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WhatsApp support bot with Google Drive RAG, GPT-4.1-mini and Cohere reranking

Basil IrfanBasil Irfan
645 views
2/3/2026
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WhatsApp RAG Agent (Text + Voice) with Weekly Google Drive Sync

One-line summary : Answers WhatsApp in under 100 words, understands voice notes, and retrieves trusted answers from your Google Drive docs (RAG) kept fresh weekly.


What this template does

  • Reply to WhatsApp messages in a polite, human tone with ≤100 words.
  • Understands text and voice notes: auto-downloads audio and transcribes to text.
  • Retrieves answers from your knowledge base (RAG): Google Drive docs → chunk → embed → store in Supabase → rerank with Cohere.
  • Keeps short-term memory across the conversation to avoid repetition.
  • Weekly doc sync from a selected Google Drive folder so non-technical staff can update content without touching n8n.

Why it matters

  • Zero busywork: Update a Google Doc; the bot learns it on the next sync.
  • Trustworthy answers: Responses come from your vetted docs, not random web text.
  • Voice-first friendly: Handles the WhatsApp reality of “send a voice note.”
  • Safer by design: Guardrails—no pricing unless in KB, no pushy sales, no medical advice.

Triggers

  • WhatsApp Trigger: Receives incoming messages (text or audio).
  • Google Drive Trigger (weekly): Detects new/updated files in the chosen folder for ingestion.

App credentials required

  • WhatsApp Business Cloud (App ID, Token, Phone Number ID)
  • OpenAI (Chat + Embeddings)
  • Cohere (Rerank)
  • Supabase (SUPABASE_URL, ANON_KEY)
  • Google Drive (OAuth2) + target Folder ID

Suggested environment variables

WHATSAPP_APP_ID=
WHATSAPP_TOKEN=
WHATSAPP_PHONE_NUMBER_ID=
OPENAI_API_KEY=
COHERE_API_KEY=
SUPABASE_URL=
SUPABASE_ANON_KEY=
GDRIVE_FOLDER_ID=
RAG_TABLE_NAME="documents"     # table to store vectors/metadata
MAX_ANSWER_WORDS=100            # guardrail for concise replies

Architecture overview

  • Answer-time lane (RAG Tool):

    1. Receive WhatsApp message → 2) Transcribe audio if present → 3) Maintain short-term memory → 4) Retrieve from Supabase vectors (topK) → 5) Rerank with Cohere → 6) Compose ≤100-word reply with sources → 7) Send on WhatsApp.
  • Ingest lane (Weekly Sync): A) Detect Drive file updates → B) Download & convert (Docs → text/plain) → C) Chunk (size/overlap) → D) Embed with OpenAI → E) Upsert to Supabase with metadata & hashes.


How it works (node rundown)

| # | Node | Key Inputs | Key Outputs | | -- | ------------------------------------------- | ------------------------------- | --------------------------------- | | 1 | WhatsApp Trigger | Incoming message | Raw WhatsApp payload | | 2 | Switch (Attachment presence/type) | Payload | Route: Text or Audio | | 3 | HTTP Request (Audio path) | attachments[0].data_url | Audio file | | 4 | OpenAI – Translate/ASR | Audio file | Transcribed text | | 5 | Merge | Text path + Audio path | Unified text message | | 6 | Simple Memory | Recent turns | Short-term context | | 7 | OpenAI Chat Model | Prompt + message + memory | Draft answer (tool calls allowed) | | 8 | Supabase Vector Tool (retrieve-as-tool) | Query text, topK=10 | Candidate KB passages | | 9 | Cohere Reranker | Candidates | Re-ranked context | | 10 | Send WhatsApp Message | to, body | Reply sent | | 11 | Google Drive Trigger (weekly) | Folder ID, fileUpdated | Changed files | | 12 | Set (File Id) | id from trigger | File ref | | 13 | Google Drive – Download File | Id (Docs→txt) | Raw text | | 14 | Character Text Splitter | chunkSize=2000, overlap=300 | Chunks | | 15 | Default Data Loader | Binary→Document | Clean docs | | 16 | OpenAI Embeddings (ingest) | Chunks | Vectors | | 17 | Supabase Vector Store (insert) | Table: documents | Upserted KB |

Notes

  • The KB Tool is the combo of steps 8–9–7 at answer time (retrieve → rerank → answer).
  • The Ingest lane is steps 11–17 (weekly sync of your Drive folder).

