DeepDoc vs Docframe

DeepDoc turns a code repository into a navigable documentation site, regenerating pages affected by code changes through its update command. It scans source files, plans and generates documentation, stages OpenAPI references when present, and builds a site organized around topics such as architecture, endpoints, integrations, and schemas. Its AI answers can cite repository file paths and line ranges. Listed inputs include Python, TypeScript, JavaScript, Go, PHP, Vue, GraphQL, and OpenAPI or Swagger specifications. Output options include Markdown, Mermaid diagrams, a MkDocs Material site, a static Next.js/Fumadocs site, and an interactive API reference. Generated sites can include navigation and search, with an optional AI chatbot widget. DeepDoc is a terminal-based Python package requiring Python 3.10 or later; the maker says it needs no account or cloud service and identifies it as MIT licensed. Users bring their own LLM provider. Generate and update call that provider, so costs depend on the chosen model and documentation pages; other listed commands do not call an LLM. The deploy command produces a static site for any host.

Docframe generates interactive documentation sites from selected GitHub repositories or uploaded PDF, DOCX, and HTML ZIP files. For code, it uses AST-aware chunking across 40+ languages and infers architecture from imports. Templates can create quickstarts, API references, architecture pages, and guides populated from repository code and usage. Generated sites include structured navigation, ⌘K search, and dark and light themes. You can revise pages with chat-based AI edits or edit them manually; manual editing does not use credits. GitHub connects through OAuth, with read-only access to repositories you select. The Free plan allows manual editing and publishing on a Docframe domain, but excludes AI editing and static-site export. Paid plans start at $5.99/mo, billed monthly; Pro includes 1,000 AI credits and export. Chat edits use 20 credits, while repository generation or re-sync uses 50, and unused credits reset each billing cycle. AI processing may send relevant content and prompts to language-model inference subprocessors. Published pages are available to anyone with the link or more broadly if indexed.