pysaif

A local-first library that handles AI provider logistics — API calls, config, memory, quota — so you don't have to think about them every time.

from pysaif import AI

ai = AI()
response = ai.send("Hello!")
print(response)

Install

pip install pysaif

Setup

On first run, pysaif creates a Config/ folder next to your project with config.toml (API keys, model, personality — the stuff you'll actually touch) and advanced_config.toml (timeouts, retries, per-model metadata — the stuff most people never open). Drop your API key into config.toml and you're done.

Each project gets its own config and its own key — pysaif never shares keys or settings across projects, and never reads them from your environment implicitly.

What's implemented right now

• Config: self-healing setup, two-file split, schema versioning and migration hook
• Providers: Google Gemini, OpenAI, Anthropic Claude, OpenRouter (sync and async)
• Provider selection: manual, cheapest, fastest, and smart strategies
• Quota-aware daily token limits and automatic provider failover with retries
• Local memory under Memory/ (rolling window, important, interests) with inject/store toggles
• Usage tracking under Usage/ (state + optional JSONL logs; message content off by default)
• In-memory response cache (opt-in via cache.enabled)
• Prompt assembly from optional context, background, personality, and instructions

Configuration highlights

Config/config.toml:

• provider.strategy — manual | cheapest | fastest | smart
• provider.fallback_order — provider names to try on errors
• memory.store / memory.inject — persist conversation vs. feed it into prompts
• quota.daily_token_limit — 0 means unlimited

What's designed but not built yet

Interactive setup wizard, richer capability tools (search/look/make), and automated config migrations beyond schema backfill — see the module skeleton under pysaif/capabilities/ for planned expansion points.

License

See LICENSE.