Merge branch 'main' into feature/BabyAGI

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

@@ -1,5 +1,5 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { initializeAgentExecutor, AgentExecutor } from 'langchain/agents'
+import { initializeAgentExecutorWithOptions, AgentExecutor } from 'langchain/agents'
 import { Tool } from 'langchain/tools'
 import { BaseChatModel } from 'langchain/chat_models/base'
 import { BaseChatMemory } from 'langchain/memory'
@@ -48,7 +48,10 @@ class ConversationalAgent_Agents implements INode {
         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)
+        const executor = await initializeAgentExecutorWithOptions(tools, model, {
+            agentType: 'chat-conversational-react-description',
+            verbose: true
+        })
         executor.memory = memory
         return executor
     }

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

@@ -1,8 +1,8 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { initializeAgentExecutor, AgentExecutor } from 'langchain/agents'
-import { Tool } from 'langchain/tools'
+import { initializeAgentExecutorWithOptions, AgentExecutor } from 'langchain/agents'
 import { BaseChatModel } from 'langchain/chat_models/base'
 import { getBaseClasses } from '../../../src/utils'
+import { Tool } from 'langchain/tools'
 
 class MRKLAgentChat_Agents implements INode {
     label: string
@@ -40,8 +40,10 @@ class MRKLAgentChat_Agents implements INode {
     async init(nodeData: INodeData): Promise<any> {
         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)
+        const executor = await initializeAgentExecutorWithOptions(tools, model, {
+            agentType: 'chat-zero-shot-react-description',
+            verbose: true
+        })
         return executor
     }
 

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

@@ -1,5 +1,5 @@
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { initializeAgentExecutor, AgentExecutor } from 'langchain/agents'
+import { initializeAgentExecutorWithOptions, AgentExecutor } from 'langchain/agents'
 import { Tool } from 'langchain/tools'
 import { BaseLLM } from 'langchain/llms/base'
 import { getBaseClasses } from '../../../src/utils'
@@ -41,7 +41,10 @@ class MRKLAgentLLM_Agents implements INode {
         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)
+        const executor = await initializeAgentExecutorWithOptions(tools, model, {
+            agentType: 'zero-shot-react-description',
+            verbose: true
+        })
         return executor
     }
 

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

@@ -1,8 +1,7 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { ICommonObject, INode, INodeData, INodeOutputsValue, 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
@@ -13,6 +12,7 @@ class LLMChain_Chains implements INode {
     baseClasses: string[]
     description: string
     inputs: INodeParams[]
+    outputs: INodeOutputsValue[]
 
     constructor() {
         this.label = 'LLM Chain'
@@ -34,65 +34,99 @@ class LLMChain_Chains implements INode {
                 type: 'BasePromptTemplate'
             },
             {
-                label: 'Format Prompt Values',
-                name: 'promptValues',
+                label: 'Chain Name',
+                name: 'chainName',
                 type: 'string',
-                rows: 5,
-                placeholder: `{
-  "input_language": "English",
-  "output_language": "French"
-}`,
+                placeholder: 'Name Your Chain',
                 optional: true
             }
         ]
+        this.outputs = [
+            {
+                label: 'LLM Chain',
+                name: 'llmChain',
+                baseClasses: [this.type, ...getBaseClasses(LLMChain)]
+            },
+            {
+                label: 'Output Prediction',
+                name: 'outputPrediction',
+                baseClasses: ['string']
+            }
+        ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
+    async init(nodeData: INodeData, input: string): Promise<any> {
         const model = nodeData.inputs?.model as BaseLanguageModel
-        const prompt = nodeData.inputs?.prompt as BasePromptTemplate
+        const prompt = nodeData.inputs?.prompt
+        const output = nodeData.outputs?.output as string
+        const promptValues = prompt.promptValues as ICommonObject
 
