Merge branch 'main' into feature/BabyAGI

# Conflicts:
#	packages/components/package.json

.github/workflows/main.yml

@@ -17,7 +17,7 @@ jobs:
         strategy:
             matrix:
                 platform: [ubuntu-latest]
-                node-version: [14.x, 16.x]
+                node-version: [18.15.0]
         runs-on: ${{ matrix.platform }}
 
         steps:

CONTRIBUTING.md

@@ -116,7 +116,7 @@ In-Progress
 
 ## 🏷️ Pull Request process
 
-A member of the FlowiseAI team will automatically be notified/assigned when you open a pull request. You can also reach out to us on [Discord](https://discord.gg/GWcGczPk).
+A member of the FlowiseAI team will automatically be notified/assigned when you open a pull request. You can also reach out to us on [Discord](https://discord.gg/7C5xTWP8).
 
 ## 📃 Contributor License Agreement
 

README.md

@@ -13,7 +13,7 @@ Drag & drop UI to build your customized LLM flow using [LangchainJS](https://git
     ```bash
     npm install -g flowise
     ```
-2. Start FlowiseAI
+2. Start Flowise
 
     ```bash
     npx flowise start
@@ -104,7 +104,7 @@ Feel free to ask any questions, raise problems, and request new features in [dis
 
 ## 🙌 Contributing
 
-See [contributing guide](CONTRIBUTING.md). Reach out to us at [Discord](https://discord.gg/GWcGczPk) if you have any questions or issues.
+See [contributing guide](CONTRIBUTING.md). Reach out to us at [Discord](https://discord.gg/7C5xTWP8) if you have any questions or issues.
 
 ## 📄 License
 

package.json

@@ -1,6 +1,6 @@
 {
     "name": "flowise",
-    "version": "1.0.0",
+    "version": "1.1.1",
     "private": true,
     "homepage": "https://flowiseai.com",
     "workspaces": [
@@ -11,6 +11,7 @@
     ],
     "scripts": {
         "build": "turbo run build",
+        "build-force": "turbo run build --force",
         "dev": "turbo run dev --parallel",
         "start": "run-script-os",
         "start:windows": "cd packages/server/bin && run start",

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

@@ -1,4 +1,9 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { initializeAgentExecutor, AgentExecutor } from 'langchain/agents'
+import { Tool } from 'langchain/tools'
+import { BaseChatModel } from 'langchain/chat_models/base'
+import { BaseChatMemory } from 'langchain/memory'
+import { getBaseClasses } from '../../../src/utils'
 
 class ConversationalAgent_Agents implements INode {
     label: string
@@ -17,6 +22,7 @@ class ConversationalAgent_Agents implements INode {
         this.category = 'Agents'
         this.icon = 'agent.svg'
         this.description = 'Conversational agent for a chat model. It will utilize chat specific prompts'
+        this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)]
         this.inputs = [
             {
                 label: 'Allowed Tools',
@@ -37,16 +43,10 @@ class ConversationalAgent_Agents implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        return ['AgentExecutor']
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { initializeAgentExecutor } = await import('langchain/agents')
-
-        const model = nodeData.inputs?.model
-        const tools = nodeData.inputs?.tools
-        const memory = nodeData.inputs?.memory
+        const model = nodeData.inputs?.model as BaseChatModel
+        const tools = nodeData.inputs?.tools as Tool[]
+        const memory = nodeData.inputs?.memory as BaseChatMemory
 
         const executor = await initializeAgentExecutor(tools, model, 'chat-conversational-react-description', true)
         executor.memory = memory
@@ -54,7 +54,7 @@ class ConversationalAgent_Agents implements INode {
     }
 
     async run(nodeData: INodeData, input: string): Promise<string> {
-        const executor = nodeData.instance
+        const executor = nodeData.instance as AgentExecutor
         const result = await executor.call({ input })
 
         return result?.output

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

@@ -1,6 +1,10 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { initializeAgentExecutor, AgentExecutor } from 'langchain/agents'
+import { Tool } from 'langchain/tools'
+import { BaseChatModel } from 'langchain/chat_models/base'
+import { getBaseClasses } from '../../../src/utils'
 
-class MRLKAgentChat_Agents implements INode {
+class MRKLAgentChat_Agents implements INode {
     label: string
     name: string
     description: string
@@ -11,12 +15,13 @@ class MRLKAgentChat_Agents implements INode {
     inputs: INodeParams[]
 
     constructor() {
-        this.label = 'MRLK Agent for Chat Models'
-        this.name = 'mrlkAgentChat'
+        this.label = 'MRKL Agent for Chat Models'
+        this.name = 'mrklAgentChat'
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'agent.svg'
         this.description = 'Agent that uses the ReAct Framework to decide what action to take, optimized to be used with Chat Models'
+        this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)]
         this.inputs = [
             {
                 label: 'Allowed Tools',
@@ -32,27 +37,20 @@ class MRLKAgentChat_Agents implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        return ['AgentExecutor']
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { initializeAgentExecutor } = await import('langchain/agents')
-
-        const model = nodeData.inputs?.model
-        const tools = nodeData.inputs?.tools
+        const model = nodeData.inputs?.model as BaseChatModel
+        const tools = nodeData.inputs?.tools as Tool[]
 
         const executor = await initializeAgentExecutor(tools, model, 'chat-zero-shot-react-description', true)
-
         return executor
     }
 
     async run(nodeData: INodeData, input: string): Promise<string> {
-        const executor = nodeData.instance
+        const executor = nodeData.instance as AgentExecutor
         const result = await executor.call({ input })
 
         return result?.output
     }
 }
 
-module.exports = { nodeClass: MRLKAgentChat_Agents }
+module.exports = { nodeClass: MRKLAgentChat_Agents }

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

@@ -1,6 +1,10 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { initializeAgentExecutor, AgentExecutor } from 'langchain/agents'
+import { Tool } from 'langchain/tools'
+import { BaseLLM } from 'langchain/llms/base'
+import { getBaseClasses } from '../../../src/utils'
 
-class MRLKAgentLLM_Agents implements INode {
+class MRKLAgentLLM_Agents implements INode {
     label: string
     name: string
     description: string
@@ -11,12 +15,13 @@ class MRLKAgentLLM_Agents implements INode {
     inputs: INodeParams[]
 
     constructor() {
-        this.label = 'MRLK Agent for LLMs'
-        this.name = 'mrlkAgentLLM'
+        this.label = 'MRKL Agent for LLMs'
+        this.name = 'mrklAgentLLM'
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'agent.svg'
         this.description = 'Agent that uses the ReAct Framework to decide what action to take, optimized to be used with LLMs'
+        this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)]
         this.inputs = [
             {
                 label: 'Allowed Tools',
@@ -27,32 +32,25 @@ class MRLKAgentLLM_Agents implements INode {
             {
                 label: 'LLM Model',
                 name: 'model',
-                type: 'BaseLanguageModel'
+                type: 'BaseLLM'
             }
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        return ['AgentExecutor']
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { initializeAgentExecutor } = await import('langchain/agents')
-
-        const model = nodeData.inputs?.model
-        const tools = nodeData.inputs?.tools
+        const model = nodeData.inputs?.model as BaseLLM
+        const tools = nodeData.inputs?.tools as Tool[]
 
         const executor = await initializeAgentExecutor(tools, model, 'zero-shot-react-description', true)
-
         return executor
     }
 
     async run(nodeData: INodeData, input: string): Promise<string> {
-        const executor = nodeData.instance
+        const executor = nodeData.instance as AgentExecutor
         const result = await executor.call({ input })
 
         return result?.output
     }
 }
 
-module.exports = { nodeClass: MRLKAgentLLM_Agents }
+module.exports = { nodeClass: MRKLAgentLLM_Agents }

packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts

@@ -1,5 +1,8 @@
 import { ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { ConversationalRetrievalQAChain } from 'langchain/chains'
+import { BaseLLM } from 'langchain/llms/base'
+import { BaseRetriever } from 'langchain/schema'
 
 class ConversationalRetrievalQAChain_Chains implements INode {
     label: string
@@ -18,11 +21,12 @@ class ConversationalRetrievalQAChain_Chains implements INode {
         this.icon = 'chain.svg'
         this.category = 'Chains'
         this.description = 'Document QA - built on RetrievalQAChain to provide a chat history component'
+        this.baseClasses = [this.type, ...getBaseClasses(ConversationalRetrievalQAChain)]
         this.inputs = [
             {
                 label: 'LLM',
                 name: 'llm',
-                type: 'BaseLanguageModel'
+                type: 'BaseLLM'
             },
             {
                 label: 'Vector Store Retriever',
@@ -32,23 +36,16 @@ class ConversationalRetrievalQAChain_Chains implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        const { ConversationalRetrievalQAChain } = await import('langchain/chains')
-        return getBaseClasses(ConversationalRetrievalQAChain)
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { ConversationalRetrievalQAChain } = await import('langchain/chains')
-
-        const llm = nodeData.inputs?.llm
-        const vectorStoreRetriever = nodeData.inputs?.vectorStoreRetriever
+        const llm = nodeData.inputs?.llm as BaseLLM
+        const vectorStoreRetriever = nodeData.inputs?.vectorStoreRetriever as BaseRetriever
 
         const chain = ConversationalRetrievalQAChain.fromLLM(llm, vectorStoreRetriever)
         return chain
     }
 
     async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
-        const chain = nodeData.instance
+        const chain = nodeData.instance as ConversationalRetrievalQAChain
         let chatHistory = ''
 
         if (options && options.chatHistory) {

packages/components/nodes/chains/LLMChain/LLMChain.ts

@@ -1,5 +1,8 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { LLMChain } from 'langchain/chains'
+import { BaseLanguageModel } from 'langchain/base_language'
+import { BasePromptTemplate } from 'langchain/prompts'
 
 class LLMChain_Chains implements INode {
     label: string
@@ -18,10 +21,11 @@ class LLMChain_Chains implements INode {
         this.icon = 'chain.svg'
         this.category = 'Chains'
         this.description = 'Chain to run queries against LLMs'
+        this.baseClasses = [this.type, ...getBaseClasses(LLMChain)]
         this.inputs = [
             {
-                label: 'LLM',
-                name: 'llm',
+                label: 'Language Model',
+                name: 'model',
                 type: 'BaseLanguageModel'
             },
             {
@@ -43,24 +47,17 @@ class LLMChain_Chains implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        const { LLMChain } = await import('langchain/chains')
-        return getBaseClasses(LLMChain)
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { LLMChain } = await import('langchain/chains')
+        const model = nodeData.inputs?.model as BaseLanguageModel
+        const prompt = nodeData.inputs?.prompt as BasePromptTemplate
 
-        const llm = nodeData.inputs?.llm
-        const prompt = nodeData.inputs?.prompt
-
-        const chain = new LLMChain({ llm, prompt })
+        const chain = new LLMChain({ llm: model, prompt })
         return chain
     }
 
     async run(nodeData: INodeData, input: string): Promise<string> {
-        const inputVariables = nodeData.instance.prompt.inputVariables // ["product"]
-        const chain = nodeData.instance
+        const inputVariables = nodeData.instance.prompt.inputVariables as string[] // ["product"]
+        const chain = nodeData.instance as LLMChain
 
         if (inputVariables.length === 1) {
             const res = await chain.run(input)
@@ -71,7 +68,7 @@ class LLMChain_Chains implements INode {
 
             const promptValues = JSON.parse(promptValuesStr.replace(/\s/g, ''))
 
-            let seen = []
+            let seen: string[] = []
 
             for (const variable of inputVariables) {
                 seen.push(variable)
@@ -81,13 +78,17 @@ class LLMChain_Chains implements INode {
             }
 
             if (seen.length === 1) {
+                const lastValue = seen.pop()
+                if (!lastValue) throw new Error('Please provide Prompt Values')
                 const options = {
                     ...promptValues,
-                    [seen.pop()]: input
+                    [lastValue]: input
                 }
                 const res = await chain.call(options)
                 return res?.text
-            } else throw new Error('Please provide Prompt Values')
+            } else {
+                throw new Error('Please provide Prompt Values')
+            }
         } else {
             const res = await chain.run(input)
             return res

packages/components/nodes/chains/RetrievalQAChain/RetrievalQAChain.ts

@@ -1,4 +1,8 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { RetrievalQAChain } from 'langchain/chains'
+import { BaseLLM } from 'langchain/llms/base'
+import { BaseRetriever } from 'langchain/schema'
+import { getBaseClasses } from '../../../src/utils'
 
 class RetrievalQAChain_Chains implements INode {
     label: string
@@ -17,11 +21,12 @@ class RetrievalQAChain_Chains implements INode {
         this.icon = 'chain.svg'
         this.category = 'Chains'
         this.description = 'QA chain to answer a question based on the retrieved documents'
+        this.baseClasses = [this.type, ...getBaseClasses(RetrievalQAChain)]
         this.inputs = [
             {
                 label: 'LLM',
                 name: 'llm',
-                type: 'BaseLanguageModel'
+                type: 'BaseLLM'
             },
             {
                 label: 'Vector Store Retriever',
@@ -31,21 +36,16 @@ class RetrievalQAChain_Chains implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        return ['BaseChain']
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { RetrievalQAChain } = await import('langchain/chains')
-        const llm = nodeData.inputs?.llm
-        const vectorStoreRetriever = nodeData.inputs?.vectorStoreRetriever
+        const llm = nodeData.inputs?.llm as BaseLLM
+        const vectorStoreRetriever = nodeData.inputs?.vectorStoreRetriever as BaseRetriever
 
         const chain = RetrievalQAChain.fromLLM(llm, vectorStoreRetriever)
         return chain
     }
 
     async run(nodeData: INodeData, input: string): Promise<string> {
-        const chain = nodeData.instance
+        const chain = nodeData.instance as RetrievalQAChain
         const obj = {
             query: input
         }

packages/components/nodes/chains/SqlDatabaseChain/SqlDatabaseChain.ts

@@ -0,0 +1,81 @@
+import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { SqlDatabaseChain } from 'langchain/chains'
+import { getBaseClasses } from '../../../src/utils'
+import { DataSource } from 'typeorm'
+import { SqlDatabase } from 'langchain/sql_db'
+import { BaseLLM } from 'langchain/llms/base'
+
+class SqlDatabaseChain_Chains implements INode {
+    label: string
+    name: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Sql Database Chain'
+        this.name = 'sqlDatabaseChain'
+        this.type = 'SqlDatabaseChain'
+        this.icon = 'sqlchain.svg'
+        this.category = 'Chains'
+        this.description = 'Answer questions over a SQL database'
+        this.baseClasses = [this.type, ...getBaseClasses(SqlDatabaseChain)]
+        this.inputs = [
+            {
+                label: 'LLM',
+                name: 'llm',
+                type: 'BaseLLM'
+            },
+            {
+                label: 'Database',
+                name: 'database',
+                type: 'options',
+                options: [
+                    {
+                        label: 'SQlite',
+                        name: 'sqlite'
+                    }
+                ],
+                default: 'sqlite'
+            },
+            {
+                label: 'Database File Path',
+                name: 'dbFilePath',
+                type: 'string',
+                placeholder: 'C:/Users/chinook.db'
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData): Promise<any> {
+        const databaseType = nodeData.inputs?.database
+        const llm = nodeData.inputs?.llm as BaseLLM
+        const dbFilePath = nodeData.inputs?.dbFilePath
+
+        const datasource = new DataSource({
+            type: databaseType,
+            database: dbFilePath
+        })
+
+        const db = await SqlDatabase.fromDataSourceParams({
+            appDataSource: datasource
+        })
+
+        const chain = new SqlDatabaseChain({
+            llm,
+            database: db
+        })
+        return chain
+    }
+
+    async run(nodeData: INodeData, input: string): Promise<string> {
+        const chain = nodeData.instance as SqlDatabaseChain
+        const res = await chain.run(input)
+        return res
+    }
+}
+
+module.exports = { nodeClass: SqlDatabaseChain_Chains }

