Merge branch 'main' into FEATURE/Vision

# Conflicts:
#	packages/components/nodes/agents/MRKLAgentChat/MRKLAgentChat.ts

CONTRIBUTING-ZH.md

@@ -30,7 +30,7 @@
 
 不确定要贡献什么？一些想法：
 
--   从 Langchain 创建新组件
+-   从 `packages/components` 创建新组件
 -   更新现有组件，如扩展功能、修复错误
 -   添加新的 Chatflow 想法
 
@@ -40,7 +40,7 @@ Flowise 在一个单一的单体存储库中有 3 个不同的模块。
 
 -   `server`：用于提供 API 逻辑的 Node 后端
 -   `ui`：React 前端
--   `components`：Langchain 组件
+-   `components`：Langchain/LlamaIndex 组件
 
 #### 先决条件
 

CONTRIBUTING.md

@@ -30,7 +30,7 @@ Found an issue? [Report it](https://github.com/FlowiseAI/Flowise/issues/new/choo
 
 Not sure what to contribute? Some ideas:
 
--   Create new components from Langchain
+-   Create new components from `packages/components`
 -   Update existing components such as extending functionality, fixing bugs
 -   Add new chatflow ideas
 
@@ -40,7 +40,7 @@ Flowise has 3 different modules in a single mono repository.
 
 -   `server`: Node backend to serve API logics
 -   `ui`: React frontend
--   `components`: Langchain components
+-   `components`: Third-party nodes integrations
 
 #### Prerequisite
 

README-ZH.md

@@ -71,7 +71,7 @@ Flowise 在一个单一的代码库中有 3 个不同的模块。
 
 -   `server`：用于提供 API 逻辑的 Node 后端
 -   `ui`：React 前端
--   `components`：Langchain 组件
+-   `components`：第三方节点集成
 
 ### 先决条件
 

README.md

@@ -71,7 +71,7 @@ Flowise has 3 different modules in a single mono repository.
 
 -   `server`: Node backend to serve API logics
 -   `ui`: React frontend
--   `components`: Langchain components
+-   `components`: Third-party nodes integrations
 
 ### Prerequisite
 

package.json

@@ -53,5 +53,8 @@
     },
     "engines": {
         "node": ">=18.15.0"
+    },
+    "resolutions": {
+        "@qdrant/openapi-typescript-fetch": "1.2.1"
     }
 }

packages/components/nodes/agents/MRKLAgentChat/MRKLAgentChat.ts

@@ -1,16 +1,17 @@
 import { flatten } from 'lodash'
-import { AgentExecutor, createReactAgent } from 'langchain/agents'
+import { AgentExecutor } from 'langchain/agents'
 import { pull } from 'langchain/hub'
 import { Tool } from '@langchain/core/tools'
 import type { PromptTemplate } from '@langchain/core/prompts'
 import { BaseChatModel } from '@langchain/core/language_models/chat_models'
 import { additionalCallbacks } from '../../../src/handler'
-import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { FlowiseMemory, ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
-import { ChatOpenAI } from "../../chatmodels/ChatOpenAI/FlowiseChatOpenAI";
+import { createReactAgent } from '../../../src/agents'
-import { HumanMessage } from "@langchain/core/messages";
+import { ChatOpenAI } from '../../chatmodels/ChatOpenAI/FlowiseChatOpenAI'
-import { addImagesToMessages } from "../../../src/multiModalUtils";
+import { HumanMessage } from '@langchain/core/messages'
-import { ChatPromptTemplate, SystemMessagePromptTemplate } from "langchain/prompts";
+import { addImagesToMessages } from '../../../src/multiModalUtils'
+import { ChatPromptTemplate, SystemMessagePromptTemplate } from 'langchain/prompts'
 // import { injectLcAgentExecutorNodeData } from '../../../src/multiModalUtils'
 
 class MRKLAgentChat_Agents implements INode {
@@ -23,11 +24,12 @@ class MRKLAgentChat_Agents implements INode {
     category: string
     baseClasses: string[]
     inputs: INodeParams[]
+    sessionId?: string
 
