Entry points (no sixth tab): Ask in the Library header (desktop button, phone icon), Ask about this deck in the deck menu, Ask a question on study/homework results (compact result travels as context), and a Chat row in the desktop sidebar. Phones get a full-screen route with back + New chat; the tab bar steps aside. - Client-side retrieval: chunk scoped decks (~800 tokens), BM25 against the question + recent turns, top chunks under ~7k tokens, each labelled with deck + section. Notes come from the deck's stored sourceText (already kept for Regenerate); decks without it fall back to generated content and the UI says so. - Stateless server: /api/chat validates against the CHAT_MODELS allowlist, trims the history to ~6k tokens, caps context at ~9k and streams token/thinking/done/error NDJSON. /api/chat/extract reduces attachments to text through the existing vision step. - UI: user bubbles + full-width assistant text, streaming with stop, auto-scroll that pauses with a jump-to-bottom button, safe markdown (React nodes, no HTML injection; KaTeX dynamically imported only when a message has math), Thinking row for reasoning, copy/regenerate/ edit-and-resend, model + context pickers (last model remembered), composer with visualViewport keyboard handling, safe-area, 16px textarea, Enter-to-send on desktop. - Usage-limit failures keep the draft and show the shared message with Settings/Ollama actions; stopping maps the reader abort to a clean stopped state; offline disables sending with a reason. - Settings: Keep notes text for chat toggle; deck menu: Delete notes text. RATE_LIMIT_CHAT + CHAT_MODELS in .env.example and README. - Tests: chat suite (63 checks, stub Ollama) wired into run-all. Full set: 12/12 suites, 487 checks. SW -> freezmo-v32. Also: tests/model-compare.mjs (diagnostic) benchmarks two models on the same notes (latency, repair rounds, activity types) so the gpt-oss vs gemma default can be decided on numbers; defaults unchanged.
89 lines
4.2 KiB
Bash
89 lines
4.2 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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# CHAT MODELS (optional) -------------------------------------------------------
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# The allowlist the chat model picker offers, comma-separated. The server never
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# accepts a model name outside this list. The first entry is the default.
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# When unset, the configured TEXT_MODEL and VISION_MODEL are used.
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# Example: CHAT_MODELS=gemma4:31b-cloud,gpt-oss:120b-cloud
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# CHAT_MODELS=
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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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# Homework follow-ups (short rewrites).
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# RATE_LIMIT_REFINE=30
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# RATE_LIMIT_HEALTH=90
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# Encrypted sync (no model calls, but shouldn't be hammered).
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# RATE_LIMIT_SYNC=60
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# Push subscription changes and test sends.
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# RATE_LIMIT_PUSH=30
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# Chat turns (one model call each; users send them in bursts).
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# RATE_LIMIT_CHAT=60
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# PUSH REMINDERS (optional) ----------------------------------------------------
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# Web Push reminders only appear in the UI when BOTH VAPID keys are set.
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# Generate them once with: npx web-push generate-vapid-keys
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# VAPID_PUBLIC_KEY=
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# VAPID_PRIVATE_KEY=
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# VAPID_SUBJECT=mailto:you@example.com
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# Where subscriptions are stored (endpoint + keys only, no personal data).
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# PUSH_DIR=.freezmo/push
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# The daily sender is a script you schedule yourself (cron/systemd timer):
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# node scripts/send-reminders.mjs
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# PUSH_REMINDER_TITLE=Time to review
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# PUSH_REMINDER_BODY=Your decks are waiting — a few due cards keep the streak alive.
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# ENCRYPTED SYNC STORAGE -------------------------------------------------------
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# Opt-in sync uploads an opaque AES-GCM blob; the server can't read it and
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# never sees the passphrase or the API key. One small JSON file per sync ID.
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# SYNC_DIR=.freezmo/sync
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# Per-blob cap in bytes (larger uploads are refused with HTTP 413).
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# SYNC_MAX_BYTES=12582912
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# Total cap for the directory in bytes (new blobs refused with HTTP 507).
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# SYNC_TOTAL_BYTES=1073741824
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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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