packages/components/nodes/chains/SqlDatabaseChain/sqlchain.svg

@@ -0,0 +1,7 @@
+<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-sql" 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="M12 8a2 2 0 0 1 2 2v4a2 2 0 1 1 -4 0v-4a2 2 0 0 1 2 -2z"></path>
+   <path d="M17 8v8h4"></path>
+   <path d="M13 15l1 1"></path>
+   <path d="M3 15a1 1 0 0 0 1 1h2a1 1 0 0 0 1 -1v-2a1 1 0 0 0 -1 -1h-2a1 1 0 0 1 -1 -1v-2a1 1 0 0 1 1 -1h2a1 1 0 0 1 1 1"></path>
+</svg>

packages/components/nodes/chatmodels/ChatOpenAI/ChatOpenAI.ts

@@ -1,5 +1,6 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { ChatOpenAI } from 'langchain/chat_models/openai'
 
 class ChatOpenAI_ChatModels implements INode {
     label: string
@@ -18,6 +19,7 @@ class ChatOpenAI_ChatModels implements INode {
         this.icon = 'openai.png'
         this.category = 'Chat Models'
         this.description = 'Wrapper around OpenAI large language models that use the Chat endpoint'
+        this.baseClasses = [this.type, ...getBaseClasses(ChatOpenAI)]
         this.inputs = [
             {
                 label: 'OpenAI Api Key',
@@ -63,14 +65,7 @@ class ChatOpenAI_ChatModels implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        const { ChatOpenAI } = await import('langchain/chat_models')
-        return getBaseClasses(ChatOpenAI)
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { ChatOpenAI } = await import('langchain/chat_models')
-
         const temperature = nodeData.inputs?.temperature as string
         const modelName = nodeData.inputs?.modelName as string
         const openAIApiKey = nodeData.inputs?.openAIApiKey as string

packages/components/nodes/documentloaders/Cheerio/Cheerio.ts

@@ -0,0 +1,64 @@
+import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { TextSplitter } from 'langchain/text_splitter'
+import { CheerioWebBaseLoader } from 'langchain/document_loaders/web/cheerio'
+
+class Cheerio_DocumentLoaders implements INode {
+    label: string
+    name: string
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Cheerio Web Scraper'
+        this.name = 'cheerioWebScraper'
+        this.type = 'Document'
+        this.icon = 'cheerio.svg'
+        this.category = 'Document Loaders'
+        this.description = `Load data from webpages`
+        this.baseClasses = [this.type]
+        this.inputs = [
+            {
+                label: 'URL',
+                name: 'url',
+                type: 'string'
+            },
+            {
+                label: 'Text Splitter',
+                name: 'textSplitter',
+                type: 'TextSplitter',
+                optional: true
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData): Promise<any> {
+        const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
+        let url = nodeData.inputs?.url as string
+
+        var urlPattern = new RegExp(
+            '^(https?:\\/\\/)?' + // validate protocol
+                '((([a-z\\d]([a-z\\d-]*[a-z\\d])*)\\.)+[a-z]{2,}|' + // validate domain name
+                '((\\d{1,3}\\.){3}\\d{1,3}))' + // validate OR ip (v4) address
+                '(\\:\\d+)?(\\/[-a-z\\d%_.~+]*)*' + // validate port and path
+                '(\\?[;&a-z\\d%_.~+=-]*)?' + // validate query string
+                '(\\#[-a-z\\d_]*)?$',
+            'i'
+        ) // validate fragment locator
+
+        const loader = new CheerioWebBaseLoader(urlPattern.test(url.trim()) ? url.trim() : '')
+
+        if (textSplitter) {
+            const docs = await loader.loadAndSplit(textSplitter)
+            return docs
+        } else {
+            const docs = await loader.load()
+            return docs
+        }
+    }
+}
+
+module.exports = { nodeClass: Cheerio_DocumentLoaders }

packages/components/nodes/documentloaders/Cheerio/cheerio.svg

@@ -0,0 +1,5 @@
+<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-circle-letter-c" 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="M12 12m-9 0a9 9 0 1 0 18 0a9 9 0 1 0 -18 0"></path>
+   <path d="M14 10a2 2 0 1 0 -4 0v4a2 2 0 1 0 4 0"></path>
+</svg>

packages/components/nodes/documentloaders/Csv/Csv.ts

@@ -0,0 +1,68 @@
+import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { TextSplitter } from 'langchain/text_splitter'
+import { CSVLoader } from 'langchain/document_loaders/fs/csv'
+
+class Csv_DocumentLoaders implements INode {
+    label: string
+    name: string
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Csv File'
+        this.name = 'csvFile'
+        this.type = 'Document'
+        this.icon = 'Csv.png'
+        this.category = 'Document Loaders'
+        this.description = `Load data from CSV files`
+        this.baseClasses = [this.type]
+        this.inputs = [
+            {
+                label: 'Csv File',
+                name: 'csvFile',
+                type: 'file',
+                fileType: '.csv'
+            },
+            {
+                label: 'Text Splitter',
+                name: 'textSplitter',
+                type: 'TextSplitter',
+                optional: true
+            },
+            {
+                label: 'Single Column Extraction',
+                name: 'columnName',
+                type: 'string',
+                description: 'Extracting a single column',
+                placeholder: 'Enter column name',
+                optional: true
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData): Promise<any> {
+        const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
+        const csvFileBase64 = nodeData.inputs?.csvFile as string
+        const columnName = nodeData.inputs?.columnName as string
+        const splitDataURI = csvFileBase64.split(',')
+        splitDataURI.pop()
+        const bf = Buffer.from(splitDataURI.pop() || '', 'base64')
+
+        const blob = new Blob([bf])
+        const loader = new CSVLoader(blob, columnName.trim().length === 0 ? undefined : columnName.trim())
+
+        if (textSplitter) {
+            const docs = await loader.loadAndSplit(textSplitter)
+            return docs
+        } else {
+            const docs = await loader.load()
+            return docs
+        }
+    }
+}
+
+module.exports = { nodeClass: Csv_DocumentLoaders }

packages/components/nodes/documentloaders/Github/Github.ts

@@ -1,4 +1,6 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { TextSplitter } from 'langchain/text_splitter'
+import { GithubRepoLoader, GithubRepoLoaderParams } from 'langchain/document_loaders/web/github'
 
 class Github_DocumentLoaders implements INode {
     label: string
@@ -13,10 +15,11 @@ class Github_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Github'
         this.name = 'github'
-        this.type = 'Github'
+        this.type = 'Document'
         this.icon = 'github.png'
         this.category = 'Document Loaders'
         this.description = `Load data from a GitHub repository`
+        this.baseClasses = [this.type]
         this.inputs = [
             {
                 label: 'Repo Link',
@@ -46,23 +49,17 @@ class Github_DocumentLoaders implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        return ['Document']
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { GithubRepoLoader } = await import('langchain/document_loaders')
-
         const repoLink = nodeData.inputs?.repoLink as string
         const branch = nodeData.inputs?.branch as string
         const accessToken = nodeData.inputs?.accessToken as string
-        const textSplitter = nodeData.inputs?.textSplitter
+        const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
 
-        const options = {
+        const options: GithubRepoLoaderParams = {
             branch,
             recursive: false,
             unknown: 'warn'
-        } as any
+        }
 
         if (accessToken) options.accessToken = accessToken
 

packages/components/nodes/documentloaders/Pdf/Pdf.ts

@@ -1,4 +1,6 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { TextSplitter } from 'langchain/text_splitter'
+import { PDFLoader } from 'langchain/document_loaders/fs/pdf'
 
 class Pdf_DocumentLoaders implements INode {
     label: string
@@ -13,10 +15,11 @@ class Pdf_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Pdf File'
         this.name = 'pdfFile'
-        this.type = 'PDF'
+        this.type = 'Document'
         this.icon = 'pdf.svg'
         this.category = 'Document Loaders'
         this.description = `Load data from PDF files`
+        this.baseClasses = [this.type]
         this.inputs = [
             {
                 label: 'Pdf File',
@@ -49,14 +52,8 @@ class Pdf_DocumentLoaders implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        return ['Document']
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { PDFLoader } = await import('langchain/document_loaders')
-
-        const textSplitter = nodeData.inputs?.textSplitter
+        const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
         const pdfFileBase64 = nodeData.inputs?.pdfFile as string
         const usage = nodeData.inputs?.usage as string
 
@@ -66,7 +63,8 @@ class Pdf_DocumentLoaders implements INode {
         const blob = new Blob([bf])
 
         if (usage === 'perFile') {
-            const loader = new PDFLoader(blob, { splitPages: false })
+            // @ts-ignore
+            const loader = new PDFLoader(blob, { splitPages: false, pdfjs: () => import('pdf-parse/lib/pdf.js/v1.10.100/build/pdf.js') })
             if (textSplitter) {
                 const docs = await loader.loadAndSplit(textSplitter)
                 return docs
@@ -75,7 +73,8 @@ class Pdf_DocumentLoaders implements INode {
                 return docs
             }
         } else {
-            const loader = new PDFLoader(blob)
+            // @ts-ignore
+            const loader = new PDFLoader(blob, { pdfjs: () => import('pdf-parse/lib/pdf.js/v1.10.100/build/pdf.js') })
             if (textSplitter) {
                 const docs = await loader.loadAndSplit(textSplitter)
                 return docs

packages/components/nodes/documentloaders/Text/Text.ts

@@ -1,4 +1,6 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { TextSplitter } from 'langchain/text_splitter'
+import { TextLoader } from 'langchain/document_loaders/fs/text'
 
 class Text_DocumentLoaders implements INode {
     label: string
@@ -13,10 +15,11 @@ class Text_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Text File'
         this.name = 'textFile'
-        this.type = 'Text'
+        this.type = 'Document'
         this.icon = 'textFile.svg'
         this.category = 'Document Loaders'
         this.description = `Load data from text files`
+        this.baseClasses = [this.type]
         this.inputs = [
             {
                 label: 'Txt File',
@@ -33,13 +36,8 @@ class Text_DocumentLoaders implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        return ['Document']
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { TextLoader } = await import('langchain/document_loaders')
-        const textSplitter = nodeData.inputs?.textSplitter
+        const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
         const txtFileBase64 = nodeData.inputs?.txtFile as string
         const splitDataURI = txtFileBase64.split(',')
         splitDataURI.pop()

packages/components/nodes/embeddings/CohereEmbedding/CohereEmbedding.ts

@@ -0,0 +1,40 @@
+import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses } from '../../../src/utils'
+import { CohereEmbeddings } from 'langchain/embeddings/cohere'
+
+class CohereEmbedding_Embeddings implements INode {
+    label: string
+    name: string
+    type: string
+    icon: string
+    category: string
+    description: string
+    baseClasses: string[]
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Cohere Embeddings'
+        this.name = 'cohereEmbeddings'
+        this.type = 'CohereEmbeddings'
+        this.icon = 'cohere.png'
+        this.category = 'Embeddings'
+        this.description = 'Cohere API to generate embeddings for a given text'
+        this.baseClasses = [this.type, ...getBaseClasses(CohereEmbeddings)]
+        this.inputs = [
+            {
+                label: 'Cohere API Key',
+                name: 'cohereApiKey',
+                type: 'password'
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData): Promise<any> {
+        const apiKey = nodeData.inputs?.cohereApiKey as string
+
+        const model = new CohereEmbeddings({ apiKey })
+        return model
+    }
+}
+
+module.exports = { nodeClass: CohereEmbedding_Embeddings }

packages/components/nodes/embeddings/OpenAIEmbedding/OpenAIEmbedding.ts

@@ -1,5 +1,6 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { OpenAIEmbeddings } from 'langchain/embeddings/openai'
 
 class OpenAIEmbedding_Embeddings implements INode {
     label: string
@@ -18,6 +19,7 @@ class OpenAIEmbedding_Embeddings implements INode {
         this.icon = 'openai.png'
         this.category = 'Embeddings'
         this.description = 'OpenAI API to generate embeddings for a given text'
+        this.baseClasses = [this.type, ...getBaseClasses(OpenAIEmbeddings)]
         this.inputs = [
             {
                 label: 'OpenAI Api Key',
@@ -27,13 +29,7 @@ class OpenAIEmbedding_Embeddings implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        const { OpenAIEmbeddings } = await import('langchain/embeddings')
-        return getBaseClasses(OpenAIEmbeddings)
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { OpenAIEmbeddings } = await import('langchain/embeddings')
         const openAIApiKey = nodeData.inputs?.openAIApiKey as string
 
         const model = new OpenAIEmbeddings({ openAIApiKey })

packages/components/nodes/llms/HuggingFaceInference/HuggingFaceInference.ts

@@ -1,5 +1,6 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { HuggingFaceInference } from 'langchain/llms/hf'
 
 class HuggingFaceInference_LLMs implements INode {
     label: string
@@ -17,7 +18,8 @@ class HuggingFaceInference_LLMs implements INode {
         this.type = 'HuggingFaceInference'
         this.icon = 'huggingface.png'
         this.category = 'LLMs'
-        this.description = 'Wrapper around OpenAI large language models'
+        this.description = 'Wrapper around HuggingFace large language models'
+        this.baseClasses = [this.type, ...getBaseClasses(HuggingFaceInference)]
         this.inputs = [
             {
                 label: 'Model',
@@ -42,14 +44,7 @@ class HuggingFaceInference_LLMs implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        const { HuggingFaceInference } = await import('langchain/llms')
-        return getBaseClasses(HuggingFaceInference)
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { HuggingFaceInference } = await import('langchain/llms')
-
         const temperature = nodeData.inputs?.temperature as string
         const model = nodeData.inputs?.model as string
 

packages/components/nodes/llms/OpenAI/OpenAI.ts

@@ -1,5 +1,6 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { OpenAI } from 'langchain/llms/openai'
 
 class OpenAI_LLMs implements INode {
     label: string
@@ -18,6 +19,7 @@ class OpenAI_LLMs implements INode {
         this.icon = 'openai.png'
         this.category = 'LLMs'
         this.description = 'Wrapper around OpenAI large language models'
+        this.baseClasses = [this.type, ...getBaseClasses(OpenAI)]
         this.inputs = [
             {
                 label: 'OpenAI Api Key',
@@ -59,14 +61,7 @@ class OpenAI_LLMs implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        const { OpenAI } = await import('langchain/llms')
-        return getBaseClasses(OpenAI)
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { OpenAI } = await import('langchain/llms')
-
         const temperature = nodeData.inputs?.temperature as string
         const modelName = nodeData.inputs?.modelName as string
         const openAIApiKey = nodeData.inputs?.openAIApiKey as string

packages/components/nodes/memory/BufferMemory/BufferMemory.ts

@@ -1,5 +1,6 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { BufferMemory } from 'langchain/memory'
 
 class BufferMemory_Memory implements INode {
     label: string
@@ -17,7 +18,8 @@ class BufferMemory_Memory implements INode {
         this.type = 'BufferMemory'
         this.icon = 'memory.svg'
         this.category = 'Memory'
-        this.description = 'Perform calculations on response'
+        this.description = 'Remembers previous conversational back and forths directly'
+        this.baseClasses = [this.type, ...getBaseClasses(BufferMemory)]
         this.inputs = [
             {
                 label: 'Memory Key',
@@ -34,13 +36,7 @@ class BufferMemory_Memory implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        const { BufferMemory } = await import('langchain/memory')
-        return getBaseClasses(BufferMemory)
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { BufferMemory } = await import('langchain/memory')
         const memoryKey = nodeData.inputs?.memoryKey as string
         const inputKey = nodeData.inputs?.inputKey as string
         return new BufferMemory({

packages/components/nodes/prompts/ChatPromptTemplate/ChatPromptTemplate.ts

@@ -1,5 +1,6 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate } from 'langchain/prompts'
 
 class ChatPromptTemplate_Prompts implements INode {
     label: string
@@ -18,6 +19,7 @@ class ChatPromptTemplate_Prompts implements INode {
         this.icon = 'prompt.svg'
         this.category = 'Prompts'
         this.description = 'Schema to represent a chat prompt'
+        this.baseClasses = [this.type, ...getBaseClasses(ChatPromptTemplate)]
         this.inputs = [
             {
                 label: 'System Message',
@@ -36,13 +38,7 @@ class ChatPromptTemplate_Prompts implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        const { ChatPromptTemplate } = await import('langchain/prompts')
-        return getBaseClasses(ChatPromptTemplate)
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate } = await import('langchain/prompts')
         const systemMessagePrompt = nodeData.inputs?.systemMessagePrompt as string
         const humanMessagePrompt = nodeData.inputs?.humanMessagePrompt as string
 

