add claude 3 and xml agent

packages/components/nodes/agents/XMLAgent/XMLAgent.ts

@@ -0,0 +1,203 @@
+import { flatten } from 'lodash'
+import { ChainValues } from '@langchain/core/utils/types'
+import { AgentStep } from '@langchain/core/agents'
+import { RunnableSequence } from '@langchain/core/runnables'
+import { ChatOpenAI } from '@langchain/openai'
+import { Tool } from '@langchain/core/tools'
+import { ChatPromptTemplate, HumanMessagePromptTemplate, MessagesPlaceholder } from '@langchain/core/prompts'
+import { XMLAgentOutputParser } from 'langchain/agents/xml/output_parser'
+import { formatLogToMessage } from 'langchain/agents/format_scratchpad/log_to_message'
+import { getBaseClasses } from '../../../src/utils'
+import { FlowiseMemory, ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler'
+import { AgentExecutor } from '../../../src/agents'
+//import { AgentExecutor } from "langchain/agents";
+
+const defaultSystemMessage = `You are a helpful assistant. Help the user answer any questions.
+
+You have access to the following tools:
+
+{tools}
+
+In order to use a tool, you can use <tool></tool> and <tool_input></tool_input> tags. You will then get back a response in the form <observation></observation>
+For example, if you have a tool called 'search' that could run a google search, in order to search for the weather in SF you would respond:
+
+<tool>search</tool><tool_input>weather in SF</tool_input>
+<observation>64 degrees</observation>
+
+When you are done, respond with a final answer between <final_answer></final_answer>. For example:
+
+<final_answer>The weather in SF is 64 degrees</final_answer>
+
+Begin!
+
+Previous Conversation:
+{chat_history}
+
+Question: {input}
+{agent_scratchpad}`
+
+class XMLAgent_Agents implements INode {
+    label: string
+    name: string
+    version: number
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    inputs: INodeParams[]
+    sessionId?: string
+
+    constructor(fields?: { sessionId?: string }) {
+        this.label = 'XML Agent'
+        this.name = 'xmlAgent'
+        this.version = 1.0
+        this.type = 'XMLAgent'
+        this.category = 'Agents'
+        this.icon = 'xmlagent.svg'
+        this.description = `Agent that is designed for LLMs that are good for reasoning/writing XML (e.g: Anthropic Claude)`
+        this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)]
+        this.inputs = [
+            {
+                label: 'Tools',
+                name: 'tools',
+                type: 'Tool',
+                list: true
+            },
+            {
+                label: 'Memory',
+                name: 'memory',
+                type: 'BaseChatMemory'
+            },
+            {
+                label: 'Chat Model',
+                name: 'model',
+                type: 'BaseChatModel'
+            },
+            {
+                label: 'System Message',
+                name: 'systemMessage',
+                type: 'string',
+                warning: 'Prompt must include input variables: {tools}, {chat_history}, {input} and {agent_scratchpad}',
+                rows: 4,
+                default: defaultSystemMessage,
+                additionalParams: true
+            }
+        ]
+        this.sessionId = fields?.sessionId
+    }
+
+    async init(): Promise<any> {
+        return null
+    }
+
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | ICommonObject> {
+        const memory = nodeData.inputs?.memory as FlowiseMemory
+        const executor = await prepareAgent(nodeData, { sessionId: this.sessionId, chatId: options.chatId, input }, options.chatHistory)
+
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
+        const callbacks = await additionalCallbacks(nodeData, options)
+
+        let res: ChainValues = {}
+        let sourceDocuments: ICommonObject[] = []
+
+        if (options.socketIO && options.socketIOClientId) {
+            const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
+            res = await executor.invoke({ input }, { callbacks: [loggerHandler, handler, ...callbacks] })
+            if (res.sourceDocuments) {
+                options.socketIO.to(options.socketIOClientId).emit('sourceDocuments', flatten(res.sourceDocuments))
+                sourceDocuments = res.sourceDocuments
+            }
+        } else {
+            res = await executor.invoke({ input }, { callbacks: [loggerHandler, ...callbacks] })
+            if (res.sourceDocuments) {
+                sourceDocuments = res.sourceDocuments
+            }
+        }
+
+        await memory.addChatMessages(
+            [
+                {
+                    text: input,
+                    type: 'userMessage'
+                },
+                {
+                    text: res?.output,
+                    type: 'apiMessage'
+                }
+            ],
+            this.sessionId
+        )
+
+        return sourceDocuments.length ? { text: res?.output, sourceDocuments: flatten(sourceDocuments) } : res?.output
+    }
+}
+
+const prepareAgent = async (
+    nodeData: INodeData,
+    flowObj: { sessionId?: string; chatId?: string; input?: string },
+    chatHistory: IMessage[] = []
+) => {
+    const model = nodeData.inputs?.model as ChatOpenAI
+    const memory = nodeData.inputs?.memory as FlowiseMemory
+    const systemMessage = nodeData.inputs?.systemMessage as string
+    let tools = nodeData.inputs?.tools
+    tools = flatten(tools)
+    const inputKey = memory.inputKey ? memory.inputKey : 'input'
+    const memoryKey = memory.memoryKey ? memory.memoryKey : 'chat_history'
+
+    let promptMessage = systemMessage ? systemMessage : defaultSystemMessage
+    if (memory.memoryKey) promptMessage = promptMessage.replaceAll('{chat_history}', `{${memory.memoryKey}}`)
+    if (memory.inputKey) promptMessage = promptMessage.replaceAll('{input}', `{${memory.inputKey}}`)
+
+    const prompt = ChatPromptTemplate.fromMessages([
+        HumanMessagePromptTemplate.fromTemplate(promptMessage),
+        new MessagesPlaceholder('agent_scratchpad')
+    ])
+
+    const missingVariables = ['tools', 'agent_scratchpad'].filter((v) => !prompt.inputVariables.includes(v))
+
+    if (missingVariables.length > 0) {
+        throw new Error(`Provided prompt is missing required input variables: ${JSON.stringify(missingVariables)}`)
+    }
+
+    const llmWithStop = model.bind({ stop: ['</tool_input>', '</final_answer>'] })
+
+    const messages = (await memory.getChatMessages(flowObj.sessionId, false, chatHistory)) as IMessage[]
+    let chatHistoryMsgTxt = ''
+    for (const message of messages) {
+        if (message.type === 'apiMessage') {
+            chatHistoryMsgTxt += `\\nAI:${message.message}`
+        } else if (message.type === 'userMessage') {
+            chatHistoryMsgTxt += `\\nHuman:${message.message}`
+        }
+    }
+
+    const runnableAgent = RunnableSequence.from([
+        {
+            [inputKey]: (i: { input: string; tools: Tool[]; steps: AgentStep[] }) => i.input,
+            agent_scratchpad: (i: { input: string; tools: Tool[]; steps: AgentStep[] }) => formatLogToMessage(i.steps),
+            tools: (_: { input: string; tools: Tool[]; steps: AgentStep[] }) =>
+                tools.map((tool: Tool) => `${tool.name}: ${tool.description}`),
+            [memoryKey]: (_: { input: string; tools: Tool[]; steps: AgentStep[] }) => chatHistoryMsgTxt
+        },
+        prompt,
+        llmWithStop,
+        new XMLAgentOutputParser()
+    ])
+
+    const executor = AgentExecutor.fromAgentAndTools({
+        agent: runnableAgent,
+        tools,
+        sessionId: flowObj?.sessionId,
+        chatId: flowObj?.chatId,
+        input: flowObj?.input,
+        isXML: true,
+        verbose: process.env.DEBUG === 'true' ? true : false
+    })
+
+    return executor
+}
+
+module.exports = { nodeClass: XMLAgent_Agents }

