SPRAPP documentation
Three products, sold separately: a multi-model reasoning panel, a short-string compression API, and offline on-device language models. This page is the hub — each section covers setup, usage, and pricing pointers.
SPRAPP Panel
The Panel is a browser app at sprapp.com. Ask once; a panel of models (Claude, GPT, Grok, Gemini, and 300+ via OpenRouter or local Ollama) reasons through the question in three phases — fan-out, peer review, synthesis — and returns one converged answer with disagreements kept visible.
Key points
- BYOK on every plan — bring your own API keys; they stay in your browser.
- No conversation storage — chats live in your browser (IndexedDB), not on our servers.
- Plans — Free forever; Lite from $3–9/mo depending on region. See pricing.
- Coordination patterns — 7 ways to combine models: panel debate, routing, cascades, and more.
smoltext — compression API
Short-string compression as an API. General-purpose compressors lose money on payloads under ~1 KB; smoltext layers a semantic JSON codec, dictionary deflate, and a trained codebook, returning whichever is smallest. Lossless by construction — output never exceeds input + 1 byte.
Full reference: smoltext.sprapp.com/docs.
Base URL: https://api.smoltext.sprapp.com
Quick start
curl -X POST https://api.smoltext.sprapp.com/v1/compress \
-H 'content-type: application/json' \
-d '{"text":"{\"event\":\"login\",\"user\":\"550e8400-e29b-41d4-a716-446655440000\",\"ip\":\"192.168.1.100\",\"ok\":true}"}'
# → 94 bytes in, 36 out — 61.7% savings, lossless roundtrip
Endpoints
| Endpoint | What |
|---|---|
POST /v1/compress | {"text": "..."} → compressed base64 + byte stats |
POST /v1/decompress | {"compressed": "..."} → original text |
POST /v1/signup | {"email": "..."} → API key (sk_live_…) |
GET /v1/usage | current usage; requires Authorization: Bearer |
Plans
| Plan | Price | Included/mo |
|---|---|---|
| Free | $0 | 10 calls/day |
| Starter | $3 | 100k |
| Pro | $9 | 500k |
| Scale | $29 | 2M |
Overage $1 per 100k calls. Annual billing is 10× monthly (two months free). Anonymous calls share the free quota per IP; signed-up keys get their own.
TinyLM — offline on-device models
Tiny instruct models (the eeny / meeny / miny family, ~50M–135M class, with larger ternary variants) that run fully offline in any phone browser on our own Rust→WASM inference engine — SIMD int8 and 1.58-bit ternary paths, no llama.cpp, no cloud.
- Offline by design — the model downloads once (IndexedDB cache) and then works with the network off.
- Fine-tune in minutes — LoRA on-device or in the cloud; export SFT pairs from your own data.
- Private by physics — inference never leaves the device.
TinyLM is in early access. The browser demo is being prepared at
tinylm.sprapp.com. Request access via contact.