AI-powered financial terminal — local LLM + multi-source market data
Project description
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
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.shto create venv, install all packages, and register thearia-codecommand
Already cloned the repo? Just run
bash bootstrap.shfrom 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-only → workspace-write → full-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
- Open Feishu Open Platform → Create custom app
- Set event URL:
https://yourdomain.com/api/v1/feishu/webhook - Subscribe to
im.message.receive_v1
FEISHU_APP_ID=cli_xxxxxxxxxxxxxxxxx
FEISHU_APP_SECRET=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
ARIA_RELAY_MODE=own_app
📱 Telegram Integration
Setup
- Message @BotFather →
/newbot→ copy your Bot Token - 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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- Size: 1.2 MB
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