-        const chain = new LLMChain({ llm: model, prompt })
-        return chain
+        if (output === this.name) {
+            const chain = new LLMChain({ llm: model, prompt })
+            return chain
+        } else if (output === 'outputPrediction') {
+            const chain = new LLMChain({ llm: model, prompt })
+            const inputVariables = chain.prompt.inputVariables as string[] // ["product"]
+            const res = await runPrediction(inputVariables, chain, input, promptValues)
+            // eslint-disable-next-line no-console
+            console.log('\x1b[92m\x1b[1m\n*****OUTPUT PREDICTION*****\n\x1b[0m\x1b[0m')
+            // eslint-disable-next-line no-console
+            console.log(res)
+            return res
+        }
     }
 
     async run(nodeData: INodeData, input: string): Promise<string> {
         const inputVariables = nodeData.instance.prompt.inputVariables as string[] // ["product"]
         const chain = nodeData.instance as LLMChain
+        const promptValues = nodeData.inputs?.prompt.promptValues as ICommonObject
 
-        if (inputVariables.length === 1) {
-            const res = await chain.run(input)
-            return res
-        } else if (inputVariables.length > 1) {
-            const promptValuesStr = nodeData.inputs?.promptValues as string
-            if (!promptValuesStr) throw new Error('Please provide Prompt Values')
+        const res = await runPrediction(inputVariables, chain, input, promptValues)
+        // eslint-disable-next-line no-console
+        console.log('\x1b[93m\x1b[1m\n*****FINAL RESULT*****\n\x1b[0m\x1b[0m')
+        // eslint-disable-next-line no-console
+        console.log(res)
+        return res
+    }
+}
 
-            const promptValues = JSON.parse(promptValuesStr.replace(/\s/g, ''))
+const runPrediction = async (inputVariables: string[], chain: LLMChain, input: string, promptValues: ICommonObject) => {
+    if (inputVariables.length === 1) {
+        const res = await chain.run(input)
+        return res
+    } else if (inputVariables.length > 1) {
+        let seen: string[] = []
 
-            let seen: string[] = []
-
-            for (const variable of inputVariables) {
-                seen.push(variable)
-                if (promptValues[variable]) {
-                    seen.pop()
-                }
+        for (const variable of inputVariables) {
+            seen.push(variable)
+            if (promptValues[variable]) {
+                seen.pop()
             }
-
-            if (seen.length === 1) {
-                const lastValue = seen.pop()
-                if (!lastValue) throw new Error('Please provide Prompt Values')
-                const options = {
-                    ...promptValues,
-                    [lastValue]: input
-                }
-                const res = await chain.call(options)
-                return res?.text
-            } else {
-                throw new Error('Please provide Prompt Values')
-            }
-        } else {
-            const res = await chain.run(input)
-            return res
         }
+
+        if (seen.length === 0) {
+            // All inputVariables have fixed values specified
+            const options = {
+                ...promptValues
+            }
+            const res = await chain.call(options)
+            return res?.text
+        } else if (seen.length === 1) {
+            // If one inputVariable is not specify, use input (user's question) as value
+            const lastValue = seen.pop()
+            if (!lastValue) throw new Error('Please provide Prompt Values')
+            const options = {
+                ...promptValues,
+                [lastValue]: input
+            }
+            const res = await chain.call(options)
+            return res?.text
+        } else {
+            throw new Error(`Please provide Prompt Values for: ${seen.join(', ')}`)
+        }
+    } else {
+        const res = await chain.run(input)
+        return res
     }
 }
 

packages/components/nodes/chains/VectorDBQAChain/VectorDBQAChain.ts

@@ -0,0 +1,57 @@
+import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses } from '../../../src/utils'
+import { VectorDBQAChain } from 'langchain/chains'
+import { BaseLanguageModel } from 'langchain/base_language'
+import { VectorStore } from 'langchain/vectorstores'
+
+class VectorDBQAChain_Chains implements INode {
+    label: string
+    name: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'VectorDB QA Chain'
+        this.name = 'vectorDBQAChain'
+        this.type = 'VectorDBQAChain'
+        this.icon = 'chain.svg'
+        this.category = 'Chains'
+        this.description = 'QA chain for vector databases'
+        this.baseClasses = [this.type, ...getBaseClasses(VectorDBQAChain)]
+        this.inputs = [
+            {
+                label: 'Language Model',
+                name: 'model',
+                type: 'BaseLanguageModel'
+            },
+            {
+                label: 'Vector Store',
+                name: 'vectorStore',
+                type: 'VectorStore'
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData): Promise<any> {
+        const model = nodeData.inputs?.model as BaseLanguageModel
+        const vectorStore = nodeData.inputs?.vectorStore as VectorStore
+
+        const chain = VectorDBQAChain.fromLLM(model, vectorStore)
+        return chain
+    }
+
+    async run(nodeData: INodeData, input: string): Promise<string> {
+        const chain = nodeData.instance as VectorDBQAChain
+        const obj = {
+            query: input
+        }
+        const res = await chain.call(obj)
+        return res?.text
+    }
+}
+
+module.exports = { nodeClass: VectorDBQAChain_Chains }