Setup (7‑minute sprint)

  1. Import the workflow JSON.

  2. Connect credentials: WhatsApp, OpenAI, Cohere, Supabase, Google Drive.

  3. Google Drive Trigger: paste your Folder ID; keep fileUpdated event.

  4. Download File: ensure Google Docs convert to text/plain.

  5. Supabase Vector Store (insert): set table name to documents (or your schema).

  6. Character Text Splitter: keep chunkSize=2000, overlap=300 (balanced recall/latency).

  7. Retrieve-as-tool: set topK=10 and enable reranker.

  8. Send WhatsApp Message mapping:

    • Recipient: {{$("WhatsApp Trigger").item.json.messages[0].from}}
    • Body: {{$json.output}}
  9. Test:

    • Send a text and a voice note to your WhatsApp number → confirm concise answers.
    • Drop a Google Doc into the watched folder → verify it’s chunked/embedded on the next weekly poll (or run ingest nodes once manually).

Prompt, tone & guardrails

  • System prompt:

    • Be polite, human, and concise (MAX_ANSWER_WORDS).
    • Cite or reference only the KB content; if unknown, say so and offer to escalate.
    • No prices unless present in the KB. No medical advice.
  • Temperature: start at 0.2 for factual replies.

  • Memory window: keep a short rolling buffer (e.g., last 4–6 turns).


Data model (minimum viable)

Table documents (example columns):

  • id (uuid)
  • source_url (text)
  • title (text)
  • chunk (text)
  • embedding (vector/float[] depending on extension)
  • chunk_hash (text)
  • updated_at (timestamp)

Indexes

  • Unique index on chunk_hash to dedupe
  • Index on updated_at for syncs

Observability & ops

  • Log question, selected chunk ids/hashes, and final response to a DB/Sheet for QA.
  • Add a low-confidence route (score threshold) → Slack/Telegram escalation to a human.
  • Track latency and token usage to tune topK and chunk sizes.

Customization

  • Latency vs quality: try topK=6–8 and chunkSize=1200 for speed.
  • Languages: ASR node can be swapped for native multilingual output.
  • Escalation: add channel handoff on low confidence or no KB hits.
  • Sync cadence: change Drive Trigger to daily if content updates frequently.

Safety & compliance

  • No medical advice. If uncertain or clinical, ask to schedule a consult or refer to the right department.
  • PII: Don’t log full phone numbers in plaintext analytics; hash where possible.
  • Prices & rates: Only answer if present in the KB; otherwise hand off to front desk.

Troubleshooting

  • No reply sent: Ensure Send message node reads {{$json.output}} (Agent’s response property).
  • Audio path failing: Confirm attachments[0].data_url exists and HTTP node fetches a valid file.
  • KB not updating: Manually execute the ingest lane; check rows in Supabase.
  • Irrelevant answers: Lower temperature to 0.2, increase overlap to 400, and verify Drive docs are clean and structured.

Categories & tags

  • Categories: AI, Customer Support, Healthcare Ops, RAG, WhatsApp
  • Tags: WhatsApp, RAG, Google Drive, Supabase, OpenAI, Cohere, Voice Notes

Pricing (rough, BYO keys)

  • n8n: self-host free; n8n.cloud billed by plan.
  • OpenAI, Cohere: usage-based by tokens/calls.
  • Supabase: free tier + usage; vector storage billed by size.
  • WhatsApp Cloud: Meta pricing per conversation.

Nodes used in workflow

WhatsApp Trigger, Switch, HTTP Request, OpenAI (ASR + Chat + Embeddings), Merge, Simple Memory, Supabase Vector Tool (retrieve), Cohere Reranker, Google Drive Trigger, Set, Google Drive – Download, Character Text Splitter, Default Data Loader.

