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Update gradio clients documentation examples for file handling (#8970)

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* Replacing file() deprecated function by handle_file()

* Add handle_file() function to example

* Fix example synthax error

* Add handle_file() function to examples
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20
guides/08_gradio-clients-and-lite/01_getting-started-with-the-python-client.md
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@ -11,12 +11,12 @@ Using the `gradio_client` library, we can easily use the Gradio as an API to tra
Here's the entire code to do it:
```python
from gradio_client import Client, file
from gradio_client import Client, handle_file
client = Client("abidlabs/whisper")
client.predict(
audio=file("audio_sample.wav")
audio=handle_file("audio_sample.wav")
)
>> "This is a test of the whisper speech recognition model."
@ -64,12 +64,12 @@ The `gradio_client` includes a class method: `Client.duplicate()` to make this p
```python
import os
from gradio_client import Client, file
from gradio_client import Client, handle_file
HF_TOKEN = os.environ.get("HF_TOKEN")
client = Client.duplicate("abidlabs/whisper", hf_token=HF_TOKEN)
client.predict(file("audio_sample.wav"))
client.predict(handle_file("audio_sample.wav"))
>> "This is a test of the whisper speech recognition model."
```
@ -184,14 +184,14 @@ client = Client("abidlabs/image_generator")
client.predict(text="an astronaut riding a camel", steps=25)
```
For providing files or URLs as inputs, you should pass in the filepath or URL to the file enclosed within `gradio_client.file()`. This takes care of uploading the file to the Gradio server and ensures that the file is preprocessed correctly:
For providing files or URLs as inputs, you should pass in the filepath or URL to the file enclosed within `gradio_client.handle_file()`. This takes care of uploading the file to the Gradio server and ensures that the file is preprocessed correctly:
```python
from gradio_client import Client, file
from gradio_client import Client, handle_file
client = Client("abidlabs/whisper")
client.predict(
audio=file("https://audio-samples.github.io/samples/mp3/blizzard_unconditional/sample-0.mp3")
audio=handle_file("https://audio-samples.github.io/samples/mp3/blizzard_unconditional/sample-0.mp3")
)
>> "My thought I have nobody by a beauty and will as you poured. Mr. Rochester is serve in that so don't find simpus, and devoted abode, to at might in a r—"
@ -258,8 +258,8 @@ The `Job` class also has a `.cancel()` instance method that cancels jobs that ha
```py
client = Client("abidlabs/whisper")
job1 = client.submit(file("audio_sample1.wav"))
job2 = client.submit(file("audio_sample2.wav"))
job1 = client.submit(handle_file("audio_sample1.wav"))
job2 = client.submit(handle_file("audio_sample2.wav"))
job1.cancel() # will return False, assuming the job has started
job2.cancel() # will return True, indicating that the job has been canceled
```
@ -348,4 +348,4 @@ Named API endpoints: 1
- [Number] value_31: float
```
That is because the Python client handles state automatically for you -- as you make a series of requests, the returned state from one request is stored internally and automatically supplied for the subsequent request. If you'd like to reset the state, you can do that by calling `Client.reset_session()`.
That is because the Python client handles state automatically for you -- as you make a series of requests, the returned state from one request is stored internally and automatically supplied for the subsequent request. If you'd like to reset the state, you can do that by calling `Client.reset_session()`.

14
guides/08_gradio-clients-and-lite/02_getting-started-with-the-js-client.md
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@ -11,7 +11,7 @@ Using the `@gradio/client` library, we can easily use the Gradio as an API to tr
Here's the entire code to do it:
```js
import { Client } from "@gradio/client";
import { Client, handle_file } from "@gradio/client";
const response = await fetch(
"https://github.com/audio-samples/audio-samples.github.io/raw/master/samples/wav/ted_speakers/SalmanKhan/sample-1.wav"
@ -19,7 +19,7 @@ const response = await fetch(
const audio_file = await response.blob();
const app = await Client.connect("abidlabs/whisper");
const transcription = await app.predict("/predict", [audio_file]);
const transcription = await app.predict("/predict", [handle_file(audio_file)]);
console.log(transcription.data);
// [ "I said the same phrase 30 times." ]
@ -66,7 +66,7 @@ You can also connect to private Spaces by passing in your HF token with the `hf_
```js
import { Client } from "@gradio/client";
const app = Client.connect("abidlabs/my-private-space", { hf_token="hf_..." })
const app = Client.connect("abidlabs/my-private-space", { hf_token: "hf_..." })
```
## Duplicating a Space for private use
@ -76,7 +76,7 @@ While you can use any public Space as an API, you may get rate limited by Huggin
`Client.duplicate` is almost identical to `Client.connect`, the only difference is under the hood:
```js
import { Client } from "@gradio/client";
import { Client, handle_file } from "@gradio/client";
const response = await fetch(
"https://audio-samples.github.io/samples/mp3/blizzard_unconditional/sample-0.mp3"
@ -84,7 +84,7 @@ const response = await fetch(
const audio_file = await response.blob();
const app = await Client.duplicate("abidlabs/whisper", { hf_token: "hf_..." });
const transcription = await app.predict("/predict", [audio_file]);
const transcription = await app.predict("/predict", [handle_file(audio_file)]);
```
If you have previously duplicated a Space, re-running `Client.duplicate` will _not_ create a new Space. Instead, the client will attach to the previously-created Space. So it is safe to re-run the `Client.duplicate` method multiple times with the same space.
@ -203,7 +203,7 @@ const result = await app.predict("/predict", [4, "add", 5]);
For certain inputs, such as images, you should pass in a `Buffer`, `Blob` or `File` depending on what is most convenient. In node, this would be a `Buffer` or `Blob`; in a browser environment, this would be a `Blob` or `File`.
```js
import { Client } from "@gradio/client";
import { Client, handle_file } from "@gradio/client";
const response = await fetch(
"https://audio-samples.github.io/samples/mp3/blizzard_unconditional/sample-0.mp3"
@ -211,7 +211,7 @@ const response = await fetch(
const audio_file = await response.blob();
const app = await Client.connect("abidlabs/whisper");
const result = await app.predict("/predict", [audio_file]);
const result = await app.predict("/predict", [handle_file(audio_file)]);
```
## Using events

4
guides/08_gradio-clients-and-lite/07_fastapi-app-with-the-gradio-client.md
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@ -35,12 +35,12 @@ Luckily for us, there's an existing Space we can use to make this process easier
Open a new Python file, say `main.py`, and start by importing the `Client` class from `gradio_client` and connecting it to this Space:
```py
from gradio_client import Client
from gradio_client import Client, handle_file
client = Client("abidlabs/music-separation")
def acapellify(audio_path):
result = client.predict(audio_path, api_name="/predict")
result = client.predict(handle_file(audio_path), api_name="/predict")
return result[0]
```