packages/components/nodes/chains/VectorDBQAChain/chain.svg

@@ -0,0 +1,6 @@
+<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-dna" 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="M14.828 14.828a4 4 0 1 0 -5.656 -5.656a4 4 0 0 0 5.656 5.656z"></path>
+   <path d="M9.172 20.485a4 4 0 1 0 -5.657 -5.657"></path>
+   <path d="M14.828 3.515a4 4 0 0 0 5.657 5.657"></path>
+</svg>

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

@@ -1,4 +1,4 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
 import { ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate } from 'langchain/prompts'
 
@@ -25,15 +25,28 @@ class ChatPromptTemplate_Prompts implements INode {
                 label: 'System Message',
                 name: 'systemMessagePrompt',
                 type: 'string',
-                rows: 3,
+                rows: 4,
                 placeholder: `You are a helpful assistant that translates {input_language} to {output_language}.`
             },
             {
                 label: 'Human Message',
                 name: 'humanMessagePrompt',
                 type: 'string',
-                rows: 3,
+                rows: 4,
                 placeholder: `{text}`
+            },
+            {
+                label: 'Format Prompt Values',
+                name: 'promptValues',
+                type: 'string',
+                rows: 4,
+                placeholder: `{
+  "input_language": "English",
+  "output_language": "French"
+}`,
+                optional: true,
+                acceptVariable: true,
+                list: true
             }
         ]
     }
@@ -41,11 +54,20 @@ class ChatPromptTemplate_Prompts implements INode {
     async init(nodeData: INodeData): Promise<any> {
         const systemMessagePrompt = nodeData.inputs?.systemMessagePrompt as string
         const humanMessagePrompt = nodeData.inputs?.humanMessagePrompt as string
+        const promptValuesStr = nodeData.inputs?.promptValues as string
 
         const prompt = ChatPromptTemplate.fromPromptMessages([
             SystemMessagePromptTemplate.fromTemplate(systemMessagePrompt),
             HumanMessagePromptTemplate.fromTemplate(humanMessagePrompt)
         ])
+
+        let promptValues: ICommonObject = {}
+        if (promptValuesStr) {
+            promptValues = JSON.parse(promptValuesStr.replace(/\s/g, ''))
+        }
+        // @ts-ignore
+        prompt.promptValues = promptValues
+
         return prompt
     }
 }

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

@@ -27,7 +27,7 @@ class FewShotPromptTemplate_Prompts implements INode {
                 label: 'Examples',
                 name: 'examples',
                 type: 'string',
-                rows: 5,
+                rows: 4,
                 placeholder: `[
   { "word": "happy", "antonym": "sad" },
   { "word": "tall", "antonym": "short" },
@@ -42,14 +42,14 @@ class FewShotPromptTemplate_Prompts implements INode {
                 label: 'Prefix',
                 name: 'prefix',
                 type: 'string',
-                rows: 3,
+                rows: 4,
                 placeholder: `Give the antonym of every input`
             },
             {
                 label: 'Suffix',
                 name: 'suffix',
                 type: 'string',
-                rows: 3,
+                rows: 4,
                 placeholder: `Word: {input}\nAntonym:`
             },
             {

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

@@ -1,6 +1,6 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { ICommonObject, INode, INodeData, INodeParams, PromptTemplate } from '../../../src/Interface'
 import { getBaseClasses, getInputVariables } from '../../../src/utils'
-import { PromptTemplate, PromptTemplateInput } from 'langchain/prompts'
+import { PromptTemplateInput } from 'langchain/prompts'
 