-    constructor() {
+    constructor(fields?: { sessionId?: string }) {
         this.label = 'ReAct Agent for Chat Models'
         this.name = 'mrklAgentChat'
-        this.version = 2.0
+        this.version = 3.0
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'agent.svg'
@@ -44,8 +46,14 @@ class MRKLAgentChat_Agents implements INode {
                 label: 'Chat Model',
                 name: 'model',
                 type: 'BaseChatModel'
+            },
+            {
+                label: 'Memory',
+                name: 'memory',
+                type: 'BaseChatMemory'
             }
         ]
+        this.sessionId = fields?.sessionId
     }
 
     async init(): Promise<any> {
@@ -53,6 +61,7 @@ class MRKLAgentChat_Agents implements INode {
     }
 
     async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+        const memory = nodeData.inputs?.memory as FlowiseMemory
         const model = nodeData.inputs?.model as BaseChatModel
         let tools = nodeData.inputs?.tools as Tool[]
         tools = flatten(tools)
@@ -94,10 +103,25 @@ class MRKLAgentChat_Agents implements INode {
 
         const callbacks = await additionalCallbacks(nodeData, options)
 
-        const result = await executor.invoke({
+        const prevChatHistory = options.chatHistory
-            input,
+        const chatHistory = ((await memory.getChatMessages(this.sessionId, false, prevChatHistory)) as IMessage[]) ?? []
-            callbacks
+        const chatHistoryString = chatHistory.map((hist) => hist.message).join('\\n')
-        })
+
+        const result = await executor.invoke({ input, chat_history: chatHistoryString }, { callbacks })
+
+        await memory.addChatMessages(
+            [
+                {
+                    text: input,
+                    type: 'userMessage'
+                },
+                {
+                    text: result?.output,
+                    type: 'apiMessage'
+                }
+            ],
+            this.sessionId
+        )
 
         return result?.output
     }

packages/components/nodes/agents/MRKLAgentLLM/MRKLAgentLLM.ts

@@ -1,5 +1,5 @@
 import { flatten } from 'lodash'
-import { AgentExecutor, createReactAgent } from 'langchain/agents'
+import { AgentExecutor } from 'langchain/agents'
 import { pull } from 'langchain/hub'
 import { Tool } from '@langchain/core/tools'
 import type { PromptTemplate } from '@langchain/core/prompts'
@@ -7,6 +7,7 @@ import { BaseLanguageModel } from 'langchain/base_language'
 import { additionalCallbacks } from '../../../src/handler'
 import { getBaseClasses } from '../../../src/utils'
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { createReactAgent } from '../../../src/agents'
 
 class MRKLAgentLLM_Agents implements INode {
     label: string
@@ -68,10 +69,7 @@ class MRKLAgentLLM_Agents implements INode {
 
         const callbacks = await additionalCallbacks(nodeData, options)
 
-        const result = await executor.invoke({
+        const result = await executor.invoke({ input }, { callbacks })
-            input,
-            callbacks
-        })
 
         return result?.output
     }

packages/components/package.json

@@ -63,8 +63,8 @@
         "ioredis": "^5.3.2",
         "jsonpointer": "^5.0.1",
         "langchain": "^0.1.20",
-        "langfuse": "2.0.2",
+        "langfuse": "3.1.0",
-        "langfuse-langchain": "^2.6.2-alpha.0",
+        "langfuse-langchain": "^3.1.0",
         "langsmith": "0.0.63",
         "linkifyjs": "^4.1.1",
         "llamaindex": "^0.0.48",

