Update app.py
Browse filesfixing the weather agent request.
app.py
CHANGED
@@ -1,3 +1,4 @@
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from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool
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import datetime
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import requests
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@@ -7,6 +8,7 @@ from tools.final_answer import FinalAnswerTool
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from Gradio_UI import GradioUI
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from typing import Dict, Tuple, Optional
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def get_coordinates(city: str) -> Optional[Tuple[float, float]]:
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"""Get coordinates for any city using Open-Meteo Geocoding API."""
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try:
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@@ -22,6 +24,7 @@ def get_coordinates(city: str) -> Optional[Tuple[float, float]]:
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except Exception:
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return None
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@tool
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def get_weather(city: str) -> str:
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"""Get current weather information for a specified city.
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@@ -68,12 +71,138 @@ def get_weather(city: str) -> str:
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except Exception as e:
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return f"Error fetching weather data: {str(e)}"
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-
#
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final_answer = FinalAnswerTool()
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# Initialize the model
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model = HfApiModel(
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max_tokens=2096,
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temperature=0.5,
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@@ -81,16 +210,28 @@ model = HfApiModel(
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custom_role_conversions=None,
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)
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# Import tool from Hub
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image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
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# Load prompt templates
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with open("prompts.yaml", 'r') as stream:
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prompt_templates = yaml.safe_load(stream)
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# Initialize agent with all tools
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agent = CodeAgent(
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model=model,
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tools=[
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final_answer,
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get_weather,
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@@ -109,4 +250,5 @@ agent = CodeAgent(
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)
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# Launch Gradio UI
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# Import required libraries
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from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool
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import datetime
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import requests
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from Gradio_UI import GradioUI
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from typing import Dict, Tuple, Optional
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# Utility function for geocoding
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def get_coordinates(city: str) -> Optional[Tuple[float, float]]:
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"""Get coordinates for any city using Open-Meteo Geocoding API."""
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try:
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except Exception:
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return None
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# Tool 1: Weather Information
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@tool
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def get_weather(city: str) -> str:
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"""Get current weather information for a specified city.
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except Exception as e:
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return f"Error fetching weather data: {str(e)}"
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# Tool 2: Biking Conditions
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@tool
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def check_biking_conditions(city: str) -> str:
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"""Check if current weather conditions are good for biking in specified city.
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Args:
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city: Name of any city in the world
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Returns:
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str: Assessment of biking conditions based on weather
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"""
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try:
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coords = get_coordinates(city)
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if not coords:
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return f"Sorry, couldn't find coordinates for {city}."
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lat, lon = coords
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api_url = "https://api.open-meteo.com/v1/forecast"
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params = {
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"latitude": lat,
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"longitude": lon,
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"current": "temperature_2m,wind_speed_10m",
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"hourly": "temperature_2m,relative_humidity_2m,wind_speed_10m"
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}
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response = requests.get(api_url, params=params, timeout=10)
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if response.status_code == 200:
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data = response.json()
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current = data["current"]
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temp = current['temperature_2m']
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wind_speed = current['wind_speed_10m']
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# Assess conditions for biking
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conditions = []
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if wind_speed > 20:
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conditions.append(f"⚠️ Wind speeds are high ({wind_speed} km/h)")
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if temp < 10:
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conditions.append(f"🌡️ It's cold ({temp}°C) - dress warmly")
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elif temp > 30:
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conditions.append(f"🌡️ It's hot ({temp}°C) - stay hydrated")
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if conditions:
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return f"Biking conditions in {city}:\n" + "\n".join(conditions)
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else:
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return f"👍 Great conditions for biking in {city}! {temp}°C with moderate wind speeds."
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else:
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return f"Error checking conditions. Status code: {response.status_code}"
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except Exception as e:
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return f"Error checking biking conditions: {str(e)}"
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# Tool 3: Current Time in Timezone
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@tool
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def get_current_time_in_timezone(timezone: str) -> str:
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"""A tool that fetches the current local time in a specified timezone.
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Args:
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timezone: A string representing a valid timezone (e.g., 'America/New_York')
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"""
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try:
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tz = pytz.timezone(timezone)
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local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
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return f"The current local time in {timezone} is: {local_time}"
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except Exception as e:
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return f"Error fetching time for timezone '{timezone}': {str(e)}"
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# Mock trails data for dynamic trail suggestions
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MOCK_TRAILS = {
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"default_trails": [
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{
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"name": "{city} Riverside Path",
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"difficulty": "Easy",
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"length": "5.5 miles",
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"description": "Scenic waterfront trail perfect for casual rides",
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"features": ["Waterfront views", "Paved path", "Family-friendly"]
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},
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{
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"name": "{city} Urban Loop",
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"difficulty": "Moderate",
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"length": "8.2 miles",
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"description": "Popular city loop with diverse urban scenery",
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"features": ["City views", "Mixed terrain", "Cultural spots"]
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}
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]
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}
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# Tool 4: Bike Trails
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@tool
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def get_bike_trails(city: str) -> str:
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"""Get information about bike trails in a specified city.
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Args:
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city: Name of any city in the world
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Returns:
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str: Information about available bike trails
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"""
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# Generate dynamic trails for any city
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trails = []
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for trail_template in MOCK_TRAILS["default_trails"]:
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trail = {
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"name": trail_template["name"].format(city=city),
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"difficulty": trail_template["difficulty"],
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"length": trail_template["length"],
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"description": trail_template["description"],
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"features": trail_template["features"]
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}
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trails.append(trail)
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response = f"🚲 Suggested Bike Trails in {city}:\n\n"
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for trail in trails:
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response += (
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f"📍 {trail['name']}\n"
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f" • Difficulty: {trail['difficulty']}\n"
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f" • Length: {trail['length']}\n"
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f" • Description: {trail['description']}\n"
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f" • Features: {', '.join(trail['features'])}\n\n"
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)
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response += "(Note: These are suggested routes based on typical city features. Always verify local trails and conditions.)"
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return response
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# Initialize components
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final_answer = FinalAnswerTool()
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# Initialize the model
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model = HfApiModel(
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max_tokens=2096,
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temperature=0.5,
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custom_role_conversions=None,
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)
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# Import image generation tool from Hub
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image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
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# Example prompts.yaml content - save this in a file named prompts.yaml
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PROMPT_TEMPLATES = """
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default: |
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You are a helpful assistant that provides weather information and local activity suggestions.
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When someone asks about the weather, also consider suggesting bike trails and checking biking conditions.
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Always provide helpful context about weather conditions for outdoor activities.
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"""
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# Save prompts to file
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with open("prompts.yaml", 'w') as f:
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f.write(PROMPT_TEMPLATES)
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# Load prompt templates
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with open("prompts.yaml", 'r') as stream:
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prompt_templates = yaml.safe_load(stream)
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# Initialize agent with all tools
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agent = CodeAgent(
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model=model,
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tools=[
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final_answer,
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get_weather,
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)
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# Launch Gradio UI
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if __name__ == "__main__":
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GradioUI(agent).launch()
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