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AI-powered financial terminal — local LLM + multi-source market data

Project description

Aria Code

中文 English

npm python ollama providers license stars

Aria Code

AI-powered financial terminal for the command line
Runs fully offline · 19+ cloud providers · Auto language detection · Built for investors & quant researchers

Quick Start · Shortcuts · Models · Commands · Feishu · Telegram · Architecture

Aria Code demo


What is Aria Code?

Aria Code is a terminal-first AI financial agent — think of it as Claude Code, but with deep finance domain knowledge and full offline capability. Ask it about stocks, portfolio optimization, quantitative strategies, or code, and it replies with real data, formulas, and analysis right in your terminal.

$ aria-code

  ▣ Aria Code  v4.0  local-first agent
  model      qwen2.5-coder:7b  local
  workspace  ~/my-portfolio
  mode       workspace-write · network on · local-only
  status     Ollama online · 3 models

  try  analyze AAPL  ·  /project load ./myapp  ·  /help

> analyze NVDA momentum — give me RSI, MACD, and a short thesis

  NVIDIA Corp (NVDA)  ── Technical Snapshot
  ─────────────────────────────────────────
  Price     $875.40    +2.3% today          (Finnhub real-time)
  RSI (14)  68.4       Approaching overbought
  MACD      +4.2       Bullish crossover 3 days ago
  BB Width  0.18       Moderate volatility

  Signal:  ↑ BULLISH  (momentum intact, watch RSI > 70)
  Support: $842 / $810     Resistance: $900 / $925

  Thesis: AI infrastructure spending cycle still early …

  1.9s · qwen2.5-coder:7b (local)

✨ What's New in v4.1

Feature Description
Bloomberg UI /ui <desc> generates Bloomberg Terminal-style HTML dashboards — amber-on-black, IBM Plex Mono, zero border-radius, prefers-color-scheme
Tool transparency ✓ action (42ms) after every tool call · per-turn cost display · phase dividers in multi-step commands
User profile ~/.arthera/ARIA.md auto-injected every session · /memory profile add <text> to persist your preferences
Quant engine Citadel/Jane Street-style 5-module engine · limit-up prediction · dynamic market pool
MCP tools 5 new quantitative MCP tools in the tool registry
83 commands Consolidated from ~150 — removed all LLM-replaceable commands; natural language handles the rest
LLM routing fix Model now knows it can call real-time data tools instead of saying "I don't have live data"

See CHANGELOG.md for the full history.

v4.0 highlights

Feature Description
⌨️ Keyboard shortcuts Shift+Tab cycle modes · Alt+T thinking · Alt+P model picker · Ctrl+O transcript · Ctrl+T tasks
! Shell mode Type ! git status to run shell commands, output auto-added to AI context
@ File autocomplete Type @src/ to get instant file path completion anywhere in input
/btw Side questions Ask quick questions without polluting conversation history
🌍 Auto language UI and responses auto-detect Chinese/English from OS locale on first run
🤖 19+ cloud providers Google Gemini · xAI Grok · Mistral · Cohere · Perplexity · Baidu ERNIE · ByteDance · MiniMax · StepFun · 01.AI + all originals
🔢 All Ollama models Qwen3 · DeepSeek-R1 · Llama 3.x · Phi-4 · Gemma3 · Mistral families

🧠 Intelligence Pipeline

mindmap
  root((Aria Code))
    Data Layer
      Real-time Quotes
        A-shares via Eastmoney
        US stocks via Finnhub + yfinance
        HK stocks via yfinance
        Crypto via ccxt
      Fundamentals
        Financial statements akshare
        SEC EDGAR US filings
        Tushare A-share data
      Macro Economics
        FRED Fed Reserve data
        GDP · Inflation · Rates
    Analysis Layer
      Quantitative Research
        Technical signals RSI MACD Ichimoku
        Factor analysis PE PB ROE Momentum
        Backtest engine multi-strategy
        Kelly criterion position sizing
        Black-Scholes options pricing
      Fundamental Analysis
        DCF discounted cash flow
        Piotroski F-Score
        Altman Z-Score
        DuPont decomposition
      Risk Metrics
        Max Drawdown MDD
        Sharpe Ratio
        Value at Risk VaR
        Correlation matrix
    Intelligence Layer
      Local-first Routing
        Ollama qwen3 deepseek-r1 llama3
        Auto model discovery on first run
      19+ Cloud Providers
        Anthropic Claude Google Gemini
        OpenAI xAI DeepSeek Groq
        Baidu ByteDance MiniMax StepFun
      Multi-agent Team
        Fundamental Technical Macro Risk Synthesis
    Channel Layer
      Terminal CLI with full keyboard shortcuts
      Feishu enterprise chat relay
      Telegram personal bot
      iOS push notifications APNs

