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Turn any LLM into an interactive UI. One line of Python — no React, no frontend setup.

Project description

Tilo

Turn any LLM into an interactive UI. One line of Python — no React, no frontend setup.

pip install "tilo[openai]"
import tilo

spec = tilo.generate(
    "Review this SaaS contract for payment, liability, and IP risks.",
    model="gpt-4o",          # or claude-opus-4-8 — provider auto-detected
)

tilo.view(spec)              # opens in your browser. that's it.

The LLM doesn't return a wall of text — it generates a structured, interactive surface: a risk chart, a before/after diff, a checklist, a human-approval gate, and a memory card, organised into tabs. Rendered with zero frontend setup.

No API key? Run tilo demo to open a sample surface. tilo serve then open http://localhost:8000/playground for a live editor.

Works with your stack

# OpenAI
from tilo.adapters.openai import generate_aip_spec
spec = generate_aip_spec(OpenAI(), "Analyse Q3 pipeline", skill="sales_dashboard")

# Anthropic
from tilo.adapters.anthropic_sdk import generate_aip_spec
spec = generate_aip_spec(Anthropic(), "Review this PR", skill="code_review")

# LangChain / LangGraph
from tilo.adapters.langchain import generate_aip_spec
spec = generate_aip_spec(ChatOpenAI(model="gpt-4o"), "Plan a trip to Tokyo")

# Bring your own LLM client
from tilo.prompt import AIPPromptBuilder
b = AIPPromptBuilder("Summarise this incident", skill="incident_response")
# b.system_prompt(), b.user_prompt() → your LLM → b.parse(response)

Render anywhere

Browser tilo.view(spec)
Jupyter / Colab tilo.notebook(spec)
Standalone HTML tilo.save_html(spec, "out.html")
Production React npm install @adam2go/tilo-react

Install options

pip install "tilo[openai]"      # OpenAI SDK
pip install "tilo[anthropic]"   # Anthropic SDK
pip install "tilo[langchain]"   # LangChain
pip install "tilo[all]"         # everything + Postgres driver

Why Tilo

As LLMs get stronger, a wall of text is still a wall of text. Tilo turns model output into something a human can click, edit, approve, and reject — and turns those actions into structured signal the model can learn from.

  • Structured UI beats prose for decisions.
  • Human confirmation is infrastructure — stronger models need more gates, not fewer.
  • Confirmed memory, not auto-memory — Tilo proposes; the human confirms.

Links

MIT License

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