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OrcaRouter provider support for ShellSage

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まだ誰も着手していません。

評価

難易度
4/5
見積もり時間
3〜5日
初心者へのやさしさ
35/100
issue の種類
機能追加
明瞭さ
おおむね明確
活発さ
活発
技術スタック
shell
領域
api, cli

調査の方向性

まず fastllm プロバイダーの解決と、既存の base_url/api_key の AsyncChat へのフローを追跡し、次に現在のベンダープレフィックスと CLI のモデルオプションを比較します。既存のプロバイダーを変更せずに、オプションの OrcaRouter 互換プロバイダーが統合され、そのプロバイダーの動作がプロジェクト既存のチェックでカバーされていれば完了です。

索引モデルが issue の本文から書いたものです。

説明

ShellSage's tmux integration is what makes it click: because it reads your pane history (or a named pane via --pid) and accepts piped input, a line like journalctl --since "1 hour ago" | ssage explain this error turns a stack trace into a plain-language diagnosis without leaving the terminal. The ssage_clear binding is a thoughtful design choice too — Ctrl-L gains real clear semantics for the assistant while your own scrollback stays intact.

That matters because people who live in a shell want answers where they already are, and model choice is part of that. ShellSage already resolves models through fastllm and accepts a custom base_url/api_key, so OrcaRouter would slot in as one more optional provider alongside Claude, GPT, and Ollama.

Proposal

I'd like to propose adding OrcaRouter as an optional provider. It would not replace or change any existing provider — Claude, GPT, Gemini, Ollama, OpenRouter, and the rest would keep working exactly as they do today.

I'm an engineer on the OrcaRouter team, so I'll be upfront about my angle here.

What this would give ShellSage users
  • One endpoint, many models — chat, reasoning, image, and video models behind a single OpenAI-compatible API, so --model can point at a much wider catalog.
  • Automatic routing and provider failover — if a provider degrades mid-session, a request routes to a healthy equivalent instead of dropping your question.
  • Prompt caching — especially relevant here, since history_lines = -1 ships the whole terminal history on every call; caching makes that repeated context cheaper and faster.
  • Usage tracking and budgets — visibility into what a long-running shell session actually costs.
Integration

OrcaRouter exposes an OpenAI-compatible API and uses standard API-key authentication. Concretely, this fits the abstraction you already have: an orcarouter-style prefix resolved by fastllm next to the current vendor prefixes, or simply the existing base_url / api_key config and CLI options, both of which already flow through to AsyncChat. To be clear, I haven't written or tested any code for this — it's a proposal for your consideration.

OrcaRouter is already part of the open-source ecosystem, with integrations such as goose, promptfoo, and models.dev / OpenCode.

One disclosure: we run an optional open-source partner program where approved OSS projects can receive a 5% revenue share from OrcaRouter usage attributed to their integration. Taking part is not a prerequisite for the integration, and I'm glad to follow whatever disclosure or governance rules you'd prefer.

Details: https://www.orcarouter.ai/built-with

Would you be open to this? If so, I'd be happy to prepare an implementation PR once you've had a chance to weigh in.

主要言語
Jupyter Notebook
スター
409
フォーク
44
30日以内にマージされた PR はありません

環境構築

はじめの一歩

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  3. リポジトリをフォークし、ブランチを切って変更します。
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