✨ Core Features

Capability Details
🦙 100% offline mode Powered by Ollama — no API key, no data leaves your machine
📊 Financial intelligence DCF / WACC / PE / Sharpe / Kelly / Black-Scholes + 30 more built-in formulas
📈 Live market data A-shares (Eastmoney) · US stocks (Finnhub) · HK · Crypto (ccxt)
🔍 Quant research /backtest /signal /kelly /factor /portfolio /screen /corr /ptbt
🤖 19+ cloud providers All major international + Chinese LLM APIs supported
🔌 MCP protocol Connect any Model Context Protocol server
⌨️ Rich keyboard UX Vim mode · ! shell · @ files · Shift+Tab modes · transcript viewer
💬 Feishu / Telegram Ask Aria from any chat app, anytime
📱 iOS push alerts Real-time price alerts via APNs
🌍 Auto bilingual OS language auto-detected on first run; output follows user's input language
🏠 Real estate Property valuation, REIT screening, rental yield, 70-city China housing

🚀 Quick Start

Option 1: Bootstrap (fresh Mac / Linux — recommended)

No Node.js, Python, or Xcode required. One command handles everything:

curl -fsSL https://raw.githubusercontent.com/artherahq/aria-code/aria-code/bootstrap.sh | bash

What it does automatically:

  • ✅ Installs Xcode Command Line Tools (macOS) — provides git, make, compiler
  • ✅ Installs Homebrew (macOS package manager)
  • ✅ Installs Python 3.12 if not present
  • ✅ Clones the repo into ~/aria-code
  • ✅ Runs install.sh to create venv, install all packages, and register the aria-code command

Already cloned the repo? Just run bash bootstrap.sh from inside the folder.

Option 2: npm (requires Node.js ≥ 16)

If you already have Node.js installed, the npm installer handles Python, Xcode CLT, and Homebrew automatically:

npm install -g @artheras/aria-code
aria-code

What happens under the hood:

  • ✅ Detects / installs Xcode Command Line Tools (macOS)
  • ✅ Detects / installs Homebrew (macOS)
  • ✅ Detects / installs Python 3.12 if missing
  • ✅ Clones Aria Code into ~/.aria-code/
  • ✅ Uses uv to create a venv and install dependencies from pyproject.toml (falls back to pip)

Update: npm update -g @artheras/aria-code

Repair if broken: npm explore -g @artheras/aria-code -- npm run repair

Option 3: Git clone

install.sh is uv-powered — it installs uv if missing and lets uv download a managed Python automatically, so you don't need Python pre-installed. Dependencies come from pyproject.toml.

git clone https://github.com/artherahq/aria-code.git
cd aria-code
bash install.sh              # full install (recommended)
# bash install.sh --core     # slim core only — add features later
# bash install.sh --dev      # everything incl. brokers + dev tools

Add to PATH (if prompted):

echo 'export PATH="$HOME/.local/bin:$PATH"' >> ~/.zshrc && source ~/.zshrc

Option 4: Windows

git clone https://github.com/artherahq/aria-code.git
cd aria-code
.\install.ps1

Option 5: PyPI (pip / uv / pipx)

Aria Code ships a proper Python package, so any standard tool works:

uv tool install aria-code          # isolated, fast (recommended)
pipx install aria-code             # isolated alternative
pip install aria-code              # into the current environment

This installs the slim core (CLI + yfinance). Add features with extras:

uv tool install "aria-code[full]"      # all data sources + files + charts + SQL
pip install "aria-code[cn]"            # + China A-share data (akshare)
pip install "aria-code[files]"         # + PDF/Word/Excel parsing
pip install "aria-code[all]"           # + brokers + backtest + dev tools

Available extras: cn · crypto · charts · data · files · web · browser · desktop · sports · lsp · brokers · backtest · full · all.

