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Flowise — Visual AI Agent Builder

Overview

Flowise provides a drag-and-drop UI for building LLM workflows, RAG pipelines, and AI agents without code.

  • Subdomain: flow.<domain>
  • Container port: 3000
  • Data: Docker volume flowise-data
  • Docs: docs.flowiseai.com

Configuration

Environment Variables

In .env:

FLOWISE_VERSION=latest
FLOWISE_USERNAME=admin
FLOWISE_PASSWORD=<strong-password>
FLOWISE_SECRETKEY_OVERWRITE=<random-secret>

Generate secrets:

openssl rand -hex 32  # for FLOWISE_SECRETKEY_OVERWRITE
openssl rand -base64 16  # for FLOWISE_PASSWORD

First Login

  1. Open https://flow.<domain> in browser
  2. Login with FLOWISE_USERNAME / FLOWISE_PASSWORD from .env
  3. Start building flows

Connecting to Ollama

  1. In Flowise, add a ChatOllama node
  2. Set Base URL: http://ollama-compose:11434 (Docker network)
  3. Select model: llama3.2

Use ollama-compose (container name), not localhost — Flowise runs inside Docker and needs the container network name.

Connecting to Qdrant

  1. Add a Qdrant node
  2. Set URL: http://qdrant-compose:6333
  3. Set API Key if configured
  4. Set Collection Name

Building a RAG Pipeline

  1. Document Loader → PDF, text, or web scraper
  2. Text Splitter → Recursive Character Text Splitter (chunk size: 1000)
  3. Embeddings → Ollama Embeddings (nomic-embed-text)
  4. Vector Store → Qdrant (http://qdrant-compose:6333)
  5. Chat Model → ChatOllama (llama3.2)
  6. Conversational Retrieval QA Chain → connects all nodes

API Usage

# List chatflows
curl -H "Authorization: Bearer <api-key>" \
  https://flow.<domain>/api/v1/chatflows

# Send message to chatflow
curl -X POST https://flow.<domain>/api/v1/prediction/<chatflow-id> \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer <api-key>" \
  -d '{"question": "What is Docker?"}'

Create API Key

  1. Settings → API Keys → Add New
  2. Copy the key for external access

Backup and Restore

# Backup
docker compose stop flowise
docker run --rm -v ai-lab-server-setup_flowise-data:/data -v $(pwd):/backup \
  ubuntu tar czf /backup/flowise-backup-$(date +%Y%m%d).tar.gz /data
docker compose start flowise

# Restore
docker compose stop flowise
docker run --rm -v ai-lab-server-setup_flowise-data:/data -v $(pwd):/backup \
  ubuntu bash -c "rm -rf /data/* && tar xzf /backup/flowise-backup-YYYYMMDD.tar.gz -C /"
docker compose start flowise

Troubleshooting

Issue Solution
Can't connect to Ollama Use http://ollama-compose:11434, not localhost
Can't connect to Qdrant Use http://qdrant-compose:6333, not localhost
502 Bad Gateway Check container: docker compose ps flowise
Login fails Verify credentials in .env, restart: docker compose restart flowise
Slow responses Normal for CPU-only Ollama — consider larger server