Introducing Gradio 5.0
Read MoreIntroducing Gradio 5.0
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To install the Gradio Python Client from main, run the following command:
pip install 'gradio-client @ git+https://github.com/gradio-app/gradio@b5eaba1d6d6938197f105e5906a07fe2b2bba704#subdirectory=client/python'
We’re excited to unveil the first major release of the Gradio clients. We’ve made it even easier to turn any Gradio application into a production endpoint thanks to the clients’ ergonomic, transparent, and portable design.
Stream From a Gradio app in 5 lines
Use the submit
method to get a job you can iterate over.
In python:
from gradio_client import Client
client = Client("gradio/llm_stream")
for result in client.submit("What's the best UI framework in Python?"):
print(result)
In typescript:
import { Client } from "@gradio/client";
const client = await Client.connect("gradio/llm_stream")
const job = client.submit("/predict", {"text": "What's the best UI framework in Python?"})
for await (const msg of job) console.log(msg.data)
Use the same keyword arguments as the app
In python:
from gradio_client import Client
client = Client("http://127.0.0.1:7860/")
result = client.predict(
message="Hello!!",
system_prompt="You are helpful AI.",
tokens=10,
api_name="/chat"
)
print(result)
In typescript:
import { Client } from "@gradio/client";
const client = await Client.connect("http://127.0.0.1:7860/");
const result = await client.predict("/chat", {
message: "Hello!!",
system_prompt: "Hello!!",
tokens: 10,
});
console.log(result.data);
Better Error Messages
Anything you can do in the UI, you can do with the client:
from gradio_client import Client
client = Client("gradio/diffusion_model")
job = client.submit("A cute cat")
while not job.done():
status = job.status()
print(f"Current in position {status.rank} out of {status.queue_size}")
from gevent import monkey
monkey.patch_all()
from gradio_client import Client
from flask import Flask, send_file
import time
app = Flask(__name__)
imageclient = Client("gradio/diffusion_model")
@app.route("/gen")
def gen():
result = imageclient.predict(
"A cute cat",
api_name="/predict"
)
return send_file(result)
if __name__ == "__main__":
app.run(host="0.0.0.0", port=5000)
Python
Javascript
const app = await Client.connect("gradio/whisper")
The app variable has the same methods as the python class (submit
, predict
, view_api
, duplicate
).