packages/components/nodes/agents/XMLAgent/xmlagent.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-file-type-xml" width="24" height="24" viewBox="0 0 24 24" stroke-width="1.5" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><path stroke="none" d="M0 0h24v24H0z" fill="none"/><path d="M14 3v4a1 1 0 0 0 1 1h4" /><path d="M5 12v-7a2 2 0 0 1 2 -2h7l5 5v4" /><path d="M4 15l4 6" /><path d="M4 21l4 -6" /><path d="M19 15v6h3" /><path d="M11 21v-6l2.5 3l2.5 -3v6" /></svg>

packages/components/nodes/chatmodels/AWSBedrock/AWSChatBedrock.ts

@@ -95,6 +95,8 @@ class AWSChatBedrock_ChatModels implements INode {
                 name: 'model',
                 type: 'options',
                 options: [
+                    { label: 'anthropic.claude-3-sonnet', name: 'anthropic.claude-3-sonnet-20240229-v1:0' },
+                    { label: 'anthropic.claude-instant-v1', name: 'anthropic.claude-instant-v1' },
                     { label: 'anthropic.claude-instant-v1', name: 'anthropic.claude-instant-v1' },
                     { label: 'anthropic.claude-v1', name: 'anthropic.claude-v1' },
                     { label: 'anthropic.claude-v2', name: 'anthropic.claude-v2' },

