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import os
import gradio as gr
import modelscope_studio.components.base as ms
import modelscope_studio.components.legacy as mgr
from modelscope_studio.components.legacy.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"""
Use accordion tag:
<accordion title="Using tool">
```json
{{"text": "glorious weather", "resolution": "1024*1024"}}
```
</accordion>
Qwen preset:
Action: image_gen
Action Input: {{"text": "glorious weather", "resolution": "1024*1024"}}
Observation: <result>![IMAGEGEN]({resolve_assets("screen.jpeg")})</result> Based on your description"glorious weather",I generated a picture.![]({resolve_assets("screen.jpeg")})
Action: 「An arbitrary text representation that will be displayed as the name of the thought chain call」
Action Input: 「Any json or md content will be displayed in the drop-down box of the calling process」
Observation: <result>「Any md content will be displayed in the drop-down box when the call is completed」</result>
""",
"flushing": False
}
],
]
with gr.Blocks() as demo, ms.Application():
mgr.Chatbot(
value=conversation,
llm_thinking_presets=[qwen()],
height=600,
)
if __name__ == "__main__":
demo.queue().launch()
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