Option 6: Run directly (no install)

git clone https://github.com/artherahq/aria-code.git
cd aria-code
uv venv && uv pip install -e ".[full]"   # uv (fast); or use python -m venv + pip
python3 aria_cli.py

🇨🇳 China / behind a firewall (network timeouts)

If installs time out reaching GitHub or PyPI (e.g. curl: (56) Recv failure), set ARIA_CN=1 — every installer then uses the Tsinghua PyPI mirror and a Python-build mirror. The installers also auto-retry through these mirrors if a download fails, so you usually don't need the flag.

ARIA_CN=1 bash install.sh                 # git clone path
ARIA_CN=1 npm install -g @artheras/aria-code   # npm path
$env:ARIA_CN=1; .\install.ps1             # Windows

You can also point at your own mirrors via standard env vars: UV_DEFAULT_INDEX, UV_PYTHON_INSTALL_MIRROR, PIP_INDEX_URL.

Step 1: Install Ollama (local LLM — free, fully offline)

# macOS / Linux
curl -fsSL https://ollama.ai/install.sh | sh

# Pull a model (choose one — auto-detected on first run)
ollama pull qwen2.5-coder:7b    # Recommended — fast, great Chinese support (~4.7GB)
ollama pull qwen3:8b            # Latest Qwen, stronger reasoning
ollama pull deepseek-r1:7b      # Strong reasoning for complex quant tasks
ollama pull llama3.2:3b         # Smallest, fastest (~2GB)
ollama pull phi4-mini           # Microsoft Phi-4 mini, excellent code

Aria auto-discovers the best installed model on first run — no configuration needed.

Step 2: Cloud API keys (all optional)

# Interactive setup wizard
python3 setup_wizard.py

# Or manually copy and edit
cp .env.example .env

The setup wizard now covers all 19 cloud providers including Google Gemini, xAI Grok, Mistral, Baidu ERNIE, ByteDance Doubao, and more.


⌨️ Keyboard Shortcuts

Aria Code has a full keyboard shortcut system powered by prompt_toolkit:

General

Shortcut Action
Shift+Tab Cycle permission modes: read-onlyworkspace-writefull-access
Alt+T Toggle thinking mode on/off
Alt+P Open model switcher (fills /model in prompt)
Ctrl+O Toggle transcript viewer — shows all tool calls with timestamps
Ctrl+T Toggle task list — live pending/in-progress/done indicator
Ctrl+L Redraw terminal screen (fixes garbled display)
Ctrl+C Cancel current response / clear input
Ctrl+D Exit Aria
Esc Interrupt streaming response

Input Modes

Prefix Mode Example
/ Slash command with fuzzy autocomplete /backtest momentum SPY
! Shell mode — runs command, adds output to context ! git diff HEAD~1
@ File path autocomplete @src/components/
""" Multi-line input mode (end with """) For pasting code blocks

Bottom Toolbar (always visible)

qwen2.5-coder:7b · ~/my-project ⎇ main ✓3/5 · rw · local-only · /help · 1,240/16,384
│                    │           │      │       │    │
│                    │           │      │       │    └── context usage
│                    │           │      │       └── privacy status
│                    │           │      └── permission: ro/rw/full (color-coded)
│                    │           └── task progress
│                    └── git branch
└── current model

🤖 Model Support

Local Models (via Ollama — offline, free)

Model Command Size Best For
qwen2.5-coder:7b ollama pull qwen2.5-coder:7b 4.7GB Code + Chinese (recommended)
qwen3:8b ollama pull qwen3:8b 5.2GB Latest Qwen, reasoning
qwen3:30b-a3b ollama pull qwen3:30b-a3b 17GB High capability
deepseek-r1:7b ollama pull deepseek-r1:7b 4.7GB Strong math/reasoning
deepseek-r1:1.5b ollama pull deepseek-r1:1.5b 1.1GB Ultra-light reasoning
llama3.2:3b ollama pull llama3.2:3b 2GB General, fastest
llama3.1:8b ollama pull llama3.1:8b 4.7GB General purpose
mistral:7b ollama pull mistral:7b 4.1GB European quality
phi4-mini ollama pull phi4-mini 2.5GB Excellent code, small
gemma3:4b ollama pull gemma3:4b 3.3GB Google, efficient

Switch model anytime:

/model                    # Interactive picker with install status
/model qwen3:8b           # Direct switch
/model openai/gpt-4.5     # Cloud model
Alt+P                     # Keyboard shortcut

Cloud Providers (19+ supported)

