📖 RAG chatbot with Supabase + TogetherAI + Openrouter

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Description

⚠️ RUN the FIRST WORKFLOW ONLY ONCE

(as it will convert your content in Embedding format and save it in DB and is ready for the RAG Chat)

📌 Telegram Trigger

• Type: telegramTrigger
• Purpose: Waits for new Telegram messages to trigger the workflow.
• Note: Currently disabled.

📄 Content for the Training

• Type: googleDocs
• Purpose: Fetches document content from Google Docs using its URL.
• Details: Uses Service Account authentication.

✂️ Splitting into Chunks

• Type: code
• Purpose: Splits the fetched document text into smaller chunks (1000 chars each) for processing.
• Logic: Loops over text and slices it.

🧠 Embedding Uploaded Document

• Type: httpRequest
• Purpose: Calls Together AI embedding API to get vector embeddings for each text chunk.
• Details: Sends JSON with model name and chunk as input.

🛢 Save the embedding in DB

• Type: supabase
• Purpose: Saves each text chunk and its embedding vector into the Supabase embed table.

SECOND WORKFLOW EXPLAINATION:

💬 When chat message received

• Type: chatTrigger
• Purpose: Starts the workflow when a user sends a chat message.
• Details: Sends an initial greeting message to the user.

🧩 Embend User Message

• Type: httpRequest
• Purpose: Generates embedding for the user’s input message.
• Details: Calls Together AI embeddings API.

🔍 Search Embeddings

• Type: httpRequest
• Purpose: Searches Supabase DB for the top 5 most similar text chunks based on the generated embedding.
• Details: Calls Supabase RPC function matchembeddings1.

📦 Aggregate

• Type: aggregate
• Purpose: Combines all retrieved text chunks into a single aggregated context for the LLM.

🧠 Basic LLM Chain

• Type: chainLlm
• Purpose: Passes the user’s question + aggregated context to the LLM to generate a detailed answer.
• Details: Contains prompt instructing the LLM to answer only based on context.

🤖 OpenRouter Chat Model

• Type: lmChatOpenRouter
• Purpose: Provides the actual AI language model that processes the prompt.
• Details: Uses qwen/qwen3-8b:free model via OpenRouter and you can use any of your choice.

🔗 Nodes Used

HTTP Request, Telegram Trigger, Google Docs, Supabase, Basic LLM Chain, Chat Trigger

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup