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scriptc
scriptc compiles ordinary TypeScript into small, fast native executables without needing Node.js, V8, or any JavaScript runtime in the binary.
AI repository intelligence
FR-AI / ANALYSISWhy it is worth attention
It provides an end-to-end pipeline for uploading knowledge, importing conversations, creating evaluation batches, and iteratively improving AI agent responses based on automated quality assessments.
Who it is for
- Customer service operations managers
- AI chatbot quality assurance teams
- Developers building or maintaining AI customer service systems
Use cases
- Evaluate the quality of existing AI customer service conversations
- Identify knowledge gaps and improve the knowledge base through batch scoring
- Simulate and test AI responses with imported dialogues before production deployment
Strengths
- Self-contained Docker Compose setup for easy local deployment
- Includes automated testing (pytest), linting (ruff), and type checking (mypy) for code quality
- Clear business and technical requirements defined in AGENTS.md and docs/requirements.md
- Designed for iterative improvement with a clear workflow from data import to evaluation
Considerations
- Single-administrator, single-server architecture – not suitable for multi‑user or high‑scale production environments
- Requires manual configuration of API keys and initial data import (knowledge, conversations)
- No built‑in support for A/B testing or advanced analytics beyond batch evaluation
README quick start
AI 测评自迭代工作台
单管理员、单服务器部署的 AI 客服质量评测与知识改进工作台。
本地启动
需要 Python 3.12、Docker、Docker Compose。
cp .env.example .env
docker compose up --build
docker compose exec web python manage.py createsuperuser
访问 http://127.0.0.1:8000，登录后依次配置密钥、上传知识、导入对话并创建评测批次。
本地测试
python3.12 -m venv .venv
.venv/bin/pip install -e '.[dev]'
.venv/bin/pytest
.venv/bin/ruff check .
.venv/bin/mypy apps config
业务与技术约束以 AGENTS.md 和 docs/requirements.md 为准。
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