skill
Flux Kontext
نبذة
# Flux Kontext Pro — Pro Pack on RunComfy
[runcomfy.com](https://www.runcomfy.com/?utm_source=skills.sh&utm_medium=skill&utm_campaign=flux-kontext) · [Model page](https://www.runcomfy.com/models/blackforestlabs/flux-1-kontext-pro/image-to-image?utm_source=skills.sh&utm_medium=skill&utm_campaign=flux-kontext) · [GitHub](https://github.com/agentspace-so/runcomfy-skills/tree/main/flux-kontext)
Black Forest Labs' **Flux 1 Kontext Pro** — single-reference precise local image edit — hosted on the **RunComfy Model API**. Strong prompt control, consistent outputs, high fidelity.
```bash npx skills add agentspace-so/runcomfy-skills --skill flux-kontext -g ```
## When to pick this model (vs siblings)
| You want | Use | |---|---| | Single-image precise local edit ("she's now holding X") | **Flux Kontext** | | High-fidelity preservation of source identity | **Flux Kontext** | | Batch edits across 1–20 images | Nano Banana Edit | | Edit multilingual / embedded text in image | GPT Image 2 edit | | Generate from scratch, no source image | Flux 2 Klein |
If the user said "Flux Kontext" / "kontext" / "BFL Kontext" explicitly, route here regardless.
## Prerequisites
1. **RunComfy CLI** — `npm i -g @runcomfy/cli` 2. **RunComfy account** — `runcomfy login` opens a browser device-code flow. 3. **CI / containers** — set `RUNCOMFY_TOKEN=<token>` instead of `runcomfy login`.
## Endpoints + input schema
### `blackforestlabs/flux-1-kontext/pro/edit`
| Field | Type | Required | Default | Notes | |---|---|---|---|---| | `prompt` | string | yes | — | Single declarative edit instruction. | | `image` | string | yes | — | Single source image URL (publicly fetchable HTTPS). | | `aspect_ratio` | enum | no | (input) | Pick from supported W:H options on the model page. | | `seed` | int | no | — | Reuse for variant comparisons. |
The schema is intentionally minimal — Kontext leans on prompt + single ref. For multi-image or web-grounded edits, route to Nano Banana Edit.
## How to invoke
**Default — local edit, preserve everything else:**
```bash runcomfy run blackforestlabs/flux-1-kontext/pro/edit \ --input '{ "prompt": "Keep the person'\''s face, pose, and clothing unchanged. Add an orange umbrella in her left hand and a slight smile.", "image": "https://.../portrait.jpg" }' \ --output-dir <absolute/path> ```
**With seed for reproducible variant series:**
```bash runcomfy run blackforestlabs/flux-1-kontext/pro/edit \ --input '{ "prompt": "Keep the bottle, label, and lighting unchanged. Replace the brand text on the label from \"ALPHA\" to \"AURA\".", "image": "https://.../bottle.jpg", "seed": 42 }' \ --output-dir <absolute/path> ```
## Prompting — what actually works
**One declarative instruction.** Kontext shines on prompts shaped like the docs example: `"She is now holding an orange umbrella and smiling"`. Imperative mood, single change.
**Preservation first.** Lead with `"Keep [identity / pose / framing / brand] unchanged."` Then the change. Models honor what's stated up front.
**Single ref only — pick the right one.** No multi-image fanout here. If you have multiple references, decide which is primary and pass that one. For multi-image flows, route to Nano Banana Edit.
**Iterate on small changes.** If Kontext drifts, split a compound edit into sequential single-instruction passes (pass 1: change background, pass 2: change clothing).
**Aspect ratio — pick from the supported enum.** Out-of-list values 422 or crop.
**Anti-patterns:** - Compound prompts ("change A and add B and remove C") → drift. - Trying to fan out to multiple source images → wrong model (use Nano Banana Edit). - Prompts written in passive voice → less reliable. - Asking for novel composition without a source image → wrong model (use Flux 2 Klein t2i).
## Where it shines
| Use case | Why Flux Kontext | |---|---| | **Single-shot precise local edit** | Specifically designed for this; high fidelity | | **Preserve source identity through targeted change** | Strong preservation under explicit instruction | | **Brand-asset text or color swap** | Quoted text + preservation lead-in works well | | **Quick iteration on one image** | Short prompts + single ref = fast result loop |
## Sample prompts (verified to produce strong results)
**Page example:**
``` She is now holding an orange umbrella and smiling ```
**Preservation-led brand edit:**
``` Keep the bottle silhouette, table, and lighting exactly as in the input. Replace only the brand text on the label, from "ALPHA" to "AURA". Same font weight, white on black, centered. ```
**Compositional micro-edit:**
``` Keep the person's face, pose, and clothing unchanged. Add a leather shoulder bag, dark brown, hanging on the right shoulder. ```
## Limitations
- **Single source image only.** For multi-image flows, use Nano Banana Edit (1–20). - **Public RunComfy docs are minimal** — schema fields beyond prompt + image + aspect_ratio + seed may exist; check the [model page](ht
التثبيت
شغل هذا الأمر
npx skills add prime-skills/runcomfy-agent-skillsيعمل مع
خطوات التثبيت
Install with `npx skills add prime-skills/runcomfy-agent-skills`, or clone the repository and copy the `flux-kontext` folder into your Claude skills directory.
أسئلة شائعة
كيف أثبت Flux Kontext؟
شغل هذا الأمر في الطرفية:
npx skills add prime-skills/runcomfy-agent-skillsمع أي أدوات ذكاء اصطناعي تعمل Flux Kontext؟
تعمل مع claude_app، claude_code، claude_api، cursor، codex، windsurf، cline، zed.
من طور Flux Kontext؟
طورها prime-skills، وتصدر بترخيص MIT.
هل Flux Kontext مجانية؟
نعم، يمكنك استخدامها مجانا وفق ترخيص MIT.
npx skills add vercel-labs/skills
npx skills add mattpocock/skills
npx skills add mattpocock/skills
npx skills add mattpocock/skills
npx skills add mattpocock/skills
npx skills add genmedia-labs/skills
افحص قبل التثبيت
شغل أي مصدر عبر فحوصاتنا - الظهور في الذكاء الاصطناعي والأمان والأداء واكتشاف التقنيات.
فحص أمني تلقائي للموقع
الأمان
محلل سرعة الصفحة
الأداء
اختبار جودة المحتوى العربي بالذكاء الاصطناعي
جودة المحتوى
مختبر وكلاء الذكاء الاصطناعي
اختبار الذكاء الاصطناعي
كاشف منصة الموقع
الترحيل
تدقيق الظهور في محركات الذكاء الاصطناعي
الظهور في الذكاء الاصطناعي
مولد ملف llms.txt
الظهور في الذكاء الاصطناعي
مقياس سهولة القراءة بالعربية
جودة المحتوى
منشئ البيانات المنظمة
الظهور في الذكاء الاصطناعي
حاسبة تكاليف الذكاء الاصطناعي
اختبار الذكاء الاصطناعي
محلل العناوين العربية
جودة المحتوى