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Create app.py
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app.py
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import os
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import gradio as gr
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from smolagents import CodeAgent, DuckDuckGoSearchTool, InferenceClientModel, tool
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# ============================================
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# CUSTOM TOOLS FOR ALFRED
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# ============================================
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@tool
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def calculator(operation: str) -> str:
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"""
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Performs basic math calculations.
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Args:
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operation: A math expression like "2 + 2" or "10 * 5"
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Returns:
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The result of the calculation as a string
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"""
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try:
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allowed_chars = set('0123456789+-*/(). ')
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if all(c in allowed_chars for c in operation):
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result = eval(operation)
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return f"The result of {operation} is: {result}"
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else:
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return "Invalid operation. Please use only numbers and basic operators."
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except Exception as e:
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return f"Could not calculate. Error: {str(e)}"
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@tool
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def get_current_time() -> str:
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"""
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Gets the current date and time in UTC.
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Returns:
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The current date and time as a string
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"""
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from datetime import datetime
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now = datetime.utcnow()
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return f"Current date and time (UTC): {now.strftime('%Y-%m-%d %H:%M:%S')}"
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@tool
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def get_weather_info(city: str) -> str:
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"""
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Gets a simple weather description for a city (mock data for demo).
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Args:
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city: The name of the city to get weather for
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Returns:
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A weather description string
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"""
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# This is mock data - in production you'd use a real weather API
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import random
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conditions = ["sunny", "partly cloudy", "cloudy", "rainy", "windy"]
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temp = random.randint(15, 30)
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condition = random.choice(conditions)
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return f"Weather in {city}: {temp}°C, {condition}"
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# ============================================
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# MODEL SETUP - Using free-tier compatible model
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# ============================================
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model = InferenceClientModel(
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model_id="Qwen/Qwen2.5-7B-Instruct", # Smaller model that works on free tier
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token=os.environ.get("HF_TOKEN"),
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)
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# ============================================
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# ALFRED AGENT SETUP
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# ============================================
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alfred = CodeAgent(
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tools=[
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DuckDuckGoSearchTool(),
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calculator,
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get_current_time,
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get_weather_info,
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],
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model=model,
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max_steps=5,
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verbosity_level=1,
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)
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# ============================================
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# CHAT FUNCTION
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# ============================================
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def chat_with_alfred(message, history):
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"""
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Process user message and return Alfred's response.
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"""
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if not message.strip():
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return "Please ask me something. How may I assist you today?"
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try:
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response = alfred.run(message)
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return str(response)
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except Exception as e:
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error_msg = str(e)
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# Provide helpful error messages
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if "404" in error_msg or "not found" in error_msg.lower():
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return "I'm having trouble connecting to my AI backend. Please check the HF_TOKEN and model availability."
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elif "rate" in error_msg.lower() or "limit" in error_msg.lower():
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return "I've hit a rate limit. Please wait a moment and try again."
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else:
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return f"I encountered an issue: {error_msg}"
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# ============================================
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# GRADIO INTERFACE
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# ============================================
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with gr.Blocks(title="Alfred - AI Butler Agent") as demo:
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gr.Markdown(
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"""
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# 🎩 Alfred - Your AI Butler
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Good day! I am Alfred, your personal AI assistant. I am at your service.
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### My Capabilities:
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- 🔍 **Web Search** - I can search the internet for information
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- 🧮 **Calculator** - I can perform mathematical calculations
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- 🕐 **Current Time** - I can tell you the current time (UTC)
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- 🌤️ **Weather** - I can provide weather information
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---
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"""
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)
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chatbot = gr.ChatInterface(
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fn=chat_with_alfred,
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examples=[
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"What is artificial intelligence?",
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"Calculate 25 * 4 + 10",
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"What time is it now?",
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"What's the weather in London?",
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"Search for the latest news about AI",
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"Calculate (100 + 50) * 2 / 5",
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],
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)
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gr.Markdown(
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"""
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---
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*Built with [smolagents](https://github.com/huggingface/smolagents) and Gradio | Unit 1 Project*
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"""
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)
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# ============================================
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# LAUNCH APP
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# ============================================
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if __name__ == "__main__":
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demo.launch()
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