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Create AI-Ready Vector Datasets for LLMs with Bright Data, Gemini & Pinecone

Configured with Agent, Chain LLM, Document Default Data Loader, Embeddings Google Gemini, and additional nodes. Review the connections and setup before adapting this template.

Download workflow JSONView files on GitHub ↗16 nodes · MIT
Workflow preview
TriggerWhen clicking ‘Testworkflow’Manual TriggerAI & modelsAI AgentAgentData storePinecone Vector StoreVector Store PineconeAI & modelsEmbeddings GoogleGeminiEmbeddings Google GeminiFiles / mediaDefault Data LoaderDocument Default Data Lo…TransformRecursive CharacterText SplitterText Splitter Recursive …AI & modelsGoogle Gemini ChatModel1LM Chat Google GeminiAI & modelsGoogle Gemini ChatModel2LM Chat Google GeminiAI & modelsGoogle Gemini ChatModelLM Chat Google GeminiTransformStructured OutputParserOutput Parser StructuredTransformSet Fields - URL andWebhook URLEdit FieldsWeb / APIMake a web requestHTTP RequestAI & modelsStructured JSON DataFormatterChain LLMWeb / APIWebhook for structureddataHTTP RequestWeb / APIWebhook for structuredAI agent responseHTTP RequestAI & modelsInformation Extractorwith Data FormatterInformation Extractor

Node categories in this workflow

  • Trigger
  • AI & models
  • Data store
  • Files / media
  • Transform
  • Web / API

Icons describe general node roles, inferred from node types. Inspect the parameters for the configured action.

Drag to pan; use + and − to zoom. Reconstructed from the exported node positions; nothing runs here. Dashed lines represent non-main connections. Full node names and notes appear below.

How it works

The exported workflow contains the following configured nodes. Their connections are shown above; inspect the JSON for the complete logic, expressions, and external actions.

Workflow node names, types, and operations
NodeCategoryTypeOperation
When clicking ‘Test workflow’TriggerManual TriggerSee node parameters
AI AgentAI & modelsAgentSee node parameters
Pinecone Vector StoreData storeVector Store PineconeSee node parameters
Embeddings Google GeminiAI & modelsEmbeddings Google GeminiSee node parameters
Default Data LoaderFiles / mediaDocument Default Data LoaderSee node parameters
Recursive Character Text SplitterTransformText Splitter Recursive Character Text SplitterSee node parameters
Google Gemini Chat Model1AI & modelsLM Chat Google GeminiSee node parameters
Google Gemini Chat Model2AI & modelsLM Chat Google GeminiSee node parameters
Google Gemini Chat ModelAI & modelsLM Chat Google GeminiSee node parameters
Structured Output ParserTransformOutput Parser StructuredSee node parameters
Set Fields - URL and Webhook URLTransformEdit FieldsSee node parameters
Make a web requestWeb / APIHTTP RequestPOST
Structured JSON Data FormatterAI & modelsChain LLMSee node parameters
Webhook for structured dataWeb / APIHTTP RequestSee node parameters
Webhook for structured AI agent responseWeb / APIHTTP RequestSee node parameters
Information Extractor with Data FormatterAI & modelsInformation ExtractorSee node parameters

Setup

  1. Download the JSON and import it into an isolated n8n instance. Leave the workflow inactive.
  2. Connect your own credentials through n8n’s credential store. Replace REPLACE_WITH_* values with your resource identifiers.
  3. Inspect API destinations, Code nodes, database queries, file paths, and outbound actions.
  4. Run with synthetic data and harmless destinations. Enable triggers only after checking the actual outputs.

Requirements

An n8n instance with the listed node types and compatible versions. Service-connected workflows may require accounts, credentials, or paid APIs.

Credential types declared in the source

  • googlePalmApi
  • httpHeaderAuth
  • pineconeApi

Workflow notes

Note

Note

Please make sure to set the URL for web crawling.

Web-Unlocker Product is being utilized for performing the web scrapping.

This workflow is utilizing the Basic LLM Chain, Information Extraction with the AI Agents for formatting, extracting and persisting the response in PineCone Vector Database

Set Fields - URL and Webhook URL

Set the URL which you are interested to scrap the data

Create AI-Ready Vector Datasets for LLMs with Bright Data, Gemini & Pinecone

Create AI-Ready Vector Datasets for LLMs with Bright Data, Gemini & Pinecone

Purpose and structure

This folder contains the Create AI-Ready Vector Datasets for LLMs with Bright Data, Gemini & Pinecone workflow. Its executable nodes use agent, chainLlm, documentDefaultDataLoader, embeddingsGoogleGemini, httpRequest, informationExtractor, lmChatGoogleGemini, manualTrigger, outputParserStructured, set, textSplitterRecursiveCharacterTextSplitter, vectorStorePinecone. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.

Setup

Import inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.

Entry points

When clicking ‘Test workflow’

Verification

Sanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.

Attribution

https://github.com/Zie619/n8n-workflows/blob/94007c1445d9258a7da116646b79473e7c7c3282/workflows/Manual/0933_Manual_Stickynote_Create_Webhook.json MIT; preserve source notices.

Canvas section labels

These name areas of the original canvas; they do not include explanatory instructions.

  • AI Data Formatter
  • Vector Database Persistence
  • Webhook Notification Handler
  • Data Extraction/Formatting with the AI Agent

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