packages/components/nodes/prompts/FewShotPromptTemplate/FewShotPromptTemplate.ts

@@ -1,5 +1,8 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses, getInputVariables } from '../../../src/utils'
+import { FewShotPromptTemplate, FewShotPromptTemplateInput, PromptTemplate } from 'langchain/prompts'
+import { Example } from 'langchain/schema'
+import { TemplateFormat } from 'langchain/dist/prompts/template'
 
 class FewShotPromptTemplate_Prompts implements INode {
     label: string
@@ -18,6 +21,7 @@ class FewShotPromptTemplate_Prompts implements INode {
         this.icon = 'prompt.svg'
         this.category = 'Prompts'
         this.description = 'Prompt template you can build with examples'
+        this.baseClasses = [this.type, ...getBaseClasses(FewShotPromptTemplate)]
         this.inputs = [
             {
                 label: 'Examples',
@@ -32,7 +36,7 @@ class FewShotPromptTemplate_Prompts implements INode {
             {
                 label: 'Example Prompt',
                 name: 'examplePrompt',
-                type: 'BasePromptTemplate'
+                type: 'PromptTemplate'
             },
             {
                 label: 'Prefix',
@@ -73,27 +77,19 @@ class FewShotPromptTemplate_Prompts implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        const { FewShotPromptTemplate } = await import('langchain/prompts')
-        return getBaseClasses(FewShotPromptTemplate)
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { FewShotPromptTemplate } = await import('langchain/prompts')
-
         const examplesStr = nodeData.inputs?.examples as string
-
         const prefix = nodeData.inputs?.prefix as string
         const suffix = nodeData.inputs?.suffix as string
         const exampleSeparator = nodeData.inputs?.exampleSeparator as string
-        const templateFormat = nodeData.inputs?.templateFormat
-        const examplePrompt = nodeData.inputs?.examplePrompt
+        const templateFormat = nodeData.inputs?.templateFormat as TemplateFormat
+        const examplePrompt = nodeData.inputs?.examplePrompt as PromptTemplate
 
         const inputVariables = getInputVariables(suffix)
-        const examples = JSON.parse(examplesStr.replace(/\s/g, ''))
+        const examples: Example[] = JSON.parse(examplesStr.replace(/\s/g, ''))
 
         try {
-            const prompt = new FewShotPromptTemplate({
+            const obj: FewShotPromptTemplateInput = {
                 examples,
                 examplePrompt,
                 prefix,
@@ -101,7 +97,8 @@ class FewShotPromptTemplate_Prompts implements INode {
                 inputVariables,
                 exampleSeparator,
                 templateFormat
-            })
+            }
+            const prompt = new FewShotPromptTemplate(obj)
             return prompt
         } catch (e) {
             throw new Error(e)

packages/components/nodes/prompts/PromptTemplate/PromptTemplate.ts

@@ -1,5 +1,6 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses, getInputVariables } from '../../../src/utils'
+import { PromptTemplate, PromptTemplateInput } from 'langchain/prompts'
 
 class PromptTemplate_Prompts implements INode {
     label: string
@@ -18,6 +19,7 @@ class PromptTemplate_Prompts implements INode {
         this.icon = 'prompt.svg'
         this.category = 'Prompts'
         this.description = 'Schema to represent a basic prompt for an LLM'
+        this.baseClasses = [this.type, ...getBaseClasses(PromptTemplate)]
         this.inputs = [
             {
                 label: 'Template',
@@ -29,19 +31,12 @@ class PromptTemplate_Prompts implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        const { PromptTemplate } = await import('langchain/prompts')
-        return getBaseClasses(PromptTemplate)
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { PromptTemplate } = await import('langchain/prompts')
-
         const template = nodeData.inputs?.template as string
         const inputVariables = getInputVariables(template)
 
         try {
-            const options = {
+            const options: PromptTemplateInput = {
                 template,
                 inputVariables
             }

packages/components/nodes/textsplitters/RecursiveCharacterTextSplitter/RecursiveCharacterTextSplitter.ts

@@ -1,5 +1,6 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { RecursiveCharacterTextSplitter, RecursiveCharacterTextSplitterParams } from 'langchain/text_splitter'
 
 class RecursiveCharacterTextSplitter_TextSplitters implements INode {
     label: string
@@ -18,6 +19,7 @@ class RecursiveCharacterTextSplitter_TextSplitters implements INode {
         this.icon = 'textsplitter.svg'
         this.category = 'Text Splitters'
         this.description = `Split documents recursively by different characters - starting with "\n\n", then "\n", then " "`
+        this.baseClasses = [this.type, ...getBaseClasses(RecursiveCharacterTextSplitter)]
         this.inputs = [
             {
                 label: 'Chunk Size',
@@ -35,17 +37,11 @@ class RecursiveCharacterTextSplitter_TextSplitters implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        const { RecursiveCharacterTextSplitter } = await import('langchain/text_splitter')
-        return getBaseClasses(RecursiveCharacterTextSplitter)
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { RecursiveCharacterTextSplitter } = await import('langchain/text_splitter')
         const chunkSize = nodeData.inputs?.chunkSize as string
         const chunkOverlap = nodeData.inputs?.chunkOverlap as string
 
-        const obj = {} as any
+        const obj = {} as RecursiveCharacterTextSplitterParams
 
         if (chunkSize) obj.chunkSize = parseInt(chunkSize, 10)
         if (chunkOverlap) obj.chunkOverlap = parseInt(chunkOverlap, 10)

packages/components/nodes/tools/Calculator/Calculator.ts

@@ -1,7 +1,8 @@
 import { INode } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { Calculator } from 'langchain/tools/calculator'
 
-class Calculator implements INode {
+class Calculator_Tools implements INode {
     label: string
     name: string
     description: string
@@ -17,17 +18,12 @@ class Calculator implements INode {
         this.icon = 'calculator.svg'
         this.category = 'Tools'
         this.description = 'Perform calculations on response'
-    }
-
-    async getBaseClasses(): Promise<string[]> {
-        const { Calculator } = await import('langchain/tools')
-        return getBaseClasses(Calculator)
+        this.baseClasses = [this.type, ...getBaseClasses(Calculator)]
     }
 
     async init(): Promise<any> {
-        const { Calculator } = await import('langchain/tools')
         return new Calculator()
     }
 }
 
-module.exports = { nodeClass: Calculator }
+module.exports = { nodeClass: Calculator_Tools }

packages/components/nodes/tools/RequestsGet/RequestsGet.ts

@@ -0,0 +1,29 @@
+import { INode } from '../../../src/Interface'
+import { getBaseClasses } from '../../../src/utils'
+import { RequestsGetTool } from 'langchain/tools'
+
+class RequestsGet_Tools implements INode {
+    label: string
+    name: string
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+
+    constructor() {
+        this.label = 'Requests Get'
+        this.name = 'requestsGet'
+        this.type = 'RequestsGet'
+        this.icon = 'requestsget.svg'
+        this.category = 'Tools'
+        this.description = 'Execute HTTP GET requests'
+        this.baseClasses = [this.type, ...getBaseClasses(RequestsGetTool)]
+    }
+
+    async init(): Promise<any> {
+        return new RequestsGetTool()
+    }
+}
+
+module.exports = { nodeClass: RequestsGet_Tools }

packages/components/nodes/tools/RequestsGet/requestsget.svg

@@ -0,0 +1,8 @@
+<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-http-get" 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 8h-2a2 2 0 0 0 -2 2v4a2 2 0 0 0 2 2h2v-4h-1"></path>
+   <path d="M14 8h-4v8h4"></path>
+   <path d="M10 12h2.5"></path>
+   <path d="M17 8h4"></path>
+   <path d="M19 8v8"></path>
+</svg>

packages/components/nodes/tools/RequestsPost/RequestsPost.ts

@@ -0,0 +1,29 @@
+import { INode } from '../../../src/Interface'
+import { getBaseClasses } from '../../../src/utils'
+import { RequestsPostTool } from 'langchain/tools'
+
+class RequestsPost_Tools implements INode {
+    label: string
+    name: string
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+
+    constructor() {
+        this.label = 'Requests Post'
+        this.name = 'requestsPost'
+        this.type = 'RequestsPost'
+        this.icon = 'requestspost.svg'
+        this.category = 'Tools'
+        this.description = 'Execute HTTP POST requests'
+        this.baseClasses = [this.type, ...getBaseClasses(RequestsPostTool)]
+    }
+
+    async init(): Promise<any> {
+        return new RequestsPostTool()
+    }
+}
+
+module.exports = { nodeClass: RequestsPost_Tools }

packages/components/nodes/tools/RequestsPost/requestspost.svg

@@ -0,0 +1,6 @@
+<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-http-post" 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="M3 12h2a2 2 0 1 0 0 -4h-2v8"></path>
+   <path d="M12 8a2 2 0 0 1 2 2v4a2 2 0 1 1 -4 0v-4a2 2 0 0 1 2 -2z"></path>
+   <path d="M17 15a1 1 0 0 0 1 1h2a1 1 0 0 0 1 -1v-2a1 1 0 0 0 -1 -1h-2a1 1 0 0 1 -1 -1v-2a1 1 0 0 1 1 -1h2a1 1 0 0 1 1 1"></path>
+</svg>

packages/components/nodes/tools/SerpAPI/SerpAPI.ts

@@ -1,7 +1,8 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { SerpAPI } from 'langchain/tools'
 
-class SerpAPI implements INode {
+class SerpAPI_Tools implements INode {
     label: string
     name: string
     description: string
@@ -25,18 +26,13 @@ class SerpAPI implements INode {
                 type: 'password'
             }
         ]
-    }
-
-    async getBaseClasses(): Promise<string[]> {
-        const { SerpAPI } = await import('langchain/tools')
-        return getBaseClasses(SerpAPI)
+        this.baseClasses = [this.type, ...getBaseClasses(SerpAPI)]
     }
 
     async init(nodeData: INodeData): Promise<any> {
-        const { SerpAPI } = await import('langchain/tools')
         const apiKey = nodeData.inputs?.apiKey as string
         return new SerpAPI(apiKey)
     }
 }
 
-module.exports = { nodeClass: SerpAPI }
+module.exports = { nodeClass: SerpAPI_Tools }

packages/components/nodes/vectorstores/Chroma_Existing/Chroma_Existing.ts

@@ -1,4 +1,6 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { Chroma } from 'langchain/vectorstores/chroma'
+import { Embeddings } from 'langchain/embeddings/base'
 
 class Chroma_Existing_VectorStores implements INode {
     label: string
@@ -17,6 +19,7 @@ class Chroma_Existing_VectorStores implements INode {
         this.icon = 'chroma.svg'
         this.category = 'Vector Stores'
         this.description = 'Load existing index from Chroma (i.e: Document has been upserted)'
+        this.baseClasses = [this.type, 'BaseRetriever']
         this.inputs = [
             {
                 label: 'Embeddings',
@@ -31,15 +34,9 @@ class Chroma_Existing_VectorStores implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        return ['BaseRetriever']
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { Chroma } = await import('langchain/vectorstores')
-
         const collectionName = nodeData.inputs?.collectionName as string
-        const embeddings = nodeData.inputs?.embeddings
+        const embeddings = nodeData.inputs?.embeddings as Embeddings
 
         const vectorStore = await Chroma.fromExistingCollection(embeddings, {
             collectionName

packages/components/nodes/vectorstores/Chroma_Upsert/Chroma_Upsert.ts

@@ -1,4 +1,7 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { Chroma } from 'langchain/vectorstores/chroma'
+import { Embeddings } from 'langchain/embeddings/base'
+import { Document } from 'langchain/document'
 
 class ChromaUpsert_VectorStores implements INode {
     label: string
@@ -17,6 +20,7 @@ class ChromaUpsert_VectorStores implements INode {
         this.icon = 'chroma.svg'
         this.category = 'Vector Stores'
         this.description = 'Upsert documents to Chroma'
+        this.baseClasses = [this.type, 'BaseRetriever']
         this.inputs = [
             {
                 label: 'Document',
@@ -36,28 +40,20 @@ class ChromaUpsert_VectorStores implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        return ['BaseRetriever']
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { Chroma } = await import('langchain/vectorstores')
-        const { Document } = await import('langchain/document')
-
         const collectionName = nodeData.inputs?.collectionName as string
-        const docs = nodeData.inputs?.document
-        const embeddings = nodeData.inputs?.embeddings
+        const docs = nodeData.inputs?.document as Document[]
+        const embeddings = nodeData.inputs?.embeddings as Embeddings
 
         const finalDocs = []
         for (let i = 0; i < docs.length; i += 1) {
             finalDocs.push(new Document(docs[i]))
         }
 
-        const result = await Chroma.fromDocuments(finalDocs, embeddings, {
+        const vectorStore = await Chroma.fromDocuments(finalDocs, embeddings, {
             collectionName
         })
-
-        const retriever = result.asRetriever()
+        const retriever = vectorStore.asRetriever()
         return retriever
     }
 }

packages/components/nodes/vectorstores/Pinecone_Existing/Pinecone_Existing.ts

@@ -1,5 +1,7 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { PineconeClient } from '@pinecone-database/pinecone'
+import { PineconeStore } from 'langchain/vectorstores/pinecone'
+import { Embeddings } from 'langchain/embeddings/base'
 
 class Pinecone_Existing_VectorStores implements INode {
     label: string
@@ -18,6 +20,7 @@ class Pinecone_Existing_VectorStores implements INode {
         this.icon = 'pinecone.png'
         this.category = 'Vector Stores'
         this.description = 'Load existing index from Pinecone (i.e: Document has been upserted)'
+        this.baseClasses = [this.type, 'BaseRetriever']
         this.inputs = [
             {
                 label: 'Embeddings',
@@ -42,17 +45,11 @@ class Pinecone_Existing_VectorStores implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        return ['BaseRetriever']
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { PineconeStore } = await import('langchain/vectorstores')
-
         const pineconeApiKey = nodeData.inputs?.pineconeApiKey as string
         const pineconeEnv = nodeData.inputs?.pineconeEnv as string
         const index = nodeData.inputs?.pineconeIndex as string
-        const embeddings = nodeData.inputs?.embeddings
+        const embeddings = nodeData.inputs?.embeddings as Embeddings
 
         const client = new PineconeClient()
         await client.init({

packages/components/nodes/vectorstores/Pinecone_Upsert/Pinecone_Upsert.ts

@@ -1,5 +1,8 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { PineconeClient } from '@pinecone-database/pinecone'
+import { PineconeStore } from 'langchain/vectorstores/pinecone'
+import { Embeddings } from 'langchain/embeddings/base'
+import { Document } from 'langchain/document'
 
 class PineconeUpsert_VectorStores implements INode {
     label: string
@@ -18,6 +21,7 @@ class PineconeUpsert_VectorStores implements INode {
         this.icon = 'pinecone.png'
         this.category = 'Vector Stores'
         this.description = 'Upsert documents to Pinecone'
+        this.baseClasses = [this.type, 'BaseRetriever']
         this.inputs = [
             {
                 label: 'Document',
@@ -47,19 +51,12 @@ class PineconeUpsert_VectorStores implements INode {
         ]
     }
 
-    async getBaseClasses(): Promise<string[]> {
-        return ['BaseRetriever']
-    }
-
     async init(nodeData: INodeData): Promise<any> {
-        const { PineconeStore } = await import('langchain/vectorstores')
-        const { Document } = await import('langchain/document')
-
         const pineconeApiKey = nodeData.inputs?.pineconeApiKey as string
         const pineconeEnv = nodeData.inputs?.pineconeEnv as string
         const index = nodeData.inputs?.pineconeIndex as string
-        const docs = nodeData.inputs?.document
-        const embeddings = nodeData.inputs?.embeddings
+        const docs = nodeData.inputs?.document as Document[]
+        const embeddings = nodeData.inputs?.embeddings as Embeddings
 
         const client = new PineconeClient()
         await client.init({
@@ -74,11 +71,10 @@ class PineconeUpsert_VectorStores implements INode {
             finalDocs.push(new Document(docs[i]))
         }
 
