Document analysis & chatbot creation with Llama Parser, Gemini LLM & Pinecone DB
Needs changesNeeds changes. This template uses 1 thing(s) that n8n 3.0 removes: AI Agent v1 (old agent modes). 1 breaking item(s) found. Static check, last run 2026-10-19.
What to replace before upgrading
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) AI Agent (v1.8), AI Agent1 (v1.8), Translator Agent (v1.8), Analyzer Agent (v1.8) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (19)
- n8n Form Trigger
n8n-nodes-base.formTrigger - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - If
n8n-nodes-base.if - Aggregate
n8n-nodes-base.aggregate - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Code
n8n-nodes-base.code - HTTP Request
n8n-nodes-base.httpRequest - Markdown
n8n-nodes-base.markdown - Gmail
n8n-nodes-base.gmail - Convert to File
n8n-nodes-base.convertToFile - AI Agent
@n8n/n8n-nodes-langchain.agent - Information Extractor
@n8n/n8n-nodes-langchain.informationExtractor - Pinecone Vector Store
@n8n/n8n-nodes-langchain.vectorStorePinecone - Embeddings Mistral Cloud
@n8n/n8n-nodes-langchain.embeddingsMistralCloud - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Question and Answer Chain
@n8n/n8n-nodes-langchain.chainRetrievalQa - Vector Store Retriever
@n8n/n8n-nodes-langchain.retrieverVectorStore
What it does
📄Description This automation workflow enables users to upload files via an N8N form, automatically analyzes the content using Google Gemini agents, and delivers the analyzed results via email along with a chatbot link. The system leverages Llama Cloud API, Google Gemini LLM, Pinecone vector database, and Gmail to provide a seamless, multilingual content analysis experience. ✅ Prerequisites Before setting up this workflow, ensure the following are in place: An active N8N instance. Access to Llama Cloud API. Google Gemini LLM API keys (for Translator & Analyzer agents). A Pinecone account with an active index. A Gmail account with API access configured. Basic knowledge of N8N workflow setup. ⚙️ Setup Instructions Deploy the N8N Form Create a public-facing form using N8N. Configure it to accept: File uploads. User email input. File Preprocessing Store the uploaded files temporarily. Organize and preprocess them as needed. Content Extraction using Llama Cloud API Feed the files into the Llama Cloud API. Extract and parse the content for further processing. Translation (if required) Use a Translator Agent (Google Gemini). Check if the content is in English. If not, translate it. Content Analysis Forward the (translated) content to the Analyzer Agent (Google Gemini). Perform deep analysis to extract insights. Vector Storage in Pinecone Store both: The parsed and translated content. The analyzed content. Use Pinecone to store the content as embeddings for chatbot use. User Notification via Gmail Send the analyzed content and chatbot link to the user’s provided email using Gmail API. 🧩 Customization Guidance To add more languages: Update the translation logic to include additional language support. To modify analysis depth: Adjust the prompts sent to the Gemini Analyzer Agent. To change the chatbot behavior: Retrain or reconfigure the chatbot to utilize the new Pinecone index contextually. 🔁 Workflow Summary User uploads files and email via N8N form. Files are parsed using Llama Cloud API. Content is translated (if needed) using Gemini Translator Agent. Translated content is analyzed by the Gemini Analyzer Agent. Parsed and analyzed data is stored in Pinecone. User receives email with analyzed results and a chatbot link.