Merge branch 'main' into feature/WebCrawl

# Conflicts: # packages/components/nodes/documentloaders/Puppeteer/Puppeteer.ts
2026-06-28 19:00:59 +03:00 · 2023-07-08 23:47:05 +01:00
parent 6f77461921 21552776d6
commit 251a55972c
12 changed files with 156 additions and 23 deletions
@@ -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 }
@@ -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'
@@ -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 res = await this.caller.callWithOptions({ signal: options.signal }, hf.textGeneration.bind(hf), {
-            model: this.model,
+        const obj: any = {
            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
    }

@@ -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 {
@@ -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(() =>
-            this.client.featureExtraction({
-                model: this.model,
-                inputs: clean
-            })
-        ) as Promise<number[][]>
+        const obj: any = {
+            inputs: clean
+        }
+        if (!this.endpoint) obj.model = this.model
+        return this.caller.call(() => this.client.featureExtraction(obj)) as Promise<number[][]>
    }

    embedQuery(document: string): Promise<number[]> {
@@ -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 res = await this.caller.callWithOptions({ signal: options.signal }, hf.textGeneration.bind(hf), {
-            model: this.model,
+        const obj: any = {
            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
    }

@@ -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",
@@ -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": [],
@@ -680,10 +680,16 @@ export const isFlowValidForStream = (reactFlowNodes: IReactFlowNode[], endingNod
        }
    }

-    return (
-        isChatOrLLMsExist &&
-        (endingNodeData.category === 'Chains' || endingNodeData.name === 'openAIFunctionAgent') &&
-        !isVectorStoreFaiss(endingNodeData) &&
-        process.env.EXECUTION_MODE !== 'child'
-    )
+    let isValidChainOrAgent = false
+    if (endingNodeData.category === 'Chains') {
+        // Chains that are not available to stream
+        const blacklistChains = ['openApiChain']
+        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'
 }