Audio transcription & chat bot with AssemblyAI, Gemini, and Pinecone RAG

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Who’s it for This template is designed for podcasters, researchers, educators, product teams, and support teams who work with audio content and want to turn it into searchable knowledge. It is espe...

Best for

Document Extraction automation workflows
AI RAG automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.formtrigger, n8n-nodes-base.httprequest, n8n-nodes-base.wait, n8n-nodes-base.if, n8n-nodes-base.converttofile, @n8n/n8n-nodes-langchain.vectorstorepinecone, @n8n/n8n-nodes-langchain.embeddingsgooglegemini, @n8n/n8n-nodes-langchain.textsplitterrecursivecharactertextsplitter

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Pixcels Themes.

Original n8n.io source

1.1 Workflow description

Title: Audio transcription & chat bot with AssemblyAI, Gemini, and Pinecone RAG
Workflow name: Audio transcription & chat bot with AssemblyAI, Gemini, and Pinecone RAG

Who’s it for

This template is designed for podcasters, researchers, educators, product teams, and support teams who work with audio content and want to turn it into searchable knowledge. It is especially useful for users who need automated transcription, structured summaries, and conversational access to audio data.

What it does / How it works

This workflow starts with a public form where users upload an audio file.
The audio is sent to AssemblyAI for speech-to-text processing, including speaker labels and bullet-point summarization.
Once transcription is complete, the full text is converted into a document, split into chunks, and embedded using Google Gemini.
The embeddings are stored in a Pinecone vector database along with metadata, making the content retrievable for future use.

In parallel, the workflow logs uploaded file information into Google Sheets for tracking.
A separate chat trigger allows users to ask questions about the uploaded audio files.
An AI agent retrieves relevant context from Pinecone and responds using Gemini, enabling conversational search over audio transcripts.

Requirements

AssemblyAI API credentials
Google Gemini (PaLM) API credentials
Pinecone API credentials
Google Sheets OAuth2 credentials
A Pinecone index for storing audio embeddings

How to set up

Connect AssemblyAI, Gemini, Pinecone, and Google Sheets credentials in n8n.
Configure the Pinecone index for storing transcripts.
Verify the Google Sheet has columns for file name and status.
Test by uploading an audio file through the form.
Enable the workflow for continuous use.

How to customize the workflow

Change summary style or transcript options in AssemblyAI
Adjust chunk size and overlap for better retrieval
Add email or Slack notifications after processing
Extend the chatbot to support multiple knowledge bases

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - On form submission

Type / Role: n8n-nodes-base.formTrigger - formTrigger
Config choices: Version 2.3

Block 2 - HTTP Request

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.3

Block 3 - HTTP Request1

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.3

Block 4 - HTTP Request2

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.3

Block 5 - Wait

Type / Role: n8n-nodes-base.wait - wait
Config choices: Version 1.1

Block 6 - If

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.3

Block 7 - Convert to File

Type / Role: n8n-nodes-base.convertToFile - convertToFile
Config choices: Version 1.1

Block 8 - Pinecone Vector Store

Type / Role: @n8n/n8n-nodes-langchain.vectorStorePinecone - vectorStorePinecone
Config choices: Version 1.3

Block 9 - Embeddings Google Gemini

Type / Role: @n8n/n8n-nodes-langchain.embeddingsGoogleGemini - embeddingsGoogleGemini
Config choices: Version 1

Block 10 - Recursive Character Text Splitter

Type / Role: @n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - textSplitterRecursiveCharacterTextSplitter
Config choices: Version 1

Block 11 - Default Data Loader

Type / Role: @n8n/n8n-nodes-langchain.documentDefaultDataLoader - documentDefaultDataLoader
Config choices: Version 1.1

Block 12 - Append row in sheet

Type / Role: n8n-nodes-base.googleSheets - googleSheets
Config choices: Version 4.7

Block 13 - When chat message received

Type / Role: @n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices: Version 1.3

Block 14 - AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2.2

Block 15 - Google Gemini Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatGoogleGemini - lmChatGoogleGemini
Config choices: Version 1

Block 16 - Simple Memory

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 17 - Pinecone Vector Store1

Type / Role: @n8n/n8n-nodes-langchain.vectorStorePinecone - vectorStorePinecone
Config choices: Version 1.3

Block 18 - Embeddings Google Gemini1

Type / Role: @n8n/n8n-nodes-langchain.embeddingsGoogleGemini - embeddingsGoogleGemini
Config choices: Version 1

Block 19 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 20 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 21 - Sticky Note2

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 22 - Sticky Note3

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 23 - Sticky Note4

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

3. Summary Table

Workflow	Audio transcription & chat bot with AssemblyAI, Gemini, and Pinecone RAG
Complexity	advanced
Nodes	23
Categories	Document Extraction, AI RAG
Author	Pixcels Themes
Published	17 Dec 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/11888/11888.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Document Extraction workflows AI RAG workflows

Frequently asked questions

What does Audio transcription & chat bot with AssemblyAI, Gemini, and Pinecone RAG do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Document Extraction, AI RAG use case.

Pixcels Themes

11 workflows

Nodes

n8n-nodes-base.formtrigger n8n-nodes-base.httprequest n8n-nodes-base.wait n8n-nodes-base.if n8n-nodes-base.converttofile @n8n/n8n-nodes-langchain.vectorstorepinecone @n8n/n8n-nodes-langchain.embeddingsgooglegemini @n8n/n8n-nodes-langchain.textsplitterrecursivecharactertextsplitter

Complexity

advanced

Published 17 Dec 2025

Likes 0

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Install path: /data/workflows/11888/11888.json

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Audio transcription & chat bot with AssemblyAI, Gemini, and Pinecone RAG

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Who’s it for

What it does / How it works

Requirements

How to set up

How to customize the workflow

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - On form submission

Block 2 - HTTP Request

Block 3 - HTTP Request1

Block 4 - HTTP Request2

Block 5 - Wait

Block 6 - If

Block 7 - Convert to File

Block 8 - Pinecone Vector Store

Block 9 - Embeddings Google Gemini

Block 10 - Recursive Character Text Splitter

Block 11 - Default Data Loader

Block 12 - Append row in sheet

Block 13 - When chat message received

Block 14 - AI Agent

Block 15 - Google Gemini Chat Model

Block 16 - Simple Memory

Block 17 - Pinecone Vector Store1

Block 18 - Embeddings Google Gemini1

Block 19 - Sticky Note

Block 20 - Sticky Note1

Block 21 - Sticky Note2

Block 22 - Sticky Note3

Block 23 - Sticky Note4

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions