aria-x 1.6.1

ARIA — Autonomous Reasoning and Intelligent Agent. Writes code AND proves it works — verified end-to-end.

◉ ARIA

Autonomous Reasoning and Intelligent Agent

Your project-aware coding partner. Reason before action.

ARIA is an open-source CLI agent that works inside your project boundaries like a senior engineer — it plans before acting, validates its work, remembers context across sessions, and never silently modifies your system.

---

Website: https://lonerider007.github.io/aria-landing/

Benchmark — ARIA vs Aider

Tested on: autonomous production backend build (Node.js + Express + SQLite + JWT + RBAC)

Capability	ARIA	Aider
Runtime grounding	Excellent	Weak
Autonomous debugging	Excellent	Poor
Recovery behavior	Excellent	Poor
Runtime validation	Successful	Incomplete
Convergence stability	Strong	Fragile
Production readiness	Near-complete	Incomplete

Verdict: ARIA completed the full backend autonomously. Aider got stuck in edit-format desynchronization loops before reaching runtime execution.

Tested on nemotron-3-super:cloud. Both agents given identical task from scratch.

---

Install

pipx install aria-x

Note: Use pipx (not pip) on Ubuntu/Debian/macOS. pip install will fail with "externally-managed-environment" error on modern systems. If pipx is not installed: pip install pipx --break-system-packages

aria --model nemotron-3-super:cloud

Requirements: Python 3.10+, Ollama

Minimum Model Requirements

Use case	Minimum model
Local (free)	qwen2.5-coder:7b or llama3.2:8b — minimum 7B params
Cloud (recommended)	nemotron-3-super:cloud via Ollama
Not supported	Models under 7B (3B models cannot tool-call reliably)

---

Demo

◉ aria(my-project) › Build a REST API with FastAPI and test it

─────────────────── Plan ───────────────────
  Goal: Build FastAPI REST API

  1. Scaffold project with venv + git
  2. Write endpoints
  3. Install dependencies in .venv
  4. Run server and test with curl

Proceed? (yes / no / modify): yes

  ◉ Scaffolding 'fastapi-api'...  step 1
  1. new_project  'fastapi-api'

  ◉ Writing main.py...  step 2
  2. write_file  'main.py'

  ◉ Installing fastapi uvicorn...  step 3
  3. run_command  '.venv/bin/pip install -r requirements.txt'
     │ Successfully installed fastapi uvicorn

  ◉ Running tests...  step 4
  4. run_command  'curl http://localhost:8000/health'
     │ {"status":"ok"}

─────────────────── Report ─────────────────
API built and tested. Run: uvicorn main:app --reload

---

What's New in v1.6.0 — The Comeback Release

"Agent that writes code AND proves it works — verified end-to-end."

Most coding agents (Aider, Cursor, even Claude Code) mark tasks done on structural completion. ARIA v1.6 enforces three gates at the code level — before any task is marked done:

1. fetch_api_spec — for any HTTP integration, the real API docs must be fetched first. No more hardcoded params from training-era memory.
2. verify_goal — concrete evidence (files exist, commands exited 0, expected output present) must back every completion claim.
3. acceptance_test — a small runnable script proves the goal works end-to-end before "done".

If ARIA says it works, it actually works.

Architecture upgrades (all code-level, not prompt rules)

• Mode router — conversational vs task classification at the input layer; skips tool schema entirely for greetings/questions (saves ~600 tokens/turn).
• Plan/Approval FSM — mutating tools (write/edit/run) blocked at runtime until plan is approved. Bypass-proof.
• Delta context memory — duplicate tool outputs replaced with short references; long sessions stay flat in tokens.
• Adaptive recall — TF-IDF + relation-graph proximity; old irrelevant messages pruned first when over budget, not FIFO.
• Tool guards — bare pip install, rm -rf /, multiple delete_file/turn, HTTP code without spec — all blocked deterministically.
• Loop guard — error fingerprints; 3 identical errors → automatic pivot; 2 failed pivots → honest "I can't" report.
• Runtime validator — hallucinated file paths blocked; "task complete" claims rejected when recent results contain errors; stale-belief catch when the same factual claim repeats across 3+ turns.
• Time awareness — system prompt refreshed every turn with real wall-clock; LLM forbidden to quote versions from training memory without search_web.
• Relation graph — SQLite at ~/.aria/relations.db recording file edits, project switches, verified tasks. Foundation for semantic recall.