WhatsApp Support Bot with Google Drive RAG, GPT-4o-mini, and Cohere Reranking

This n8n workflow automates a WhatsApp support bot that leverages Retrieval Augmented Generation (RAG) to answer user queries based on documents stored in Google Drive. It uses GPT-4o-mini for conversational AI and Cohere for reranking search results to provide more relevant answers.

Description

This workflow streamlines customer support by providing an intelligent, automated response system via WhatsApp. When a user sends a message, the bot retrieves relevant information from a Google Drive knowledge base, processes it using a large language model, and responds with a helpful answer. It also monitors for new documents in Google Drive to keep its knowledge base up-to-date.

What it does

  1. Listens for WhatsApp Messages: The workflow is triggered by incoming messages to a configured WhatsApp Business Cloud account.
  2. Initializes AI Agent: It sets up an AI Agent with a conversational memory to maintain context throughout the chat.
  3. Configures Document Retrieval:
    • It uses an OpenAI Embeddings model to convert text into vector representations.
    • It connects to a Supabase Vector Store to store and retrieve document embeddings.
    • It employs a Cohere Reranker to improve the relevance of retrieved documents.
  4. Processes User Query: The AI Agent receives the user's message and uses its configured tools to search the vector store for relevant information.
  5. Generates Response: Using the retrieved information and the OpenAI Chat Model (GPT-4o-mini), the AI Agent generates a comprehensive answer to the user's query.
  6. Sends WhatsApp Reply: The generated answer is sent back to the user via WhatsApp.
  7. Monitors Google Drive for New Documents: Separately, the workflow continuously monitors a specified Google Drive folder for new or updated files.
  8. Ingests New Documents: When new documents are detected in Google Drive:
    • It downloads the document content.
    • It splits the document into smaller chunks using a Character Text Splitter.
    • It generates embeddings for these chunks using OpenAI Embeddings.
    • It stores these new embeddings in the Supabase Vector Store, updating the knowledge base.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • WhatsApp Business Cloud Account: Configured with a webhook pointing to your n8n instance.
  • OpenAI API Key: For generating embeddings and using the GPT-4o-mini chat model.
  • Cohere API Key: For the Cohere Reranker.
  • Google Drive Account: With a dedicated folder for your knowledge base documents.
  • Supabase Account: Configured with a PostgreSQL database and pg_vector extension enabled to act as the vector store. You'll need your Supabase URL and API Key.

Setup/Usage

  1. Import the workflow: Download the JSON provided and import it into your n8n instance.
  2. Configure Credentials:
    • WhatsApp Business Cloud: Set up your WhatsApp Business Cloud credential with your Access Token and Phone Number ID.
    • OpenAI: Configure your OpenAI credential with your API Key.
    • Cohere: Configure your Cohere credential with your API Key.
    • Google Drive: Set up a Google Drive OAuth2 credential. Ensure it has access to the folder containing your knowledge base documents.
    • Supabase: Set up a Supabase credential with your Project URL and API Key.
  3. Google Drive Trigger:
    • Select the Google Drive credential.
    • Specify the "Folder ID" in Google Drive where your knowledge base documents are stored.
    • Set the "Check Interval" to your desired frequency for checking new documents.
  4. Supabase Vector Store:
    • In the "Supabase Vector Store" node, ensure your Supabase credential is selected.
    • Configure the "Table Name" where your vectors will be stored.
    • Ensure the "Embeddings OpenAI" node is correctly linked for generating embeddings.
  5. AI Agent:
    • In the "AI Agent" node, ensure the "OpenAI Chat Model" and "Simple Memory" nodes are correctly linked.
    • Review the agent's prompt to customize its persona or instructions if needed.
  6. Activate the workflow: Once all credentials and configurations are set, activate the workflow.

The workflow will now listen for WhatsApp messages and automatically update its knowledge base from Google Drive.

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