AI agent that turns natural language into executable automation. 412 batteries included.
Project description
flyto-ai
Natural language → executable automation workflows
aider writes code. open-interpreter runs code. flyto-ai builds & runs workflows.
What is flyto-ai?
An AI agent that turns natural language into real results + reusable automation workflows.
Say "scrape the title from example.com" — the agent executes it immediately and gives you the result, plus a YAML workflow you can save, share, schedule, and run again.
> scrape the title from example.com
Result: "Example Domain"
```yaml
name: Scrape Title
params:
url: "https://example.com"
steps:
- id: launch
module: browser.launch
- id: goto
module: browser.goto
params:
url: "${{params.url}}"
- id: extract
module: browser.extract
params:
selector: "h1"
Quick Start
pip install flyto-ai
playwright install chromium # download browser for web automation
export OPENAI_API_KEY=sk-... # or ANTHROPIC_API_KEY
flyto-ai
One install, one command — interactive chat with 412 automation modules, browser automation, and self-learning blueprints.
Why flyto-ai?
| aider | open-interpreter | flyto-ai | |
|---|---|---|---|
| Output | Code changes (git diff) | One-time code execution | Results + reusable YAML workflows |
| Tools | Your codebase | Raw Python/JS/Shell | 412 pre-built modules |
| Learns | No | No | Yes — self-learning blueprints |
| Reusable | Yes (code) | No (ephemeral) | Yes (save, share, schedule) |
| Webhook/API | No | No | Yes |
| For | Developers | Power users | Developers & ops automation |
| License | Apache-2.0 | AGPL-3.0 | Apache-2.0 |
Use Cases
Web Scraping
> extract all product names and prices from example-shop.com/products
name: Scrape Products
params:
url: "https://example-shop.com/products"
steps:
- id: launch
module: browser.launch
- id: goto
module: browser.goto
params:
url: "${{params.url}}"
- id: extract
module: browser.extract
params:
selector: ".product"
fields:
name: ".product-name"
price: ".product-price"
Form Automation
> log in to staging.example.com, fill the contact form, and take a screenshot
name: Fill Contact Form
steps:
- id: launch
module: browser.launch
- id: login
module: browser.login
params:
url: "https://staging.example.com/login"
username_selector: "#email"
password_selector: "#password"
submit_selector: "button[type=submit]"
- id: fill
module: browser.form
params:
url: "https://staging.example.com/contact"
fields:
name: "Test User"
message: "Hello from flyto-ai"
- id: proof
module: browser.screenshot
API Monitoring + Notification
> check if https://api.example.com/health returns 200, if not send a Slack message
name: Health Check Alert
params:
endpoint: "https://api.example.com/health"
steps:
- id: check
module: http.get
params:
url: "${{params.endpoint}}"
- id: notify
module: notification.slack
params:
webhook_url: "${{params.slack_webhook}}"
message: "Health check failed: ${{steps.check.status_code}}"
condition: "${{steps.check.status_code}} != 200"
412 Batteries Included
Powered by flyto-core — 412 automation modules across 78 categories:
| Category | Modules | Examples |
|---|---|---|
| Browser | 38 | launch, goto, click, type, extract, screenshot, wait |
| HTTP / API | 15 | GET, POST, download, upload, GraphQL |
| String | 12 | split, replace, template, regex, slugify |
| Image | 10 | resize, crop, convert, watermark, compress |
| File | 9 | read, write, copy, zip, CSV, JSON |
| Database | 6 | query, insert, SQLite, PostgreSQL |
| Notification | 5 | email, Slack, Telegram, webhook |
| + 71 more | 317 | array, math, crypto, convert, flow, ... |
Browse available modules:
flyto-ai version # Shows installed module count
Self-Learning Blueprints
The agent remembers what works. Good workflows are automatically saved as blueprints — reusable patterns that make future tasks faster.
First time: "screenshot example.com" → 15s (discover modules, build from scratch)
Second time: "screenshot another.com" → 3s (reuse learned blueprint)
When are blueprints saved?
