How to Add File Storage to Flowise Chatflows

Flowise is an open-source platform for building LLM apps without code. It lets you build chatflows that handle documents, manage knowledge bases, and save agent outputs. However, the default setup uses a local database and the local filesystem for uploads. This causes three main issues for real-world apps:

Data Loss in Containers: If you run Flowise on Docker, Railway, or Render, the local disk is temporary. When the container restarts, your uploads and files vanish. 2.

Scaling Issues: Storing big PDFs or datasets on the same server as your app makes the instance heavy and hard to scale. 3.

Handoff Friction: If an agent generates a report, there is no easy way for a user to find it later. You usually end up with broken download links and no history for the user. Using external storage fixes this by keeping your data separate from the code running your agents.

Helpful references: Fastio Workspaces, Fastio Collaboration, and Fastio AI.

Flowise has basic support for external storage through environment variables. You can change where files are saved by updating your config.

Local Storage (Default)

By default, STORAGE_TYPE is set to local. Files go to .flowise/storage on the machine running the app. This is fine for testing on your laptop but risky for anything else.

AWS S3 Integration

You can tell

Flowise to use AWS S3 by setting STORAGE_TYPE=s3 and adding your AWS keys (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION, AWS_BUCKET_NAME).

The Good:

• Files stay safe even if the container dies. * Uses a standard industry tool.

The Bad:

• Setting up IAM permissions is a chore. * There is no interface for users to see their files. * You have to write extra code to create shareable links for users.

If your agents need to give files to people (or if people need to send files to agents), Fastio is a better way to handle it. It goes beyond simple storage by providing a branded portal for your users, global speed, and a dedicated MCP server for your agents.

Why use Fastio with Flowise? * Built-in Delivery Portals: When an agent saves a file, it shows up in a secure, branded portal. You don't have to build a frontend for file downloads. * Simple MCP Connection: The Fastio MCP server connects your Flowise agent to storage with one command, giving it 251 tools to manage files. * Free for Developers: The free plan gives you 50GB of storage and 5,000 API credits a month, which is plenty for building and testing. Industry trends suggest enterprise AI workflows increasingly require persistent file handoffs between agents and humans.

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You can connect Flowise to Fastio in two ways: with the HTTP Request Tool (simple) or the MCP Tool (for advanced agents).

Method 1: Using the HTTP Request Node

Use this for simple file uploads.

Get your API Key: Sign up for a free account at Fastio and grab an API key. 2.

Add HTTP Request Node: Drag a "Custom Tool" or "HTTP Request" node into your Flowise chatflow. 3.

Configure the Endpoint: * URL: https://api.fast.io/v1/files/upload * Method: POST * Headers: Authorization: Bearer <YOUR_KEY>

• Body: Send the file content from the previous node in your chain.

Fastio MCP Server Method

If your agent needs to search, read, and organize files, use the Model Context Protocol.

Start the MCP Server: Run the Fastio MCP server using Docker or Node.js. 2.

Connect Flowise: In Flowise, use the "MCP Tool" node and point it to your server. 3.

Choose Your Tools: Enable tools like files_list, files_read, or files_write. Now the agent can decide when to save its work, check for existing files, or look up information from a previous chat.

A popular use for Flowise is building an automated document pipeline. Here is how you can set one up with reliable storage:

Upload: A user drops a PDF into a Fastio "Input" folder using a shared link. 2.

Trigger: A webhook tells your Flowise workflow that a new file is ready. 3.

Process: * The agent uses the files_read tool to pull the PDF. * The LLM (like GPT-4o or Claude) pulls out the data you need, like invoice dates or totals. 4.

Save: * The agent saves the results as a JSON file in an "Output" folder. * The agent moves the original PDF to an archive folder. This way, nothing gets lost in the chat window. Everything is stored, logged, and easy to find later.

When agents handle files, security is the top priority. Standard local storage doesn't give you much control over who sees what.

How Fastio secures agent data:

• Full Audit Logs: You can see every time an agent reads or writes a file.
• File Locking: This prevents two agents from trying to edit the same file at the same time, which stops data from getting corrupted.
• Isolation: Your files live in the cloud, separate from your Flowise server. This keeps your data safe even if your agent environment has a security issue. For teams in serious industries, keeping your compute (Flowise) and your storage (Fastio) separate is a key security practice.