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zero-dependency AI coding agent for the HackerRank AI Gateway.","maintainers":[{"name":"sp2hari","email":"hari@hackerrank.com"}],"readme":"# astra\n\nA minimal, **zero-dependency** AI coding agent for the **HackerRank AI Gateway**,\nwritten in plain Node.js (ESM, Node ≥ 20).\n\nastra is a small, self-contained agent that talks to the `hackerrank-ai-gateway` and\nworks with **every** model on it. It runs in two modes from one engine:\n\n- an **interactive assistant** — a chat REPL that can read files and run commands\n  (with your approval), like a lightweight cline / claude-code;\n- an **autonomous task runner** — give it a task and it works to completion on its own.\n\nEvery run is a resumable session, with exact token accounting and USD cost tracking.\n\n## Why it's minimal\n\n- **No dependencies.** Uses Node's built-in `fetch`, `spawn`, and `fs`. No install step.\n- **Text-based action protocol.** The model returns one fenced ` ```bash ` block per\n  turn, so it works with *every* model on the gateway — no provider tool-calling required.\n- **Linear history.** Every step just appends to the message list. The session *is* the\n  conversation; trivial to debug and inspect.\n- **Stateless actions.** Each command runs in a fresh `bash -c` subshell, so runs are\n  easy to reason about and sandbox.\n\n## Layout\n\n| File | Role |\n|---|---|\n| `src/model.js` | Gateway client (OpenAI-compatible `/chat/completions`). Handles retries, the `max_tokens` vs `max_completion_tokens` difference, and cost accounting. |\n| `src/environment.js` | Runs one command per action in a fresh subshell, with a per-command timeout that kills the whole process group and output truncation. |\n| `src/prompts.js` | System / instance / format-error / observation templates + a tiny `{{var}}` renderer, split into interactive vs autonomous rules. |\n| `src/agent.js` | The turn-based engine: query → parse shell blocks → execute → observe → repeat. Autonomous runs can combine related blocks; interactive runs remain strict. |\n| `src/repl.js` | The interactive assistant loop: prompts, command approval, slash commands. |\n| `src/session.js` | Resumable sessions stored under `~/.astra/sessions/`. |\n| `src/config.js` | Dedicated `~/.astra/config.json`, credential resolution, interactive key prompt. |\n| `src/prices.js` | Public list prices used to estimate cost for models that don't report it. |\n| `src/cli.js` | Argument parsing, mode dispatch, and streaming output. |\n\n## Setup\n\nNode ≥ 20. Install from npm:\n\n```bash\nnpm install -g @hackerrank/astra\n\n# or without a global install\nnpx @hackerrank/astra -m claude-sonnet-5\n```\n\nFrom a git checkout of this repo you can also run the CLI directly, or link it:\n\n```bash\nnode src/cli.js -m claude-sonnet-5\nnpm link    # then `astra` uses this checkout\n```\n\nYou also need an API key for the gateway. The CLI resolves it in this order\n(first hit wins):\n\n1. `--api-key` flag\n2. `ASTRA_GATEWAY_API_KEY` environment variable\n3. `~/.astra/config.json` — astra's own config (written with `0600` perms)\n4. **interactive prompt** when run in a terminal — offers to save the key to\n   `~/.astra/config.json` so future runs pick it up automatically\n\nThe first interactive run asks for the key and can remember it. In CI, pass the\nkey via flag or env var.\n\n## Usage\n\nastra has **two modes**, sharing one engine:\n\n### Interactive assistant (no task)\n\nA personal coding-assistant REPL. Commands need your approval by default; the\nwhole chat is saved as a resumable session.\n\n```bash\nastra -m claude-sonnet-5            # start chatting\nastra -m claude-sonnet-5 -y         # auto-run commands (no prompts)\n```\n\nIn-REPL commands: `/help /plan <task> /exit /clear /history /tokens /yolo`.\n\nKeyboard shortcuts: `Shift+Return` (or `Opt+Return`) for multi-line input, `Opt+Left/Right` to cycle models, `Opt+Up/Down` to cycle reasoning effort, `Esc` to clear input.\n\n### Autonomous task run\n\nWhen you pass a task with `-t`/`-f`, astra appends the autonomous rules and runs\nto completion, submitting via the sentinel when done.\n\n```bash\n# from an inline task\nastra -m claude-sonnet-5 -t \"Fix the failing test in ./app and submit.\"\n\n# from a task file, running inside a specific repo\nastra \\\n  -m gpt-5.6-sol \\\n  -f ./task/instruction.md \\\n  -C ./task/repo \\\n  -s 60 \\\n  -o ./runs/run-01.traj.json\n```\n\n### Container benchmark packages\n\nThe supported way to operate a container benchmark is to run its root wrappers.\nFrom the task directory:\n\n```bash\npython3 generate.py --model gpt-5.6-luna --reasoning medium\npython3 verify.py --solution solutions/gpt-5.6-luna-medium-20260914T000000Z-abc123\n```\n\nThe task-root `task.toml`, `Dockerfile`, and wrappers create a fresh container\nattempt for every invocation. Generation publishes an immutable candidate under\n`solutions/`; verification publishes the generic report, logs, and metadata\nunder `results/` without mutating that candidate. Legacy benchmark exports are\nread-only history, not a supported operational path.