New commands

• /undo — reverses the most recent write_file/edit_file/delete_file. /undo list shows recent mutations.

Bug fixes

• git_commit shell injection (subprocess list form now)
• git_create_branch rejects unsafe branch names
• Web bridge no longer hardcodes stale version string
• Onboarding fast-path no longer re-triggers full TnC on saved configs
• list_files recursive: caps at 500 entries, skips .git/node_modules/__pycache__/.venv/...
• read_file, search_in_files: output capped at 16KB
• /clear now also resets the FSM, loop guard, and validator state

Prompt economy

• System prompt: 153 lines → 77 lines. Behaviors that used to be prompt rules ("never run bare pip install", "use Pydantic V2") are now enforced in code.

---

What's New in v1.4.3

• aria web — access ARIA from any browser on your local network, including phone
• WebSocket streaming — real-time token streaming in browser, same as terminal
• Plan approval in browser — approve/reject plans via buttons, no terminal needed
• Mobile-first UI — dark terminal theme, responsive, works on phone screen
• Session timeline — live history panel in browser
• Auto-reconnect — browser reconnects automatically if connection drops
• Install: pip install aria-x[web] → aria web

What's New in v1.4.2

• Personalized greeting — ARIA shows your last session context on every startup
• Python 3.14 AST compatibility — detects removed node types (ast.Str, ast.Bytes, ast.Num, ast.NameConstant) before execution
• Test suite — 9 unit tests for AST validator, all passing
• Updated dependencies — latest floors for openai, rich, prompt_toolkit, ddgs

What's New in v1.4.1

• Sandbox mode — isolated workspace for experiments (/sandbox)
• Web search — search_web tool searches DuckDuckGo in real time
• 8 security & stability bugs fixed — code audit pass
• Rate limit & 500 error handling — clean messages, auto-retry

What's New in v1.4.0

• Humanized tool display — ◉ Writing auth.py... instead of raw tool names
• Persistent token counter — bottom bar shows ↑ 1.2k tokens · 3 turns · 2m 30s
• Internet access — search_web tool for real-time information
• Config system — first run saves settings, next run is instant
• /history, /init, /tokens — new slash commands
• --quiet mode — hide tool details, show only final report
• Context auto-trim — prevents context overflow crashes
• English-only responses — consistent regardless of input language
• Frozen header — ARIA info stays visible at startup

---

Features

• Plan before action — shows what it will do, waits for your approval
• AST pre-validation — catches errors before running code (no hallucination at this layer)
• RAG with web search — searches real docs when stuck, not model memory
• Loop detection — detects repeated failures, pivots to alternative approach
• Project isolation — all packages go in .venv only, never touches system Python
• Project memory — remembers stack, decisions, and context across sessions
• Approval system — asks before dangerous operations
• Beautiful diffs — shows exactly what changed in every file
• Live status bar — always know what ARIA is doing

---

Slash Commands

Command	Description
/help	Show all commands
/fix	Fix bugs in current project
/test	Run tests, fix failures
/explain <file>	Explain code
/commit	Smart git commit
/review	Code review
/status	Session info
/model <name>	Switch model
/memory	Show project memory
/projects	List all ARIA projects
/undo	Undo last file write/edit/delete (/undo list to view)
/exit	Exit

---

Models

aria --model nemotron-3-super:cloud   # Ollama cloud
aria --model devstral-2:123b          # Coding specialist
aria --model llama3.3                 # Local via Ollama
aria --model qwen2.5-coder:32b        # Local coding model

---

How it works

Clarify → Plan → Approve → Execute → Validate → Remember → Report

• AST Validator catches errors before execution
• RAG injects real documentation on errors
• Loop detector pivots approach after 3 repeated failures
• Memory persists decisions across sessions

---

Project Memory

~/.aria/
├── user_memory.json
└── projects/
    └── my-project/
        ├── meta.json      # Stack, status, path
        ├── memory.json    # Key decisions
        └── progress.md   # Milestone history

---

Built by

Sumit — independent developer
GitHub: Lonerider007
Email: [e-mail]

---

License

ARIA Source by Sumit @ [e-mail]