packages/components/nodes/chatmodels/ChatAnthropic/ChatAnthropic.ts

@@ -43,6 +43,16 @@ class ChatAnthropic_ChatModels implements INode {
                 name: 'modelName',
                 type: 'options',
                 options: [
+                    {
+                        label: 'claude-3-opus',
+                        name: 'claude-3-opus-20240229',
+                        description: 'Most powerful model for highly complex tasks'
+                    },
+                    {
+                        label: 'claude-3-sonnet',
+                        name: 'claude-3-sonnet-20240229',
+                        description: 'Ideal balance of intelligence and speed for enterprise workloads'
+                    },
                     {
                         label: 'claude-2',
                         name: 'claude-2',

packages/components/src/agents.ts

@@ -257,6 +257,8 @@ export class AgentExecutor extends BaseChain<ChainValues, AgentExecutorOutput> {
 
     input?: string
 
+    isXML?: boolean
+
     /**
      * How to handle errors raised by the agent's output parser.
         Defaults to `False`, which raises the error.
@@ -277,7 +279,7 @@ export class AgentExecutor extends BaseChain<ChainValues, AgentExecutorOutput> {
         return this.agent.returnValues
     }
 
-    constructor(input: AgentExecutorInput & { sessionId?: string; chatId?: string; input?: string }) {
+    constructor(input: AgentExecutorInput & { sessionId?: string; chatId?: string; input?: string; isXML?: boolean }) {
         let agent: BaseSingleActionAgent | BaseMultiActionAgent
         if (Runnable.isRunnable(input.agent)) {
             agent = new RunnableAgent({ runnable: input.agent })
@@ -305,13 +307,17 @@ export class AgentExecutor extends BaseChain<ChainValues, AgentExecutorOutput> {
         this.sessionId = input.sessionId
         this.chatId = input.chatId
         this.input = input.input
+        this.isXML = input.isXML
     }
 
-    static fromAgentAndTools(fields: AgentExecutorInput & { sessionId?: string; chatId?: string; input?: string }): AgentExecutor {
+    static fromAgentAndTools(
+        fields: AgentExecutorInput & { sessionId?: string; chatId?: string; input?: string; isXML?: boolean }
+    ): AgentExecutor {
         const newInstance = new AgentExecutor(fields)
         if (fields.sessionId) newInstance.sessionId = fields.sessionId
         if (fields.chatId) newInstance.chatId = fields.chatId
         if (fields.input) newInstance.input = fields.input
+        if (fields.isXML) newInstance.isXML = fields.isXML
         return newInstance
     }
 
@@ -405,12 +411,16 @@ export class AgentExecutor extends BaseChain<ChainValues, AgentExecutorOutput> {
                          * - flowConfig?: { sessionId?: string, chatId?: string, input?: string }
                          */
                         observation = tool
-                            ? // @ts-ignore
-                              await tool.call(action.toolInput, runManager?.getChild(), undefined, {
+                            ? await (tool as any).call(
+                                  this.isXML && typeof action.toolInput === 'string' ? { input: action.toolInput } : action.toolInput,
+                                  runManager?.getChild(),
+                                  undefined,
+                                  {
                                       sessionId: this.sessionId,
                                       chatId: this.chatId,
                                       input: this.input
-                              })
+                                  }
+                              )
                             : `${action.tool} is not a valid tool, try another one.`
                     } catch (e) {
                         if (e instanceof ToolInputParsingException) {
@@ -526,12 +536,16 @@ export class AgentExecutor extends BaseChain<ChainValues, AgentExecutorOutput> {
                      * - tags?: string[]
                      * - flowConfig?: { sessionId?: string, chatId?: string, input?: string }
                      */
-                    // @ts-ignore
-                    observation = await tool.call(agentAction.toolInput, runManager?.getChild(), undefined, {
+                    observation = await (tool as any).call(
+                        this.isXML && typeof agentAction.toolInput === 'string' ? { input: agentAction.toolInput } : agentAction.toolInput,
+                        runManager?.getChild(),
+                        undefined,
+                        {
                             sessionId: this.sessionId,
                             chatId: this.chatId,
                             input: this.input
-                    })
+                        }
+                    )
                     if (observation?.includes(SOURCE_DOCUMENTS_PREFIX)) {
                         const observationArray = observation.split(SOURCE_DOCUMENTS_PREFIX)
                         observation = observationArray[0]

packages/server/marketplaces/chatflows/Claude LLM.json

@@ -179,6 +179,16 @@
                         "name": "modelName",
                         "type": "options",
                         "options": [
+                            {
+                                "label": "claude-3-opus",
+                                "name": "claude-3-opus-20240229",
+                                "description": "Most powerful model for highly complex tasks"
+                            },
+                            {
+                                "label": "claude-3-sonnet",
+                                "name": "claude-3-sonnet-20240229",
+                                "description": "Ideal balance of intelligence and speed for enterprise workloads"
+                            },
                             {
                                 "label": "claude-2",
                                 "name": "claude-2",