 class PromptTemplate_Prompts implements INode {
     label: string
@@ -19,20 +19,40 @@ 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.baseClasses = [...getBaseClasses(PromptTemplate)]
         this.inputs = [
             {
                 label: 'Template',
                 name: 'template',
                 type: 'string',
-                rows: 5,
+                rows: 4,
                 placeholder: `What is a good name for a company that makes {product}?`
+            },
+            {
+                label: 'Format Prompt Values',
+                name: 'promptValues',
+                type: 'string',
+                rows: 4,
+                placeholder: `{
+  "input_language": "English",
+  "output_language": "French"
+}`,
+                optional: true,
+                acceptVariable: true,
+                list: true
             }
         ]
     }
 
     async init(nodeData: INodeData): Promise<any> {
         const template = nodeData.inputs?.template as string
+        const promptValuesStr = nodeData.inputs?.promptValues as string
+
+        let promptValues: ICommonObject = {}
+        if (promptValuesStr) {
+            promptValues = JSON.parse(promptValuesStr.replace(/\s/g, ''))
+        }
+
         const inputVariables = getInputVariables(template)
 
         try {
@@ -41,6 +61,7 @@ class PromptTemplate_Prompts implements INode {
                 inputVariables
             }
             const prompt = new PromptTemplate(options)
+            prompt.promptValues = promptValues
             return prompt
         } catch (e) {
             throw new Error(e)

packages/components/nodes/tools/AIPlugin/AIPlugin.ts

@@ -0,0 +1,41 @@
+import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { AIPluginTool } from 'langchain/tools'
+import { getBaseClasses } from '../../../src/utils'
+
+class AIPlugin implements INode {
+    label: string
+    name: string
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    inputs?: INodeParams[]
+
+    constructor() {
+        this.label = 'AI Plugin'
+        this.name = 'aiPlugin'
+        this.type = 'AIPlugin'
+        this.icon = 'aiplugin.svg'
+        this.category = 'Tools'
+        this.description = 'Execute actions using ChatGPT Plugin Url'
+        this.baseClasses = [this.type, ...getBaseClasses(AIPluginTool)]
+        this.inputs = [
+            {
+                label: 'Plugin Url',
+                name: 'pluginUrl',
+                type: 'string',
+                placeholder: 'https://www.klarna.com/.well-known/ai-plugin.json'
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData): Promise<any> {
+        const pluginUrl = nodeData.inputs?.pluginUrl as string
+        const aiplugin = await AIPluginTool.fromPluginUrl(pluginUrl)
+
+        return aiplugin
+    }
+}
+
+module.exports = { nodeClass: AIPlugin }

packages/components/nodes/tools/AIPlugin/aiplugin.svg

@@ -0,0 +1,7 @@
+<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-plug" 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="M9.785 6l8.215 8.215l-2.054 2.054a5.81 5.81 0 1 1 -8.215 -8.215l2.054 -2.054z"></path>
+   <path d="M4 20l3.5 -3.5"></path>
+   <path d="M15 4l-3.5 3.5"></path>
+   <path d="M20 9l-3.5 3.5"></path>
+</svg>

packages/components/nodes/tools/ChainTool/ChainTool.ts

@@ -0,0 +1,73 @@
+import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses } from '../../../src/utils'
+import { ChainTool } from 'langchain/tools'
+import { BaseChain } from 'langchain/chains'
+
+class ChainTool_Tools implements INode {
+    label: string
+    name: string
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Chain Tool'
+        this.name = 'chainTool'
+        this.type = 'ChainTool'
+        this.icon = 'chaintool.svg'
+        this.category = 'Tools'
+        this.description = 'Use a chain as allowed tool for agent'
+        this.baseClasses = [this.type, ...getBaseClasses(ChainTool)]
+        this.inputs = [
+            {
+                label: 'Chain Name',
+                name: 'name',
+                type: 'string',
+                placeholder: 'state-of-union-qa'
+            },
+            {
+                label: 'Chain Description',
+                name: 'description',
+                type: 'string',
+                rows: 3,
+                placeholder:
+                    'State of the Union QA - useful for when you need to ask questions about the most recent state of the union address.'
+            },
+            {
+                label: 'Return Direct',
+                name: 'returnDirect',
+                type: 'boolean',
+                optional: true
+            },
+            {
+                label: 'Base Chain',
+                name: 'baseChain',
+                type: 'BaseChain'
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData): Promise<any> {
+        const name = nodeData.inputs?.name as string
+        const description = nodeData.inputs?.description as string
+        const baseChain = nodeData.inputs?.baseChain as BaseChain
+        const returnDirect = nodeData.inputs?.returnDirect as boolean
+
+        const obj = {
+            name,
+            description,
+            chain: baseChain
+        } as any
+
+        if (returnDirect) obj.returnDirect = returnDirect
+
+        const tool = new ChainTool(obj)
+
+        return tool
+    }
+}
+
+module.exports = { nodeClass: ChainTool_Tools }

