(node.data, { chatId, appDataSource, databaseEntities, logger }) - return + if (initializedInstance.clearChatMessages) { + await initializedInstance.clearChatMessages() } } } @@ -400,7 +376,7 @@ export const getVariableValue = ( paramValue: string, reactFlowNodes: IReactFlowNode[], question: string, - chatHistory: IMessage[] | string, + chatHistory: IMessage[], isAcceptVariable = false ) => { let returnVal = paramValue @@ -433,10 +409,7 @@ export const getVariableValue = ( } if (isAcceptVariable && variableFullPath === CHAT_HISTORY_VAR_PREFIX) { - variableDict[`{{${variableFullPath}}}`] = handleEscapeCharacters( - typeof chatHistory === 'string' ? chatHistory : convertChatHistoryToText(chatHistory), - false - ) + variableDict[`{{${variableFullPath}}}`] = handleEscapeCharacters(convertChatHistoryToText(chatHistory), false) } // Split by first occurrence of '.' to get just nodeId @@ -479,7 +452,7 @@ export const resolveVariables = ( reactFlowNodeData: INodeData, reactFlowNodes: IReactFlowNode[], question: string, - chatHistory: IMessage[] | string + chatHistory: IMessage[] ): INodeData => { let flowNodeData = cloneDeep(reactFlowNodeData) const types = 'inputs' @@ -558,7 +531,7 @@ export const isStartNodeDependOnInput = (startingNodes: IReactFlowNode[], nodes: if (inputVariables.length > 0) return true } } - const whitelistNodeNames = ['vectorStoreToDocument', 'autoGPT'] + const whitelistNodeNames = ['vectorStoreToDocument', 'autoGPT', 'chatPromptTemplate', 'promptTemplate'] //If these nodes are found, chatflow cannot be reused for (const node of nodes) { if (whitelistNodeNames.includes(node.data.name)) return true } @@ -706,7 +679,15 @@ export const findAvailableConfigs = (reactFlowNodes: IReactFlowNode[], component */ export const isFlowValidForStream = (reactFlowNodes: IReactFlowNode[], endingNodeData: INodeData) => { const streamAvailableLLMs = { - 'Chat Models': ['azureChatOpenAI', 'chatOpenAI', 'chatAnthropic', 'chatOllama', 'awsChatBedrock'], + 'Chat Models': [ + 'azureChatOpenAI', + 'chatOpenAI', + 'chatOpenAI_LlamaIndex', + 'chatAnthropic', + 'chatAnthropic_LlamaIndex', + 'chatOllama', + 'awsChatBedrock' + ], LLMs: ['azureOpenAI', 'openAI', 'ollama'] } @@ -729,6 +710,9 @@ export const isFlowValidForStream = (reactFlowNodes: IReactFlowNode[], endingNod // Agent that are available to stream const whitelistAgents = ['openAIFunctionAgent', 'csvAgent', 'airtableAgent', 'conversationalRetrievalAgent'] isValidChainOrAgent = whitelistAgents.includes(endingNodeData.name) + } else if (endingNodeData.category === 'Engine') { + const whitelistEngine = ['contextChatEngine', 'simpleChatEngine'] + isValidChainOrAgent = whitelistEngine.includes(endingNodeData.name) } // If no output parser, flow is available to stream @@ -866,7 +850,7 @@ export const redactCredentialWithPasswordType = ( * @param {any} instance * @param {string} chatId */ -export const checkMemorySessionId = (instance: any, chatId: string): string | undefined => { +export const replaceMemorySessionId = (instance: any, chatId: string): string | undefined => { if (instance.memory && instance.memory.isSessionIdUsingChatMessageId && chatId) { instance.memory.sessionId = chatId instance.memory.chatHistory.sessionId = chatId @@ -893,7 +877,7 @@ export const replaceChatHistory = async ( appDataSource: DataSource, databaseEntities: IDatabaseEntity, logger: any -): Promise => { +): Promise => { const nodeInstanceFilePath = memoryNode.data.filePath as string const nodeModule = await import(nodeInstanceFilePath) const newNodeInstance = new nodeModule.nodeClass() @@ -902,14 +886,12 @@ export const replaceChatHistory = async ( memoryNode.data.inputs.sessionId = incomingInput.overrideConfig.sessionId } - if (newNodeInstance.memoryMethods && newNodeInstance.memoryMethods.getChatMessages) { - return await newNodeInstance.memoryMethods.getChatMessages(memoryNode.data, { - chatId: incomingInput.chatId, - appDataSource, - databaseEntities, - logger - }) - } + const initializedInstance = await newNodeInstance.init(memoryNode.data, '', { + chatId: incomingInput.chatId, + appDataSource, + databaseEntities, + logger + }) - return '' + return await initializedInstance.getChatMessages() } diff --git a/packages/ui/src/assets/images/llamaindex.png b/packages/ui/src/assets/images/llamaindex.png new file mode 100644 index 00000000..139c33eb Binary files /dev/null and b/packages/ui/src/assets/images/llamaindex.png differ diff --git a/packages/ui/src/ui-component/dialog/NodeInfoDialog.js b/packages/ui/src/ui-component/dialog/NodeInfoDialog.js index 6f3bec5d..a5dbd411 100644 --- a/packages/ui/src/ui-component/dialog/NodeInfoDialog.js +++ b/packages/ui/src/ui-component/dialog/NodeInfoDialog.js @@ -132,6 +132,35 @@ const NodeInfoDialog = ({ show, dialogProps, onCancel }) => { )} + {dialogProps.data.tags && + dialogProps.data.tags.length && + dialogProps.data.tags.map((tag, index) => ( +
+ + {tag.toLowerCase()} + +
+ ))} diff --git a/packages/ui/src/utils/genericHelper.js b/packages/ui/src/utils/genericHelper.js index b34d6c72..69491fbc 100644 --- a/packages/ui/src/utils/genericHelper.js +++ b/packages/ui/src/utils/genericHelper.js @@ -286,6 +286,7 @@ export const generateExportFlowData = (flowData) => { name: node.data.name, type: node.data.type, baseClasses: node.data.baseClasses, + tags: node.data.tags, category: node.data.category, description: node.data.description, inputParams: node.data.inputParams, diff --git a/packages/ui/src/views/canvas/AddNodes.js b/packages/ui/src/views/canvas/AddNodes.js index 7bf3e7ff..ea813df5 100644 --- a/packages/ui/src/views/canvas/AddNodes.js +++ b/packages/ui/src/views/canvas/AddNodes.js @@ -22,7 +22,9 @@ import { Popper, Stack, Typography, - Chip + Chip, + Tab, + Tabs } from '@mui/material' import ExpandMoreIcon from '@mui/icons-material/ExpandMore' @@ -36,12 +38,20 @@ import { StyledFab } from 'ui-component/button/StyledFab' // icons import { IconPlus, IconSearch, IconMinus, IconX } from '@tabler/icons' +import LlamaindexPNG from 'assets/images/llamaindex.png' +import LangChainPNG from 'assets/images/langchain.png' // const import { baseURL } from 'store/constant' import { SET_COMPONENT_NODES } from 'store/actions' // ==============================|| ADD NODES||============================== // +function a11yProps(index) { + return { + id: `attachment-tab-${index}`, + 'aria-controls': `attachment-tabpanel-${index}` + } +} const AddNodes = ({ nodesData, node }) => { const theme = useTheme() @@ -52,6 +62,7 @@ const AddNodes = ({ nodesData, node }) => { const [nodes, setNodes] = useState({}) const [open, setOpen] = useState(false) const [categoryExpanded, setCategoryExpanded] = useState({}) + const [tabValue, setTabValue] = useState(0) const anchorRef = useRef(null) const prevOpen = useRef(open) @@ -86,6 +97,11 @@ const AddNodes = ({ nodesData, node }) => { } } + const handleTabChange = (event, newValue) => { + setTabValue(newValue) + filterSearch(searchValue, newValue) + } + const getSearchedNodes = (value) => { const passed = nodesData.filter((nd) => { const passesQuery = nd.name.toLowerCase().includes(value.toLowerCase()) @@ -95,23 +111,34 @@ const AddNodes = ({ nodesData, node }) => { return passed } - const filterSearch = (value) => { + const filterSearch = (value, newTabValue) => { setSearchValue(value) setTimeout(() => { if (value) { const returnData = getSearchedNodes(value) - groupByCategory(returnData, true) + groupByCategory(returnData, newTabValue ?? tabValue, true) scrollTop() } else if (value === '') { - groupByCategory(nodesData) + groupByCategory(nodesData, newTabValue ?? tabValue) scrollTop() } }, 500) } - const groupByCategory = (nodes, isFilter) => { + const groupByTags = (nodes, newTabValue = 0) => { + const langchainNodes = nodes.filter((nd) => !nd.tags) + const llmaindexNodes = nodes.filter((nd) => nd.tags && nd.tags.includes('LlamaIndex')) + if (newTabValue === 0) { + return langchainNodes + } else { + return llmaindexNodes + } + } + + const groupByCategory = (nodes, newTabValue, isFilter) => { + const taggedNodes = groupByTags(nodes, newTabValue) const accordianCategories = {} - const result = nodes.reduce(function (r, a) { + const result = taggedNodes.reduce(function (r, a) { r[a.category] = r[a.category] || [] r[a.category].push(a) accordianCategories[a.category] = isFilter ? true : false @@ -244,13 +271,61 @@ const AddNodes = ({ nodesData, node }) => { 'aria-label': 'weight' }} /> + + {['LangChain', 'LlamaIndex'].map((item, index) => ( + + {item} + + } + iconPosition='start' + key={index} + label={ + item === 'LlamaIndex' ? ( + <> +

