AI-powered document chat with Nextcloud files using LangChain and OpenAI
Transform your Nextcloud storage into an intelligent knowledge base by allowing a LangChain agent to interact directly with your documents. This workflow automatically extracts text from PDFs, Word files, and Markdown notes to provide an AI with the precise context needed for accurate chat responses. It is the perfect solution for teams looking to query their private file repositories using natural language.
Run this with your team's AIWhat This Recipe Does
This AI-driven document management automation transforms how your organization interacts with stored data. By integrating a conversational AI interface with NextCloud, this workflow allows team members to query, extract, and analyze information from files using natural language. Instead of manually searching through folders and reading dozens of documents to find specific details, users can simply ask questions and receive structured summaries or specific data points instantly. The system intelligently routes requests, processes various file types through automated extraction, and aggregates results into a cohesive response. This significantly reduces the time spent on administrative research and ensures that critical information trapped in static documents becomes an accessible, actionable asset for your entire team. By bridging the gap between raw file storage and intelligent retrieval, this automation empowers better decision-making and accelerates project timelines.
What your team gets
Forms and dashboards, so it is not a script only one person understands
Runs on your schedule in the cloud, so it does not stop when a laptop closes
Endpoints, so the rest of your stack can trigger the same work
Langchain.chatTrigger, Langchain.lmChatOpenAi, Langchain.memoryBufferWindow, Langchain.agent, ExecuteWorkflowTrigger connected for the team, not per person
How It Works
- 1
Open the recipe and connect your accounts
Connect Langchain.chatTrigger and Langchain.lmChatOpenAi once, in your team cloud, and nobody has to do it again on their own machine
- 2
Tell your own agent what is different about your process
Claude, ChatGPT, Cursor, whichever your team already uses. It adapts the recipe to how you actually work
- 3
Run it, then leave it running
It lives in your team cloud, so it keeps going after you close the laptop and every teammate's AI can use it
Who Uses This
- Legal and compliance teams use this to quickly query contract terms and policy documents without manual review.
- Project managers use this to extract status updates and key milestones from a large volume of archived project reports.
- HR departments use this to search through employee handbooks and internal documentation to provide instant answers to staff inquiries.
Frequently Asked Questions
Do I need to know how to code to use this AI agent?
No. Once deployed, users interact with the system through a simple chat interface using everyday language.
What types of files can the AI extract information from?
The automation is designed to process standard document formats stored in NextCloud, including PDFs and text-based files.
Can I limit the AI's access to specific folders?
Yes, you can configure the integration to only access specific directories within your NextCloud environment to maintain data security.
How does the AI handle multiple documents at once?
The workflow includes an aggregation step that gathers information from multiple sources and synthesizes them into a single, comprehensive answer.
Coming from n8n?
This recipe uses nodes like Langchain.chatTrigger, Langchain.lmChatOpenAi, Langchain.memoryBufferWindow, Langchain.agent and 10 more. On Runwork, you don't need to learn n8n's workflow syntax. Describe what you want to your own AI agent in plain English.
Based on n8n community workflow. View original
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Run this with the AI your team already uses
Your agent adapts it, your team cloud keeps it running, and everyone's AI can find it.
Open this recipe in Runwork