-        const result = await PineconeStore.fromDocuments(finalDocs, embeddings, {
+        const vectorStore = await PineconeStore.fromDocuments(finalDocs, embeddings, {
             pineconeIndex
         })
-
-        const retriever = result.asRetriever()
+        const retriever = vectorStore.asRetriever()
         return retriever
     }
 }

packages/components/package.json

@@ -1,6 +1,6 @@
 {
     "name": "flowise-components",
-    "version": "1.0.0",
+    "version": "1.1.1",
     "description": "Flowiseai Components",
     "main": "dist/src/index",
     "types": "dist/src/index.d.ts",
@@ -20,15 +20,17 @@
         "@huggingface/inference": "^1.6.3",
         "@pinecone-database/pinecone": "^0.0.12",
         "axios": "^0.27.2",
+        "cheerio": "^1.0.0-rc.12",
         "chromadb": "^1.3.1",
+        "cohere-ai": "^6.2.0",
+        "d3-dsv": "2",
         "dotenv": "^16.0.0",
         "express": "^4.17.3",
         "form-data": "^4.0.0",
-        "langchain": "^0.0.44",
+        "langchain": "^0.0.53",
         "moment": "^2.29.3",
         "node-fetch": "2",
-        "pdfjs-dist": "^3.5.141",
-        "uuid": "^9.0.0",
+        "pdf-parse": "^1.1.1",
         "ws": "^8.9.0"
     },
     "devDependencies": {

packages/components/src/Interface.ts

@@ -75,7 +75,6 @@ export interface INodeProperties {
 
 export interface INode extends INodeProperties {
     inputs?: INodeParams[]
-    getBaseClasses?(): Promise<string[]>
     getInstance?(nodeData: INodeData): Promise<string>
     run?(nodeData: INodeData, input: string, options?: ICommonObject): Promise<string>
 }

packages/components/tsconfig.json

@@ -14,8 +14,7 @@
         "strictPropertyInitialization": false,
         "useUnknownInCatchVariables": false,
         "declaration": true,
-        "module": "commonjs",
-        "moduleResolution": "node16"
+        "module": "commonjs"
     },
     "include": ["src", "nodes"]
 }

packages/server/README.md

@@ -38,7 +38,7 @@ Feel free to ask any questions, raise problems, and request new features in [dis
 
 ## 🙌 Contributing
 
-See [contributing guide](https://github.com/FlowiseAI/Flowise/blob/master/CONTRIBUTING.md). Reach out to us at [Discord](https://discord.gg/GWcGczPk) if you have any questions or issues.
+See [contributing guide](https://github.com/FlowiseAI/Flowise/blob/master/CONTRIBUTING.md). Reach out to us at [Discord](https://discord.gg/7C5xTWP8) if you have any questions or issues.
 
 ## 📄 License
 

packages/server/marketplaces/Antonym.json

@@ -3,11 +3,58 @@
     "nodes": [
         {
             "width": 300,
-            "height": 885,
+            "height": 360,
+            "id": "promptTemplate_0",
+            "position": {
+                "x": 294.38456937448433,
+                "y": 66.5400435451831
+            },
+            "type": "customNode",
+            "data": {
+                "id": "promptTemplate_0",
+                "label": "Prompt Template",
+                "name": "promptTemplate",
+                "type": "PromptTemplate",
+                "baseClasses": ["PromptTemplate", "BaseStringPromptTemplate", "BasePromptTemplate"],
+                "category": "Prompts",
+                "description": "Schema to represent a basic prompt for an LLM",
+                "inputParams": [
+                    {
+                        "label": "Template",
+                        "name": "template",
+                        "type": "string",
+                        "rows": 5,
+                        "placeholder": "What is a good name for a company that makes {product}?"
+                    }
+                ],
+                "inputAnchors": [],
+                "inputs": {
+                    "template": "Word: {word}\\nAntonym: {antonym}\\n"
+                },
+                "outputAnchors": [
+                    {
+                        "id": "promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate",
+                        "name": "promptTemplate",
+                        "label": "PromptTemplate",
+                        "type": "PromptTemplate | BaseStringPromptTemplate | BasePromptTemplate"
+                    }
+                ],
+                "selected": false
+            },
+            "selected": false,
+            "positionAbsolute": {
+                "x": 294.38456937448433,
+                "y": 66.5400435451831
+            },
+            "dragging": false
+        },
+        {
+            "width": 300,
+            "height": 886,
             "id": "fewShotPromptTemplate_0",
             "position": {
-                "x": 495.78246013667433,
-                "y": 168.3684510250569
+                "x": 719.2200337843097,
+                "y": 67.20405755860693
             },
             "type": "customNode",
             "data": {
@@ -15,7 +62,7 @@
                 "label": "Few Shot Prompt Template",
                 "name": "fewShotPromptTemplate",
                 "type": "FewShotPromptTemplate",
-                "baseClasses": ["BaseStringPromptTemplate", "BasePromptTemplate"],
+                "baseClasses": ["FewShotPromptTemplate", "BaseStringPromptTemplate", "BasePromptTemplate"],
                 "category": "Prompts",
                 "description": "Prompt template you can build with examples",
                 "inputParams": [
@@ -24,7 +71,7 @@
                         "name": "examples",
                         "type": "string",
                         "rows": 5,
-                        "placeholder": "[\n  { word: \"happy\", antonym: \"sad\" },\n  { word: \"tall\", antonym: \"short\" },\n]"
+                        "placeholder": "[\n  { \"word\": \"happy\", \"antonym\": \"sad\" },\n  { \"word\": \"tall\", \"antonym\": \"short\" },\n]"
                     },
                     {
                         "label": "Prefix",
@@ -67,12 +114,12 @@
                     {
                         "label": "Example Prompt",
                         "name": "examplePrompt",
-                        "type": "BasePromptTemplate",
-                        "id": "fewShotPromptTemplate_0-input-examplePrompt-BasePromptTemplate"
+                        "type": "PromptTemplate",
+                        "id": "fewShotPromptTemplate_0-input-examplePrompt-PromptTemplate"
                     }
                 ],
                 "inputs": {
-                    "examples": "[\n    { \"word\": \"happy\", \"antonym\": \"sad\" },\n    { \"word\": \"tall\", \"antonym\": \"short\" }\n]",
+                    "examples": "[\n  { \"word\": \"happy\", \"antonym\": \"sad\" },\n  { \"word\": \"tall\", \"antonym\": \"short\" }\n]",
                     "examplePrompt": "{{promptTemplate_0.data.instance}}",
                     "prefix": "Give the antonym of every input",
                     "suffix": "Word: {input}\\nAntonym:",
@@ -81,128 +128,28 @@
                 },
                 "outputAnchors": [
                     {
-                        "id": "fewShotPromptTemplate_0-output-fewShotPromptTemplate-BaseStringPromptTemplate|BasePromptTemplate",
+                        "id": "fewShotPromptTemplate_0-output-fewShotPromptTemplate-FewShotPromptTemplate|BaseStringPromptTemplate|BasePromptTemplate",
                         "name": "fewShotPromptTemplate",
                         "label": "FewShotPromptTemplate",
-                        "type": "BaseStringPromptTemplate | BasePromptTemplate"
+                        "type": "FewShotPromptTemplate | BaseStringPromptTemplate | BasePromptTemplate"
                     }
                 ],
                 "selected": false
             },
             "selected": false,
             "positionAbsolute": {
-                "x": 495.78246013667433,
-                "y": 168.3684510250569
+                "x": 719.2200337843097,
+                "y": 67.20405755860693
             },
             "dragging": false
         },
         {
             "width": 300,
-            "height": 359,
-            "id": "promptTemplate_0",
-            "position": {
-                "x": 13.229214123006699,
-                "y": 171.79555808656028
-            },
-            "type": "customNode",
-            "data": {
-                "id": "promptTemplate_0",
-                "label": "Prompt Template",
-                "name": "promptTemplate",
-                "type": "PromptTemplate",
-                "baseClasses": ["BaseStringPromptTemplate", "BasePromptTemplate"],
-                "category": "Prompts",
-                "description": "Schema to represent a basic prompt for an LLM",
-                "inputParams": [
-                    {
-                        "label": "Template",
-                        "name": "template",
-                        "type": "string",
-                        "rows": 5,
-                        "placeholder": "What is a good name for a company that makes {product}?"
-                    }
-                ],
-                "inputAnchors": [],
-                "inputs": {
-                    "template": "Word: {word}\\nAntonym: {antonym}\\n"
-                },
-                "outputAnchors": [
-                    {
-                        "id": "promptTemplate_0-output-promptTemplate-BaseStringPromptTemplate|BasePromptTemplate",
-                        "name": "promptTemplate",
-                        "label": "PromptTemplate",
-                        "type": "BaseStringPromptTemplate | BasePromptTemplate"
-                    }
-                ],
-                "selected": false
-            },
-            "selected": false,
-            "positionAbsolute": {
-                "x": 13.229214123006699,
-                "y": 171.79555808656028
-            },
-            "dragging": false
-        },
-        {
-            "width": 300,
-            "height": 279,
-            "id": "llmChain_0",
-            "position": {
-                "x": 1237.4411644942688,
-                "y": 508.82448993622904
-            },
-            "type": "customNode",
-            "data": {
-                "id": "llmChain_0",
-                "label": "LLM Chain",
-                "name": "llmChain",
-                "type": "LLMChain",
-                "baseClasses": ["BaseChain"],
-                "category": "Chains",
-                "description": "Chain to run queries against LLMs",
-                "inputParams": [],
-                "inputAnchors": [
-                    {
-                        "label": "LLM",
-                        "name": "llm",
-                        "type": "BaseLanguageModel",
-                        "id": "llmChain_0-input-llm-BaseLanguageModel"
-                    },
-                    {
-                        "label": "Prompt",
-                        "name": "prompt",
-                        "type": "BasePromptTemplate",
-                        "id": "llmChain_0-input-prompt-BasePromptTemplate"
-                    }
-                ],
-                "inputs": {
-                    "llm": "{{openAI_0.data.instance}}",
-                    "prompt": "{{fewShotPromptTemplate_0.data.instance}}"
-                },
-                "outputAnchors": [
-                    {
-                        "id": "llmChain_0-output-llmChain-BaseChain",
-                        "name": "llmChain",
-                        "label": "LLMChain",
-                        "type": "BaseChain"
-                    }
-                ],
-                "selected": false
-            },
-            "selected": false,
-            "positionAbsolute": {
-                "x": 1237.4411644942688,
-                "y": 508.82448993622904
-            },
-            "dragging": false
-        },
-        {
-            "width": 300,
-            "height": 471,
+            "height": 472,
             "id": "openAI_0",
             "position": {
-                "x": 859.220671981777,
-                "y": 166.25170842824588
+                "x": 1089.6434062122398,
+                "y": 27.515288538129425
             },
             "type": "customNode",
             "data": {
@@ -210,7 +157,7 @@
                 "label": "OpenAI",
                 "name": "openAI",
                 "type": "OpenAI",
-                "baseClasses": ["BaseLLM", "BaseLanguageModel"],
+                "baseClasses": ["OpenAI", "BaseLLM", "BaseLanguageModel"],
                 "category": "LLMs",
                 "description": "Wrapper around OpenAI large language models",
                 "inputParams": [
@@ -259,18 +206,81 @@
                 },
                 "outputAnchors": [
                     {
-                        "id": "openAI_0-output-openAI-BaseLLM|BaseLanguageModel",
+                        "id": "openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel",
                         "name": "openAI",
                         "label": "OpenAI",
-                        "type": "BaseLLM | BaseLanguageModel"
+                        "type": "OpenAI | BaseLLM | BaseLanguageModel"
                     }
                 ],
                 "selected": false
             },
             "selected": false,
             "positionAbsolute": {
-                "x": 859.220671981777,
-                "y": 166.25170842824588
+                "x": 1089.6434062122398,
+                "y": 27.515288538129425
+            },
+            "dragging": false
+        },
+        {
+            "width": 300,
+            "height": 461,
+            "id": "llmChain_0",
+            "position": {
+                "x": 1499.2654451385026,
+                "y": 356.3275374721362
+            },
+            "type": "customNode",
+            "data": {
+                "id": "llmChain_0",
+                "label": "LLM Chain",
+                "name": "llmChain",
+                "type": "LLMChain",
+                "baseClasses": ["LLMChain", "BaseChain"],
+                "category": "Chains",
+                "description": "Chain to run queries against LLMs",
+                "inputParams": [
+                    {
+                        "label": "Format Prompt Values",
+                        "name": "promptValues",
+                        "type": "string",
+                        "rows": 5,
+                        "placeholder": "{\n  \"input_language\": \"English\",\n  \"output_language\": \"French\"\n}",
+                        "optional": true
+                    }
+                ],
+                "inputAnchors": [
+                    {
+                        "label": "Language Model",
+                        "name": "model",
+                        "type": "BaseLanguageModel",
+                        "id": "llmChain_0-input-model-BaseLanguageModel"
+                    },
+                    {
+                        "label": "Prompt",
+                        "name": "prompt",
+                        "type": "BasePromptTemplate",
+                        "id": "llmChain_0-input-prompt-BasePromptTemplate"
+                    }
+                ],
+                "inputs": {
+                    "model": "{{openAI_0.data.instance}}",
+                    "prompt": "{{fewShotPromptTemplate_0.data.instance}}",
+                    "promptValues": ""
+                },
+                "outputAnchors": [
+                    {
+                        "id": "llmChain_0-output-llmChain-LLMChain|BaseChain",
+                        "name": "llmChain",
+                        "label": "LLMChain",
+                        "type": "LLMChain | BaseChain"
+                    }
+                ],
+                "selected": false
+            },
+            "selected": false,
+            "positionAbsolute": {
+                "x": 1499.2654451385026,
+                "y": 356.3275374721362
             },
             "dragging": false
         }
@@ -278,33 +288,33 @@
     "edges": [
         {
             "source": "promptTemplate_0",
-            "sourceHandle": "promptTemplate_0-output-promptTemplate-BaseStringPromptTemplate|BasePromptTemplate",
+            "sourceHandle": "promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate",
             "target": "fewShotPromptTemplate_0",
-            "targetHandle": "fewShotPromptTemplate_0-input-examplePrompt-BasePromptTemplate",
+            "targetHandle": "fewShotPromptTemplate_0-input-examplePrompt-PromptTemplate",
             "type": "buttonedge",
-            "id": "promptTemplate_0-promptTemplate_0-output-promptTemplate-BaseStringPromptTemplate|BasePromptTemplate-fewShotPromptTemplate_0-fewShotPromptTemplate_0-input-examplePrompt-BasePromptTemplate",
-            "data": {
-                "label": ""
-            }
-        },
-        {
-            "source": "fewShotPromptTemplate_0",
-            "sourceHandle": "fewShotPromptTemplate_0-output-fewShotPromptTemplate-BaseStringPromptTemplate|BasePromptTemplate",
-            "target": "llmChain_0",
-            "targetHandle": "llmChain_0-input-prompt-BasePromptTemplate",
-            "type": "buttonedge",
-            "id": "fewShotPromptTemplate_0-fewShotPromptTemplate_0-output-fewShotPromptTemplate-BaseStringPromptTemplate|BasePromptTemplate-llmChain_0-llmChain_0-input-prompt-BasePromptTemplate",
+            "id": "promptTemplate_0-promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate-fewShotPromptTemplate_0-fewShotPromptTemplate_0-input-examplePrompt-PromptTemplate",
             "data": {
                 "label": ""
             }
         },
         {
             "source": "openAI_0",
-            "sourceHandle": "openAI_0-output-openAI-BaseLLM|BaseLanguageModel",
+            "sourceHandle": "openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel",
             "target": "llmChain_0",
-            "targetHandle": "llmChain_0-input-llm-BaseLanguageModel",
+            "targetHandle": "llmChain_0-input-model-BaseLanguageModel",
             "type": "buttonedge",
-            "id": "openAI_0-openAI_0-output-openAI-BaseLLM|BaseLanguageModel-llmChain_0-llmChain_0-input-llm-BaseLanguageModel",
+            "id": "openAI_0-openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel-llmChain_0-llmChain_0-input-model-BaseLanguageModel",
+            "data": {
+                "label": ""
+            }
+        },
+        {
+            "source": "fewShotPromptTemplate_0",
+            "sourceHandle": "fewShotPromptTemplate_0-output-fewShotPromptTemplate-FewShotPromptTemplate|BaseStringPromptTemplate|BasePromptTemplate",
+            "target": "llmChain_0",
+            "targetHandle": "llmChain_0-input-prompt-BasePromptTemplate",
+            "type": "buttonedge",
+            "id": "fewShotPromptTemplate_0-fewShotPromptTemplate_0-output-fewShotPromptTemplate-FewShotPromptTemplate|BaseStringPromptTemplate|BasePromptTemplate-llmChain_0-llmChain_0-input-prompt-BasePromptTemplate",
             "data": {
                 "label": ""
             }