International

Provider Models Env Var
Anthropic Claude Sonnet 4, Opus 4 ANTHROPIC_API_KEY
OpenAI GPT-4.5, o3, o4-mini OPENAI_API_KEY
DeepSeek deepseek-chat, deepseek-reasoner DEEPSEEK_API_KEY
Google Gemini gemini-2.0-flash, 2.5-pro GOOGLE_API_KEY
xAI Grok grok-3, grok-3-fast XAI_API_KEY
Groq llama-3.3-70b (fast inference) GROQ_API_KEY
Mistral mistral-large, codestral MISTRAL_API_KEY
Cohere command-r-plus COHERE_API_KEY
Perplexity sonar-pro (web search) PERPLEXITY_API_KEY
Together AI 100+ open-source models TOGETHER_API_KEY

Chinese Providers (国内)

Provider Models Env Var
SiliconFlow 硅基流动 Qwen/DeepSeek hosted SILICONFLOW_API_KEY
DashScope 阿里百炼 qwen-max, qwen-turbo DASHSCOPE_API_KEY
Moonshot Kimi moonshot-v1-128k MOONSHOT_API_KEY
Zhipu GLM 智谱 glm-4-plus ZHIPU_API_KEY
Baidu ERNIE 百度千帆 ernie-4.5-turbo QIANFAN_ACCESS_KEY
ByteDance Doubao 豆包 (endpoint-based) ARK_API_KEY
MiniMax MiniMax-Text-01 MINIMAX_API_KEY
StepFun 阶跃星辰 step-2-16k STEPFUN_API_KEY
01.AI Yi 零一万物 yi-large ONEAI_API_KEY

Use any provider:

/model anthropic/claude-sonnet-4-6
/model google/gemini-2.0-flash-exp
/model baidu/ernie-4.5-turbo-128k
/model moonshot/moonshot-v1-128k
/apikey       # Interactive wizard for all 19 providers

⚡ Commands Reference

Market & Quotes

/quote AAPL MSFT TSLA              # Real-time multi-symbol quotes (Finnhub)
/quote 000001 600519 300750        # A-share quotes (Eastmoney)
/quote BTC/USDT ETH/USDT           # Crypto prices
/news AAPL                         # Latest financial news
/regime                            # Market regime (bull / bear / neutral)
/alert add AAPL gt 200             # Price alert
/alert list                        # View all alerts

Quantitative Research

/signal TSLA                       # Technical signals (RSI / MACD / Bollinger)
/backtest momentum SPY 2023-01-01 2024-12-31
/backtest ml 600519 300750 NVDA    # ML signal backtest (3-strategy comparison)
/wf SPY momentum                   # Walk-forward backtest
/kelly AAPL 0.6 2.0                # Kelly formula — position size recommendation
/factor PE PB ROE                  # Multi-factor analysis
/screen PE<15 ROE>20               # Stock screener with filters
/portfolio AAPL MSFT GOOGL         # Portfolio optimization
/ptbt AAPL MSFT GOOG 0.4 0.3 0.3  # Portfolio backtest with weights
/corr AAPL MSFT TSLA SPY           # Correlation matrix
/ichimoku AAPL                     # Ichimoku cloud chart
/options AAPL calls 2025-01        # Options chain
/quality AAPL                      # Piotroski + Altman Z-score

Analysis

/analyze AAPL                      # AI full analysis
/peer AAPL MSFT GOOGL META         # Peer comparison
/macro                             # Macro dashboard (GDP / CPI / Fed rates)
/macro cn                          # China macro data
/sector tech                       # Sector analysis
/realty Shanghai Pudong            # Real estate analysis
/feargreed                         # Crypto Fear & Greed Index
/funding BTC ETH                   # Perpetual funding rates

Session & UI

/btw what was that function name?  # Side question — no history pollution
/recap                             # Session summary (turns + topics)
/clear                             # Clear conversation
/compact                           # Smart context compression
/history                           # Show recent conversation
/sessions                          # List saved sessions
/export md report.md               # Export conversation
/rename "NVDA Research"            # Name current session

System

/model                             # View / switch LLM (interactive picker)
/apikey                            # API key wizard for all 19 providers
/config set ui_lang=zh             # Force Chinese UI
/config set ui_lang=en             # Force English UI
/thinking on                       # Enable extended thinking mode
/privacy status                    # Privacy settings
/tools                             # List all enabled tools
/skills                            # List skills
/mcp list                          # MCP server status
/doctor                            # Diagnose installation issues
/providers                         # All provider status

🌍 Language Auto-Detection

On first run, Aria reads your OS locale and sets the UI language automatically:

# Chinese system → Chinese UI + hints
LANG=zh_CN.UTF-8    本地优先智能体 · Ollama 在线 · 试试 分析 AAPL

# English system → English UI + hints
LANG=en_US.UTF-8    local-first agent · Ollama online · try analyze AAPL

AI output language always follows your input — ask in Chinese, get Chinese; ask in English, get English.

