4e854ba8c2
Native /login with a verified API key, automatic model discovery from UniGPT's /models endpoint, per-deployment deployment-id headers, and model metadata from pi's bundled catalog.
126 lines
3.7 KiB
Markdown
126 lines
3.7 KiB
Markdown
# pi-unigpt
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Use [UniGPT](https://unigpt.uni-graz.at), the University of Graz's MyGPT
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platform, as a model provider in [pi](https://pi.dev).
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- Log in with **`/login unigpt`**; your key is checked before pi saves it.
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- Models are discovered automatically. No model list to maintain.
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- Context size, output limit, and image support come from pi's own model
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catalog, so they stay current as pi updates.
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- Tool calling, streaming, and image input work through pi's built-in
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OpenAI Responses support.
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Requires pi **1.5.x** and Node.js **22.19+**.
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## Install
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```sh
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pi install git:github.com/behackl/pi-unigpt
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```
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Then start pi (or run `/reload` in a running session) and log in:
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```text
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/login unigpt
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```
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Paste your UniGPT API key into the masked dialog, **not into the chat**. Pi
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confirms how many models your key can use. Pick one with `/model`; UniGPT
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models are listed under `unigpt`.
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To try the extension without installing it:
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```sh
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pi -e git:github.com/behackl/pi-unigpt
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```
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## Commands
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| Command | What it does |
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| --- | --- |
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| `/login unigpt` | Save and verify your API key |
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| `/logout` | Remove the saved key from pi (it stays valid at UniGPT) |
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| `/model` | Pick a model; also reloads the model list |
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| `/unigpt-refresh` | Reload the UniGPT model list now and show how many models you have |
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## How models are described
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UniGPT's API only lists deployment IDs such as `gpt-5.4`. Those IDs are
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OpenAI model names, so the extension looks each one up in pi's bundled model
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catalog and uses its name, context window, output limit, and image support.
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Where OpenAI and Azure list different limits, the smaller one is used.
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IDs that pi does not know get pi's standard defaults for custom models:
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128k context, 16k output, text only. Update pi to pick up newer models.
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Two things are deliberately not taken from the catalog:
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- **Thinking levels are off for every model.** UniGPT ignores the requested
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reasoning effort and uses a fixed one per deployment, so pi's thinking
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levels would have no effect. Reasoning models still reason.
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- **Costs are shown as zero.** That means "not tracked", not "free".
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You can override any value in `~/.pi/agent/models.json`:
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```json
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{
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"providers": {
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"unigpt": {
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"modelOverrides": {
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"gpt-5.4": { "contextWindow": 200000 }
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}
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}
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}
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}
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```
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## Your API key
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Pi stores the key under `unigpt` in `~/.pi/agent/auth.json`. That file is
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private to your user account but **not encrypted**. To keep the key out of
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it, replace the stored value with an environment variable or a password
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manager command; pi resolves either when it needs the key:
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```json
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{
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"unigpt": { "type": "api_key", "key": "${UNIGPT_API_KEY}" }
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}
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```
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```json
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{
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"unigpt": { "type": "api_key", "key": "!op read op://Private/UniGPT/credential" }
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}
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```
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## Upgrading from a models.json setup
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If you configured UniGPT by hand before, delete the `unigpt` entry under
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`providers` in `~/.pi/agent/models.json` (overrides as shown above are
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fine). Otherwise your old model list and key take precedence over the
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extension. Then run `/reload` and `/login unigpt`.
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## Troubleshooting
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- **No UniGPT models in `/model`:** run `/unigpt-refresh`; it reports the
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exact problem (rejected key, unreachable server, empty model list).
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- **`pi -p` says a UniGPT model was not found:** print mode only reads the
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saved model list and never fetches it. Start pi interactively once after
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logging in; later print runs reuse that list.
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- **A specific model fails with HTTP 500:** some deployments are
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misconfigured on the server side; try another model and tell the UniGPT
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team.
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## Development
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```sh
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pnpm install
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pnpm run ci # type check + tests
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```
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Tests use fake keys and a local HTTP server; they never contact UniGPT or
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read your pi configuration.
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## License
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MIT
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