What is Skill_Seekers built with?

Skill_Seekers is a Python repo built with FastAPI, uvicorn, anyio, starlette, Vite, and 2 more. It uses AI through mcp, LangChain, and llama-index, makes its content with html5lib, beautifulsoup4, pytesseract, pillow, and pymupdf, validates its data with annotated-types, jsonschema, jsonschema-specifications, pydantic-core, referencing, and 1 more, and is tested with pytest-asyncio, pytest-cov, Pytest, and @playwright/test. It has 213,544 written lines, with 204 test files.

Read on November 8, 2026, at commit 5b5d8df. Read it as markdown

The card says what it's built with. Its whole map opens it up: every part of the code and how it connects to the rest.

Frontend

Backend

The base 2

AI 3

Support

The base 2

Content 5

Validation 6

Testing 4

  • Pytest102 files
  • @playwright/test2 files
  • pytest-asyncio
  • pytest-cov

Tools 9

  • click
  • coverage
  • pygments
  • gitpython3 files
  • pathspec2 files
  • iniconfig
  • packaging
  • pluggy
  • typing-extensions

Other 23

  • pyyaml9 files
  • networkx1 file
  • attrs
  • certifi
  • pydantic-settings
  • urllib3
  • requests14 files
  • httpx7 files
  • tomli2 files
  • clsx1 file
  • schedule1 file
  • charset-normalizer
11 more
  • h11
  • httpcore
  • httpx-sse
  • idna
  • pygithub
  • python-dotenv
  • python-multipart
  • rpds-py
  • sniffio
  • sse-starlette
  • typing-inspection

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Frequently asked questions

What language is Skill_Seekers written in?
Skill_Seekers is written in Python, with 213,544 written lines.
What framework does Skill_Seekers use?
Skill_Seekers is built with FastAPI, uvicorn, anyio, starlette, Vite, React, and React Router.
Does Skill_Seekers use AI?
Yes. Skill_Seekers uses AI through mcp, LangChain, and llama-index.
Does Skill_Seekers have tests?
Yes. Skill_Seekers has 204 test files and is tested with pytest-asyncio, pytest-cov, Pytest, and @playwright/test.
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