packages/components/nodes/tools/ChainTool/chaintool.svg

@@ -0,0 +1,4 @@
+<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-tool" 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 10h3v-3l-3.5 -3.5a6 6 0 0 1 8 8l6 6a2 2 0 0 1 -3 3l-6 -6a6 6 0 0 1 -8 -8l3.5 3.5"></path>
+</svg>

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

@@ -1,6 +1,7 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
 import { Chroma } from 'langchain/vectorstores/chroma'
 import { Embeddings } from 'langchain/embeddings/base'
+import { getBaseClasses } from '../../../src/utils'
 
 class Chroma_Existing_VectorStores implements INode {
     label: string
@@ -11,6 +12,7 @@ class Chroma_Existing_VectorStores implements INode {
     category: string
     baseClasses: string[]
     inputs: INodeParams[]
+    outputs: INodeOutputsValue[]
 
     constructor() {
         this.label = 'Chroma Load Existing Index'
@@ -32,17 +34,36 @@ class Chroma_Existing_VectorStores implements INode {
                 type: 'string'
             }
         ]
+        this.outputs = [
+            {
+                label: 'Chroma Retriever',
+                name: 'retriever',
+                baseClasses: [this.type, 'BaseRetriever']
+            },
+            {
+                label: 'Chroma Vector Store',
+                name: 'vectorStore',
+                baseClasses: [this.type, ...getBaseClasses(Chroma)]
+            }
+        ]
     }
 
     async init(nodeData: INodeData): Promise<any> {
         const collectionName = nodeData.inputs?.collectionName as string
         const embeddings = nodeData.inputs?.embeddings as Embeddings
+        const output = nodeData.outputs?.output as string
 
         const vectorStore = await Chroma.fromExistingCollection(embeddings, {
             collectionName
         })
-        const retriever = vectorStore.asRetriever()
-        return retriever
+
+        if (output === 'retriever') {
+            const retriever = vectorStore.asRetriever()
+            return retriever
+        } else if (output === 'vectorStore') {
+            return vectorStore
+        }
+        return vectorStore
     }
 }
 

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

@@ -1,7 +1,8 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
 import { Chroma } from 'langchain/vectorstores/chroma'
 import { Embeddings } from 'langchain/embeddings/base'
 import { Document } from 'langchain/document'
+import { getBaseClasses } from '../../../src/utils'
 
 class ChromaUpsert_VectorStores implements INode {
     label: string
@@ -12,6 +13,7 @@ class ChromaUpsert_VectorStores implements INode {
     category: string
     baseClasses: string[]
     inputs: INodeParams[]
+    outputs: INodeOutputsValue[]
 
     constructor() {
         this.label = 'Chroma Upsert Document'
@@ -38,12 +40,25 @@ class ChromaUpsert_VectorStores implements INode {
                 type: 'string'
             }
         ]
+        this.outputs = [
+            {
+                label: 'Chroma Retriever',
+                name: 'retriever',
+                baseClasses: [this.type, 'BaseRetriever']
+            },
+            {
+                label: 'Chroma Vector Store',
+                name: 'vectorStore',
+                baseClasses: [this.type, ...getBaseClasses(Chroma)]
+            }
+        ]
     }
 
     async init(nodeData: INodeData): Promise<any> {
         const collectionName = nodeData.inputs?.collectionName as string
         const docs = nodeData.inputs?.document as Document[]
         const embeddings = nodeData.inputs?.embeddings as Embeddings
+        const output = nodeData.outputs?.output as string
 
         const finalDocs = []
         for (let i = 0; i < docs.length; i += 1) {
@@ -53,8 +68,14 @@ class ChromaUpsert_VectorStores implements INode {
         const vectorStore = await Chroma.fromDocuments(finalDocs, embeddings, {
             collectionName
         })
-        const retriever = vectorStore.asRetriever()
-        return retriever
+
+        if (output === 'retriever') {
+            const retriever = vectorStore.asRetriever()
+            return retriever
+        } else if (output === 'vectorStore') {
+            return vectorStore
+        }
+        return vectorStore
     }
 }
 

