add conversational retrieval agent

packages/components/nodes/agents/ConversationalAgent/ConversationalAgent.ts

@@ -1,9 +1,8 @@
-import { ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { initializeAgentExecutorWithOptions, AgentExecutor, InitializeAgentExecutorOptions } from 'langchain/agents'
 import { Tool } from 'langchain/tools'
-import { BaseChatMemory, ChatMessageHistory } from 'langchain/memory'
-import { getBaseClasses } from '../../../src/utils'
-import { AIMessage, HumanMessage } from 'langchain/schema'
+import { BaseChatMemory } from 'langchain/memory'
+import { getBaseClasses, mapChatHistory } from '../../../src/utils'
 import { BaseLanguageModel } from 'langchain/base_language'
 import { flatten } from 'lodash'
 
@@ -93,19 +92,10 @@ class ConversationalAgent_Agents implements INode {
         const memory = nodeData.inputs?.memory as BaseChatMemory
 
         if (options && options.chatHistory) {
-            const chatHistory = []
-            const histories: IMessage[] = options.chatHistory
-
-            for (const message of histories) {
-                if (message.type === 'apiMessage') {
-                    chatHistory.push(new AIMessage(message.message))
-                } else if (message.type === 'userMessage') {
-                    chatHistory.push(new HumanMessage(message.message))
-                }
-            }
-            memory.chatHistory = new ChatMessageHistory(chatHistory)
+            memory.chatHistory = mapChatHistory(options)
             executor.memory = memory
         }
+
         const result = await executor.call({ input })
 
         return result?.output

packages/components/nodes/agents/ConversationalRetrievalAgent/ConversationalRetrievalAgent.ts

@@ -0,0 +1,100 @@
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { initializeAgentExecutorWithOptions, AgentExecutor } from 'langchain/agents'
+import { getBaseClasses, mapChatHistory } from '../../../src/utils'
+import { flatten } from 'lodash'
+import { BaseChatMemory } from 'langchain/memory'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
+
+class ConversationalRetrievalAgent_Agents implements INode {
+    label: string
+    name: string
+    version: number
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Conversational Retrieval Agent'
+        this.name = 'conversationalRetrievalAgent'
+        this.version = 1.0
+        this.type = 'AgentExecutor'
+        this.category = 'Agents'
+        this.icon = 'agent.svg'
+        this.description = `An agent optimized for retrieval during conversation, answering questions based on past dialogue, all using OpenAI's Function Calling`
+        this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)]
+        this.inputs = [
+            {
+                label: 'Allowed Tools',
+                name: 'tools',
+                type: 'Tool',
+                list: true
+            },
+            {
+                label: 'Memory',
+                name: 'memory',
+                type: 'BaseChatMemory'
+            },
+            {
+                label: 'OpenAI Chat Model',
+                name: 'model',
+                type: 'ChatOpenAI'
+            },
+            {
+                label: 'System Message',
+                name: 'systemMessage',
+                type: 'string',
+                rows: 4,
+                optional: true,
+                additionalParams: true
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData): Promise<any> {
+        const model = nodeData.inputs?.model
+        const memory = nodeData.inputs?.memory as BaseChatMemory
+        const systemMessage = nodeData.inputs?.systemMessage as string
+
+        let tools = nodeData.inputs?.tools
+        tools = flatten(tools)
+
+        const executor = await initializeAgentExecutorWithOptions(tools, model, {
+            agentType: 'openai-functions',
+            verbose: process.env.DEBUG === 'true' ? true : false,
+            agentArgs: {
+                prefix: systemMessage ?? `You are a helpful AI assistant.`
+            },
+            returnIntermediateSteps: true
+        })
+        executor.memory = memory
+        return executor
+    }
+
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+        const executor = nodeData.instance as AgentExecutor
+
+        if (options && options.chatHistory) {
+            if (executor.memory) {
+                ;(executor.memory as any).memoryKey = 'chat_history'
+                ;(executor.memory as any).outputKey = 'output'
+                ;(executor.memory as any).chatHistory = mapChatHistory(options)
+            }
+        }
+
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
+
+        if (options.socketIO && options.socketIOClientId) {
+            const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
+            const result = await executor.call({ input }, [loggerHandler, handler])
+            return result?.output
+        } else {
+            const result = await executor.call({ input }, [loggerHandler])
+            return result?.output
+        }
+    }
+}
+
+module.exports = { nodeClass: ConversationalRetrievalAgent_Agents }

packages/components/nodes/agents/ConversationalRetrievalAgent/agent.svg

@@ -0,0 +1,9 @@
+<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-robot" width="24" height="24" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round">
+   <path stroke="none" d="M0 0h24v24H0z" fill="none"></path>
+   <path d="M7 7h10a2 2 0 0 1 2 2v1l1 1v3l-1 1v3a2 2 0 0 1 -2 2h-10a2 2 0 0 1 -2 -2v-3l-1 -1v-3l1 -1v-1a2 2 0 0 1 2 -2z"></path>
+   <path d="M10 16h4"></path>
+   <circle cx="8.5" cy="11.5" r=".5" fill="currentColor"></circle>
+   <circle cx="15.5" cy="11.5" r=".5" fill="currentColor"></circle>
+   <path d="M9 7l-1 -4"></path>
+   <path d="M15 7l1 -4"></path>
+</svg>

packages/components/nodes/agents/OpenAIFunctionAgent/OpenAIFunctionAgent.ts

@@ -1,10 +1,9 @@
-import { ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { initializeAgentExecutorWithOptions, AgentExecutor } from 'langchain/agents'
-import { getBaseClasses } from '../../../src/utils'
+import { getBaseClasses, mapChatHistory } from '../../../src/utils'
 import { BaseLanguageModel } from 'langchain/base_language'
 import { flatten } from 'lodash'
-import { BaseChatMemory, ChatMessageHistory } from 'langchain/memory'
-import { AIMessage, HumanMessage } from 'langchain/schema'
+import { BaseChatMemory } from 'langchain/memory'
 import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
 
 class OpenAIFunctionAgent_Agents implements INode {
@@ -82,17 +81,7 @@ class OpenAIFunctionAgent_Agents implements INode {
         const memory = nodeData.inputs?.memory as BaseChatMemory
 
         if (options && options.chatHistory) {
-            const chatHistory = []
-            const histories: IMessage[] = options.chatHistory
-
-            for (const message of histories) {
-                if (message.type === 'apiMessage') {
-                    chatHistory.push(new AIMessage(message.message))
-                } else if (message.type === 'userMessage') {
-                    chatHistory.push(new HumanMessage(message.message))
-                }
-            }
-            memory.chatHistory = new ChatMessageHistory(chatHistory)
+            memory.chatHistory = mapChatHistory(options)
             executor.memory = memory
         }