mirror of https://github.com/kevinveenbirkenbach/computer-playbook.git synced 2025-10-09 18:28:10 +02:00

Files

Kevin Veen-Birkenbach 6f3522dc28 fix(csp): resolve all CSP-related issues and extend webserver health checks

- Added _normalize_codes to support lists of valid HTTP status codes
- Updated web_health_expectations to handle multiple codes, deduplication, and fallback logic
- Extended unit tests with coverage for list/default combinations, invalid values, and alias behavior
- Fixed Flowise CSP flags and whitelist entries
- Adjusted Flowise, MinIO, and Pretix docker service resource limits
- Updated docker-compose templates with explicit service_name
- Corrected MinIO status_codes to 301 redirects

✅ All CSP errors fixed

See details: https://chatgpt.com/share/68d557ad-fc10-800f-b68b-0411d20ea6eb

2025-09-25 18:05:41 +02:00

config

fix(csp): resolve all CSP-related issues and extend webserver health checks

2025-09-25 18:05:41 +02:00

README.md

Flowise

Description

Flowise is a visual builder for AI workflows. Create, test, and publish chains that combine LLMs, your documents, tools, and vector search—without writing glue code.

Overview

Users design flows on a drag-and-drop canvas (LLM, RAG, tools, webhooks), test them interactively, and publish endpoints that applications or bots can call. Flowise works well with local backends such as Ollama (directly or via LiteLLM) and Qdrant for retrieval.

Features

No/low-code canvas to build assistants and pipelines
Publish flows as HTTP endpoints for easy integration
Retrieval-augmented generation (RAG) with vector DBs (e.g., Qdrant)
Pluggable model backends via OpenAI-compatible API or direct Ollama
Keep data and prompts on your own infrastructure

README.md

Flowise

Description

Overview

Features

Further Resources