Override anytime:

/config set ui_lang=zh    # Force Chinese
/config set ui_lang=en    # Force English
/config set ui_lang=auto  # Back to OS auto-detect

💬 Feishu Integration

Connect Aria to Feishu (Lark) and ask financial questions from any group or DM.

How it works

Your Feishu message
       │
       ▼
  Feishu servers
       │
  ┌────┴────────────────────────────────────┐
  │  Mode A: Relay (recommended, 5 min)     │  Mode B: Own App (20 min)
  │  Aria Relay Server                       │  Feishu Open Platform App
  │  wss://relay.aria.ai                     │  Requires public IP or tunnel
  └────┬────────────────────────────────────┘
       │
       ▼
 aria_relay_client.py  (your machine)
       │
       ▼
 aria_cli.py → LLM → response sent back

Mode A: Relay (Recommended)

python3 setup_wizard.py
# Select "Feishu relay mode"
# Output: ✅ Your Client ID: ARIA-xxxxxxxx-xxxx

Send to the Aria Bot in Feishu:

/bind ARIA-xxxxxxxx-xxxx

Configure ~/.aria/.env:

ARIA_RELAY_URL=wss://relay.aria.ai
ARIA_RELAY_CLIENT_ID=ARIA-xxxxxxxx-xxxx
ARIA_RELAY_MODE=relay
ARIA_CODE_DIR=~/aria-code

Start:

python3 aria_daemon.py start

Mode B: Own Feishu App

  1. Open Feishu Open Platform → Create custom app
  2. Set event URL: https://yourdomain.com/api/v1/feishu/webhook
  3. Subscribe to im.message.receive_v1
FEISHU_APP_ID=cli_xxxxxxxxxxxxxxxxx
FEISHU_APP_SECRET=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
ARIA_RELAY_MODE=own_app

📱 Telegram Integration

Setup

  1. Message @BotFather/newbot → copy your Bot Token
  2. Message @userinfobot → copy your Chat ID

Configure:

TELEGRAM_BOT_TOKEN=1234567890:ABCDEFGxxxxxxxxxxxxxx
TELEGRAM_ALLOWED_IDS=123456789
ARIA_CODE_DIR=~/aria-code

Start:

python3 aria_daemon.py start

Use in Telegram:

/price AAPL                → Apple real-time quote
/price 600519              → Moutai A-share
/price BTC/USDT            → Bitcoin
Analyze NVDA momentum      → Full AI analysis

🏗️ Architecture

┌─────────────────────────────────────────────────────────────────┐
│                          Aria Code v4.0                         │
│                                                                 │
│  ┌──────────┐  ┌────────────┐  ┌──────────┐  ┌─────────────┐ │
│  │ Terminal │  │Feishu Bot  │  │ Telegram │  │   Webhook   │ │
│  │   CLI    │  │(relay/app) │  │   Bot    │  │  External   │ │
│  └────┬─────┘  └─────┬──────┘  └────┬─────┘  └──────┬──────┘ │
│       └───────────────┴──────────────┴────────────────┘        │
│                               │                                 │
│                     ┌─────────▼──────────┐                     │
│                     │   aria_daemon.py    │                     │
│                     │  Message router     │                     │
│                     └─────────┬──────────┘                     │
│                               │                                 │
│              ┌────────────────┼────────────────┐               │
│              │                │                │               │
│   ┌──────────▼───┐  ┌─────────▼───┐  ┌────────▼──────┐       │
│   │  LLM Router  │  │  Tool Exec  │  │  Data Layer   │       │
│   │19+ providers │  │  bash/file  │  │Finnhub/EastMny│       │
│   └──────────────┘  └─────────────┘  └───────────────┘       │
└─────────────────────────────────────────────────────────────────┘

