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Update app.py
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app.py
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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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import pytz
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import yaml
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from tools.final_answer import FinalAnswerTool
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from Gradio_UI import GradioUI
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#
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@tool
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def
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"""A tool that does nothing yet
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Args:
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"""
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@tool
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def
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"""A tool that
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Args:
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"""
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try:
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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
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# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud'
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model = HfApiModel(
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max_tokens=2096,
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temperature=0.5,
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model_id='Qwen/Qwen2.5-Coder-32B-Instruct'
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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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with open("prompts.yaml", 'r') as stream:
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prompt_templates = yaml.safe_load(stream)
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agent = CodeAgent(
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model=model,
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tools=[final_answer
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max_steps=6,
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verbosity_level=1,
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grammar=None,
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planning_interval=None,
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name=
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description=
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prompt_templates=prompt_templates
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)
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GradioUI(agent).launch()
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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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import pytz
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import yaml
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from tools.final_answer import FinalAnswerTool
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from Gradio_UI import GradioUI
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from transformers import pipeline
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from geopy.distance import geodesic
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# Strumento per la traduzione
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@tool
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def translate_text(text: str, target_lang: str) -> str:
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"""A tool that translates text into the specified language.
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Args:
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text: The text to translate.
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target_lang: The target language code (e.g., 'en', 'fr', 'de').
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"""
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try:
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translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-{target_lang}")
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translated_text = translator(text)[0]['translation_text']
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return translated_text
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except Exception as e:
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return f"Error in translation: {str(e)}"
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# Strumento per calcolare la distanza tra due coordinate GPS
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@tool
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def calculate_distance(coord1: str, coord2: str) -> str:
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"""A tool that calculates the distance between two GPS coordinates.
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Args:
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coord1: The first coordinate in 'lat,lon' format.
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coord2: The second coordinate in 'lat,lon' format.
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"""
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try:
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lat1, lon1 = map(float, coord1.split(','))
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lat2, lon2 = map(float, coord2.split(','))
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distance_km = geodesic((lat1, lon1), (lat2, lon2)).kilometers
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return f"The distance between {coord1} and {coord2} is {distance_km:.2f} km."
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except Exception as e:
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return f"Error calculating distance: {str(e)}"
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# Strumento per analisi del sentimento
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@tool
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def analyze_sentiment(text: str) -> str:
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"""A tool that analyzes the sentiment of a given text.
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Args:
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text: The text to analyze.
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"""
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try:
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sentiment_analyzer = pipeline("sentiment-analysis")
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result = sentiment_analyzer(text)[0]
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return f"Sentiment: {result['label']} (Confidence: {result['score']:.2f})"
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except Exception as e:
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return f"Error in sentiment analysis: {str(e)}"
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# Strumento per generare testo creativo
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@tool
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def generate_creative_text(prompt: str) -> str:
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"""A tool that generates creative text based on a given prompt.
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Args:
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prompt: The input prompt for text generation.
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"""
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try:
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generator = pipeline("text-generation", model="gpt2")
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response = generator(prompt, max_length=100, num_return_sequences=1)
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return response[0]['generated_text']
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except Exception as e:
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return f"Error in text generation: {str(e)}"
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# Strumento per ottenere il meteo attuale
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@tool
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def get_weather(city: str) -> str:
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"""A tool that fetches the current weather for a specified city.
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Args:
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city: The city name.
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"""
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try:
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api_key = "YOUR_OPENWEATHER_API_KEY"
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url = f"https://api.openweathermap.org/data/2.5/weather?q={city}&appid={api_key}&units=metric"
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response = requests.get(url).json()
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weather = response['weather'][0]['description']
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temp = response['main']['temp']
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return f"Current weather in {city}: {weather}, {temp}°C."
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except Exception as e:
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return f"Error fetching weather: {str(e)}"
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final_answer = FinalAnswerTool()
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model = HfApiModel(
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max_tokens=2096,
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temperature=0.5,
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model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
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custom_role_conversions=None,
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)
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image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
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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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agent = CodeAgent(
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model=model,
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tools=[final_answer, translate_text, calculate_distance, analyze_sentiment, generate_creative_text, get_weather],
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max_steps=6,
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verbosity_level=1,
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grammar=None,
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planning_interval=None,
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name="AdvancedCodeAgent",
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description="An enhanced AI agent with additional capabilities.",
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prompt_templates=prompt_templates
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)
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GradioUI(agent).launch()
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