packages/server/marketplaces/Conversational Agent.json

@@ -3,11 +3,11 @@
     "nodes": [
         {
             "width": 300,
-            "height": 277,
+            "height": 278,
             "id": "serpAPI_0",
             "position": {
-                "x": 738.3791942291381,
-                "y": 61.26790912730354
+                "x": 509.0449726750261,
+                "y": 40.29354052812607
             },
             "type": "customNode",
             "data": {
@@ -15,7 +15,7 @@
                 "label": "Serp API",
                 "name": "serpAPI",
                 "type": "SerpAPI",
-                "baseClasses": ["Tool"],
+                "baseClasses": ["SerpAPI", "Tool"],
                 "category": "Tools",
                 "description": "Wrapper around SerpAPI - a real-time API to access Google search results",
                 "inputParams": [
@@ -29,28 +29,28 @@
                 "inputs": {},
                 "outputAnchors": [
                     {
-                        "id": "serpAPI_0-output-serpAPI-Tool",
+                        "id": "serpAPI_0-output-serpAPI-SerpAPI|Tool",
                         "name": "serpAPI",
                         "label": "SerpAPI",
-                        "type": "Tool"
+                        "type": "SerpAPI | Tool"
                     }
                 ],
                 "selected": false
             },
             "selected": false,
             "positionAbsolute": {
-                "x": 738.3791942291381,
-                "y": 61.26790912730354
+                "x": 509.0449726750261,
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@@ -58,7 +58,7 @@
                 "label": "Calculator",
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@@ -66,28 +66,28 @@
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@@ -95,7 +95,7 @@
                 "label": "ChatOpenAI",
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@@ -109,6 +109,18 @@
                         "name": "modelName",
                         "type": "options",
                         "options": [
+                            {
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+                                "name": "gpt-4"
+                            },
+                            {
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+                                "name": "gpt-4-0314"
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                         "name": "chatOpenAI",
                         "label": "ChatOpenAI",
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+                "baseClasses": ["BufferMemory", "BaseChatMemory", "BaseMemory"],
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@@ -189,28 +201,28 @@
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                         "label": "BufferMemory",
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@@ -218,7 +230,7 @@
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-                "baseClasses": ["AgentExecutor"],
+                "baseClasses": ["AgentExecutor", "BaseChain"],
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                 "description": "Conversational agent for a chat model. It will utilize chat specific prompts",
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@@ -250,18 +262,18 @@
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                         "label": "AgentExecutor",
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@@ -269,44 +281,44 @@
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packages/server/marketplaces/Conversational Retrieval QA Chain.json

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@@ -40,35 +40,35 @@
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                         "name": "recursiveCharacterTextSplitter",
                         "label": "RecursiveCharacterTextSplitter",
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@@ -96,7 +96,7 @@
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@@ -104,61 +104,18 @@
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@@ -166,7 +123,7 @@
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@@ -215,28 +172,71 @@
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                         "label": "OpenAI",
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@@ -323,8 +323,8 @@
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                         "name": "llm",
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-                        "id": "conversationalRetrievalQAChain_0-input-llm-BaseLanguageModel"
+                        "type": "BaseLLM",
+                        "id": "conversationalRetrievalQAChain_0-input-llm-BaseLLM"
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@@ -339,18 +339,18 @@
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                         "name": "conversationalRetrievalQAChain",
                         "label": "ConversationalRetrievalQAChain",
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packages/server/marketplaces/Github Repo QnA.json

@@ -3,64 +3,177 @@
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-                "type": "ConversationalRetrievalQAChain",
-                "baseClasses": ["BaseChain"],
-                "category": "Chains",
-                "description": "Document QA - built on RetrievalQAChain to provide a chat history component",
-                "inputParams": [],
-                "inputAnchors": [
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+                "label": "Recursive Character Text Splitter",
+                "name": "recursiveCharacterTextSplitter",
+                "type": "RecursiveCharacterTextSplitter",
+                "baseClasses": ["RecursiveCharacterTextSplitter", "TextSplitter"],
+                "category": "Text Splitters",
+                "description": "Split documents recursively by different characters - starting with \"\n\n\", then \"\n\", then \" \"",
+                "inputParams": [
                     {
-                        "label": "LLM",
-                        "name": "llm",
-                        "type": "BaseLanguageModel",
-                        "id": "conversationalRetrievalQAChain_0-input-llm-BaseLanguageModel"
+                        "label": "Chunk Size",
+                        "name": "chunkSize",
+                        "type": "number",
+                        "default": 1000,
+                        "optional": true
                     },
                     {
-                        "label": "Vector Store Retriever",
-                        "name": "vectorStoreRetriever",
-                        "type": "BaseRetriever",
-                        "id": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever"
+                        "label": "Chunk Overlap",
+                        "name": "chunkOverlap",
+                        "type": "number",
+                        "optional": true
                     }
                 ],
+                "inputAnchors": [],
                 "inputs": {
-                    "llm": "{{openAI_0.data.instance}}",
-                    "vectorStoreRetriever": "{{pineconeUpsert_0.data.instance}}"
+                    "chunkSize": 1000,
+                    "chunkOverlap": ""
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                 "outputAnchors": [
                     {
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-                        "name": "conversationalRetrievalQAChain",
-                        "label": "ConversationalRetrievalQAChain",
-                        "type": "BaseChain"
+                        "id": "recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter",
+                        "name": "recursiveCharacterTextSplitter",
+                        "label": "RecursiveCharacterTextSplitter",
+                        "type": "RecursiveCharacterTextSplitter | TextSplitter"
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                 "selected": false
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             "selected": false,
             "positionAbsolute": {
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+                "label": "Github",
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+                "baseClasses": ["Document"],
+                "category": "Document Loaders",
+                "description": "Load data from a GitHub repository",
+                "inputParams": [
+                    {
+                        "label": "Repo Link",
+                        "name": "repoLink",
+                        "type": "string",
+                        "placeholder": "https://github.com/FlowiseAI/Flowise"
+                    },
+                    {
+                        "label": "Branch",
+                        "name": "branch",
+                        "type": "string",
+                        "default": "main"
+                    },
+                    {
+                        "label": "Access Token",
+                        "name": "accessToken",
+                        "type": "password",
+                        "placeholder": "<GITHUB_ACCESS_TOKEN>",
+                        "optional": true
+                    }
+                ],
+                "inputAnchors": [
+                    {
+                        "label": "Text Splitter",
+                        "name": "textSplitter",
+                        "type": "TextSplitter",
+                        "optional": true,
+                        "id": "github_0-input-textSplitter-TextSplitter"
+                    }
+                ],
+                "inputs": {
+                    "repoLink": "https://github.com/kyrolabs/awesome-langchain",
+                    "branch": "main",
+                    "textSplitter": "{{recursiveCharacterTextSplitter_0.data.instance}}"
+                },
+                "outputAnchors": [
+                    {
+                        "id": "github_0-output-github-Document",
+                        "name": "github",
+                        "label": "Document",
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+            "id": "openAIEmbeddings_0",
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+            "data": {
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+                "label": "OpenAI Embeddings",
+                "name": "openAIEmbeddings",
+                "type": "OpenAIEmbeddings",
+                "baseClasses": ["OpenAIEmbeddings", "Embeddings"],
+                "category": "Embeddings",
+                "description": "OpenAI API to generate embeddings for a given text",
+                "inputParams": [
+                    {
+                        "label": "OpenAI Api Key",
+                        "name": "openAIApiKey",
+                        "type": "password"
+                    }
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+                "inputAnchors": [],
+                "inputs": {},
+                "outputAnchors": [
+                    {
+                        "id": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings",
+                        "name": "openAIEmbeddings",
+                        "label": "OpenAIEmbeddings",
+                        "type": "OpenAIEmbeddings | Embeddings"
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+                "selected": false
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             "id": "openAI_0",
             "position": {
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@@ -68,7 +181,7 @@
                 "label": "OpenAI",
                 "name": "openAI",
                 "type": "OpenAI",
-                "baseClasses": ["BaseLLM", "BaseLanguageModel"],
+                "baseClasses": ["OpenAI", "BaseLLM", "BaseLanguageModel"],
                 "category": "LLMs",
                 "description": "Wrapper around OpenAI large language models",
                 "inputParams": [
@@ -113,198 +226,32 @@
                 "inputAnchors": [],
                 "inputs": {
                     "modelName": "text-davinci-003",
-                    "temperature": "0"
+                    "temperature": 0.7
                 },
                 "outputAnchors": [
                     {
-                        "id": "openAI_0-output-openAI-BaseLLM|BaseLanguageModel",
+                        "id": "openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel",
                         "name": "openAI",
                         "label": "OpenAI",
-                        "type": "BaseLLM | BaseLanguageModel"
+                        "type": "OpenAI | BaseLLM | BaseLanguageModel"
                     }
                 ],
                 "selected": false
             },
             "selected": false,
             "positionAbsolute": {
-                "x": 1079.79101466888,
-                "y": -178.54116849152098
+                "x": 1268.0020638568344,
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-                "name": "recursiveCharacterTextSplitter",
-                "type": "RecursiveCharacterTextSplitter",
-                "baseClasses": ["TextSplitter"],
-                "category": "Text Splitters",
-                "description": "Split documents recursively by different characters - starting with \"\n\n\", then \"\n\", then \" \"",
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-                        "label": "Chunk Size",
-                        "name": "chunkSize",
-                        "type": "number",
-                        "default": 1000,
-                        "optional": true
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-                        "label": "Chunk Overlap",
-                        "name": "chunkOverlap",
-                        "type": "number",
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-                "inputs": {
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-                        "name": "recursiveCharacterTextSplitter",
-                        "label": "RecursiveCharacterTextSplitter",
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-                "type": "OpenAIEmbeddings",
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-                "description": "OpenAI API to generate embeddings for a given text",
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-                        "name": "openAIApiKey",
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-                "outputAnchors": [
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-                        "label": "OpenAIEmbeddings",
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-                "category": "Document Loaders",
-                "description": "Load data from a GitHub repository",
-                "inputParams": [
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-                        "placeholder": "<GITHUB_ACCESS_TOKEN>",
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-                        "name": "textSplitter",
-                        "type": "TextSplitter",
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-                    "textSplitter": "{{recursiveCharacterTextSplitter_0.data.instance}}"
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@@ -364,8 +311,61 @@
             },
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+                "x": 1265.1304547629002,
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+            "data": {
+                "id": "conversationalRetrievalQAChain_0",
+                "label": "Conversational Retrieval QA Chain",
+                "name": "conversationalRetrievalQAChain",
+                "type": "ConversationalRetrievalQAChain",
+                "baseClasses": ["ConversationalRetrievalQAChain", "BaseChain"],
+                "category": "Chains",
+                "description": "Document QA - built on RetrievalQAChain to provide a chat history component",
+                "inputParams": [],
+                "inputAnchors": [
+                    {
+                        "label": "LLM",
+                        "name": "llm",
+                        "type": "BaseLLM",
+                        "id": "conversationalRetrievalQAChain_0-input-llm-BaseLLM"
+                    },
+                    {
+                        "label": "Vector Store Retriever",
+                        "name": "vectorStoreRetriever",
+                        "type": "BaseRetriever",
+                        "id": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever"
+                    }
+                ],
+                "inputs": {
+                    "llm": "{{openAI_0.data.instance}}",
+                    "vectorStoreRetriever": "{{pineconeUpsert_0.data.instance}}"
+                },
+                "outputAnchors": [
+                    {
+                        "id": "conversationalRetrievalQAChain_0-output-conversationalRetrievalQAChain-ConversationalRetrievalQAChain|BaseChain",
+                        "name": "conversationalRetrievalQAChain",
+                        "label": "ConversationalRetrievalQAChain",
+                        "type": "ConversationalRetrievalQAChain | BaseChain"
+                    }
+                ],
+                "selected": false
+            },
+            "selected": false,
+            "positionAbsolute": {
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@@ -373,22 +373,33 @@
     "edges": [
         {
             "source": "openAI_0",
-            "sourceHandle": "openAI_0-output-openAI-BaseLLM|BaseLanguageModel",
+            "sourceHandle": "openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel",
             "target": "conversationalRetrievalQAChain_0",
-            "targetHandle": "conversationalRetrievalQAChain_0-input-llm-BaseLanguageModel",
+            "targetHandle": "conversationalRetrievalQAChain_0-input-llm-BaseLLM",
             "type": "buttonedge",
-            "id": "openAI_0-openAI_0-output-openAI-BaseLLM|BaseLanguageModel-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-llm-BaseLanguageModel",
+            "id": "openAI_0-openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-llm-BaseLLM",
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-            "target": "github_0",
-            "targetHandle": "github_0-input-textSplitter-TextSplitter",
+            "source": "pineconeUpsert_0",
+            "sourceHandle": "pineconeUpsert_0-output-pineconeUpsert-BaseRetriever",
+            "target": "conversationalRetrievalQAChain_0",
+            "targetHandle": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
             "type": "buttonedge",
-            "id": "recursiveCharacterTextSplitter_0-recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-TextSplitter-github_0-github_0-input-textSplitter-TextSplitter",
+            "id": "pineconeUpsert_0-pineconeUpsert_0-output-pineconeUpsert-BaseRetriever-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
+            "data": {
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+        },
+        {
+            "source": "openAIEmbeddings_0",
+            "sourceHandle": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings",
+            "target": "pineconeUpsert_0",
+            "targetHandle": "pineconeUpsert_0-input-embeddings-Embeddings",
+            "type": "buttonedge",
+            "id": "openAIEmbeddings_0-openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings-pineconeUpsert_0-pineconeUpsert_0-input-embeddings-Embeddings",
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@@ -405,23 +416,12 @@
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-            "target": "pineconeUpsert_0",
-            "targetHandle": "pineconeUpsert_0-input-embeddings-Embeddings",
+            "source": "recursiveCharacterTextSplitter_0",
+            "sourceHandle": "recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter",
+            "target": "github_0",
+            "targetHandle": "github_0-input-textSplitter-TextSplitter",
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packages/server/marketplaces/MRKLAgent.json

