import gradio as gr import anthropic import base64 import httpx import os import time import random client = anthropic.Anthropic( # defaults to os.environ.get("ANTHROPIC_API_KEY") api_key="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", ) MODEL_NAME = "claude-3-opus-20240229" def print_like_dislike(x: gr.LikeData): print(x.index, x.value, x.liked) def add_message(history, message): if message["files"]: for x in message["files"]: with open(x, "rb") as image_file: binary_data = image_file.read() base_64_encoded_data = base64.b64encode(binary_data) base64_string = base_64_encoded_data.decode('utf-8') image_media_type = "image/png" # message["text"] = "What is present in the uploaded image" if message["text"] == None else message["text"] message_list = [{ "role": 'user',"content": [{"type": "image", "source": {"type": "base64", "media_type": image_media_type ,"data": base64_string}}, {"type": "text", "text": message["text"] } ]}] response = client.messages.create(model=MODEL_NAME, max_tokens=1024, messages=message_list).content[0].text history.append((x, response)) elif message["text"] is not None: response = client.messages.create( model=MODEL_NAME, max_tokens=1024, messages=[ {"role": "user", "content": message["text"]}] ).content[0].text history.append((message["text"], response)) return history, gr.MultimodalTextbox(value=None, interactive=False) def bot(history): response = history[-1][1] history[-1][1] = "" for character in response: history[-1][1] += character time.sleep(0.01) yield history with gr.Blocks() as demo: chatbot = gr.Chatbot( [], elem_id="chatbot", bubble_full_width=False, ) chat_input = gr.MultimodalTextbox(interactive=True, file_types=["image"], placeholder="Enter message or upload image file in png ...", show_label=True) chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input]) bot_msg = chat_msg.then(bot, chatbot, chatbot, api_name="bot_response") bot_msg.then(lambda: gr.MultimodalTextbox(interactive=True), None, [chat_input]) chatbot.like(print_like_dislike, None, None) demo.queue() demo.launch()