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()