- Only after validation passes + execution succeeds
- Trivial 1-2 step workflows are skipped
- Each blueprint has a score based on success/fail ratio — bad ones decay naturally
- Stored locally in
~/.flyto/blueprints.db
flyto-ai blueprints # View learned blueprints
flyto-ai blueprints --export > blueprints.yaml # Export for sharing
CLI
flyto-ai # Interactive chat — executes tasks directly
flyto-ai chat "scrape example.com" # One-shot execute mode
flyto-ai chat "scrape example.com" --plan # YAML-only mode (don't execute)
flyto-ai chat "take screenshot" -p ollama # Use Ollama (no API key needed)
flyto-ai chat "..." --webhook https://... # POST result to webhook
flyto-ai serve --port 8080 # HTTP server for triggers
flyto-ai blueprints # List learned blueprints
flyto-ai version # Version + dependency status
Interactive Mode
Just run flyto-ai — multi-turn conversation with up/down arrow history:
$ flyto-ai
_____ _ _ ____ _ ___
| ___| |_ _| |_ ___ |___ \ / \ |_ _|
| |_ | | | | | __/ _ \ __) | / _ \ | |
| _| | | |_| | || (_) |/ __/ / ___ \ | |
|_| |_|\__, |\__\___/|_____| /_/ \_\___|
|___/
v0.4.0 Interactive Mode
> scrape the title from example.com
(executes browser.launch → browser.goto → browser.extract)
Result: "Example Domain"
2 executed · 5 tool calls
> now also take a screenshot
(builds on previous context)
> /clear
Conversation cleared.
Commands: /clear, /history, /version, /help, /exit
Webhook & HTTP Server
Send results anywhere:
flyto-ai chat "scrape example.com" --webhook https://hook.site/xxx
Accept triggers from anywhere:
flyto-ai serve --port 8080
# From Slack, n8n, Make, or any HTTP client:
curl -X POST http://localhost:8080/chat \
-H "Content-Type: application/json" \
-d '{"message": "take a screenshot of example.com"}'
# Execute mode (default) or plan-only:
curl -X POST http://localhost:8080/chat \
-H "Content-Type: application/json" \
-d '{"message": "scrape example.com", "mode": "yaml"}'
Python API
from flyto_ai import Agent, AgentConfig
agent = Agent(config=AgentConfig.from_env())
# Execute mode (default) — runs modules and returns results
result = await agent.chat("extract all links from https://example.com")
print(result.message) # Result + YAML workflow
print(result.execution_results) # Module execution results
# Plan-only mode — generates YAML without executing
result = await agent.chat("extract all links from example.com", mode="yaml")
print(result.message) # YAML workflow only
Multi-Provider
Works with any LLM provider:
export OPENAI_API_KEY=sk-... # OpenAI models
export ANTHROPIC_API_KEY=sk-ant-... # Anthropic models
flyto-ai chat "..." -p ollama # Local models (Llama, Mistral, etc.)
flyto-ai chat "..." --model <name> # Any specific model
Security
- Workflows are auditable — YAML is human-readable, reviewable, and version-controllable
- Module policies — whitelist/denylist categories (e.g. block
file.*ordatabase.*) - Sensitive param redaction — API keys and passwords are masked in tool call logs
- Local-first — blueprints stored in local SQLite, nothing sent to third parties
- Webhook output — structured JSON only, no raw credentials in payload
Architecture
User message
→ LLM (OpenAI / Anthropic / Ollama)
→ Function calling: search_modules, get_module_info, execute_module, ...
→ 412 flyto-core modules
→ Self-learning blueprints
→ Browser page inspection
→ Execute mode: run modules, return results + YAML
→ Plan mode: YAML validation loop (auto-retry on errors)
→ Structured output (results + reusable workflow)
Environment Variables
| Variable | Description |
|---|---|
FLYTO_AI_PROVIDER |
openai, anthropic, or ollama |
FLYTO_AI_API_KEY |
API key (or use provider-specific vars below) |
FLYTO_AI_MODEL |
Model name override |
OPENAI_API_KEY |
Fallback for OpenAI provider |
ANTHROPIC_API_KEY |
Fallback for Anthropic provider |
FLYTO_AI_BASE_URL |
Custom API endpoint (OpenAI-compatible) |
License
Apache-2.0 — use it commercially, fork it, build on it.
Project details
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