\n\n### Sessions\n\nEvery run (either mode) is saved under `~/.astra/sessions/<id>.json`.\n\n```bash\nastra --sessions            # list saved sessions\nastra --resume <id>         # resume (continue an interactive chat,\n                            # or inspect/continue an autonomous run)\n```\n\nVerified working models on the gateway include `claude-sonnet-5`, `claude-opus-5`,\n`gpt-5.6-sol`, `gpt-5.6-terra`, `gemini-3.7-flash`, `grok-4.6`, `kimi-k3`, and others.\nSome routes (e.g. `glm-5.2`) may return HTTP 402 when the underlying provider is out of\ncredits — that's a quota issue, not a bug.\n\n### Options\n\n```\n-m, --model <id>        Model id\n-r, --reasoning <lvl>   Reasoning effort\n-t, --task <text>       Task text -> autonomous mode\n-f, --task-file <path>  Read task text from a file -> autonomous mode\n-C, --cwd <path>        Working directory for commands (default: cwd)\n-o, --output <path>     Also write trajectory JSON here (autonomous mode)\n-s, --steps <n>         Turn limit (unset = no limit)\n-w, --wall <seconds>    Wall-clock limit (default: 0 = none)\n    --timeout <seconds> Per-command timeout (default: 60)\n    --max-output <n>    Max chars of command output kept (default: 16000)\n    --base-url <url>    Override gateway base URL\n    --api-key <key>     Gateway API key (else env/config/prompt)\n    --resume <id>       Resume a saved session\n    --sessions          List saved sessions and exit\n-y, --yolo              Auto-run commands (always on in autonomous mode)\n-q, --quiet             Do not stream turns (autonomous mode)\n-h, --help              Show help\n```\n\n## How the loop works\n\n```\nsystem + instance prompt\n        │\n        ▼\n   ┌─► query model ──► parse ONE ```bash block ──► run in fresh subshell\n   │        ▲                    │ (bad format)            │\n   │        └── format-error ◄───┘                         ▼\n   │                                              observe <returncode>/<output>\n   └──────────────────────────────────────────────────────┘\n                     │ command echoes the submit sentinel\n                     ▼\n                  Submitted\n```\n\nIn interactive mode, a reply with **no** bash block is treated as a chat turn that hands\ncontrol back to you; in autonomous mode the loop keeps going until the task is submitted\nor a limit is hit.\n\nTermination reasons written to the session `info.exit_status`:\n\n- `Submitted` — a command printed `COMPLETE_TASK_AND_SUBMIT_FINAL_OUTPUT` with exit code 0.\n- `LimitsExceeded` — hit the step limit.\n- `TimeExceeded` — hit the wall-clock limit.\n- `RepeatedFormatError` — too many unparseable replies in a row.\n- `ContextWindowExceeded` — the request exceeded the model's context window.\n\n## Session / trajectory output\n\nEach run is stored as JSON (`astra-1` format):\n\n```json\n{\n  \"trajectory_format\": \"astra-1\",\n  \"info\": {\n    \"mode\": \"autonomous\",\n    \"exit_status\": \"Submitted\",\n    \"submission\": \"\",\n    \"n_steps\": 2,\n    \"model\": \"claude-sonnet-5\",\n    \"n_calls\": 2,\n    \"elapsed_seconds\": 6,\n    \"tokens\": { \"prompt\": 3414, \"completion\": 208, \"total\": 3622, \"last_context\": 1361 },\n    \"cost\": { \"usd\": 0.0139, \"source\": \"estimated\", \"reported_usd\": 0, \"estimated_usd\": 0.0139 }\n  },\n  \"messages\": [ /* full linear history: system, user, assistant, ... , exit */ ]\n}\n```\n\n## Cost & token tracking\n\nTokens are exact (from each response's `usage`). Cost is **hybrid**, tracking-only\n(no limits):\n\n- **Reported** — some routes (the OpenRouter-proxied models: `deepseek-v4-pro`,\n  `glm-5.2`, `grok-4.6`, `kimi-k3`, `qwen-3.8`) return an exact `usage.cost` in USD.\n  We use that number directly (`source: \"reported\"`).\n- **Estimated** — native routes (Claude, GPT, Gemini) return no cost, so we estimate\n  from `src/prices.js`, a table of **public list prices** ($/1M tokens). These are\n  clearly marked `source: \"estimated\"` and shown with a `~` in the per-step line.\n  Edit `src/prices.js` in one place if you have the real gateway pricing.\n\nA run that mixes both is tagged `source: \"mixed\"` with the split preserved in\n`reported_usd` / `estimated_usd`.\n\nHistorical compatibility note: older archived material may mention multi-model\nbenchmark commands, `bench/` output, reports, or the `astra-bench` sibling\nrepository. Those legacy entry points and artifacts are read-only history; the\nroot `generate.py` and `verify.py` wrappers are the only supported task benchmark\nworkflow.\n","readmeFilename":"README.md"}