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import os | |
import gradio as gr | |
import base64 | |
import requests | |
import io | |
from PIL import Image | |
import numpy as np | |
URL = os.environ['URL'] | |
def sketch_to_text(image, api_key): | |
if image is None or not isinstance(image, dict) or 'composite' not in image: | |
return "Please draw something first." | |
# Extract the image data from the dictionary | |
image_data = image['composite'] | |
# Convert the image data to a PIL Image | |
pil_image = Image.fromarray(image_data.astype(np.uint8)) | |
# Convert the image to base64 | |
buffered = io.BytesIO() | |
pil_image.save(buffered, format="PNG") | |
img_str = base64.b64encode(buffered.getvalue()).decode() | |
if api_key: | |
API_KEY = api_key | |
else: | |
API_KEY = os.environ['API_KEY'] | |
# Prepare the API request | |
headers = { | |
"Content-Type": "application/json", | |
"Authorization": f"Bearer {API_KEY}" | |
} | |
payload = { | |
"model": "Llama-3.2-11B-Vision-Instruct", | |
"messages": [ | |
{ | |
"role": "user", | |
"content": [ | |
{ | |
"type": "text", | |
"text": "You are playing a game of pictionary. Please guess what I am trying to draw. Answer in short words only." | |
}, | |
{ | |
"type": "image_url", | |
"image_url": { | |
"url": f"data:image/png;base64,{img_str}" | |
} | |
} | |
] | |
} | |
], | |
"max_tokens": 300 | |
} | |
# Make the API request | |
response = requests.post(URL, headers=headers, json=payload) | |
if response.status_code == 200: | |
return response.json()["choices"][0]["message"]["content"] | |
else: | |
return f"Error: {response.status_code}, {response.text}" | |
# Create the Gradio interface | |
with gr.Blocks() as iface: | |
gr.Markdown("# Pictionary with Llama3.2 Instruct") | |
gr.Markdown("Draw something and let Llama3.2 guess it! [Powered by SambaNova Cloud, Get Your API Key Here](https://cloud.sambanova.ai/apis)") | |
with gr.Row(): | |
api_key = gr.Textbox(label="API Key", type="password", placeholder="(Optional) Enter your API key here for more availability") | |
with gr.Row(): | |
with gr.Column(scale=1): | |
output = gr.Textbox(label="Description", lines=5) | |
with gr.Column(scale=1): | |
input_image = gr.ImageEditor() | |
input_image.change(fn=sketch_to_text, inputs=[input_image, api_key], outputs=output) | |
gr.Markdown("How to use: 1. Draw your sketch in the box above. 2. See guessing in real time. Have fun sketching!") | |
# Launch the app | |
iface.launch() |