@@ -3,102 +3,11 @@
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-                "baseClasses": ["Tool"],
-                "category": "Tools",
-                "description": "Perform calculations on response",
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+                "x": 571.585786437627,
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@@ -106,7 +15,7 @@
                 "label": "Serp API",
                 "name": "serpAPI",
                 "type": "SerpAPI",
-                "baseClasses": ["Tool"],
+                "baseClasses": ["SerpAPI", "Tool"],
                 "category": "Tools",
                 "description": "Wrapper around SerpAPI - a real-time API to access Google search results",
                 "inputParams": [
@@ -120,28 +29,119 @@
                 "inputs": {},
                 "outputAnchors": [
                     {
-                        "id": "serpAPI_0-output-serpAPI-Tool",
+                        "id": "serpAPI_0-output-serpAPI-SerpAPI|Tool",
                         "name": "serpAPI",
                         "label": "SerpAPI",
-                        "type": "Tool"
+                        "type": "SerpAPI | Tool"
+                    }
+                ],
+                "selected": false
+            },
+            "positionAbsolute": {
+                "x": 571.585786437627,
+                "y": 127.14213562373095
+            },
+            "selected": false,
+            "dragging": false
+        },
+        {
+            "width": 300,
+            "height": 143,
+            "id": "calculator_0",
+            "position": {
+                "x": 904.7519886598635,
+                "y": 135.4705627484772
+            },
+            "type": "customNode",
+            "data": {
+                "id": "calculator_0",
+                "label": "Calculator",
+                "name": "calculator",
+                "type": "Calculator",
+                "baseClasses": ["Calculator", "Tool"],
+                "category": "Tools",
+                "description": "Perform calculations on response",
+                "inputParams": [],
+                "inputAnchors": [],
+                "inputs": {},
+                "outputAnchors": [
+                    {
+                        "id": "calculator_0-output-calculator-Calculator|Tool",
+                        "name": "calculator",
+                        "label": "Calculator",
+                        "type": "Calculator | Tool"
                     }
                 ],
                 "selected": false
             },
             "selected": false,
             "positionAbsolute": {
-                "x": 797.0350733284566,
-                "y": 199.36655049779267
+                "x": 904.7519886598635,
+                "y": 135.4705627484772
             },
             "dragging": false
         },
         {
             "width": 300,
-            "height": 471,
+            "height": 280,
+            "id": "mrklAgentLLM_0",
+            "position": {
+                "x": 1251.3621617151298,
+                "y": 323.8137084989848
+            },
+            "type": "customNode",
+            "data": {
+                "id": "mrklAgentLLM_0",
+                "label": "MRKL Agent for LLMs",
+                "name": "mrklAgentLLM",
+                "type": "AgentExecutor",
+                "baseClasses": ["AgentExecutor", "BaseChain"],
+                "category": "Agents",
+                "description": "Agent that uses the ReAct Framework to decide what action to take, optimized to be used with LLMs",
+                "inputParams": [],
+                "inputAnchors": [
+                    {
+                        "label": "Allowed Tools",
+                        "name": "tools",
+                        "type": "Tool",
+                        "list": true,
+                        "id": "mrklAgentLLM_0-input-tools-Tool"
+                    },
+                    {
+                        "label": "LLM Model",
+                        "name": "model",
+                        "type": "BaseLLM",
+                        "id": "mrklAgentLLM_0-input-model-BaseLLM"
+                    }
+                ],
+                "inputs": {
+                    "tools": ["{{calculator_0.data.instance}}", "{{serpAPI_0.data.instance}}"],
+                    "model": "{{openAI_0.data.instance}}"
+                },
+                "outputAnchors": [
+                    {
+                        "id": "mrklAgentLLM_0-output-mrklAgentLLM-AgentExecutor|BaseChain",
+                        "name": "mrklAgentLLM",
+                        "label": "AgentExecutor",
+                        "type": "AgentExecutor | BaseChain"
+                    }
+                ],
+                "selected": false
+            },
+            "selected": false,
+            "positionAbsolute": {
+                "x": 1251.3621617151298,
+                "y": 323.8137084989848
+            },
+            "dragging": false
+        },
+        {
+            "width": 300,
+            "height": 472,
             "id": "openAI_0",
             "position": {
-                "x": 917.6484006031452,
-                "y": 522.1507882519595
+                "x": 708.9235615351174,
+                "y": 438.84314575050763
             },
             "type": "customNode",
             "data": {
@@ -149,7 +149,7 @@
                 "label": "OpenAI",
                 "name": "openAI",
                 "type": "OpenAI",
-                "baseClasses": ["BaseLLM", "BaseLanguageModel"],
+                "baseClasses": ["OpenAI", "BaseLLM", "BaseLanguageModel"],
                 "category": "LLMs",
                 "description": "Wrapper around OpenAI large language models",
                 "inputParams": [
@@ -198,52 +198,52 @@
                 },
                 "outputAnchors": [
                     {
-                        "id": "openAI_0-output-openAI-BaseLLM|BaseLanguageModel",
+                        "id": "openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel",
                         "name": "openAI",
                         "label": "OpenAI",
-                        "type": "BaseLLM | BaseLanguageModel"
+                        "type": "OpenAI | BaseLLM | BaseLanguageModel"
                     }
                 ],
                 "selected": false
             },
-            "selected": false,
             "positionAbsolute": {
-                "x": 917.6484006031452,
-                "y": 522.1507882519595
+                "x": 708.9235615351174,
+                "y": 438.84314575050763
             },
+            "selected": false,
             "dragging": false
         }
     ],
     "edges": [
         {
             "source": "openAI_0",
-            "sourceHandle": "openAI_0-output-openAI-BaseLLM|BaseLanguageModel",
-            "target": "mrlkAgentLLM_0",
-            "targetHandle": "mrlkAgentLLM_0-input-model-BaseLanguageModel",
+            "sourceHandle": "openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel",
+            "target": "mrklAgentLLM_0",
+            "targetHandle": "mrklAgentLLM_0-input-model-BaseLLM",
             "type": "buttonedge",
-            "id": "openAI_0-openAI_0-output-openAI-BaseLLM|BaseLanguageModel-mrlkAgentLLM_0-mrlkAgentLLM_0-input-model-BaseLanguageModel",
+            "id": "openAI_0-openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel-mrklAgentLLM_0-mrklAgentLLM_0-input-model-BaseLLM",
             "data": {
                 "label": ""
             }
         },
         {
             "source": "calculator_0",
-            "sourceHandle": "calculator_0-output-calculator-Tool",
-            "target": "mrlkAgentLLM_0",
-            "targetHandle": "mrlkAgentLLM_0-input-tools-Tool",
+            "sourceHandle": "calculator_0-output-calculator-Calculator|Tool",
+            "target": "mrklAgentLLM_0",
+            "targetHandle": "mrklAgentLLM_0-input-tools-Tool",
             "type": "buttonedge",
-            "id": "calculator_0-calculator_0-output-calculator-Tool-mrlkAgentLLM_0-mrlkAgentLLM_0-input-tools-Tool",
+            "id": "calculator_0-calculator_0-output-calculator-Calculator|Tool-mrklAgentLLM_0-mrklAgentLLM_0-input-tools-Tool",
             "data": {
                 "label": ""
             }
         },
         {
             "source": "serpAPI_0",
-            "sourceHandle": "serpAPI_0-output-serpAPI-Tool",
-            "target": "mrlkAgentLLM_0",
-            "targetHandle": "mrlkAgentLLM_0-input-tools-Tool",
+            "sourceHandle": "serpAPI_0-output-serpAPI-SerpAPI|Tool",
+            "target": "mrklAgentLLM_0",
+            "targetHandle": "mrklAgentLLM_0-input-tools-Tool",
             "type": "buttonedge",
-            "id": "serpAPI_0-serpAPI_0-output-serpAPI-Tool-mrlkAgentLLM_0-mrlkAgentLLM_0-input-tools-Tool",
+            "id": "serpAPI_0-serpAPI_0-output-serpAPI-SerpAPI|Tool-mrklAgentLLM_0-mrklAgentLLM_0-input-tools-Tool",
             "data": {
                 "label": ""
             }

packages/server/marketplaces/SQL DB Chain.json

@@ -0,0 +1,163 @@
+{
+    "description": "Answer questions over a SQL database",
+    "nodes": [
+        {
+            "width": 300,
+            "height": 424,
+            "id": "sqlDatabaseChain_0",
+            "position": {
+                "x": 1271.2742585099204,
+                "y": 232.91561199714107
+            },
+            "type": "customNode",
+            "data": {
+                "id": "sqlDatabaseChain_0",
+                "label": "Sql Database Chain",
+                "name": "sqlDatabaseChain",
+                "type": "SqlDatabaseChain",
+                "baseClasses": ["SqlDatabaseChain", "BaseChain"],
+                "category": "Chains",
+                "description": "Answer questions over a SQL database",
+                "inputParams": [
+                    {
+                        "label": "Database",
+                        "name": "database",
+                        "type": "options",
+                        "options": [
+                            {
+                                "label": "SQlite",
+                                "name": "sqlite"
+                            }
+                        ],
+                        "default": "sqlite"
+                    },
+                    {
+                        "label": "Database File Path",
+                        "name": "dbFilePath",
+                        "type": "string",
+                        "placeholder": "C:/Users/chinook.db"
+                    }
+                ],
+                "inputAnchors": [
+                    {
+                        "label": "LLM",
+                        "name": "llm",
+                        "type": "BaseLLM",
+                        "id": "sqlDatabaseChain_0-input-llm-BaseLLM"
+                    }
+                ],
+                "inputs": {
+                    "llm": "{{openAI_0.data.instance}}",
+                    "database": "sqlite",
+                    "dbFilePath": ""
+                },
+                "outputAnchors": [
+                    {
+                        "id": "sqlDatabaseChain_0-output-sqlDatabaseChain-SqlDatabaseChain|BaseChain",
+                        "name": "sqlDatabaseChain",
+                        "label": "SqlDatabaseChain",
+                        "type": "SqlDatabaseChain | BaseChain"
+                    }
+                ],
+                "selected": false
+            },
+            "selected": false,
+            "positionAbsolute": {
+                "x": 1271.2742585099204,
+                "y": 232.91561199714107
+            },
+            "dragging": false
+        },
+        {
+            "width": 300,
+            "height": 472,
+            "id": "openAI_0",
+            "position": {
+                "x": 867.8574087065126,
+                "y": 209.58625096303308
+            },
+            "type": "customNode",
+            "data": {
+                "id": "openAI_0",
+                "label": "OpenAI",
+                "name": "openAI",
+                "type": "OpenAI",
+                "baseClasses": ["OpenAI", "BaseLLM", "BaseLanguageModel"],
+                "category": "LLMs",
+                "description": "Wrapper around OpenAI large language models",
+                "inputParams": [
+                    {
+                        "label": "OpenAI Api Key",
+                        "name": "openAIApiKey",
+                        "type": "password"
+                    },
+                    {
+                        "label": "Model Name",
+                        "name": "modelName",
+                        "type": "options",
+                        "options": [
+                            {
+                                "label": "text-davinci-003",
+                                "name": "text-davinci-003"
+                            },
+                            {
+                                "label": "text-davinci-002",
+                                "name": "text-davinci-002"
+                            },
+                            {
+                                "label": "text-curie-001",
+                                "name": "text-curie-001"
+                            },
+                            {
+                                "label": "text-babbage-001",
+                                "name": "text-babbage-001"
+                            }
+                        ],
+                        "default": "text-davinci-003",
+                        "optional": true
+                    },
+                    {
+                        "label": "Temperature",
+                        "name": "temperature",
+                        "type": "number",
+                        "default": 0.7,
+                        "optional": true
+                    }
+                ],
+                "inputAnchors": [],
+                "inputs": {
+                    "modelName": "text-davinci-003",
+                    "temperature": "0"
+                },
+                "outputAnchors": [
+                    {
+                        "id": "openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel",
+                        "name": "openAI",
+                        "label": "OpenAI",
+                        "type": "OpenAI | BaseLLM | BaseLanguageModel"
+                    }
+                ],
+                "selected": false
+            },
+            "selected": false,
+            "positionAbsolute": {
+                "x": 867.8574087065126,
+                "y": 209.58625096303308
+            },
+            "dragging": false
+        }
+    ],
+    "edges": [
+        {
+            "source": "openAI_0",
+            "sourceHandle": "openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel",
+            "target": "sqlDatabaseChain_0",
+            "targetHandle": "sqlDatabaseChain_0-input-llm-BaseLLM",
+            "type": "buttonedge",
+            "id": "openAI_0-openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel-sqlDatabaseChain_0-sqlDatabaseChain_0-input-llm-BaseLLM",
+            "data": {
+                "label": ""
+            }
+        }
+    ]
+}

packages/server/marketplaces/Simple LLM Chain.json

@@ -3,74 +3,11 @@
     "nodes": [
         {
             "width": 300,
-            "height": 460,
-            "id": "llmChain_0",
-            "position": {
-                "x": 1515.563392772433,
-                "y": 334.61150897841924
-            },
-            "type": "customNode",
-            "data": {
-                "id": "llmChain_0",
-                "label": "LLM Chain",
-                "name": "llmChain",
-                "type": "LLMChain",
-                "baseClasses": ["BaseChain"],
-                "category": "Chains",
-                "description": "Chain to run queries against LLMs",
-                "inputParams": [
-                    {
-                        "label": "Format Prompt Values",
-                        "name": "promptValues",
-                        "type": "string",
-                        "rows": 5,
-                        "placeholder": "{\n  \"input_language\": \"English\",\n  \"output_language\": \"French\"\n}",
-                        "optional": true
-                    }
-                ],
-                "inputAnchors": [
-                    {
-                        "label": "LLM",
-                        "name": "llm",
-                        "type": "BaseLanguageModel",
-                        "id": "llmChain_0-input-llm-BaseLanguageModel"
-                    },
-                    {
-                        "label": "Prompt",
-                        "name": "prompt",
-                        "type": "BasePromptTemplate",
-                        "id": "llmChain_0-input-prompt-BasePromptTemplate"
-                    }
-                ],
-                "inputs": {
-                    "llm": "{{openAI_0.data.instance}}",
-                    "prompt": "{{promptTemplate_0.data.instance}}",
-                    "promptValues": ""
-                },
-                "outputAnchors": [
-                    {
-                        "id": "llmChain_0-output-llmChain-BaseChain",
-                        "name": "llmChain",
-                        "label": "LLMChain",
-                        "type": "BaseChain"
-                    }
-                ],
-                "selected": false
-            },
-            "selected": false,
-            "positionAbsolute": {
-                "x": 1515.563392772433,
-                "y": 334.61150897841924
-            },
-            "dragging": false
-        },
-        {
-            "width": 300,
-            "height": 471,
+            "height": 472,
             "id": "openAI_0",
             "position": {
-                "x": 954.7026430819806,
-                "y": 6.975032607064918
+                "x": 968.1753795547951,
+                "y": -8.62176310944858
             },
             "type": "customNode",
             "data": {
@@ -78,7 +15,7 @@
                 "label": "OpenAI",
                 "name": "openAI",
                 "type": "OpenAI",
-                "baseClasses": ["BaseLLM", "BaseLanguageModel"],
+                "baseClasses": ["OpenAI", "BaseLLM", "BaseLanguageModel"],
                 "category": "LLMs",
                 "description": "Wrapper around OpenAI large language models",
                 "inputParams": [
@@ -127,28 +64,28 @@
                 },
                 "outputAnchors": [
                     {
-                        "id": "openAI_0-output-openAI-BaseLLM|BaseLanguageModel",
+                        "id": "openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel",
                         "name": "openAI",
                         "label": "OpenAI",
-                        "type": "BaseLLM | BaseLanguageModel"
+                        "type": "OpenAI | BaseLLM | BaseLanguageModel"
                     }
                 ],
                 "selected": false
             },
             "selected": false,
             "positionAbsolute": {
-                "x": 954.7026430819806,
-                "y": 6.975032607064918
+                "x": 968.1753795547951,
+                "y": -8.62176310944858
             },
             "dragging": false
         },
         {
             "width": 300,
-            "height": 359,
+            "height": 360,
             "id": "promptTemplate_0",
             "position": {
-                "x": 954.1542757936061,
-                "y": 515.2247261712328
+                "x": 970.576876549135,
+                "y": 502.493937944275
             },
             "type": "customNode",
             "data": {
@@ -156,7 +93,7 @@
                 "label": "Prompt Template",
                 "name": "promptTemplate",
                 "type": "PromptTemplate",
-                "baseClasses": ["BaseStringPromptTemplate", "BasePromptTemplate"],
+                "baseClasses": ["PromptTemplate", "BaseStringPromptTemplate", "BasePromptTemplate"],
                 "category": "Prompts",
                 "description": "Schema to represent a basic prompt for an LLM",
                 "inputParams": [
@@ -174,41 +111,104 @@
                 },
                 "outputAnchors": [
                     {
-                        "id": "promptTemplate_0-output-promptTemplate-BaseStringPromptTemplate|BasePromptTemplate",
+                        "id": "promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate",
                         "name": "promptTemplate",
                         "label": "PromptTemplate",
-                        "type": "BaseStringPromptTemplate | BasePromptTemplate"
+                        "type": "PromptTemplate | BaseStringPromptTemplate | BasePromptTemplate"
                     }
                 ],
                 "selected": false
             },
             "selected": false,
             "positionAbsolute": {
-                "x": 954.1542757936061,
-                "y": 515.2247261712328
+                "x": 970.576876549135,
+                "y": 502.493937944275
+            },
+            "dragging": false
+        },
+        {
+            "width": 300,
+            "height": 461,
+            "id": "llmChain_0",
+            "position": {
+                "x": 1414.1175742139496,
+                "y": 340.4040954840462
+            },
+            "type": "customNode",
+            "data": {
+                "id": "llmChain_0",
+                "label": "LLM Chain",
+                "name": "llmChain",
+                "type": "LLMChain",
+                "baseClasses": ["LLMChain", "BaseChain"],
+                "category": "Chains",
+                "description": "Chain to run queries against LLMs",
+                "inputParams": [
+                    {
+                        "label": "Format Prompt Values",
+                        "name": "promptValues",
+                        "type": "string",
+                        "rows": 5,
+                        "placeholder": "{\n  \"input_language\": \"English\",\n  \"output_language\": \"French\"\n}",
+                        "optional": true
+                    }
+                ],
+                "inputAnchors": [
+                    {
+                        "label": "Language Model",
+                        "name": "model",
+                        "type": "BaseLanguageModel",
+                        "id": "llmChain_0-input-model-BaseLanguageModel"
+                    },
+                    {
+                        "label": "Prompt",
+                        "name": "prompt",
+                        "type": "BasePromptTemplate",
+                        "id": "llmChain_0-input-prompt-BasePromptTemplate"
+                    }
+                ],
+                "inputs": {
+                    "model": "{{openAI_0.data.instance}}",
+                    "prompt": "{{promptTemplate_0.data.instance}}",
+                    "promptValues": ""
+                },
+                "outputAnchors": [
+                    {
+                        "id": "llmChain_0-output-llmChain-LLMChain|BaseChain",
+                        "name": "llmChain",
+                        "label": "LLMChain",
+                        "type": "LLMChain | BaseChain"
+                    }
+                ],
+                "selected": false
+            },
+            "selected": false,
+            "positionAbsolute": {
+                "x": 1414.1175742139496,
+                "y": 340.4040954840462
             },
             "dragging": false
         }
     ],
     "edges": [
         {
-            "source": "openAI_0",
-            "sourceHandle": "openAI_0-output-openAI-BaseLLM|BaseLanguageModel",
+            "source": "promptTemplate_0",
+            "sourceHandle": "promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate",
             "target": "llmChain_0",
-            "targetHandle": "llmChain_0-input-llm-BaseLanguageModel",
+            "targetHandle": "llmChain_0-input-prompt-BasePromptTemplate",
             "type": "buttonedge",
-            "id": "openAI_0-openAI_0-output-openAI-BaseLLM|BaseLanguageModel-llmChain_0-llmChain_0-input-llm-BaseLanguageModel",
+            "id": "promptTemplate_0-promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate-llmChain_0-llmChain_0-input-prompt-BasePromptTemplate",
             "data": {
                 "label": ""
             }
         },
         {
-            "source": "promptTemplate_0",
-            "sourceHandle": "promptTemplate_0-output-promptTemplate-BaseStringPromptTemplate|BasePromptTemplate",
+            "source": "openAI_0",
+            "sourceHandle": "openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel",
             "target": "llmChain_0",
-            "targetHandle": "llmChain_0-input-prompt-BasePromptTemplate",
+            "targetHandle": "llmChain_0-input-model-BaseLanguageModel",
             "type": "buttonedge",
-            "id": "promptTemplate_0-promptTemplate_0-output-promptTemplate-BaseStringPromptTemplate|BasePromptTemplate-llmChain_0-llmChain_0-input-prompt-BasePromptTemplate",
+            "id": "openAI_0-openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel-llmChain_0-llmChain_0-input-model-BaseLanguageModel",
             "data": {
                 "label": ""
             }

