内容摘录
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<p><strong>Write Once, Teach Personally</strong></p>
English | 简体中文
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AI-Shifu is designed for creators, instructors, and training/education teams, offering a scalable one-on-one teaching agent. Provide your expertise and teaching intent once, AI-Shifu will expand it into complete, personalized learning experiences. It adapts in real time to each learner’s profile with tailored explanations, interactive probing, assessments, and a full feedback loop—amplifying both your efficiency and the learner’s experience.
Core Capabilities
**Personalized explanation engine** — Generates learning paths and tone based on learner background, goals, and level.
**Interactive Q&A & probing** — Decomposes questions, asks clarifiers, and suggests next actions during sessions.
**Rapid course assembly** — Author with high-level frameworks and intent; AI-Shifu elaborates into lessons, activities, and assessments.
**Reduced production & delivery overhead** — Minimizes repetitive prep and support; every learner gets a dedicated “AI tutor.”
**Multi-channel integration** — Embeddable in websites, course platforms, and enterprise training portals.
Use Cases
**Course creators** — Hand a single lesson framework to AI-Shifu; learners receive personalized explanations and real-time interaction.
**Enterprise training** — Input training content once; employees get role- and background-specific learning paths.
**Educators** — Provide a syllabus to generate personalized coaching content plus a Q&A assistant.
Roadmap
[ ] Writing AI agent for rapid script generation and maintenance
[ ] Knowledge base
[ ] Speech input and output
Using AI-Shifu
Platform
AI-Shifu.com is an education platform powered by AI-Shifu. You can try it and learn the AI-guided courses developed by human experts.
Self-hosting
For source code installation, please refer to the Installation Manual
Make sure your machine has installed Docker and Docker Compose.
Quick Start (Docker, zero config)
Notes
First verified user is automatically promoted to Admin and Creator; the bundled demo course is assigned to this user.
Default universal verification code for demos is 1024 (change via UNIVERSAL_VERIFICATION_CODE).
docker-compose.latest.yml pulls the freshest :latest images (or your own locally built latest tags). Use docker-compose.yml when you need pinned release tags for reproducible environments.
Using Docker Hub image (customize)
Development mode (dev_in_docker.sh)
dev_in_docker.sh builds the backend and frontend images from your local source tree and then launches docker-compose.dev.yml (hot reload + bind mounts). Use it whenever you need to iterate on code without managing Python/Node runtimes locally.
Compose files
docker-compose.latest.yml: tracks the :latest tags for aishifu/ai-shifu-api and aishifu/ai-shifu-cook-web. Use this when you want the freshest container build (either from Docker Hub or after running your own docker build ... -t aishifu/...:latest).
docker-compose.yml: pins each image to a specific release tag for reproducible deployments (recommended for staging/prod mirrors or CI).
Access
After Docker starts:
Open http://localhost:8080 in your browser to access Cook Web (learner interface and authoring console)
Use any phone number for login; the default universal verification code is **1024** (for demo/testing only — change or disable in production)
The first verified user becomes Admin and Creator
Internationalization (i18n)
Shared translations live in src/i18n/<locale>/**/*.json and are consumed by both Backend and Cook Web.
See the consolidated guide for conventions, scripts, and CI checks: docs/i18n.md.
Frontend language list only exposes en-US and zh-CN.
Text-to-Speech (TTS)
AI-Shifu supports multiple TTS providers. To enable Volcengine HTTP v1/tts, set:
VOLCENGINE_TTS_APP_KEY (AppID)
VOLCENGINE_TTS_ACCESS_KEY (Token used by Authorization: Bearer;{token})
VOLCENGINE_TTS_CLUSTER_ID (Cluster, default: volcano_tts)
In Shifu settings, select the provider name volcengine_http and choose a voice/model.