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import os
import gradio as gr
from together import Together
from PIL import Image
import io
import base64
# Initialize the Together AI client
client = Together(api_key=os.environ.get('TOGETHER_API_KEY'))
def encode_image(image):
buffered = io.BytesIO()
image.save(buffered, format="PNG")
return base64.b64encode(buffered.getvalue()).decode('utf-8')
def chat_with_image(message, image, history):
# Encode the image
if image is not None:
encoded_image = encode_image(Image.open(image))
image_message = {
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": f"data:image/png;base64,{encoded_image}"}},
{"type": "text", "text": message}
]
}
else:
image_message = {"role": "user", "content": message}
# Prepare the messages
messages = [{"role": "system", "content": "You are a helpful assistant."}]
for human, assistant in history:
messages.append({"role": "user", "content": human})
messages.append({"role": "assistant", "content": assistant})
messages.append(image_message)
# Call the Together AI API
response = client.chat.completions.create(
model="meta-llama/Llama-Vision-Free",
messages=messages,
max_tokens=512,
temperature=0.7,
top_p=0.7,
top_k=50,
repetition_penalty=1,
stop=["<|eot_id|>", "<|eom_id|>"],
stream=True
)
# Accumulate the response
full_response = ""
for chunk in response:
if chunk.choices[0].delta.content is not None:
full_response += chunk.choices[0].delta.content
yield full_response
return full_response
# Create the Gradio interface
with gr.Blocks() as demo:
chatbot = gr.Chatbot()
msg = gr.Textbox()
image = gr.Image(type="filepath")
clear = gr.Button("Clear")
def user(user_message, image, history):
return "", image, history + [[user_message, None]]
def bot(history):
user_message, image = history[-1][0], None
if len(history) > 1 and isinstance(history[-2][0], dict):
image = history[-2][0]['image']
bot_message = chat_with_image(user_message, image, history[:-1])
history[-1][1] = ""
for character in bot_message:
history[-1][1] += character
yield history
msg.submit(user, [msg, image, chatbot], [msg, image, chatbot], queue=False).then(
bot, chatbot, chatbot
)
clear.click(lambda: None, None, chatbot, queue=False)
demo.queue()
demo.launch() |