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Update app.py
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app.py
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@@ -1,12 +1,15 @@
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import gradio as gr
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from huggingface_hub import InferenceClient
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import os # For environment variables
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# Initialize the Hugging Face Inference Client
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client = InferenceClient()
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#
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def generate_response(prompt_template, **kwargs):
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prompt = os.getenv(prompt_template).format(**kwargs)
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response = client.chat.completions.create(
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model="Qwen/Qwen2.5-Math-1.5B-Instruct",
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@@ -15,12 +18,13 @@ def generate_response(prompt_template, **kwargs):
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max_tokens=1024,
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top_p=0.8
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)
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-
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# Gradio app interface
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with gr.Blocks() as app:
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gr.Markdown("## Mathematical Insight Tutor")
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gr.Markdown("An advanced AI-powered tutor to help you master math concepts with step-by-step explanations
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def create_tab(tab_name, prompt_template, inputs):
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with gr.Tab(tab_name):
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@@ -105,4 +109,4 @@ app.css = """
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"""
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# Launch the app
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app.launch(debug=True)
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import gradio as gr
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from huggingface_hub import InferenceClient
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import os # For environment variables
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import time # To simulate processing time if needed
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# Initialize the Hugging Face Inference Client
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client = InferenceClient()
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# Function to generate and format AI response
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def generate_response(prompt_template, **kwargs):
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# Simulate processing/loading
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time.sleep(1) # Optional: Remove or adjust based on actual execution time
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prompt = os.getenv(prompt_template).format(**kwargs)
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response = client.chat.completions.create(
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model="Qwen/Qwen2.5-Math-1.5B-Instruct",
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max_tokens=1024,
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top_p=0.8
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)
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response_content = response.choices[0].message["content"]
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return gr.update(value=f"${response_content}$")
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# Gradio app interface
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with gr.Blocks() as app:
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gr.Markdown("## Mathematical Insight Tutor")
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gr.Markdown("An advanced AI-powered tutor to help you master math concepts with step-by-step explanations.")
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def create_tab(tab_name, prompt_template, inputs):
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with gr.Tab(tab_name):
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"""
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# Launch the app
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app.launch(debug=True)
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