| import os |
| import platform |
| import signal |
| import sys |
|
|
| from transformers import AutoTokenizer, AutoModel |
| import readline |
|
|
| tokenizer = AutoTokenizer.from_pretrained("THUDM/visualglm-6b", trust_remote_code=True) |
| model = AutoModel.from_pretrained("THUDM/visualglm-6b", trust_remote_code=True).half().cuda() |
| model = model.eval() |
|
|
| os_name = platform.system() |
| clear_command = 'cls' if os_name == 'Windows' else 'clear' |
| stop_stream = False |
|
|
|
|
| def build_prompt(history, prefix): |
| prompt = prefix |
| for query, response in history: |
| prompt += f"\n\n用户:{query}" |
| prompt += f"\n\nChatGLM-6B:{response}" |
| return prompt |
|
|
|
|
| def signal_handler(signal, frame): |
| global stop_stream |
| stop_stream = True |
|
|
|
|
| def main(): |
| global stop_stream |
| while True: |
| history = [] |
| prefix = "欢迎使用 VisualGLM-6B 模型,输入图片路径和内容即可进行对话,clear 清空对话历史,stop 终止程序" |
| print(prefix) |
| image_path = input("\n请输入图片路径:") |
| if image_path == "stop": |
| break |
| prefix = prefix + "\n" + image_path |
| query = "描述这张图片。" |
| while True: |
| count = 0 |
| for response, history in model.stream_chat(tokenizer, image_path, query, history=history): |
| if stop_stream: |
| stop_stream = False |
| break |
| else: |
| count += 1 |
| if count % 8 == 0: |
| os.system(clear_command) |
| print(build_prompt(history, prefix), flush=True) |
| signal.signal(signal.SIGINT, signal_handler) |
| os.system(clear_command) |
| print(build_prompt(history, prefix), flush=True) |
| query = input("\n用户:") |
| if query.strip() == "clear": |
| break |
| if query.strip() == "stop": |
| sys.exit(0) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|