Martin Dvorak
ef2a6a3589
Homework (/homework — entry points in the drawer and on the create screen) - Assignment intake reuses the study pipeline: pasted text, photos (camera/picker, compressed in the browser) and documents (PDF/DOCX/PPTX/ ODT/text) through lib/image + lib/documents, the same vision step and the same language guard. Raw files never leave the device — only text and JPEG data URLs reach the server. - Two large choice cards: “Just make it” returns the finished homework (answer only, plain text, copy + make it again); “Explain how to make this homework” builds an interactive guide. - The guide is one step per screen in the study-feed snap layout: explanation, three progressive hints (nudge -> hint -> the answer) and an optional checkpoint rendered by the existing activity components (graded through /api/grade). The last screen assembles the solution from the step answers, with a copy button. Checkpoints carry xp 0 so the guide stays free of XP/streak chrome. - Results live in freezmo.homework.v1 with a small history (open/delete); “Make it again” re-runs from the stored assignment text (the vision transcription when photos were used) — no original files are stored. - The answer and the guide are written in the assignment's language, never translated into the UI language. Server - POST /api/homework: NDJSON stage events like /api/generate, the same http-guard, auth checked before parsing, and its own RATE_LIMIT_HOMEWORK (documented in .env.example + the README table). - New prompts in lib/prompts.ts and zod schemas in lib/schemas.ts with the same single repair retry; TEXT_MODEL for content, VISION_MODEL only for photos. New shared client pieces: useNotesIntake, lib/homework store, lib/clipboard, and a shared NDJSON reader in lib/client-api. Also finishing the mobile polish pass from the previous request - Phone ice scene: the top-left orb moved behind the glass header (it sat behind the page heading/subtitle). The settings sheet's scroll cue is now a bare chevron inside a content fade (mask) instead of a chip over the status banner, and the API key card's note/disclosure/actions are tightened. - theme-color now follows the in-app theme (SSR metas still fall back to the OS preference); apple-mobile-web-app-status-bar-style stays “default” because iOS fixes the status-bar text colour at launch. Verified: 78/78 homework checks (text/photo/PDF, both modes, EN+CS, dark+light, 360/390px, copy, history persistence, storage privacy, API language, axe), plus the existing suites re-run (mobile 47/47, pixel contrast 0 below AA, i18n 27/27, desktop regression 72/72). Lint + build clean; service worker freezmo-v6.
52 lines
2.5 KiB
Bash
52 lines
2.5 KiB
Bash
# ---------------------------------------------------------------------------
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# Freezmo - Ollama configuration
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# Copy this file to `.env.local` and adjust if needed.
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# ---------------------------------------------------------------------------
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# WHO PROVIDES THE API KEY -----------------------------------------------------
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# user-key (default) Every browser supplies its own key. The key is typed
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# into the settings dialog, kept in that browser's local
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# storage and sent with each request in the
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# `x-ollama-key` header. The server never stores it.
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# Point OLLAMA_BASE_URL at https://ollama.com.
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# server One key for everyone, read from OLLAMA_API_KEY below
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# (single-user installs). Nothing is sent from the client.
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# local No key at all: a local daemon signed in with
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# `ollama signin` proxies the cloud models.
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OLLAMA_AUTH=user-key
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# Ollama endpoint. https://ollama.com for cloud, http://localhost:11434 for a
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# local daemon. In user-key mode this is the endpoint the browser's key is sent
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# to; in server/local mode it is used directly.
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OLLAMA_BASE_URL=https://ollama.com
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# Only used when OLLAMA_AUTH=server. Never commit a real key.
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OLLAMA_API_KEY=
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# Model used for the vision/transcription step (reads photos of notes).
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# Must be multimodal — gpt-oss and other text-only models cannot be used here.
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# Free-tier friendly: gemma4:31b-cloud, kimi-k3:cloud (paid), mistral-large-3 (paid).
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VISION_MODEL=gemma4:31b-cloud
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# Model used to generate activities, grade short answers and restore the
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# language if a transcription came back translated. gpt-oss:120b is free-tier
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# friendly, very good at strict JSON and the strongest multilingual model in the
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# free plan. NOTE: it is text-only, so it can't be used as VISION_MODEL.
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# Free alternatives: nemotron-3-super:cloud, gpt-oss:20b-cloud.
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# Paid/credit: glm-5.3-flash:cloud, kimi-k3:cloud.
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TEXT_MODEL=gpt-oss:120b-cloud
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# RATE LIMITS (per client IP, sliding window, in-memory) ----------------------
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# Generation decks are expensive, so they are limited tightly by default.
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# RATE_LIMIT_WINDOW_MS=300000
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# RATE_LIMIT_GENERATE=12
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# RATE_LIMIT_GRADE=40
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# RATE_LIMIT_HOMEWORK=12
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# RATE_LIMIT_HEALTH=90
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# Optional tuning ------------------------------------------------------------
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# OLLAMA_TIMEOUT_MS=300000
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# OLLAMA_HEALTH_TIMEOUT_MS=8000
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# Send `think: false` to thinking models for faster JSON output.
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# OLLAMA_THINK=false
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# FREEZMO_DEFAULT_ACTIVITY_COUNT=10
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