{item}

+   + + + ) : ( +

{item}

+ ) + } + {...a11yProps(index)} + > + ))} + { ps.current = el }} - style={{ height: '100%', maxHeight: 'calc(100vh - 320px)', overflowX: 'hidden' }} + style={{ height: '100%', maxHeight: 'calc(100vh - 380px)', overflowX: 'hidden' }} > ({ background: theme.palette.card.main, @@ -179,9 +180,25 @@ const CanvasNode = ({ data }) => { {data.label} +
+ {data.tags && data.tags.includes('LlamaIndex') && ( + <> +
+ LlamaIndex +
+ + )} {warningMessage && ( <> -
{warningMessage}} placement='top'> diff --git a/packages/ui/src/views/marketplaces/MarketplaceCanvasNode.js b/packages/ui/src/views/marketplaces/MarketplaceCanvasNode.js index 8ec5ada3..44cb75e8 100644 --- a/packages/ui/src/views/marketplaces/MarketplaceCanvasNode.js +++ b/packages/ui/src/views/marketplaces/MarketplaceCanvasNode.js @@ -13,6 +13,7 @@ import AdditionalParamsDialog from 'ui-component/dialog/AdditionalParamsDialog' // const import { baseURL } from 'store/constant' +import LlamaindexPNG from 'assets/images/llamaindex.png' const CardWrapper = styled(MainCard)(({ theme }) => ({ background: theme.palette.card.main, @@ -87,6 +88,23 @@ const MarketplaceCanvasNode = ({ data }) => { {data.label} +
+ {data.tags && data.tags.includes('LlamaIndex') && ( + <> +
+ LlamaIndex +
+ + )} {(data.inputAnchors.length > 0 || data.inputParams.length > 0) && ( <>