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kevinveenbirkenbachandClaude Opus 4.7
16bdbf03d7
Three classes of drift cleaned up across 85 .md files:
- Em-dashes: replaced ` — ` with the contextually correct separator
(colon for `term: explanation`, period to split clauses across
sentences/source lines, parentheses for asides, semicolon for
tight-linked continuations). Two intentional exceptions remain
in `docs/contributing/documentation.md` (the rule literal) and
inside a fenced ```sh block in `docs/contributing/actions/debugging/ci.md`.
- SPOT self-labels: rewrote "This is the SPOT for X" to describe
the subject directly ("This directory holds X" / "This file
describes X"). Cross-references to other artefacts' canonical
role remain unchanged.
- Heading-emoji position: moved leading-emoji headings (`# 🧩 Title`)
to trailing position (`# Title 🧩`) per the headline rule that
emojis MUST come after the title text.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
1.3 KiB
1.3 KiB
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
Further Resources
- Flowise: flowiseai.com
- Qdrant: qdrant.tech
- LiteLLM: litellm.ai
- Ollama: ollama.com
Credits
Developed and maintained by Kevin Veen-Birkenbach. Learn more at veen.world. Part of the Infinito.Nexus Project. Licensed under the Infinito.Nexus Community License (Non-Commercial).