flyto-ai 0.2.0

AI agent that turns natural language into executable automation. 412 batteries included.

Natural language → executable automation workflows

aider writes code. open-interpreter runs code. flyto-ai builds workflows.

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What is flyto-ai?

An AI agent that turns natural language into reusable, structured automation workflows — not throwaway scripts, not chat responses.

You describe what you want. The agent calls tools, validates parameters, and produces a YAML workflow you can save, share, schedule, and run again.

"scrape the title from example.com"
         ↓
┌─────────────────────────────────────┐
│ name: Scrape Title                  │
│ steps:                              │
│   - id: launch                      │
│     module: browser.launch          │
│   - id: goto                        │
│     module: browser.goto            │
│     params:                         │
│       url: "https://example.com"    │
│   - id: extract                     │
│     module: browser.extract         │
│     params:                         │
│       selector: "h1"               │
└─────────────────────────────────────┘

Quick Start

pip install flyto-ai
export OPENAI_API_KEY=sk-...
flyto-ai chat "scrape the title from https://example.com"

That's it. One install — includes OpenAI, Anthropic, Ollama, 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	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	Anyone
License	Apache-2.0	AGPL-3.0	Apache-2.0

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 categories	317	array, math, crypto, convert, flow, ...

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)

Blueprints are stored locally (~/.flyto/blueprints.db) and scored by success rate. Export and share your best ones:

flyto-ai blueprints                             # View learned blueprints
flyto-ai blueprints --export > blueprints.yaml  # Export for sharing

CLI

flyto-ai chat "scrape example.com"           # Generate a workflow
flyto-ai chat "take screenshot" -p ollama    # Use Ollama (no API key)
flyto-ai chat "hello" --json                 # Raw JSON output
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

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

# Then 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"}'

Python API

from flyto_ai import Agent, AgentConfig

# Auto-detects API keys from environment
agent = Agent(config=AgentConfig.from_env())
result = await agent.chat("extract all links from https://example.com")
print(result.message)    # YAML workflow
print(result.tool_calls) # Tool call log

Multi-Provider

Works with any LLM:

export OPENAI_API_KEY=sk-...          # GPT-4o, GPT-4o-mini
export ANTHROPIC_API_KEY=sk-ant-...   # Claude Sonnet, Opus
flyto-ai chat "..." -p ollama         # Llama, Mistral, local models
flyto-ai chat "..." -p openai --model gpt-4o

Architecture

User message
  → LLM (OpenAI / Anthropic / Ollama)
    → Function calling: search_modules, get_module_info, validate_params, ...
      → 412 flyto-core modules
      → Self-learning blueprints
      → Browser page inspection
    → YAML validation loop (auto-retry on errors)
  → Structured workflow output

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.