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| import gradio as gr | |
| from PIL import Image | |
| import requests | |
| import os | |
| from together import Together | |
| import base64 | |
| from threading import Thread | |
| import time | |
| import io | |
| # Initialize Together client | |
| client = None | |
| def initialize_client(api_key=None): | |
| global client | |
| if api_key: | |
| client = Together(api_key=api_key) | |
| elif "TOGETHER_API_KEY" in os.environ: | |
| client = Together() | |
| else: | |
| raise ValueError("Please provide an API key or set the TOGETHER_API_KEY environment variable") | |
| def encode_image(image_path, max_size=(800, 800), quality=85): | |
| with Image.open(image_path) as img: | |
| img.thumbnail(max_size) | |
| if img.mode in ('RGBA', 'LA'): | |
| background = Image.new(img.mode[:-1], img.size, (255, 255, 255)) | |
| background.paste(img, mask=img.split()[-1]) | |
| img = background | |
| buffered = io.BytesIO() | |
| img.save(buffered, format="JPEG", quality=quality) | |
| return base64.b64encode(buffered.getvalue()).decode('utf-8') | |
| def bot_streaming(message, history, max_new_tokens=250, api_key=None, max_history=5): | |
| if client is None: | |
| initialize_client(api_key) | |
| txt = message["text"] | |
| messages = [] | |
| images = [] | |
| for i, msg in enumerate(history[-max_history:]): | |
| if isinstance(msg[0], tuple): | |
| messages.append({"role": "user", "content": [{"type": "text", "text": history[i+1][0]}, {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encode_image(msg[0][0])}"}}]}) | |
| messages.append({"role": "assistant", "content": [{"type": "text", "text": history[i+1][1]}]}) | |
| elif isinstance(history[i-1], tuple) and isinstance(msg[0], str): | |
| pass | |
| elif isinstance(history[i-1][0], str) and isinstance(msg[0], str): | |
| messages.append({"role": "user", "content": [{"type": "text", "text": msg[0]}]}) | |
| messages.append({"role": "assistant", "content": [{"type": "text", "text": msg[1]}]}) | |
| if len(message["files"]) == 1: | |
| if isinstance(message["files"][0], str): # examples | |
| image_path = message["files"][0] | |
| else: # regular input | |
| image_path = message["files"][0]["path"] | |
| messages.append({"role": "user", "content": [{"type": "text", "text": txt}, {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encode_image(image_path)}"}}]}) | |
| else: | |
| messages.append({"role": "user", "content": [{"type": "text", "text": txt}]}) | |
| try: | |
| stream = client.chat.completions.create( | |
| model="meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo", | |
| messages=messages, | |
| max_tokens=max_new_tokens, | |
| stream=True, | |
| ) | |
| buffer = "" | |
| for chunk in stream: | |
| if chunk.choices[0].delta.content is not None: | |
| buffer += chunk.choices[0].delta.content | |
| time.sleep(0.01) | |
| yield buffer | |
| except together.error.InvalidRequestError as e: | |
| if "Request Entity Too Large" in str(e): | |
| yield "The image is too large. Please try with a smaller image or compress the existing one." | |
| else: | |
| yield f"An error occurred: {str(e)}" | |
| demo = gr.ChatInterface( | |
| fn=bot_streaming, | |
| title="Meta Llama-3.2-90B-Vision-Instruct-Turbo", | |
| textbox=gr.MultimodalTextbox(), | |
| additional_inputs=[ | |
| gr.Slider( | |
| minimum=10, | |
| maximum=500, | |
| value=250, | |
| step=10, | |
| label="Maximum number of new tokens to generate", | |
| ), | |
| gr.Textbox( | |
| label="Together API Key (optional)", | |
| placeholder="Enter your API key here. (optional)", | |
| ) | |
| ], | |
| cache_examples=False, | |
| description="Try Multimodal Llama by Meta with the Together API in this demo. Upload an image, and start chatting about it. You can provide your own API key or use the default one.", | |
| stop_btn="Stop Generation", | |
| fill_height=True, | |
| multimodal=True | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch(debug=True) |