Dynamic website assistant with DeepSeek AI, Pinecone Vectorstore & site-based routing

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Important notice

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

1. Workflow Overview

This workflow contains community nodes that are only compatible with the self hosted version of n8n. Overview This workflow enables a powerful AI driven virtual assistant that dynamically respon...

Best for

Support Chatbot automation workflows
AI RAG automation workflows
advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.memorypostgreschat, @n8n/n8n-nodes-langchain.lmchatopenrouter, @n8n/n8n-nodes-langchain.vectorstorepinecone, @n8n/n8n-nodes-langchain.embeddingscohere, n8n-nodes-base.webhook, n8n-nodes-base.respondtowebhook, n8n-nodes-base.switch, @n8n/n8n-nodes-langchain.agent

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title: Dynamic website assistant with DeepSeek AI, Pinecone Vectorstore & site-based routing
Workflow name: Dynamic website assistant with DeepSeek AI, Pinecone Vectorstore & site-based routing

This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

🚀 Overview

This workflow enables a powerful AI-driven virtual assistant that dynamically responds to website queries using webhook input, Pinecone vector search, and OpenAI agents — all smartly routed based on the source website.

🔧 How It Works

Webhook Trigger
The workflow starts with a Webhook node that receives query parameters:
- query: The user's question
- userId: Unique user identifier
- site: Website identifier (e.g., test_site)
- page: Page identifier (e.g., homepage, pricing)
Smart Routing
A Switch node directs the request to the correct AI agent based on the site value. Each AI agent uses:
- OpenAI GPT-4/3.5 model
- Pinecone vector store for context-aware answers
- SQL-based memory for consistent multi-turn conversation
Contextual AI Agent
Each agent is customized per website using:
- Site-specific Pinecone namespaces
- Predefined system prompts to stay in scope
- Webhook context including page, site, and userId
Final Response
The response is sent back to the originating website using the Respond to Webhook node.

🧠 Use Case

Ideal for multi-site platforms that want to serve tailored AI chat experiences per domain or page — whether it’s support, content discovery, or interactive agents.

✅ Highlights

🧠 Vector search using Pinecone for contextual responses
🔀 Website-aware logic with Switch node routing
🔐 No hardcoded API keys
🧩 Modular agents for scalable multi-site support

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 - Postgres Chat Memory

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

Block 2 - OpenRouter Chat Model

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

Block 3 - Pinecone Vector Store5

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

Block 4 - Embeddings Cohere

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

Block 5 - Pinecone Vector Store6

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

Block 6 - Embeddings Cohere6

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

Block 7 - Pinecone Vector Store7

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

Block 8 - Embeddings Cohere7

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

Block 9 - Pinecone Vector Store9

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

Block 10 - Embeddings Cohere9

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

Block 11 - Pinecone Vector Store10

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

Block 12 - Embeddings Cohere10

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

Block 13 - Webhook

Type / Role: n8n-nodes-base.webhook - webhook
Config choices: Version 2

Block 14 - Respond to Webhook

Type / Role: n8n-nodes-base.respondToWebhook - respondToWebhook
Config choices: Version 1.4

Block 15 - Switch

Type / Role: n8n-nodes-base.switch - switch
Config choices: Version 3.2

Block 16 - Postgres Chat Memory1

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

Block 17 - OpenRouter Chat Model1

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

Block 18 - Pinecone Vector Store8

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

Block 19 - Embeddings Cohere8

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

Block 20 - Respond to Webhook1

Type / Role: n8n-nodes-base.respondToWebhook - respondToWebhook
Config choices: Version 1.4

Block 21 - AI Agent for groton

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2

Block 22 - AI Agent1 ghostwritingpartner

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2

Block 23 - Postgres Chat Memory2

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

Block 24 - OpenRouter Chat Model2

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

Showing the first 24 of 33 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow	Dynamic website assistant with DeepSeek AI, Pinecone Vectorstore & site-based routing
Complexity	advanced
Nodes	33
Categories	Support Chatbot, AI RAG
Author	moosa
Published	23 Jul 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/6295/6295.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 Support Chatbot workflows AI RAG workflows

Frequently asked questions

What does Dynamic website assistant with DeepSeek AI, Pinecone Vectorstore & site-based routing do?

This workflow contains community nodes that are only compatible with the self hosted version of n8n. Overview This workflow enables a powerful AI driven virtual assistant that dynamically respon...

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 Support Chatbot, AI RAG use case.

moosa

12 workflows

Nodes

@n8n/n8n-nodes-langchain.memorypostgreschat @n8n/n8n-nodes-langchain.lmchatopenrouter @n8n/n8n-nodes-langchain.vectorstorepinecone @n8n/n8n-nodes-langchain.embeddingscohere n8n-nodes-base.webhook n8n-nodes-base.respondtowebhook n8n-nodes-base.switch @n8n/n8n-nodes-langchain.agent

Complexity

advanced

Published 23 Jul 2025

Likes 0

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Install path: /data/workflows/6295/6295.json

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Dynamic website assistant with DeepSeek AI, Pinecone Vectorstore & site-based routing

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

🚀 Overview

🔧 How It Works

🧠 Use Case

✅ Highlights

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Postgres Chat Memory

Block 2 - OpenRouter Chat Model

Block 3 - Pinecone Vector Store5

Block 4 - Embeddings Cohere

Block 5 - Pinecone Vector Store6

Block 6 - Embeddings Cohere6

Block 7 - Pinecone Vector Store7

Block 8 - Embeddings Cohere7

Block 9 - Pinecone Vector Store9

Block 10 - Embeddings Cohere9

Block 11 - Pinecone Vector Store10

Block 12 - Embeddings Cohere10

Block 13 - Webhook

Block 14 - Respond to Webhook

Block 15 - Switch

Block 16 - Postgres Chat Memory1

Block 17 - OpenRouter Chat Model1

Block 18 - Pinecone Vector Store8

Block 19 - Embeddings Cohere8

Block 20 - Respond to Webhook1

Block 21 - AI Agent for groton

Block 22 - AI Agent1 ghostwritingpartner

Block 23 - Postgres Chat Memory2

Block 24 - OpenRouter Chat Model2

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