packages/components/src/agents.ts

@@ -3,12 +3,23 @@ import { ChainValues } from '@langchain/core/utils/types'
 import { AgentStep, AgentAction } from '@langchain/core/agents'
 import { BaseMessage, FunctionMessage, AIMessage } from '@langchain/core/messages'
 import { OutputParserException } from '@langchain/core/output_parsers'
+import { BaseLanguageModel } from '@langchain/core/language_models/base'
 import { CallbackManager, CallbackManagerForChainRun, Callbacks } from '@langchain/core/callbacks/manager'
-import { ToolInputParsingException, Tool } from '@langchain/core/tools'
+import { ToolInputParsingException, Tool, StructuredToolInterface } from '@langchain/core/tools'
-import { Runnable } from '@langchain/core/runnables'
+import { Runnable, RunnableSequence, RunnablePassthrough } from '@langchain/core/runnables'
 import { Serializable } from '@langchain/core/load/serializable'
+import { renderTemplate } from '@langchain/core/prompts'
 import { BaseChain, SerializedLLMChain } from 'langchain/chains'
-import { AgentExecutorInput, BaseSingleActionAgent, BaseMultiActionAgent, RunnableAgent, StoppingMethod } from 'langchain/agents'
+import {
+    CreateReactAgentParams,
+    AgentExecutorInput,
+    AgentActionOutputParser,
+    BaseSingleActionAgent,
+    BaseMultiActionAgent,
+    RunnableAgent,
+    StoppingMethod
+} from 'langchain/agents'
+import { formatLogToString } from 'langchain/agents/format_scratchpad/log'
 
 export const SOURCE_DOCUMENTS_PREFIX = '\n\n----FLOWISE_SOURCE_DOCUMENTS----\n\n'
 type AgentFinish = {
@@ -647,3 +658,110 @@ export const formatAgentSteps = (steps: AgentStep[]): BaseMessage[] =>
             return [new AIMessage(action.log)]
         }
     })
+
+const renderTextDescription = (tools: StructuredToolInterface[]): string => {
+    return tools.map((tool) => `${tool.name}: ${tool.description}`).join('\n')
+}
+
+export const createReactAgent = async ({ llm, tools, prompt }: CreateReactAgentParams) => {
+    const missingVariables = ['tools', 'tool_names', '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 toolNames = tools.map((tool) => tool.name)
+    const partialedPrompt = await prompt.partial({
+        tools: renderTextDescription(tools),
+        tool_names: toolNames.join(', ')
+    })
+    // TODO: Add .bind to core runnable interface.
+    const llmWithStop = (llm as BaseLanguageModel).bind({
+        stop: ['\nObservation:']
+    })
+    const agent = RunnableSequence.from([
+        RunnablePassthrough.assign({
+            //@ts-ignore
+            agent_scratchpad: (input: { steps: AgentStep[] }) => formatLogToString(input.steps)
+        }),
+        partialedPrompt,
+        llmWithStop,
+        new ReActSingleInputOutputParser({
+            toolNames
+        })
+    ])
+    return agent
+}
+
+class ReActSingleInputOutputParser extends AgentActionOutputParser {
+    lc_namespace = ['langchain', 'agents', 'react']
+
+    private toolNames: string[]
+    private FINAL_ANSWER_ACTION = 'Final Answer:'
+    private FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE = 'Parsing LLM output produced both a final answer and a parse-able action:'
+    private FORMAT_INSTRUCTIONS = `Use the following format:
+
+Question: the input question you must answer
+Thought: you should always think about what to do
+Action: the action to take, should be one of [{tool_names}]
+Action Input: the input to the action
+Observation: the result of the action
+... (this Thought/Action/Action Input/Observation can repeat N times)
+Thought: I now know the final answer
+Final Answer: the final answer to the original input question`
+
+    constructor(fields: { toolNames: string[] }) {
+        super(...arguments)
+        this.toolNames = fields.toolNames
+    }
+
+    /**
+     * Parses the given text into an AgentAction or AgentFinish object. If an
+     * output fixing parser is defined, uses it to parse the text.
+     * @param text Text to parse.
+     * @returns Promise that resolves to an AgentAction or AgentFinish object.
+     */
+    async parse(text: string): Promise<AgentAction | AgentFinish> {
+        const includesAnswer = text.includes(this.FINAL_ANSWER_ACTION)
+        const regex = /Action\s*\d*\s*:[\s]*(.*?)[\s]*Action\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)/
+        const actionMatch = text.match(regex)
+        if (actionMatch) {
+            if (includesAnswer) {
+                throw new Error(`${this.FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE}: ${text}`)
+            }
+
+            const action = actionMatch[1]
+            const actionInput = actionMatch[2]
+            const toolInput = actionInput.trim().replace(/"/g, '')
+
+            return {
+                tool: action,
+                toolInput,
+                log: text
+            }
+        }
+
+        if (includesAnswer) {
+            const finalAnswerText = text.split(this.FINAL_ANSWER_ACTION)[1].trim()
+            return {
+                returnValues: {
+                    output: finalAnswerText
+                },
+                log: text
+            }
+        }
+
+        // Instead of throwing Error, we return a AgentFinish object
+        return { returnValues: { output: text }, log: text }
+    }
+
+    /**
+     * Returns the format instructions as a string. If the 'raw' option is
+     * true, returns the raw FORMAT_INSTRUCTIONS.
+     * @param options Options for getting the format instructions.
+     * @returns Format instructions as a string.
+     */
+    getFormatInstructions(): string {
+        return renderTemplate(this.FORMAT_INSTRUCTIONS, 'f-string', {
+            tool_names: this.toolNames.join(', ')
+        })
+    }
+}

packages/server/marketplaces/chatflows/ReAct Agent.json

@@ -5,11 +5,11 @@
     "nodes": [
         {
             "width": 300,
-            "height": 143,
+            "height": 142,
             "id": "calculator_1",
             "position": {
-                "x": 664.1366474718458,
+                "x": 466.86432329033937,
-                "y": 123.16419000640141
+                "y": 230.0825123205457
             },
             "type": "customNode",
             "data": {
@@ -36,66 +36,171 @@
                 "selected": false
             },
             "positionAbsolute": {
-                "x": 664.1366474718458,
+                "x": 466.86432329033937,
-                "y": 123.16419000640141
+                "y": 230.0825123205457
             },
             "selected": false,
             "dragging": false
         },
         {
-            "width": 300,
+            "id": "mrklAgentChat_0",
-            "height": 277,
-            "id": "serper_0",
             "position": {
-                "x": 330.964079024626,
+                "x": 905.8535326018256,
-                "y": 109.83185250619351
+                "y": 388.58312223652564
             },
             "type": "customNode",
             "data": {
-                "id": "serper_0",
+                "id": "mrklAgentChat_0",
-                "label": "Serper",
+                "label": "ReAct Agent for Chat Models",
-                "version": 1,
+                "version": 3,
-                "name": "serper",
+                "name": "mrklAgentChat",
-                "type": "Serper",
+                "type": "AgentExecutor",
-                "baseClasses": ["Serper", "Tool", "StructuredTool"],
+                "baseClasses": ["AgentExecutor", "BaseChain", "Runnable"],
-                "category": "Tools",
+                "category": "Agents",
-                "description": "Wrapper around Serper.dev - Google Search API",
+                "description": "Agent that uses the ReAct logic to decide what action to take, optimized to be used with Chat Models",
-                "inputParams": [
+                "inputParams": [],
+                "inputAnchors": [
                     {
-                        "label": "Connect Credential",
+                        "label": "Allowed Tools",
-                        "name": "credential",
+                        "name": "tools",
-                        "type": "credential",
+                        "type": "Tool",
-                        "credentialNames": ["serperApi"],
+                        "list": true,
-                        "id": "serper_0-input-credential-credential"
+                        "id": "mrklAgentChat_0-input-tools-Tool"
+                    },
+                    {
+                        "label": "Chat Model",
+                        "name": "model",
+                        "type": "BaseChatModel",
+                        "id": "mrklAgentChat_0-input-model-BaseChatModel"
+                    },
+                    {
+                        "label": "Memory",
+                        "name": "memory",
+                        "type": "BaseChatMemory",
+                        "id": "mrklAgentChat_0-input-memory-BaseChatMemory"
                     }
                 ],
-                "inputAnchors": [],
+                "inputs": {
-                "inputs": {},
+                    "tools": ["{{calculator_1.data.instance}}", "{{serper_0.data.instance}}"],
+                    "model": "{{chatOpenAI_0.data.instance}}",
+                    "memory": "{{RedisBackedChatMemory_0.data.instance}}"
+                },
                 "outputAnchors": [
                     {
-                        "id": "serper_0-output-serper-Serper|Tool|StructuredTool",
+                        "id": "mrklAgentChat_0-output-mrklAgentChat-AgentExecutor|BaseChain|Runnable",
-                        "name": "serper",
+                        "name": "mrklAgentChat",
-                        "label": "Serper",
+                        "label": "AgentExecutor",
-                        "type": "Serper | Tool | StructuredTool"
+                        "description": "Agent that uses the ReAct logic to decide what action to take, optimized to be used with Chat Models",
+                        "type": "AgentExecutor | BaseChain | Runnable"
                     }
                 ],
                 "outputs": {},
                 "selected": false
             },
+            "width": 300,
+            "height": 330,
             "selected": false,
             "positionAbsolute": {
-                "x": 330.964079024626,
+                "x": 905.8535326018256,
-                "y": 109.83185250619351
+                "y": 388.58312223652564
             },
             "dragging": false
