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| import gradio as gr | |
| from agents import init_agent | |
| agent=init_agent() | |
| def run_agent(query): | |
| # Assuming the agent has a method to run a query | |
| response=agent.run(query,reset=False) | |
| if isinstance(response, list): | |
| response="\n".join(response) | |
| return response | |
| query_input = gr.Textbox( | |
| label="Query", | |
| placeholder="Enter your query here...", | |
| lines=3, | |
| max_lines=5 | |
| ) | |
| output=gr.TextArea( | |
| label="Response", | |
| placeholder="The response will appear here...", | |
| lines=10, | |
| max_lines=20 | |
| ) | |
| demo = gr.Interface( | |
| fn=run_agent, | |
| inputs=query_input, | |
| outputs=output, | |
| title="AtlasIA Assistant", | |
| description="Ask me anything and I'll help you find the information you need.", | |
| theme=gr.themes.Soft(), | |
| examples=[ | |
| ["names of datasets with image modality"], | |
| ["what is the most 3 liked datasets"], | |
| ["find the most downloaded model"], | |
| ["Who are the members of Atlasia?"], | |
| ["what is atlasIA community in 3 lines??"], | |
| ["how i can join the community?"], | |
| ["how i can contribute to the community?"] | |
| ], | |
| cache_examples=True, | |
| flagging_mode="never", | |
| css=""" | |
| .gradio-container { | |
| max-width: 800px; | |
| margin: auto; | |
| } | |
| .gradio-interface { | |
| padding: 2rem; | |
| } | |
| .output-text { | |
| white-space: pre-wrap; | |
| font-family: 'Courier New', monospace; | |
| background-color: #f5f5f5; | |
| padding: 1rem; | |
| border-radius: 5px; | |
| border: 1px solid #ddd; | |
| } | |
| .input-text { | |
| font-size: 1.1em; | |
| } | |
| .title { | |
| font-size: 2em; | |
| font-weight: bold; | |
| margin-bottom: 1rem; | |
| } | |
| .description { | |
| font-size: 1.2em; | |
| color: #666; | |
| margin-bottom: 2rem; | |
| } | |
| """ | |
| ) | |
| if __name__=="__main__": | |
| # Initialize the agent | |
| demo.launch() | |