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AI & researchAirtableChain LLMChat TriggerLM Chat Google GeminiOutput Parser Autofixing

receive chat events and categorize and name prompt and create airtable

Configured with Airtable, Chain LLM, Chat Trigger, LM Chat Google Gemini, and additional nodes. Review the connections and setup before adapting this template.

Workflow preview
TriggerWhen chat messagereceivedChat TriggerAI & modelsGoogle Gemini ChatModelLM Chat Google GeminiTransformAuto-fixing OutputParserOutput Parser AutofixingTransformStructured OutputParserOutput Parser StructuredTransformEdit FieldsEdit FieldsAI & modelsGoogle Gemini ChatModel1LM Chat Google GeminiTransformReturn resultsEdit FieldsAI & modelsCategorize and namePromptChain LLMTransformset prompt fieldsEdit FieldsData storeadd to airtableAirtableAI & modelsGenerate a new promptChain LLM

Node categories in this workflow

  • Trigger
  • AI & models
  • Transform
  • Data store

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 chat message receivedTriggerChat TriggerSee node parameters
Google Gemini Chat ModelAI & modelsLM Chat Google GeminiSee node parameters
Auto-fixing Output ParserTransformOutput Parser AutofixingSee node parameters
Structured Output ParserTransformOutput Parser StructuredSee node parameters
Edit FieldsTransformEdit FieldsSee node parameters
Google Gemini Chat Model1AI & modelsLM Chat Google GeminiSee node parameters
Return resultsTransformEdit FieldsSee node parameters
Categorize and name PromptAI & modelsChain LLMSee node parameters
set prompt fieldsTransformEdit FieldsSee node parameters
add to airtableData storeAirtablecreate
Generate a new promptAI & modelsChain LLMSee 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

  • airtableTokenApi
  • googlePalmApi

Workflow notes

receive chat events and categorize and name prompt and create airtable

receive chat events and categorize and name prompt and create airtable

Purpose and structure

This folder contains the receive chat events and categorize and name prompt and create airtable workflow. Its executable nodes use airtable, chainLlm, chatTrigger, lmChatGoogleGemini, outputParserAutofixing, outputParserStructured, set. 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 chat message received

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/Airtable/0756_Airtable_Create_Triggered.json MIT; preserve source notices.

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