pi-provider-ampersand-bridge

An unofficial Pi provider for the ai& OpenAI-compatible API at api.aiand.com. Not affiliated with or endorsed by ai&; it just talks to the public service with your own API key.

Features

• Discovers every model available to your key from ai&'s authenticated GET /v1/models endpoint
• Ships the current ai& catalog as an offline fallback (DeepSeek, GLM, Kimi, Qwen, Gemma, GPT OSS, Motif)
• Uses live context, output, modality, reasoning-effort, and pricing metadata when ai& returns it
• Supports Pi's thinking selector through the standard OpenAI reasoning_effort request field
• Uses Pi's built-in OpenAI Chat Completions transport—no custom protocol or runtime dependency

Install

pi install npm:pi-provider-ampersand-bridge

To try a local checkout:

pi -e ./src/index.ts

Authenticate

Create a key in the ai& console and export it before starting Pi:

export AMPERSAND_API_KEY="your-key"
pi

You can instead store an API-key credential for the ampersand provider in Pi's auth.json, or override the provider in models.json.

Select a model with /model. Refresh the remote catalog with Pi's normal model refresh flow (pi update --models). If discovery is temporarily unavailable, the extension retains the last successful catalog, or the bundled fallback on first use. As with every authenticated Pi provider, models become selectable after a key is configured.

Thinking effort

Use Pi's thinking-level control as usual. Each model advertises its own accepted efforts from the live catalog, and Pi never sends a level the model refuses:

• deepseek-ai/*, zai-org/glm-5.2, google/gemma-4-31b-it, motif-technologies/motif-3, qwen/qwen3.6-27b expose off, high, and (where listed) max
• zai-org/glm-5.3* and moonshotai/kimi-k3 are always-on reasoners with low, high, and max
• qwen/qwen3.8-27b runs up to xhigh; openai/gpt-oss-120b caps at high
• moonshotai/kimi-k2.7-code always reasons at high

Models that do not accept medium natively map Pi's default medium level to the catalog's reasoning_effort_default (for example Kimi K3 defaults to max, Gemma 4 to none), so a fresh session starts at the effort ai& nominates.

Model metadata

The fallback catalog mirrors the live GET /v1/models response (USD per million tokens):

An authenticated /models response replaces this list, so newly released or account-specific models appear without an extension release.

Account balance

Run /ampersand-balance in a session to fetch GET /billing/balance for your configured key. The command reports remaining credits (USD or JPY) or, for pay-as-you-go accounts, the number of requests remaining in today's allowance.

Catalog hardening

The live discovery pipeline mirrors the companion VS Code bridge so both projects see the same catalog:

• Default reasoning effort: the catalog's reasoning_effort_default (or the bundled per-model default) steers Pi's default medium thinking level whenever a model does not accept medium natively, so a fresh session lands on the effort ai& nominates.
• Chat models only: listings for embedders, rerankers, and image/audio/video models are filtered out, and model ids are canonicalized (trimmed, lowercased) before matching the bundled catalog.
• Field aliases: context_length / max_context_tokens / max_model_len are accepted alongside context_window, max_completion_tokens alongside max_output_tokens, and pricing is read from a nested pricing object (prompt / completion / cache_prompt) or the flat per-million strings. Image input falls back to architecture.input_modalities and vision-style names when no modality data is present.
• Transient-failure retry: /models and /billing/balance requests retry 429/502/503/504 responses and transient network errors up to three attempts with capped exponential backoff, honoring Retry-After (≤5s).

Development

npm install
npm run check
npm run package

Project

• Changelog
• Contributing
• Security policy
• Release process

License

MIT