Merge branch 'main' into feature/WebCrawl

# Conflicts:
#	packages/components/nodes/documentloaders/Puppeteer/Puppeteer.ts

Dockerfile

@@ -8,7 +8,12 @@ FROM node:18-alpine
 RUN apk add --update libc6-compat python3 make g++
 # needed for pdfjs-dist
 RUN apk add --no-cache build-base cairo-dev pango-dev
+
+# Install Chromium
+RUN apk add --no-cache chromium
+
 ENV PUPPETEER_SKIP_DOWNLOAD=true
+ENV PUPPETEER_EXECUTABLE_PATH=/usr/bin/chromium-browser
 
 WORKDIR /usr/src/packages
 

docker/Dockerfile

@@ -6,7 +6,12 @@ RUN apk add --no-cache git
 RUN apk add --no-cache python3 py3-pip make g++
 # needed for pdfjs-dist
 RUN apk add --no-cache build-base cairo-dev pango-dev
+
+# Install Chromium
+RUN apk add --no-cache chromium
+
 ENV PUPPETEER_SKIP_DOWNLOAD=true
+ENV PUPPETEER_EXECUTABLE_PATH=/usr/bin/chromium-browser
 
 # You can install a specific version like: flowise@1.0.0
 RUN npm install -g flowise

packages/components/nodes/chains/ApiChain/OpenAPIChain.ts

@@ -0,0 +1,95 @@
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { APIChain, createOpenAPIChain } from 'langchain/chains'
+import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
+import { ChatOpenAI } from 'langchain/chat_models/openai'
+
+class OpenApiChain_Chains implements INode {
+    label: string
+    name: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'OpenAPI Chain'
+        this.name = 'openApiChain'
+        this.type = 'openApiChain'
+        this.icon = 'openapi.png'
+        this.category = 'Chains'
+        this.description = 'Chain to run queries against OpenAPI'
+        this.baseClasses = [this.type, ...getBaseClasses(APIChain)]
+        this.inputs = [
+            {
+                label: 'ChatOpenAI Model',
+                name: 'model',
+                type: 'ChatOpenAI'
+            },
+            {
+                label: 'YAML Link',
+                name: 'yamlLink',
+                type: 'string',
+                placeholder: 'https://api.speak.com/openapi.yaml',
+                description: 'If YAML link is provided, uploaded YAML File will be ignored and YAML link will be used instead'
+            },
+            {
+                label: 'YAML File',
+                name: 'yamlFile',
+                type: 'file',
+                fileType: '.yaml',
+                description: 'If YAML link is provided, uploaded YAML File will be ignored and YAML link will be used instead'
+            },
+            {
+                label: 'Headers',
+                name: 'headers',
+                type: 'json',
+                additionalParams: true,
+                optional: true
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData): Promise<any> {
+        return await initChain(nodeData)
+    }
+
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+        const chain = await initChain(nodeData)
+        if (options.socketIO && options.socketIOClientId) {
+            const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
+            const res = await chain.run(input, [handler])
+            return res
+        } else {
+            const res = await chain.run(input)
+            return res
+        }
+    }
+}
+
+const initChain = async (nodeData: INodeData) => {
+    const model = nodeData.inputs?.model as ChatOpenAI
+    const headers = nodeData.inputs?.headers as string
+    const yamlLink = nodeData.inputs?.yamlLink as string
+    const yamlFileBase64 = nodeData.inputs?.yamlFile as string
+
+    let yamlString = ''
+
+    if (yamlLink) {
+        yamlString = yamlLink
+    } else {
+        const splitDataURI = yamlFileBase64.split(',')
+        splitDataURI.pop()
+        const bf = Buffer.from(splitDataURI.pop() || '', 'base64')
+        yamlString = bf.toString('utf-8')
+    }
+
+    return await createOpenAPIChain(yamlString, {
+        llm: model,
+        headers: typeof headers === 'object' ? headers : headers ? JSON.parse(headers) : {},
+        verbose: process.env.DEBUG === 'true' ? true : false
+    })
+}
+
+module.exports = { nodeClass: OpenApiChain_Chains }

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

@@ -1,5 +1,5 @@
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
-import { SqlDatabaseChain, SqlDatabaseChainInput } from 'langchain/chains'
+import { SqlDatabaseChain, SqlDatabaseChainInput } from 'langchain/chains/sql_db'
 import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
 import { DataSource } from 'typeorm'
 import { SqlDatabase } from 'langchain/sql_db'

packages/components/nodes/chatmodels/ChatHuggingFace/core.ts

@@ -78,9 +78,7 @@ export class HuggingFaceInference extends LLM implements HFInput {
     async _call(prompt: string, options: this['ParsedCallOptions']): Promise<string> {
         const { HfInference } = await HuggingFaceInference.imports()
         const hf = new HfInference(this.apiKey)
-        if (this.endpoint) hf.endpoint(this.endpoint)
+        const obj: any = {
-        const res = await this.caller.callWithOptions({ signal: options.signal }, hf.textGeneration.bind(hf), {
-            model: this.model,
             parameters: {
                 // make it behave similar to openai, returning only the generated text
                 return_full_text: false,
@@ -91,7 +89,13 @@ export class HuggingFaceInference extends LLM implements HFInput {
                 repetition_penalty: this.frequencyPenalty
             },
             inputs: prompt
-        })
+        }
+        if (this.endpoint) {
+            hf.endpoint(this.endpoint)
+        } else {
+            obj.model = this.model
+        }
+        const res = await this.caller.callWithOptions({ signal: options.signal }, hf.textGeneration.bind(hf), obj)
         return res.generated_text
     }
 

