import os import gradio as gr import modelscope_gradio_components as mgr from modelscope_gradio_components.components.Chatbot.llm_thinking_presets import \ qwen def resolve_assets(relative_path): return os.path.join(os.path.dirname(__file__), "../resources", relative_path) conversation = [ [ None, { "text": f""" 标签语法: ```json {{"text": "风和日丽", "resolution": "1024*1024"}} ``` qwen preset: Action: image_gen Action Input: {{"text": "风和日丽", "resolution": "1024*1024"}} Observation: ![IMAGEGEN]({resolve_assets("screen.jpeg")}) 根据您的描述"风和日丽",我生成了一张图片。![]({resolve_assets("screen.jpeg")}) Action: 「任意文本表示,将展示为思考链调用的名称」 Action Input: 「任意json or md 内容,将展示到调用过程的下拉框」 Observation: 「任意 md 内容,将作为完成调用的展示的下拉框内」 """, "flushing": False } ], ] with gr.Blocks() as demo: mgr.Chatbot( value=conversation, llm_thinking_presets=[qwen()], height=600, ) if __name__ == "__main__": demo.queue().launch()