File Structure

aria-code/
├── aria_cli.py               # Main CLI + REPL (keyboard shortcuts, ! shell, @files)
├── aria_daemon.py            # Background daemon + scheduler
├── market_data_client.py     # Unified market data (Finnhub primary for US)
├── setup_wizard.py           # Bilingual setup wizard (19 providers)
│
├── apps/cli/
│   ├── i18n.py               # Language auto-detection + UI string translations
│   ├── commands/
│   │   └── model_cmds.py     # /model /apikey /providers (19 cloud providers)
│   ├── prompts/
│   │   └── coding.py         # Code generation prompts (end_date fix, akshare fallback)
│   └── tools/
│       └── market_tools.py   # Market data tools (Finnhub dp field)
│
├── ui/
│   ├── banner.py             # Bilingual banner (i18n aware)
│   └── completer.py          # Fuzzy autocomplete: / commands · @ files · ! history
│
├── providers/llm/            # LLM adapters (19+ cloud endpoints)
├── agents/financial/         # Fundamental / Technical / Macro / Risk / Synthesis
├── brokers/                  # CN (Futu/Longbridge/Tiger) + Intl (IBKR/Alpaca)
└── datasources/sources/      # yfinance · akshare · FRED · EDGAR · Finnhub

📡 Market Data Sources

Source Coverage API Key
Finnhub US real-time quotes (primary) + earnings Optional free tier
Eastmoney A-share real-time, northbound flow, limit-up/down None (free)
akshare A-share history, financials, sector data None (free)
yfinance US/HK/global stocks, ETFs, FX, history None (free)
ccxt 100+ crypto exchanges None (free tier)
FRED Fed macro — GDP, CPI, rates Optional (free signup)
SEC EDGAR US 10-K / 10-Q filings None (free)
Alpha Vantage US history + fundamentals Optional (free tier)
Polygon US market data (professional) Optional (free tier)
Tushare A-share complete data Optional (free token)

🔌 MCP Integration

Connect any Model Context Protocol server:

{
  "servers": [
    {
      "name": "filesystem",
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/your/project"]
    },
    {
      "name": "brave-search",
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-brave-search"],
      "env": { "BRAVE_API_KEY": "your-key" }
    }
  ]
}
/mcp list      # List connected MCP servers
/mcp status    # Server health
/mcp tools     # All available MCP tools

⚙️ Configuration

Settings are stored in ~/.arthera/config.json. Add .ariarc to any project for project-level overrides:

{
  "model": "qwen2.5-coder:7b",
  "ui_lang": "auto",
  "market": "us",
  "permission_mode": "workspace-write",
  "default_symbols": ["AAPL", "NVDA", "MSFT", "GOOGL"],
  "thinking": false
}

LLM Provider Priority

Aria automatically selects the first available provider:

Local Ollama  →  Anthropic  →  OpenAI  →  DeepSeek  →  Google  →  xAI  →  Groq  →  …
(offline first)  (reasoning)   (general)  (cost-eff.)  (multi.)  (web)  (fast)

Force local mode: ARIA_MODEL=ollama/qwen2.5-coder:7b


🛠️ Requirements

  • Python 3.10+
  • Ollama (highly recommended for offline mode)
  • RAM: 4GB+ (8GB+ for 7B models)
  • macOS · Linux · Windows (WSL2)
pip install -r requirements.txt

Core dependencies: rich · prompt_toolkit · yfinance · akshare · ccxt · pandas · numpy


🤝 Contributing

Contributions welcome! See CONTRIBUTING.md.

git clone https://github.com/artherahq/aria-code.git
cd aria-code
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
pytest tests/ -v

Relation to Arthera

Aria Code is the open-source CLI component of Arthera — an AI-powered quantitative investment platform. The full Arthera platform includes a web dashboard, desktop terminal, iOS app, and institutional quant engine.

Aria Code is designed to work as a standalone tool — it does not require the Arthera backend. All financial calculations run locally. Cloud features are optional.


License

Business Source License 1.1 © 2025–2026 Arthera.

Free to use, run, modify, and self-host for personal, internal, educational, and research purposes — including trading your own account. Offering Aria Code as a hosted/managed service, or selling a competing product built on it, requires a commercial license (contact dev@arthera.finance). Each version converts to Apache 2.0 four years after release.

Versions up to and including 4.1.2 were released under MIT and remain available under those terms.


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