         },
         {
+            "id": "RedisBackedChatMemory_0",
+            "position": {
+                "x": 473.108799702029,
+                "y": 401.8098683245926
+            },
+            "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 <a target=\"_blank\" href=\"https://docs.flowiseai.com/memory/long-term-memory#ui-and-embedded-chat\">more</a>",
+                        "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"
+                    },
+                    {
+                        "label": "Window Size",
+                        "name": "windowSize",
+                        "type": "number",
+                        "description": "Window of size k to surface the last k back-and-forth to use as memory.",
+                        "additionalParams": true,
+                        "optional": true,
+                        "id": "RedisBackedChatMemory_0-input-windowSize-number"
+                    }
+                ],
+                "inputAnchors": [],
+                "inputs": {
+                    "sessionId": "",
+                    "sessionTTL": "",
+                    "memoryKey": "chat_history",
+                    "windowSize": ""
+                },
+                "outputAnchors": [
+                    {
+                        "id": "RedisBackedChatMemory_0-output-RedisBackedChatMemory-RedisBackedChatMemory|BaseChatMemory|BaseMemory",
+                        "name": "RedisBackedChatMemory",
+                        "label": "RedisBackedChatMemory",
+                        "description": "Summarizes the conversation and stores the memory in Redis server",
+                        "type": "RedisBackedChatMemory | BaseChatMemory | BaseMemory"
+                    }
+                ],
+                "outputs": {},
+                "selected": false
+            },
             "width": 300,
-            "height": 574,
+            "height": 328,
+            "selected": false,
+            "positionAbsolute": {
+                "x": 473.108799702029,
+                "y": 401.8098683245926
+            },
+            "dragging": false
+        },
+        {
             "id": "chatOpenAI_0",
             "position": {
-                "x": -27.71074046118335,
+                "x": 81.2222202723384,
-                "y": 243.62715178281059
+                "y": 59.395597724017364
             },
             "type": "customNode",
             "data": {
@@ -282,73 +387,69 @@
                         "id": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
                         "name": "chatOpenAI",
                         "label": "ChatOpenAI",
+                        "description": "Wrapper around OpenAI large language models that use the Chat endpoint",
                         "type": "ChatOpenAI | BaseChatModel | BaseLanguageModel | Runnable"
                     }
                 ],
                 "outputs": {},
                 "selected": false
             },
+            "width": 300,
+            "height": 573,
             "selected": false,
             "positionAbsolute": {
-                "x": -27.71074046118335,
+                "x": 81.2222202723384,
-                "y": 243.62715178281059
+                "y": 59.395597724017364
             },
             "dragging": false
         },
         {
-            "width": 300,
+            "id": "serper_0",
-            "height": 280,
-            "id": "mrklAgentChat_0",
             "position": {
-                "x": 1090.2058867451212,
+                "x": 466.4499611299051,
-                "y": 423.2174695788541
+                "y": -67.74721119468873
             },
             "type": "customNode",
             "data": {
-                "id": "mrklAgentChat_0",
+                "id": "serper_0",
-                "label": "ReAct Agent for Chat Models",
+                "label": "Serper",
                 "version": 1,
-                "name": "mrklAgentChat",
+                "name": "serper",
-                "type": "AgentExecutor",
+                "type": "Serper",
-                "baseClasses": ["AgentExecutor", "BaseChain", "Runnable"],
+                "baseClasses": ["Serper", "Tool", "StructuredTool", "Runnable"],
-                "category": "Agents",
+                "category": "Tools",
-                "description": "Agent that uses the ReAct logic to decide what action to take, optimized to be used with Chat Models",
+                "description": "Wrapper around Serper.dev - Google Search API",
-                "inputParams": [],
+                "inputParams": [
-                "inputAnchors": [
                     {
-                        "label": "Allowed Tools",
+                        "label": "Connect Credential",
-                        "name": "tools",
