OhMyCaptcha Skill
Operational guidance for deploying and integrating the OhMyCaptcha service.
Model architecture
OhMyCaptcha uses two model backends:
- Local model — self-hosted via SGLang/vLLM (e.g.
Qwen/Qwen3.5-2B). Handles image recognition and classification tasks. Configured via LOCAL_BASE_URL, LOCAL_API_KEY, LOCAL_MODEL.
- Cloud model — remote OpenAI-compatible API (e.g.
gpt-5.4). Handles audio transcription and complex reasoning. Configured via CLOUD_BASE_URL, CLOUD_API_KEY, CLOUD_MODEL.
Supported task types (19 total)
Browser-based (12)
RecaptchaV3TaskProxyless, RecaptchaV3TaskProxylessM1, RecaptchaV3TaskProxylessM1S7, RecaptchaV3TaskProxylessM1S9, RecaptchaV3EnterpriseTask, RecaptchaV3EnterpriseTaskM1, NoCaptchaTaskProxyless, RecaptchaV2TaskProxyless, RecaptchaV2EnterpriseTaskProxyless, HCaptchaTaskProxyless, TurnstileTaskProxyless, TurnstileTaskProxylessM1
Image recognition (3)
ImageToTextTask, ImageToTextTaskMuggle, ImageToTextTaskM1
Image classification (4)
HCaptchaClassification, ReCaptchaV2Classification, FunCaptchaClassification, AwsClassification
Local model setup (SGLang)
pip install "sglang[all]>=0.4.6.post1"
# From ModelScope (China):
export SGLANG_USE_MODELSCOPE=true
python -m sglang.launch_server --model-path Qwen/Qwen3.5-2B --port 30000
Then configure OhMyCaptcha:
export LOCAL_BASE_URL="http://localhost:30000/v1"
export LOCAL_MODEL="Qwen/Qwen3.5-2B"
Startup checklist
- Install dependencies:
pip install -r requirements.txt && playwright install --with-deps chromium
- Start local model server (SGLang on port 30000)
- Set env vars:
LOCAL_BASE_URL, CLOUD_BASE_URL, CLOUD_API_KEY, CLIENT_KEY
- Start service:
python main.py
- Verify:
curl http://localhost:8000/api/v1/health
- Test: create a reCAPTCHA v3 task against
https://antcpt.com/score_detector/ with key 6LcR_okUAAAAAPYrPe-HK_0RULO1aZM15ENyM-Mf
Response rules
- Prefer the repository's documented behavior over assumptions.
- Use placeholder credentials only. Never expose real secrets.
- Be explicit about limitations:
minScore is compatibility-only- Task storage is in-memory with 10-min TTL
- reCAPTCHA v2 and hCaptcha may require image classification fallback in headless environments
- For deployment help, reference
docs/deployment/local-model.md, docs/deployment/render.md, docs/deployment/huggingface.md.
- For API usage, reference
docs/api-reference.md and the usage guides under docs/usage/.
1---2name: ohmycaptcha3description: Deploy, configure, validate, and integrate the OhMyCaptcha captcha-solving service. Use when working with YesCaptcha-style APIs, flow2api integration, reCAPTCHA/hCaptcha/Turnstile task creation, image classification, SGLang local model deployment, Render/Hugging Face cloud deployment, or OpenAI-compatible multimodal model setup. Also use when the user asks how to self-host a captcha-solving service or wants request/response examples for OhMyCaptcha.4---56# OhMyCaptcha Skill78Operational guidance for deploying and integrating the OhMyCaptcha service.910## Model architecture1112OhMyCaptcha uses two model backends:1314- **Local model** — self-hosted via SGLang/vLLM (e.g. `Qwen/Qwen3.5-2B`). Handles image recognition and classification tasks. Configured via `LOCAL_BASE_URL`, `LOCAL_API_KEY`, `LOCAL_MODEL`.15- **Cloud model** — remote OpenAI-compatible API (e.g. `gpt-5.4`). Handles audio transcription and complex reasoning. Configured via `CLOUD_BASE_URL`, `CLOUD_API_KEY`, `CLOUD_MODEL`.1617## Supported task types (19 total)1819### Browser-based (12)20`RecaptchaV3TaskProxyless`, `RecaptchaV3TaskProxylessM1`, `RecaptchaV3TaskProxylessM1S7`, `RecaptchaV3TaskProxylessM1S9`, `RecaptchaV3EnterpriseTask`, `RecaptchaV3EnterpriseTaskM1`, `NoCaptchaTaskProxyless`, `RecaptchaV2TaskProxyless`, `RecaptchaV2EnterpriseTaskProxyless`, `HCaptchaTaskProxyless`, `TurnstileTaskProxyless`, `TurnstileTaskProxylessM1`2122### Image recognition (3)23`ImageToTextTask`, `ImageToTextTaskMuggle`, `ImageToTextTaskM1`2425### Image classification (4)26`HCaptchaClassification`, `ReCaptchaV2Classification`, `FunCaptchaClassification`, `AwsClassification`2728## Local model setup (SGLang)2930```bash31pip install "sglang[all]>=0.4.6.post1"32# From ModelScope (China):33export SGLANG_USE_MODELSCOPE=true34python -m sglang.launch_server --model-path Qwen/Qwen3.5-2B --port 3000035```3637Then configure OhMyCaptcha:38```bash39export LOCAL_BASE_URL="http://localhost:30000/v1"40export LOCAL_MODEL="Qwen/Qwen3.5-2B"41```4243## Startup checklist44451. Install dependencies: `pip install -r requirements.txt && playwright install --with-deps chromium`462. Start local model server (SGLang on port 30000)473. Set env vars: `LOCAL_BASE_URL`, `CLOUD_BASE_URL`, `CLOUD_API_KEY`, `CLIENT_KEY`484. Start service: `python main.py`495. Verify: `curl http://localhost:8000/api/v1/health`506. Test: create a reCAPTCHA v3 task against `https://antcpt.com/score_detector/` with key `6LcR_okUAAAAAPYrPe-HK_0RULO1aZM15ENyM-Mf`5152## Response rules53541. Prefer the repository's documented behavior over assumptions.552. Use placeholder credentials only. Never expose real secrets.563. Be explicit about limitations:57 - `minScore` is compatibility-only58 - Task storage is in-memory with 10-min TTL59 - reCAPTCHA v2 and hCaptcha may require image classification fallback in headless environments604. For deployment help, reference `docs/deployment/local-model.md`, `docs/deployment/render.md`, `docs/deployment/huggingface.md`.615. For API usage, reference `docs/api-reference.md` and the usage guides under `docs/usage/`.
shenhao-stu