packages/server/marketplaces/Translator.json

@@ -4,143 +4,10 @@
         {
             "width": 300,
             "height": 460,
-            "id": "llmChain_0",
-            "position": {
-                "x": 1301.8762472836022,
-                "y": 772.7199253009146
-            },
-            "type": "customNode",
-            "data": {
-                "id": "llmChain_0",
-                "label": "LLM Chain",
-                "name": "llmChain",
-                "type": "LLMChain",
-                "baseClasses": ["BaseChain"],
-                "category": "Chains",
-                "description": "Chain to run queries against LLMs",
-                "inputParams": [
-                    {
-                        "label": "Format Prompt Values",
-                        "name": "promptValues",
-                        "type": "string",
-                        "rows": 5,
-                        "placeholder": "{\n  \"input_language\": \"English\",\n  \"output_language\": \"French\"\n}",
-                        "optional": true
-                    }
-                ],
-                "inputAnchors": [
-                    {
-                        "label": "LLM",
-                        "name": "llm",
-                        "type": "BaseLanguageModel",
-                        "id": "llmChain_0-input-llm-BaseLanguageModel"
-                    },
-                    {
-                        "label": "Prompt",
-                        "name": "prompt",
-                        "type": "BasePromptTemplate",
-                        "id": "llmChain_0-input-prompt-BasePromptTemplate"
-                    }
-                ],
-                "inputs": {
-                    "llm": "{{chatOpenAI_0.data.instance}}",
-                    "prompt": "{{chatPromptTemplate_0.data.instance}}",
-                    "promptValues": "{\n  \"input_language\": \"English\",\n  \"output_language\": \"Italian\"\n}"
-                },
-                "outputAnchors": [
-                    {
-                        "id": "llmChain_0-output-llmChain-BaseChain",
-                        "name": "llmChain",
-                        "label": "LLMChain",
-                        "type": "BaseChain"
-                    }
-                ],
-                "selected": false
-            },
-            "selected": false,
-            "positionAbsolute": {
-                "x": 1301.8762472836022,
-                "y": 772.7199253009146
-            },
-            "dragging": false
-        },
-        {
-            "width": 300,
-            "height": 471,
-            "id": "chatOpenAI_0",
-            "position": {
-                "x": 821.5000372338304,
-                "y": 369.8333649665954
-            },
-            "type": "customNode",
-            "data": {
-                "id": "chatOpenAI_0",
-                "label": "ChatOpenAI",
-                "name": "chatOpenAI",
-                "type": "ChatOpenAI",
-                "baseClasses": ["BaseChatModel", "BaseLanguageModel"],
-                "category": "Chat Models",
-                "description": "Wrapper around OpenAI large language models that use the Chat endpoint",
-                "inputParams": [
-                    {
-                        "label": "OpenAI Api Key",
-                        "name": "openAIApiKey",
-                        "type": "password"
-                    },
-                    {
-                        "label": "Model Name",
-                        "name": "modelName",
-                        "type": "options",
-                        "options": [
-                            {
-                                "label": "gpt-3.5-turbo",
-                                "name": "gpt-3.5-turbo"
-                            },
-                            {
-                                "label": "gpt-3.5-turbo-0301",
-                                "name": "gpt-3.5-turbo-0301"
-                            }
-                        ],
-                        "default": "gpt-3.5-turbo",
-                        "optional": true
-                    },
-                    {
-                        "label": "Temperature",
-                        "name": "temperature",
-                        "type": "number",
-                        "default": 0.9,
-                        "optional": true
-                    }
-                ],
-                "inputAnchors": [],
-                "inputs": {
-                    "modelName": "gpt-3.5-turbo",
-                    "temperature": "0"
-                },
-                "outputAnchors": [
-                    {
-                        "id": "chatOpenAI_0-output-chatOpenAI-BaseChatModel|BaseLanguageModel",
-                        "name": "chatOpenAI",
-                        "label": "ChatOpenAI",
-                        "type": "BaseChatModel | BaseLanguageModel"
-                    }
-                ],
-                "selected": false
-            },
-            "selected": false,
-            "positionAbsolute": {
-                "x": 821.5000372338304,
-                "y": 369.8333649665954
-            },
-            "dragging": false
-        },
-        {
-            "width": 300,
-            "height": 459,
             "id": "chatPromptTemplate_0",
             "position": {
-                "x": 821.3479428749118,
-                "y": 871.7203878238932
+                "x": 524,
+                "y": 237
             },
             "type": "customNode",
             "data": {
@@ -148,7 +15,7 @@
                 "label": "Chat Prompt Template",
                 "name": "chatPromptTemplate",
                 "type": "ChatPromptTemplate",
-                "baseClasses": ["BasePromptTemplate"],
+                "baseClasses": ["ChatPromptTemplate", "BaseChatPromptTemplate", "BasePromptTemplate"],
                 "category": "Prompts",
                 "description": "Schema to represent a chat prompt",
                 "inputParams": [
@@ -174,18 +41,163 @@
                 },
                 "outputAnchors": [
                     {
-                        "id": "chatPromptTemplate_0-output-chatPromptTemplate-BasePromptTemplate",
+                        "id": "chatPromptTemplate_0-output-chatPromptTemplate-ChatPromptTemplate|BaseChatPromptTemplate|BasePromptTemplate",
                         "name": "chatPromptTemplate",
                         "label": "ChatPromptTemplate",
-                        "type": "BasePromptTemplate"
+                        "type": "ChatPromptTemplate | BaseChatPromptTemplate | BasePromptTemplate"
+                    }
+                ],
+                "selected": false
+            },
+            "selected": false,
+            "dragging": false,
+            "positionAbsolute": {
+                "x": 524,
+                "y": 237
+            }
+        },
+        {
+            "width": 300,
+            "height": 472,
+            "id": "chatOpenAI_0",
+            "position": {
+                "x": 855.1997276913991,
+                "y": 24.090553068402556
+            },
+            "type": "customNode",
+            "data": {
+                "id": "chatOpenAI_0",
+                "label": "ChatOpenAI",
+                "name": "chatOpenAI",
+                "type": "ChatOpenAI",
+                "baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
+                "category": "Chat Models",
+                "description": "Wrapper around OpenAI large language models that use the Chat endpoint",
+                "inputParams": [
+                    {
+                        "label": "OpenAI Api Key",
+                        "name": "openAIApiKey",
+                        "type": "password"
+                    },
+                    {
+                        "label": "Model Name",
+                        "name": "modelName",
+                        "type": "options",
+                        "options": [
+                            {
+                                "label": "gpt-4",
+                                "name": "gpt-4"
+                            },
+                            {
+                                "label": "gpt-4-0314",
+                                "name": "gpt-4-0314"
+                            },
+                            {
+                                "label": "gpt-4-32k-0314",
+                                "name": "gpt-4-32k-0314"
+                            },
+                            {
+                                "label": "gpt-3.5-turbo",
+                                "name": "gpt-3.5-turbo"
+                            },
+                            {
+                                "label": "gpt-3.5-turbo-0301",
+                                "name": "gpt-3.5-turbo-0301"
+                            }
+                        ],
+                        "default": "gpt-3.5-turbo",
+                        "optional": true
+                    },
+                    {
+                        "label": "Temperature",
+                        "name": "temperature",
+                        "type": "number",
+                        "default": 0.9,
+                        "optional": true
+                    }
+                ],
+                "inputAnchors": [],
+                "inputs": {
+                    "modelName": "gpt-3.5-turbo",
+                    "temperature": 0.9
+                },
+                "outputAnchors": [
+                    {
+                        "id": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel",
+                        "name": "chatOpenAI",
+                        "label": "ChatOpenAI",
+                        "type": "ChatOpenAI | BaseChatModel | BaseLanguageModel"
                     }
                 ],
                 "selected": false
             },
             "selected": false,
             "positionAbsolute": {
-                "x": 821.3479428749118,
-                "y": 871.7203878238932
+                "x": 855.1997276913991,
+                "y": 24.090553068402556
+            },
+            "dragging": false
+        },
+        {
+            "width": 300,
+            "height": 461,
+            "id": "llmChain_0",
+            "position": {
+                "x": 1192.2235692202612,
+                "y": 361.71736677076257
+            },
+            "type": "customNode",
+            "data": {
+                "id": "llmChain_0",
+                "label": "LLM Chain",
+                "name": "llmChain",
+                "type": "LLMChain",
+                "baseClasses": ["LLMChain", "BaseChain"],
+                "category": "Chains",
+                "description": "Chain to run queries against LLMs",
+                "inputParams": [
+                    {
+                        "label": "Format Prompt Values",
+                        "name": "promptValues",
+                        "type": "string",
+                        "rows": 5,
+                        "placeholder": "{\n  \"input_language\": \"English\",\n  \"output_language\": \"French\"\n}",
+                        "optional": true
+                    }
+                ],
+                "inputAnchors": [
+                    {
+                        "label": "Language Model",
+                        "name": "model",
+                        "type": "BaseLanguageModel",
+                        "id": "llmChain_0-input-model-BaseLanguageModel"
+                    },
+                    {
+                        "label": "Prompt",
+                        "name": "prompt",
+                        "type": "BasePromptTemplate",
+                        "id": "llmChain_0-input-prompt-BasePromptTemplate"
+                    }
+                ],
+                "inputs": {
+                    "model": "{{chatOpenAI_0.data.instance}}",
+                    "prompt": "{{chatPromptTemplate_0.data.instance}}",
+                    "promptValues": "{\n  \"input_language\": \"English\",\n  \"output_language\": \"French\"\n}"
+                },
+                "outputAnchors": [
+                    {
+                        "id": "llmChain_0-output-llmChain-LLMChain|BaseChain",
+                        "name": "llmChain",
+                        "label": "LLMChain",
+                        "type": "LLMChain | BaseChain"
+                    }
+                ],
+                "selected": false
+            },
+            "selected": false,
+            "positionAbsolute": {
+                "x": 1192.2235692202612,
+                "y": 361.71736677076257
             },
             "dragging": false
         }
@@ -193,22 +205,22 @@
     "edges": [
         {
             "source": "chatOpenAI_0",
-            "sourceHandle": "chatOpenAI_0-output-chatOpenAI-BaseChatModel|BaseLanguageModel",
+            "sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel",
             "target": "llmChain_0",
-            "targetHandle": "llmChain_0-input-llm-BaseLanguageModel",
+            "targetHandle": "llmChain_0-input-model-BaseLanguageModel",
             "type": "buttonedge",
-            "id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-BaseChatModel|BaseLanguageModel-llmChain_0-llmChain_0-input-llm-BaseLanguageModel",
+            "id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel-llmChain_0-llmChain_0-input-model-BaseLanguageModel",
             "data": {
                 "label": ""
             }
         },
         {
             "source": "chatPromptTemplate_0",
-            "sourceHandle": "chatPromptTemplate_0-output-chatPromptTemplate-BasePromptTemplate",
+            "sourceHandle": "chatPromptTemplate_0-output-chatPromptTemplate-ChatPromptTemplate|BaseChatPromptTemplate|BasePromptTemplate",
             "target": "llmChain_0",
             "targetHandle": "llmChain_0-input-prompt-BasePromptTemplate",
             "type": "buttonedge",
-            "id": "chatPromptTemplate_0-chatPromptTemplate_0-output-chatPromptTemplate-BasePromptTemplate-llmChain_0-llmChain_0-input-prompt-BasePromptTemplate",
+            "id": "chatPromptTemplate_0-chatPromptTemplate_0-output-chatPromptTemplate-ChatPromptTemplate|BaseChatPromptTemplate|BasePromptTemplate-llmChain_0-llmChain_0-input-prompt-BasePromptTemplate",
             "data": {
                 "label": ""
             }

packages/server/package.json

@@ -1,6 +1,6 @@
 {
     "name": "flowise",
-    "version": "1.0.1",
+    "version": "1.1.1",
     "description": "Flowiseai Server",
     "main": "dist/index",
     "types": "dist/index.d.ts",

packages/server/src/Interface.ts

@@ -95,6 +95,10 @@ export interface INodeQueue {
     depth: number
 }
 
+export interface IDepthQueue {
+    [key: string]: number
+}
+
 export interface IMessage {
     message: string
     type: MessageType

packages/server/src/NodesPool.ts

@@ -23,9 +23,6 @@ export class NodesPool {
                         const newNodeInstance = new nodeModule.nodeClass()
                         newNodeInstance.filePath = file
 
-                        const baseClasses = await newNodeInstance.getBaseClasses!.call(newNodeInstance)
-                        newNodeInstance.baseClasses = baseClasses
-
                         this.componentNodes[newNodeInstance.name] = newNodeInstance
 