packages/components/nodes/documentloaders/Puppeteer/Puppeteer.ts

@@ -86,7 +86,12 @@ class Puppeteer_DocumentLoaders implements INode {
         async function puppeteerLoader(url: string): Promise<any> {
             try {
                 let docs = []
-                const loader = new PuppeteerWebBaseLoader(url)
+                const loader = new PuppeteerWebBaseLoader(url, {
+                    launchOptions: {
+                        args: ['--no-sandbox'],
+                        headless: 'new'
+                    }
+                })
                 if (textSplitter) {
                     docs = await loader.loadAndSplit(textSplitter)
                 } else {

packages/components/nodes/embeddings/HuggingFaceInferenceEmbedding/core.ts

@@ -30,12 +30,11 @@ export class HuggingFaceInferenceEmbeddings extends Embeddings implements Huggin
     async _embed(texts: string[]): Promise<number[][]> {
         // replace newlines, which can negatively affect performance.
         const clean = texts.map((text) => text.replace(/\n/g, ' '))
-        return this.caller.call(() =>
+        const obj: any = {
-            this.client.featureExtraction({
+            inputs: clean
-                model: this.model,
+        }
-                inputs: clean
+        if (!this.endpoint) obj.model = this.model
-            })
+        return this.caller.call(() => this.client.featureExtraction(obj)) as Promise<number[][]>
-        ) as Promise<number[][]>
     }
 
     embedQuery(document: string): Promise<number[]> {

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

@@ -78,9 +78,7 @@ export class HuggingFaceInference extends LLM implements HFInput {
     async _call(prompt: string, options: this['ParsedCallOptions']): Promise<string> {
         const { HfInference } = await HuggingFaceInference.imports()
         const hf = new HfInference(this.apiKey)
-        if (this.endpoint) hf.endpoint(this.endpoint)
+        const obj: any = {
-        const res = await this.caller.callWithOptions({ signal: options.signal }, hf.textGeneration.bind(hf), {
-            model: this.model,
             parameters: {
                 // make it behave similar to openai, returning only the generated text
                 return_full_text: false,
@@ -91,7 +89,13 @@ export class HuggingFaceInference extends LLM implements HFInput {
                 repetition_penalty: this.frequencyPenalty
             },
             inputs: prompt
-        })
+        }
+        if (this.endpoint) {
+            hf.endpoint(this.endpoint)
+        } else {
+            obj.model = this.model
+        }
+        const res = await this.caller.callWithOptions({ signal: options.signal }, hf.textGeneration.bind(hf), obj)
         return res.generated_text
     }
 

packages/components/package.json

@@ -36,7 +36,7 @@
         "form-data": "^4.0.0",
         "graphql": "^16.6.0",
         "html-to-text": "^9.0.5",
-        "langchain": "^0.0.96",
+        "langchain": "^0.0.104",
         "linkifyjs": "^4.1.1",
         "mammoth": "^1.5.1",
         "moment": "^2.29.3",

packages/server/marketplaces/chatflows/HuggingFace LLM Chain.json

@@ -156,6 +156,16 @@
                         "optional": true,
                         "additionalParams": true,
                         "id": "huggingFaceInference_LLMs_0-input-frequencyPenalty-number"
+                    },
+                    {
+                        "label": "Endpoint",
+                        "name": "endpoint",
+                        "type": "string",
+                        "placeholder": "https://xyz.eu-west-1.aws.endpoints.huggingface.cloud/gpt2",
+                        "description": "Using your own inference endpoint",
+                        "optional": true,
+                        "additionalParams": true,
+                        "id": "huggingFaceInference_LLMs_0-input-endpoint-string"
                     }
                 ],
                 "inputAnchors": [],

packages/server/src/utils/index.ts

@@ -680,10 +680,16 @@ export const isFlowValidForStream = (reactFlowNodes: IReactFlowNode[], endingNod
         }
     }
 
-    return (
+    let isValidChainOrAgent = false
-        isChatOrLLMsExist &&
+    if (endingNodeData.category === 'Chains') {
-        (endingNodeData.category === 'Chains' || endingNodeData.name === 'openAIFunctionAgent') &&
+        // Chains that are not available to stream
-        !isVectorStoreFaiss(endingNodeData) &&
+        const blacklistChains = ['openApiChain']
-        process.env.EXECUTION_MODE !== 'child'
+        isValidChainOrAgent = !blacklistChains.includes(endingNodeData.name)
-    )
+    } else if (endingNodeData.category === 'Agents') {
+        // Agent that are available to stream
+        const whitelistAgents = ['openAIFunctionAgent']
+        isValidChainOrAgent = whitelistAgents.includes(endingNodeData.name)
+    }
+
+    return isChatOrLLMsExist && isValidChainOrAgent && !isVectorStoreFaiss(endingNodeData) && process.env.EXECUTION_MODE !== 'child'
 }