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Build a cost engineering RAG with Google Drive, OpenAI and Pinecone

n8nn8n17 modulesv1.0
OpenAIGoogle Drive

Quick Overview This workflow ingests PDF cost-engineering manuals from Google Drive into a Pinecone vector index using OpenAI embeddings, then answers user questions via an n8n chat webhook using a retrieval-augmented OpenAI agent that responds only with evidence from the indexed documents. How it works 1. Runs every 2 minutes on a schedule. 2. Lists files in a configured Google Drive “incoming” folder and downloads each document. 3. Extracts text from each PDF, splits it into overlapping chunks

At a glance

Build a cost engineering RAG with Google Drive, OpenAI and Pinecone is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects OpenAI, Google Drive. It's free to download. Follow the 5-step import below to go live in minutes.

Platform
n8n
Connects
OpenAI, Google Drive
Modules
17
Price
Free
Version
v1.0
Build a cost engineering RAG with Google Drive, OpenAI and Pinecone workflow diagram

About this workflow

Quick Overview This workflow ingests PDF cost-engineering manuals from Google Drive into a Pinecone vector index using OpenAI embeddings, then answers user questions via an n8n chat webhook using a retrieval-augmented OpenAI agent that responds only with evidence from the indexed documents. How it works 1. Runs every 2 minutes on a schedule. 2. Lists files in a configured Google Drive “incoming” folder and downloads each document. 3. Extracts text from each PDF, splits it into overlapping chunks, and attaches document metadata. 4. Generates OpenAI embeddings for the chunks and inserts them into the Pinecone rag index. 5. Moves each successfully processed Google Drive file into a configured “ingested/archive” folder. 6. Receives user questions through an n8n Chat webhook and uses a LangChain agent with a Pinecone retrieval tool plus an OpenAI chat model to answer strictly from retrieved passages (or returns the defined fallback message when evidence is missing). Setup 1. Connect Google Drive credentials and replace RAGINCOMINGFOLDERID and RAGINGESTEDFOLDERID with your actual folder IDs. 2. Add an OpenAI API key for both embedding generation and chat responses, and confirm the chat model selection (e.g., gpt-4.1-mini). 3. Connect Pinecone credentials, ensure an index named rag exists, and match its embedding dimension to the OpenAI embeddings model you use. 4. Upload your Technical Composition Manuals as PDFs to the Google Drive incoming folder. 5. Enable the Chat trigger and copy its webhook URL into the client/app you use to send questions (or use n8n’s chat UI).

n8n

How to import this n8n workflow

  1. 1

    Download the workflow JSON file after purchase.

  2. 2

    Open n8n → click the menu → Import from File.

  3. 3

    Select the downloaded JSON and import.

  4. 4

    Set up credentials for each node that requires them.

  5. 5

    Click Execute Workflow to test, then activate.

Setup guide

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