Create app.py

app.py

@@ -0,0 +1,73 @@
+import gradio as gr
+import aiohttp
+
+async def fetch(session, url, context, question):
+    payload = {
+        "context": context,
+        "question": question
+    }
+    async with session.post(url, json=payload) as response:
+        response.raise_for_status()
+        data = await response.json()
+        result = data.get("result", "No result")
+        inference_time = data.get("inference_time", 0)
+        return result, f"{inference_time:.2f} seconds"
+
+async def send_message(context, question, url):
+    async with aiohttp.ClientSession() as session:
+        result, time = await fetch(session, url, context, question)
+    return result, time
+
+async def send_to_qwen(context, question):
+    url = "https://qwen.nexaai.com/inference"
+    return await send_message(context, question, url)
+
+async def send_to_dolphin(context, question):
+    url = "https://dolphin.nexaai.com/inference"
+    return await send_message(context, question, url)
+
+predefined_questions = [
+    "Tell me where the Nexa AI office is?",
+    "Tell me who founded Nexa AI?",
+    "Tell me what Nexa AI is famous for?",
+    "Tell me what is the mission of Nexa AI?"
+]
+
+default_context = """Nexa AI is a Cupertino-based company founded in May 2023 that researches and develops models and tools for on-device AI applications. The company is founded by Alex and Zack. The company is known for its Octopus-series models, which rival large-scale language models in capabilities such as function-calling, multimodality, and action-planning, while remaining efficient and compact for edge device deployment. Nexa AI's mission is to advance on-device AI in collaboration with the global developer community. To this end, the company has created an on-device model hub for users to find, share, and collaborate on open-source AI models optimized for edge devices, as well as an SDK for developers to run and deploy AI models locally."""
+
+with gr.Blocks() as demo:
+    gr.Markdown("# AI Inference Comparison")
+
+    context = gr.Textbox(value=default_context, label="Background Context", lines=5)
+    question_dropdown = gr.Dropdown(choices=predefined_questions, label="Select a question")
+    custom_question = gr.Textbox(placeholder="Or enter your custom question here...", label="Custom Question")
+
+    with gr.Row():
+        output1 = gr.Textbox(label="Output from Qwen Model", interactive=False)
+        output2 = gr.Textbox(label="Output from Dolphin Model", interactive=False)
+    with gr.Row():
+        total_time1 = gr.Textbox(label="Total Time for Qwen Model", interactive=False)
+        total_time2 = gr.Textbox(label="Total Time for Dolphin Model", interactive=False)
+
+    def update_custom_question(choice):
+        return choice
+
+    question_dropdown.change(update_custom_question, inputs=question_dropdown, outputs=custom_question)
+
+    with gr.Row():
+        send_qwen_button = gr.Button("Send to Qwen")
+        send_dolphin_button = gr.Button("Send to Dolphin")
+
+    send_qwen_button.click(
+        send_to_qwen, 
+        inputs=[context, custom_question], 
+        outputs=[output1, total_time1]
+    )
+
+    send_dolphin_button.click(
+        send_to_dolphin, 
+        inputs=[context, custom_question], 
+        outputs=[output2, total_time2]
+    )
+
+demo.launch()