Hypermemory Cumfyui Extract Text Node
БесплатноНе проверенA CumfyUI node that intergrated Hypermemory into the prompt creation process to make sure the content created is on brand.
Описание
A CumfyUI node that intergrated Hypermemory into the prompt creation process to make sure the content created is on brand.
README
ComfyUI's Extract Text node, with HyperMemory brand context and OpenRouter prompt refinement behind the scenes.
What It Does
Extract Text - Hypermemory keeps the same simple shape as ComfyUI's built-in Extract Text node:
- visible inputs:
string,regex_pattern,mode - advanced regex settings:
case_insensitive,multiline,dotall,group_index - output: one
STRING
The node first extracts text using the normal regex behavior. If HyperMemory and OpenRouter are configured outside the workflow, it uses the extracted text to recall brand context from HyperMemory and asks OpenRouter to turn it into an on-brand prompt.
If credentials are not configured, it falls back to plain extracted text.
Install
Clone this repo into your ComfyUI custom nodes folder:
cd ComfyUI/custom_nodes
git clone https://github.com/RunStack-AI/hypermemory-cumfyui-extract-text-node.git
Restart ComfyUI. The node appears as:
text/HyperMemory -> Extract Text - Hypermemory
No extra Python packages are required.
Configuration
Do not put API keys into workflow nodes. Set them in the environment before starting ComfyUI:
export HYPERMEMORY_API_KEY="hm_..."
export OPENROUTER_API_KEY="..."
Optional environment settings:
export HYPERMEMORY_API_URL="https://api.hypermemory.io"
export HYPERMEMORY_MAX_RESULTS="10"
export OPENROUTER_MODEL="minimax/minimax-m3"
export OPENROUTER_TEMPERATURE="0.4"
export OPENROUTER_MAX_TOKENS="900"
No graph ID is required. HyperMemory resolves the graph from the hm_... API key.
Brand details should live in HyperMemory. Store voice, audience, palette, product rules, campaign history, and visual constraints in the graph instead of entering them in the node UI.
How To Use
1. Add The Node
In ComfyUI, right-click the canvas and add:
text/HyperMemory -> Extract Text - Hypermemory
2. Add Source Text
Paste or connect the rough text into string.
Example:
Campaign brief: 15 second teaser for the new running shoe line.
Focus on speed, city lights, and premium performance.
3. Extract The Useful Part
Set regex_pattern and mode.
Example regex:
Campaign brief:\s*(.*)
Recommended mode:
First Group
Extracted text:
15 second teaser for the new running shoe line.
Common patterns:
| Goal | Regex | Mode |
|---|---|---|
| Text after a label | Brief:\s*(.*) |
First Group |
| Every hashtag | #(\w+) |
All Groups |
| First quoted phrase | "([^"]+)" |
First Group |
| First URL | https?://\S+ |
First Match |
| Numbered lines | ^\d+\.\s*(.*) |
All Groups with multiline on |
4. Wire The Output
The node has one output. Use it where prompt text belongs:
Extract Text - Hypermemory -> CLIP Text Encode.text
With HYPERMEMORY_API_KEY and OPENROUTER_API_KEY configured, that output is the refined brand prompt. Without them, it is the extracted text.
Inputs And Output
| Name | Type | Notes |
|---|---|---|
string |
input | Source text. |
regex_pattern |
input | Regex pattern. |
mode |
input | Defaults to First Group. |
STRING |
output | Extracted text or refined prompt. |
Advanced regex controls match the source Extract Text node: case_insensitive, multiline, dotall, and group_index.
Failure Behavior
- Regex does not match: output is empty, matching the source node.
- HyperMemory is not configured or fails: the node continues without memory context.
- OpenRouter is not configured or fails: the node returns the best local output available.
Development
Run the local checks:
python3 -m py_compile core.py nodes.py __init__.py tests/test_core.py
python3 -m unittest discover -s tests -v
Project Structure
.
├── __init__.py # ComfyUI exports
├── core.py # extraction, HyperMemory, OpenRouter, prompt helpers
├── nodes.py # ComfyUI node definition
├── requirements.txt # no external dependencies
└── tests/
└── test_core.py
License
MIT. See LICENSE.
from github.com/hypermemory-ai/hypermemory-cumfyui-extract-text-node
Установка Hypermemory Cumfyui Extract Text Node
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/hypermemory-ai/hypermemory-cumfyui-extract-text-nodeFAQ
Hypermemory Cumfyui Extract Text Node MCP бесплатный?
Да, Hypermemory Cumfyui Extract Text Node MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Hypermemory Cumfyui Extract Text Node?
Нет, Hypermemory Cumfyui Extract Text Node работает без API-ключей и переменных окружения.
Hypermemory Cumfyui Extract Text Node — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Hypermemory Cumfyui Extract Text Node в Claude Desktop, Claude Code или Cursor?
Открой Hypermemory Cumfyui Extract Text Node на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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