                         // Replace file icon with absolute path

packages/server/src/index.ts

@@ -5,7 +5,7 @@ import http from 'http'
 import * as fs from 'fs'
 
 import { IChatFlow, IncomingInput, IReactFlowNode, IReactFlowObject } from './Interface'
-import { getNodeModulesPackagePath, getStartingNode, buildLangchain, getEndingNode, constructGraphs } from './utils'
+import { getNodeModulesPackagePath, getStartingNodes, buildLangchain, getEndingNode, constructGraphs } from './utils'
 import { cloneDeep } from 'lodash'
 import { getDataSource } from './DataSource'
 import { NodesPool } from './NodesPool'
@@ -209,13 +209,26 @@ export class App {
 
                     const flowData = chatflow.flowData
                     const parsedFlowData: IReactFlowObject = JSON.parse(flowData)
+
+                    /*** Get Ending Node with Directed Graph  ***/
                     const { graph, nodeDependencies } = constructGraphs(parsedFlowData.nodes, parsedFlowData.edges)
+                    const directedGraph = graph
+                    const endingNodeId = getEndingNode(nodeDependencies, directedGraph)
+                    if (!endingNodeId) return res.status(500).send(`Ending node must be either a Chain or Agent`)
 
-                    const startingNodeIds = getStartingNode(nodeDependencies)
-                    const endingNodeId = getEndingNode(nodeDependencies, graph)
-                    if (!endingNodeId) return res.status(500).send(`Ending node must be either Chain or Agent`)
+                    /*** Get Starting Nodes with Non-Directed Graph ***/
+                    const constructedObj = constructGraphs(parsedFlowData.nodes, parsedFlowData.edges, true)
+                    const nonDirectedGraph = constructedObj.graph
+                    const { startingNodeIds, depthQueue } = getStartingNodes(nonDirectedGraph, endingNodeId)
 
-                    const reactFlowNodes = await buildLangchain(startingNodeIds, parsedFlowData.nodes, graph, this.nodesPool.componentNodes)
+                    /*** BFS to traverse from Starting Nodes to Ending Node ***/
+                    const reactFlowNodes = await buildLangchain(
+                        startingNodeIds,
+                        parsedFlowData.nodes,
+                        graph,
+                        depthQueue,
+                        this.nodesPool.componentNodes
+                    )
 
                     const nodeToExecute = reactFlowNodes.find((node: IReactFlowNode) => node.id === endingNodeId)
                     if (!nodeToExecute) return res.status(404).send(`Node ${endingNodeId} not found`)

packages/server/src/utils/index.ts

@@ -2,6 +2,7 @@ import path from 'path'
 import fs from 'fs'
 import {
     IComponentNodes,
+    IDepthQueue,
     IExploredNode,
     INodeDependencies,
     INodeDirectedGraph,
@@ -54,11 +55,12 @@ export const getNodeModulesPackagePath = (packageName: string): string => {
 }
 
 /**
- * Construct directed graph and node dependencies score
+ * Construct graph and node dependencies score
  * @param {IReactFlowNode[]} reactFlowNodes
  * @param {IReactFlowEdge[]} reactFlowEdges
+ * @param {boolean} isNondirected
  */
-export const constructGraphs = (reactFlowNodes: IReactFlowNode[], reactFlowEdges: IReactFlowEdge[]) => {
+export const constructGraphs = (reactFlowNodes: IReactFlowNode[], reactFlowEdges: IReactFlowEdge[], isNondirected = false) => {
     const nodeDependencies = {} as INodeDependencies
     const graph = {} as INodeDirectedGraph
 
@@ -77,6 +79,14 @@ export const constructGraphs = (reactFlowNodes: IReactFlowNode[], reactFlowEdges
         } else {
             graph[source] = [target]
         }
+
+        if (isNondirected) {
+            if (Object.prototype.hasOwnProperty.call(graph, target)) {
+                graph[target].push(source)
+            } else {
+                graph[target] = [source]
+            }
+        }
         nodeDependencies[target] += 1
     }
 
@@ -84,18 +94,52 @@ export const constructGraphs = (reactFlowNodes: IReactFlowNode[], reactFlowEdges
 }
 
 /**
- * Get starting node and check if flow is valid
- * @param {INodeDependencies} nodeDependencies
+ * Get starting nodes and check if flow is valid
+ * @param {INodeDependencies} graph
+ * @param {string} endNodeId
  */
-export const getStartingNode = (nodeDependencies: INodeDependencies) => {
-    // Find starting node
-    const startingNodeIds = [] as string[]
-    Object.keys(nodeDependencies).forEach((nodeId) => {
-        if (nodeDependencies[nodeId] === 0) {
-            startingNodeIds.push(nodeId)
+export const getStartingNodes = (graph: INodeDirectedGraph, endNodeId: string) => {
+    const visited = new Set<string>()
+    const queue: Array<[string, number]> = [[endNodeId, 0]]
+    const depthQueue: IDepthQueue = {
+        [endNodeId]: 0
+    }
+
+    let maxDepth = 0
+    let startingNodeIds: string[] = []
+
+    while (queue.length > 0) {
+        const [currentNode, depth] = queue.shift()!
+
+        if (visited.has(currentNode)) {
+            continue
         }
-    })
-    return startingNodeIds
+
+        visited.add(currentNode)
+
+        if (depth > maxDepth) {
+            maxDepth = depth
+            startingNodeIds = [currentNode]
+        } else if (depth === maxDepth) {
+            startingNodeIds.push(currentNode)
+        }
+
+        for (const neighbor of graph[currentNode]) {
+            if (!visited.has(neighbor)) {
+                queue.push([neighbor, depth + 1])
+                depthQueue[neighbor] = depth + 1
+            }
+        }
+    }
+
+    const depthQueueReversed: IDepthQueue = {}
+    for (const nodeId in depthQueue) {
+        if (Object.prototype.hasOwnProperty.call(depthQueue, nodeId)) {
+            depthQueueReversed[nodeId] = Math.abs(depthQueue[nodeId] - maxDepth)
+        }
+    }
+
+    return { startingNodeIds, depthQueue: depthQueueReversed }
 }
 
 /**
@@ -104,7 +148,6 @@ export const getStartingNode = (nodeDependencies: INodeDependencies) => {
  * @param {INodeDirectedGraph} graph
  */
 export const getEndingNode = (nodeDependencies: INodeDependencies, graph: INodeDirectedGraph) => {
-    // Find ending node
     let endingNodeId = ''
     Object.keys(graph).forEach((nodeId) => {
         if (Object.keys(nodeDependencies).length === 1) {
@@ -121,12 +164,14 @@ export const getEndingNode = (nodeDependencies: INodeDependencies, graph: INodeD
  * @param {string} startingNodeId
  * @param {IReactFlowNode[]} reactFlowNodes
  * @param {INodeDirectedGraph} graph
+ * @param {IDepthQueue} depthQueue
  * @param {IComponentNodes} componentNodes
  */
 export const buildLangchain = async (
     startingNodeIds: string[],
     reactFlowNodes: IReactFlowNode[],
     graph: INodeDirectedGraph,
+    depthQueue: IDepthQueue,
     componentNodes: IComponentNodes
 ) => {
     const flowNodes = cloneDeep(reactFlowNodes)
@@ -166,6 +211,14 @@ export const buildLangchain = async (
         const neighbourNodeIds = graph[nodeId]
         const nextDepth = depth + 1
 
+        // Find other nodes that are on the same depth level
+        const sameDepthNodeIds = Object.keys(depthQueue).filter((key) => depthQueue[key] === nextDepth)
+
+        for (const id of sameDepthNodeIds) {
+            if (neighbourNodeIds.includes(id)) continue
+            neighbourNodeIds.push(id)
+        }
+
         for (let i = 0; i < neighbourNodeIds.length; i += 1) {
             const neighNodeId = neighbourNodeIds[i]
 

packages/ui/package.json

@@ -1,6 +1,6 @@
 {
     "name": "flowise-ui",
-    "version": "1.0.0",
+    "version": "1.1.0",
     "license": "SEE LICENSE IN LICENSE.md",
     "homepage": "https://flowiseai.com",
     "author": {

packages/ui/src/store/context/ReactFlowContext.js

@@ -13,13 +13,51 @@ export const flowContext = createContext(initialValue)
 export const ReactFlowContext = ({ children }) => {
     const [reactFlowInstance, setReactFlowInstance] = useState(null)
 
-    const deleteNode = (id) => {
-        reactFlowInstance.setNodes(reactFlowInstance.getNodes().filter((n) => n.id !== id))
-        reactFlowInstance.setEdges(reactFlowInstance.getEdges().filter((ns) => ns.source !== id && ns.target !== id))
+    const deleteNode = (nodeid) => {
+        deleteConnectedInput(nodeid, 'node')
+        reactFlowInstance.setNodes(reactFlowInstance.getNodes().filter((n) => n.id !== nodeid))
+        reactFlowInstance.setEdges(reactFlowInstance.getEdges().filter((ns) => ns.source !== nodeid && ns.target !== nodeid))
     }
 
-    const deleteEdge = (id) => {
-        reactFlowInstance.setEdges(reactFlowInstance.getEdges().filter((edge) => edge.id !== id))
+    const deleteEdge = (edgeid) => {
+        deleteConnectedInput(edgeid, 'edge')
+        reactFlowInstance.setEdges(reactFlowInstance.getEdges().filter((edge) => edge.id !== edgeid))
+    }
+
+    const deleteConnectedInput = (id, type) => {
+        const connectedEdges =
+            type === 'node'
+                ? reactFlowInstance.getEdges().filter((edge) => edge.source === id)
+                : reactFlowInstance.getEdges().filter((edge) => edge.id === id)
+
+        for (const edge of connectedEdges) {
+            const targetNodeId = edge.target
+            const sourceNodeId = edge.source
+            const targetInput = edge.targetHandle.split('-')[2]
+
+            reactFlowInstance.setNodes((nds) =>
+                nds.map((node) => {
+                    if (node.id === targetNodeId) {
+                        let value
+                        const inputAnchor = node.data.inputAnchors.find((ancr) => ancr.name === targetInput)
+                        if (inputAnchor && inputAnchor.list) {
+                            const values = node.data.inputs[targetInput] || []
+                            value = values.filter((item) => !item.includes(sourceNodeId))
+                        } else {
+                            value = ''
+                        }
+                        node.data = {
+                            ...node.data,
+                            inputs: {
+                                ...node.data.inputs,
+                                [targetInput]: value
+                            }
+                        }
+                    }
+                    return node
+                })
+            )
+        }
     }
 
     return (

packages/ui/src/views/canvas/NodeInputHandler.js

@@ -3,15 +3,21 @@ import { Handle, Position, useUpdateNodeInternals } from 'reactflow'
 import { useEffect, useRef, useState, useContext } from 'react'
 
 // material-ui
-import { useTheme } from '@mui/material/styles'
+import { useTheme, styled } from '@mui/material/styles'
 import { Box, Typography, Tooltip } from '@mui/material'
-
+import { tooltipClasses } from '@mui/material/Tooltip'
 import { Dropdown } from 'ui-component/dropdown/Dropdown'
 import { Input } from 'ui-component/input/Input'
 import { File } from 'ui-component/file/File'
 import { flowContext } from 'store/context/ReactFlowContext'
 import { isValidConnection } from 'utils/genericHelper'
 
+const CustomWidthTooltip = styled(({ className, ...props }) => <Tooltip {...props} classes={{ popper: className }} />)({
+    [`& .${tooltipClasses.tooltip}`]: {
+        maxWidth: 500
+    }
+})
+
 // ===========================|| NodeInputHandler ||=========================== //
 
 const NodeInputHandler = ({ inputAnchor, inputParam, data, disabled = false }) => {
@@ -36,14 +42,7 @@ const NodeInputHandler = ({ inputAnchor, inputParam, data, disabled = false }) =
         <div ref={ref}>
             {inputAnchor && (
                 <>
-                    <Tooltip
-                        placement='left'
-                        title={
-                            <Typography sx={{ color: 'white', p: 1 }} variant='h5'>
-                                {'Type: ' + inputAnchor.type}
-                            </Typography>
-                        }
-                    >
+                    <CustomWidthTooltip placement='left' title={inputAnchor.type}>
                         <Handle
                             type='target'
                             position={Position.Left}
@@ -57,7 +56,7 @@ const NodeInputHandler = ({ inputAnchor, inputParam, data, disabled = false }) =
                                 top: position
                             }}
                         />
-                    </Tooltip>
+                    </CustomWidthTooltip>
                     <Box sx={{ p: 2 }}>
                         <Typography>
                             {inputAnchor.label}

packages/ui/src/views/canvas/NodeOutputHandler.js

@@ -3,11 +3,18 @@ import { Handle, Position, useUpdateNodeInternals } from 'reactflow'
 import { useEffect, useRef, useState, useContext } from 'react'
 
 // material-ui
-import { useTheme } from '@mui/material/styles'
+import { useTheme, styled } from '@mui/material/styles'
 import { Box, Typography, Tooltip } from '@mui/material'
+import { tooltipClasses } from '@mui/material/Tooltip'
 import { flowContext } from 'store/context/ReactFlowContext'
 import { isValidConnection } from 'utils/genericHelper'
 
+const CustomWidthTooltip = styled(({ className, ...props }) => <Tooltip {...props} classes={{ popper: className }} />)({
+    [`& .${tooltipClasses.tooltip}`]: {
+        maxWidth: 500
+    }
+})
+
 // ===========================|| NodeOutputHandler ||=========================== //
 
 const NodeOutputHandler = ({ outputAnchor, data }) => {
@@ -34,14 +41,7 @@ const NodeOutputHandler = ({ outputAnchor, data }) => {
 
     return (
         <div ref={ref}>
-            <Tooltip
-                placement='right'
-                title={
-                    <Typography sx={{ color: 'white', p: 1 }} variant='h5'>
-                        {'Type: ' + outputAnchor.type}
-                    </Typography>
-                }
-            >
+            <CustomWidthTooltip placement='right' title={outputAnchor.type}>
                 <Handle
                     type='source'
                     position={Position.Right}
@@ -55,7 +55,7 @@ const NodeOutputHandler = ({ outputAnchor, data }) => {
                         top: position
                     }}
                 />
-            </Tooltip>
+            </CustomWidthTooltip>
             <Box sx={{ p: 2, textAlign: 'end' }}>
                 <Typography>{outputAnchor.label}</Typography>
             </Box>

packages/ui/src/views/chatmessage/ChatMessage.js

@@ -39,6 +39,7 @@ export const ChatMessage = ({ chatflowid }) => {
     const customization = useSelector((state) => state.customization)
     const { confirm } = useConfirm()
     const dispatch = useDispatch()
+    const ps = useRef()
 
     useNotifier()
     const enqueueSnackbar = (...args) => dispatch(enqueueSnackbarAction(...args))
@@ -54,7 +55,6 @@ export const ChatMessage = ({ chatflowid }) => {
         }
     ])
 
-    const messagesEndRef = useRef(null)
     const inputRef = useRef(null)
     const anchorRef = useRef(null)
     const prevOpen = useRef(open)
@@ -115,7 +115,9 @@ export const ChatMessage = ({ chatflowid }) => {
     }
 
     const scrollToBottom = () => {
-        messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' })
+        if (ps.current) {
+            ps.current.scrollTo({ top: Number.MAX_SAFE_INTEGER, behavior: 'smooth' })
+        }
     }
 
     const addChatMessage = async (message, type) => {
@@ -286,7 +288,7 @@ export const ChatMessage = ({ chatflowid }) => {
                             <ClickAwayListener onClickAway={handleClose}>
                                 <MainCard border={false} elevation={16} content={false} boxShadow shadow={theme.shadows[16]}>
                                     <div className='cloud'>
-                                        <div className='messagelist'>
+                                        <div ref={ps} className='messagelist'>
                                             {messages.map((message, index) => {
                                                 return (
                                                     // The latest message sent by the user will be animated while waiting for a response
@@ -331,7 +333,6 @@ export const ChatMessage = ({ chatflowid }) => {
                                                     </Box>
                                                 )
                                             })}
-                                            <div ref={messagesEndRef} />
                                         </div>
                                     </div>
                                     <Divider />