@czottmann/pi-tensorx

TensorX.ai API provider extension for pi coding agent.

Packages

Package details

extension

Install @czottmann/pi-tensorx from npm and Pi will load the resources declared by the package manifest.

npm repohome report
$ pi install npm:@czottmann/pi-tensorx
Package
@czottmann/pi-tensorx
Version
1.0.0
Published
Jun 28, 2026
Downloads
225/mo · 17/wk
Author
czottmann
License
MIT
Types
extension
Size
20.9 KB
Dependencies
0 dependencies · 1 peer
Pi manifest JSON
{
  "extensions": [
    "./extensions/tensorx.ts"
  ]
}

Security note

Pi packages can execute code and influence agent behavior. Review the source before installing third-party packages.

README

@czottmann/pi-tensorx

TensorX provider extension for pi. It registers tool-capable TensorX models under the tensorx provider.

Install

From npm:

pi install npm:@czottmann/pi-tensorx

From a local checkout:

cd path/to/pi-tensorx
npm install
pi install "$PWD"

Set up auth

Use pi's API-key flow:

pi
/login
# Choose "Use an API key", then "TensorX".

Or set an environment variable before starting pi:

export TENSORX_API_KEY=your-key-here

TensorX uses static API keys, so it appears under API keys in /login, not under subscriptions.

Note: the live catalog endpoint requires a key, and pi does not hand the /login-stored key to extensions. So the up-to-date catalog only loads when TENSORX_API_KEY is set in your environment. Without it, the extension registers a bundled snapshot of the catalog — enough to log in via /login and use the models. Set TENSORX_API_KEY if you want the current catalog instead of the snapshot.

Use

List registered models:

pi --list-models | grep tensorx

Start pi with TensorX:

pi --provider tensorx

In interactive mode, /tensorx-models lists the TensorX models registered by the extension.

How it works

On startup, the extension fetches GET https://api.tensorx.ai/v1/model/info, keeps models that report supports_function_calling, and registers them with pi.registerProvider() using pi's openai-completions API adapter.

Model metadata comes from each entry's model_info:

  • max_input_tokens (or max_tokens) becomes pi's context window.
  • max_output_tokens becomes the max output.
  • input_cost_per_token, output_cost_per_token, cache_read_input_token_cost, and cache_creation_input_token_cost become pi cost metadata, converted to per-million-token cost.
  • supports_vision adds image input.
  • supports_reasoning marks a model as reasoning-capable.

Duplicate model IDs in the catalog are de-duplicated, keeping the first.

If TENSORX_API_KEY is not in the environment, the extension can't reach the catalog endpoint, so it registers a bundled snapshot of the catalog instead. The snapshot is what lets TensorX appear under /login → API Keys: pi only lists providers that have registered models. Inference needs either a saved API key from /login or TENSORX_API_KEY.

Development

npm run check
npm run build
pi -e . --provider tensorx

Publishing

GitHub Actions publishes the package to npm when a GitHub Release is published. The release tag must match package.json exactly, with or without a leading v (v1.0.0 and 1.0.0 both work for version 1.0.0).

The workflow uses npm Trusted Publishing, so it does not need an npm token secret. Configure this package on npm with this repository and workflow file (.github/workflows/publish.yml). The workflow builds the package, runs npm run check, and publishes with npm provenance.

Author

Carlo Zottmann, carlo@zottmann.dev