ESP32-S3 Bench Guide
ESP32-S3 N16R8 bench guide: live pinout, lessons, simulators and the bench log.
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取自仓库 README
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A how-to guide browser: filter by category and difficulty, bookmark guides, track step-by-step progress, and generate new guides with AI. Built with React, Vite, and Tailwind CSS.
Generating new guides calls api/generate-guide.js, a Vercel serverless function that talks to the Gemini API server-side so the key never reaches the browser. It requires a GEMINI_API_KEY environment variable:
• Local dev: add it to .env.local
• Production: vercel env add GEMINI_API_KEY production (or the Vercel dashboard)查看完整 README ↗A how-to guide browser: filter by category and difficulty, bookmark guides, track step-by-step progress, and generate new guides with AI. Built with React, Vite, and Tailwind CSS.
npm install
npm run dev
npm run build
npm run preview
npm run lint
Generating new guides calls api/generate-guide.js, a Vercel serverless function that talks to an LLM server-side so no key ever reaches the browser. It supports three providers and picks one based on which API keys are present:
| Provider | API key env | Default model | Model override env | Free key |
|---|---|---|---|---|
| Groq | GROQ_API_KEY | llama-3.3-70b-versatile | GROQ_MODEL | console.groq.com |
| Gemini | GEMINI_API_KEY | gemini-3.8-flash | GEMINI_MODEL | aistudio.google.com |
| Cerebras | CEREBRAS_API_KEY | llama-3.3-70b | CEREBRAS_MODEL | cloud.cerebras.ai |
| OpenRouter | OPENROUTER_API_KEY | meta-llama/llama-3.3-70b-instruct:free | OPENROUTER_MODEL | openrouter.ai |
| Mistral | MISTRAL_API_KEY | mistral-small-latest | MISTRAL_MODEL | console.mistral.ai |
| NVIDIA NIM | NVIDIA_API_KEY | meta/llama-3.3-70b-instruct | NVIDIA_MODEL | build.nvidia.com |
Any OpenAI-compatible endpoint not listed can be added without code changes via CUSTOM_LLM_URL + CUSTOM_LLM_API_KEY (optional CUSTOM_LLM_MODEL, and CUSTOM_LLM_JSON=1 to request JSON mode).
Any provider whose key is missing is skipped, and if one fails the function automatically falls back to the others that do have a key — so the app keeps generating as long as at least one key is set.
.env.localvercel env add CEREBRAS_API_KEY production (or the Vercel dashboard)Get free keys at cloud.cerebras.ai, console.groq.com, or aistudio.google.com.
Without any key, everything else in the app works — browsing, filters, bookmarks, progress tracking — except generating new guides.
By default (no LLM_PROVIDER, or LLM_PROVIDER=auto) the function round-robins across every provider that has a key, spreading load evenly so no single free tier is exhausted first. Set LLM_PROVIDER to cerebras, groq, or gemini to pin that one as the primary instead, with the others as fallbacks.
If a provider returns a rate-limit or quota error, it's put on a short cooldown and skipped on subsequent requests until it recovers (honoring the Retry-After header when present: 60s default for 429s, 300s for auth errors, 30s for 5xx). This remembering-across-requests requires a shared key-value store — connect one in the Vercel dashboard under Storage (Vercel KV or an Upstash Redis integration). The function reads whichever of these env-var pairs the store provides:
KV_REST_API_URL + KV_REST_API_TOKEN, orUPSTASH_REDIS_REST_URL + UPSTASH_REDIS_REST_TOKENNo extra npm dependency is needed — the store is called over its REST API. Without a KV store the generator still works: it falls back to a fixed provider order with no cross-request cooldown memory (a depleted provider simply errors fast and the request falls through to the next one).
The default guides bundled with the app (src/lib/starterGuides.js) were produced by scripts/generate-starter-guides.mjs, which reads GEMINI_API_KEY from .env.local and generates a couple of guides per category. Re-run it any time to refresh that starter set:
node scripts/generate-starter-guides.mjs
Deployed via Vercel, linked to the main branch of this GitHub repository.