+                        "name": "credential",
-                        "type": "Tool",
+                        "type": "credential",
-                        "list": true,
+                        "credentialNames": ["serperApi"],
-                        "id": "mrklAgentChat_0-input-tools-Tool"
+                        "id": "serper_0-input-credential-credential"
-                    },
-                    {
-                        "label": "Language Model",
-                        "name": "model",
-                        "type": "BaseLanguageModel",
-                        "id": "mrklAgentChat_0-input-model-BaseLanguageModel"
                     }
                 ],
-                "inputs": {
+                "inputAnchors": [],
-                    "tools": ["{{calculator_1.data.instance}}", "{{serper_0.data.instance}}"],
+                "inputs": {},
-                    "model": "{{chatOpenAI_0.data.instance}}"
-                },
                 "outputAnchors": [
                     {
-                        "id": "mrklAgentChat_0-output-mrklAgentChat-AgentExecutor|BaseChain|Runnable",
+                        "id": "serper_0-output-serper-Serper|Tool|StructuredTool|Runnable",
-                        "name": "mrklAgentChat",
+                        "name": "serper",
-                        "label": "AgentExecutor",
+                        "label": "Serper",
-                        "type": "AgentExecutor | BaseChain | Runnable"
+                        "description": "Wrapper around Serper.dev - Google Search API",
+                        "type": "Serper | Tool | StructuredTool | Runnable"
                     }
                 ],
                 "outputs": {},
                 "selected": false
             },
+            "width": 300,
+            "height": 276,
+            "selected": false,
             "positionAbsolute": {
-                "x": 1090.2058867451212,
+                "x": 466.4499611299051,
-                "y": 423.2174695788541
+                "y": -67.74721119468873
             },
-            "selected": false
+            "dragging": false
         }
     ],
     "edges": [
@@ -358,32 +459,31 @@
             "target": "mrklAgentChat_0",
             "targetHandle": "mrklAgentChat_0-input-tools-Tool",
             "type": "buttonedge",
-            "id": "calculator_1-calculator_1-output-calculator-Calculator|Tool|StructuredTool|BaseLangChain-mrklAgentChat_0-mrklAgentChat_0-input-tools-Tool",
+            "id": "calculator_1-calculator_1-output-calculator-Calculator|Tool|StructuredTool|BaseLangChain-mrklAgentChat_0-mrklAgentChat_0-input-tools-Tool"
-            "data": {
-                "label": ""
-            }
         },
         {
-            "source": "serper_0",
+            "source": "RedisBackedChatMemory_0",
-            "sourceHandle": "serper_0-output-serper-Serper|Tool|StructuredTool",
+            "sourceHandle": "RedisBackedChatMemory_0-output-RedisBackedChatMemory-RedisBackedChatMemory|BaseChatMemory|BaseMemory",
             "target": "mrklAgentChat_0",
-            "targetHandle": "mrklAgentChat_0-input-tools-Tool",
+            "targetHandle": "mrklAgentChat_0-input-memory-BaseChatMemory",
             "type": "buttonedge",
-            "id": "serper_0-serper_0-output-serper-Serper|Tool|StructuredTool-mrklAgentChat_0-mrklAgentChat_0-input-tools-Tool",
+            "id": "RedisBackedChatMemory_0-RedisBackedChatMemory_0-output-RedisBackedChatMemory-RedisBackedChatMemory|BaseChatMemory|BaseMemory-mrklAgentChat_0-mrklAgentChat_0-input-memory-BaseChatMemory"
-            "data": {
-                "label": ""
-            }
         },
         {
             "source": "chatOpenAI_0",
             "sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
             "target": "mrklAgentChat_0",
-            "targetHandle": "mrklAgentChat_0-input-model-BaseLanguageModel",
+            "targetHandle": "mrklAgentChat_0-input-model-BaseChatModel",
             "type": "buttonedge",
-            "id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable-mrklAgentChat_0-mrklAgentChat_0-input-model-BaseLanguageModel",
+            "id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable-mrklAgentChat_0-mrklAgentChat_0-input-model-BaseChatModel"
-            "data": {
+        },
-                "label": ""
+        {
-            }
+            "source": "serper_0",
+            "sourceHandle": "serper_0-output-serper-Serper|Tool|StructuredTool|Runnable",
+            "target": "mrklAgentChat_0",
+            "targetHandle": "mrklAgentChat_0-input-tools-Tool",
+            "type": "buttonedge",
+            "id": "serper_0-serper_0-output-serper-Serper|Tool|StructuredTool|Runnable-mrklAgentChat_0-mrklAgentChat_0-input-tools-Tool"
         }
     ]
 }