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

@@ -1,7 +1,8 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
 import { PineconeClient } from '@pinecone-database/pinecone'
 import { PineconeStore } from 'langchain/vectorstores/pinecone'
 import { Embeddings } from 'langchain/embeddings/base'
+import { getBaseClasses } from '../../../src/utils'
 
 class Pinecone_Existing_VectorStores implements INode {
     label: string
@@ -12,6 +13,7 @@ class Pinecone_Existing_VectorStores implements INode {
     category: string
     baseClasses: string[]
     inputs: INodeParams[]
+    outputs: INodeOutputsValue[]
 
     constructor() {
         this.label = 'Pinecone Load Existing Index'
@@ -43,6 +45,18 @@ class Pinecone_Existing_VectorStores implements INode {
                 type: 'string'
             }
         ]
+        this.outputs = [
+            {
+                label: 'Pinecone Retriever',
+                name: 'retriever',
+                baseClasses: [this.type, 'BaseRetriever']
+            },
+            {
+                label: 'Pinecone Vector Store',
+                name: 'vectorStore',
+                baseClasses: [this.type, ...getBaseClasses(PineconeStore)]
+            }
+        ]
     }
 
     async init(nodeData: INodeData): Promise<any> {
@@ -50,6 +64,7 @@ class Pinecone_Existing_VectorStores implements INode {
         const pineconeEnv = nodeData.inputs?.pineconeEnv as string
         const index = nodeData.inputs?.pineconeIndex as string
         const embeddings = nodeData.inputs?.embeddings as Embeddings
+        const output = nodeData.outputs?.output as string
 
         const client = new PineconeClient()
         await client.init({
@@ -62,8 +77,14 @@ class Pinecone_Existing_VectorStores implements INode {
         const vectorStore = await PineconeStore.fromExistingIndex(embeddings, {
             pineconeIndex
         })
-        const retriever = vectorStore.asRetriever()
-        return retriever
+
+        if (output === 'retriever') {
+            const retriever = vectorStore.asRetriever()
+            return retriever
+        } else if (output === 'vectorStore') {
+            return vectorStore
+        }
+        return vectorStore
     }
 }
 

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

@@ -1,8 +1,9 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { INode, INodeData, INodeOutputsValue, 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'
+import { getBaseClasses } from '../../../src/utils'
 
 class PineconeUpsert_VectorStores implements INode {
     label: string
@@ -13,6 +14,7 @@ class PineconeUpsert_VectorStores implements INode {
     category: string
     baseClasses: string[]
     inputs: INodeParams[]
+    outputs: INodeOutputsValue[]
 
     constructor() {
         this.label = 'Pinecone Upsert Document'
@@ -49,6 +51,18 @@ class PineconeUpsert_VectorStores implements INode {
                 type: 'string'
             }
         ]
+        this.outputs = [
+            {
+                label: 'Pinecone Retriever',
+                name: 'retriever',
+                baseClasses: [this.type, 'BaseRetriever']
+            },
+            {
+                label: 'Pinecone Vector Store',
+                name: 'vectorStore',
+                baseClasses: [this.type, ...getBaseClasses(PineconeStore)]
+            }
+        ]
     }
 
     async init(nodeData: INodeData): Promise<any> {
@@ -57,6 +71,7 @@ class PineconeUpsert_VectorStores implements INode {
         const index = nodeData.inputs?.pineconeIndex as string
         const docs = nodeData.inputs?.document as Document[]
         const embeddings = nodeData.inputs?.embeddings as Embeddings
+        const output = nodeData.outputs?.output as string
 
         const client = new PineconeClient()
         await client.init({
@@ -74,8 +89,14 @@ class PineconeUpsert_VectorStores implements INode {
         const vectorStore = await PineconeStore.fromDocuments(finalDocs, embeddings, {
             pineconeIndex
         })
-        const retriever = vectorStore.asRetriever()
-        return retriever
+
+        if (output === 'retriever') {
+            const retriever = vectorStore.asRetriever()
+            return retriever
+        } else if (output === 'vectorStore') {
+            return vectorStore
+        }
+        return vectorStore
     }
 }