From 4df2c3139157ddd11313c9904e684b549467a134 Mon Sep 17 00:00:00 2001
From: Alex Mirran <90220293+galaxyxtwo@users.noreply.github.com>
Date: Mon, 23 Dec 2024 19:33:49 -0600
Subject: [PATCH] Create quickstart.md (#11)

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+# JS Lilypad CLI Wrapper
+An API endpoint that wraps using the Lilypad cli. This repo consists of the JS CLI wrapper for Lilypad as well as a Python proxy used to abstract the private key using a Gradio example application. 
+
+This Gradio example can be used to proxy for building react apps and other applications to run AI inference on Lilypad. 
+
+# Prerequisites
+- Docker installed and started
+
+# Usage
+### Quickstart
+- Clone the JS CLI repo
+
+```git clone https://github.com/Lilypad-Tech/js-cli-wrapper```
+
+```cd js-cli-wrapper```
+
+```code .```
+
+- Ensure Docker is running
+- Run from menu (F5)
+
+In inputs, each input must be preceeded by the -i flag, including tunables. For example: "inputs": "-i Prompt='an astronaut floating against a white background' -i Steps=50"
+
+# Testing
+The endpoint can then be tested using curl
+
+Note: This tool is for demonstration purposes and will be improved upon in the coming weeks for greater scalability. Use the following post request with the WEB3_PRIVATE_KEY in the .env file provided. The wallet/private key below is funded with testnet tokens only and has been setup to simplify the use of this developer tool.
+
+### Curl example
+```curl -X POST http://localhost:7860/gradio_api/call/run -s -H "Content-Type: application/json" -d '{
+"data": [
+"cowsay:v0.0.4,Message",
+"Hello!!"
+]}' \
+  | awk -F'"' '{ print $4}'  \
+  | read EVENT_ID; curl -N http://localhost:7860/gradio_api/call/run/$EVENT_ID
+```
+
+### Python example
+```pip install gradio_client```
+
+```from gradio_client import Client
+client = Client("http://localhost:7860/")
+result = client.predict(
+		dropdown="cowsay:v0.0.4,Message",
+		prompt="Hello!!",
+		api_name="/run"
+)
+print(result)
+```
+
+### Javascript example
+```npm i -D @gradio/client```
+
+```import { Client } from "@gradio/client";
+const client = await Client.connect("http://localhost:7860/");
+const result = await client.predict("/run", { 		
+		dropdown: "cowsay:v0.0.4,Message", 		
+		prompt: "Hello!!", 
+});
+
+console.log(result.data);
+```