packages/server/src/index.ts

@@ -27,7 +27,7 @@ import {
 import {
     getNodeModulesPackagePath,
     getStartingNodes,
-    buildLangchain,
+    buildFlow,
     getEndingNodes,
     constructGraphs,
     resolveVariables,
@@ -459,7 +459,7 @@ export class App {
             // chatFlowPool is initialized only when a flow is opened
             // if the user attempts to rename/update category without opening any flow, chatFlowPool will be undefined
             if (this.chatflowPool) {
-                // Update chatflowpool inSync to false, to build Langchain again because data has been changed
+                // Update chatflowpool inSync to false, to build flow from scratch again because data has been changed
                 this.chatflowPool.updateInSync(chatflow.id, false)
             }
 
@@ -1725,7 +1725,7 @@ export class App {
 
             const { startingNodeIds, depthQueue } = getStartingNodes(filteredGraph, stopNodeId)
 
-            await buildLangchain(
+            await buildFlow(
                 startingNodeIds,
                 nodes,
                 edges,
@@ -1993,7 +1993,7 @@ export class App {
 
                 logger.debug(`[server]: Start building chatflow ${chatflowid}`)
                 /*** BFS to traverse from Starting Nodes to Ending Node ***/
-                const reactFlowNodes = await buildLangchain(
+                const reactFlowNodes = await buildFlow(
                     startingNodeIds,
                     nodes,
                     edges,

packages/server/src/utils/index.ts

@@ -264,7 +264,7 @@ export const getEndingNodes = (nodeDependencies: INodeDependencies, graph: INode
  * @param {ICommonObject} overrideConfig
  * @param {CachePool} cachePool
  */
-export const buildLangchain = async (
+export const buildFlow = async (
     startingNodeIds: string[],
     reactFlowNodes: IReactFlowNode[],
     reactFlowEdges: IReactFlowEdge[],

packages/ui/public/index.html

@@ -18,13 +18,19 @@
         <meta property="og:site_name" content="flowiseai.com" />
         <meta property="article:publisher" content="https://www.facebook.com/codedthemes" />
         <meta property="og:title" content="Flowise - Low-code LLM apps builder" />
-        <meta property="og:description" content="Flowise helps you to better build LLM flows using Langchain in simple GUI" />
+        <meta
+            property="og:description"
+            content="Build customized LLM orchestration flow & agents, enable quick iterations from testing to production"
+        />
         <meta property="og:image" content="https://flowiseai.com/og-image/og-facebook.png" />
         <!-- Twitter -->
         <meta property="twitter:card" content="summary_large_image" />
         <meta property="twitter:url" content="https://flowiseai.com" />
         <meta property="twitter:title" content="Flowise - Low-code LLM apps builder" />
-        <meta property="twitter:description" content="Flowise helps you to better build LLM flows using Langchain in simple GUI" />
+        <meta
+            property="twitter:description"
+            content="Build customized LLM orchestration flow & agents, enable quick iterations from testing to production"
+        />
         <meta property="twitter:image" content="https://flowiseai.com/og-image/og-twitter.png" />
         <meta name="twitter:creator" content="@codedthemes" />
         <!--