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Update app.py
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app.py
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# Autors: [Escriu aquí el teu nom] i [nom del company si en teniu]
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# Pràctica 26/05/2025 - Agent amb eines noves: traductor i resumidor
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# Instal·lació automàtica de llibreries al principi
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import subprocess
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import sys
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def install(package):
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subprocess.check_call([sys.executable, "-m", "pip", "install", package])
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# Instalar
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install("
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install("transformers")
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install("langchain")
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install("sentencepiece")
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#
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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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@@ -22,13 +23,17 @@ 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 langchain.tools import Tool
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#
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from deep_translator import GoogleTranslator
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def translate_text(text: str) -> str:
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translate_tool = Tool(
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name="TextTranslator",
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description="Translate input text to English. Input can be in any language."
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)
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#
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from transformers import pipeline
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def summarize_text(text: str) -> str:
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-
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summarize_tool = Tool(
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name="TextSummarizer",
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description="Summarize input text. Use it for long paragraphs or documents."
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)
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#
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@tool
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def my_custom_tool(arg1: str, arg2: int) -> str:
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"""A tool that does nothing yet
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Args:
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arg1: the first argument
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arg2: the second argument
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"""
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return "What magic will you build?"
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# Eina 4: Consultar l'hora en una zona horària
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@tool
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def get_current_time_in_timezone(timezone: str) -> str:
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"""
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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
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#
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final_answer = FinalAnswerTool()
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# Model LLM
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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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image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
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#
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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 amb totes les eines
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agent = CodeAgent(
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model=model,
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tools=[
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translate_tool,
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summarize_tool,
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my_custom_tool,
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get_current_time_in_timezone,
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image_generation_tool,
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final_answer
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prompt_templates=prompt_templates
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)
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#
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GradioUI(agent).launch()
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# Autors: [Escriu aquí el teu nom] i [nom del company si en teniu]
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# Pràctica 26/05/2025 - Agent amb eines noves: traductor i resumidor
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# 1. Instal·lació automàtica de llibreries (al principi del fitxer)
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import subprocess
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import sys
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def install(package):
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subprocess.check_call([sys.executable, "-m", "pip", "install", package])
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# Instalar primero las dependencias pesadas
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install("torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu")
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install("transformers")
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install("deep-translator")
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install("langchain")
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install("sentencepiece")
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# 2. Importaciones después de las instalaciones
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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 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 langchain.tools import Tool
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# 3. Configuración del traductor (no requiere PyTorch/TensorFlow)
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from deep_translator import GoogleTranslator
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def translate_text(text: str) -> str:
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"""Traduce texto a inglés usando Google Translate"""
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try:
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return GoogleTranslator(source='auto', target='en').translate(text)
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except Exception as e:
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return f"Error en traducción: {str(e)}"
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translate_tool = Tool(
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name="TextTranslator",
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description="Translate input text to English. Input can be in any language."
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)
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# 4. Configuración alternativa del resumidor (sin PyTorch/TensorFlow)
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from transformers import pipeline
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try:
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# Intentamos cargar un modelo pequeño que pueda funcionar sin GPU
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summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
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except:
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# Fallback a una implementación más simple si falla
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def simple_summarizer(text: str) -> str:
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"""Resumen básico tomando las primeras oraciones"""
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sentences = text.split('.')
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return '. '.join(sentences[:3]) + '.' if len(sentences) > 3 else text
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summarizer = simple_summarizer
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def summarize_text(text: str) -> str:
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try:
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if callable(summarizer):
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summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
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return summary[0]['summary_text'] if isinstance(summary, list) else summary
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return summarizer(text)
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except Exception as e:
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return f"Error en resumen: {str(e)}"
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summarize_tool = Tool(
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name="TextSummarizer",
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description="Summarize input text. Use it for long paragraphs or documents."
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)
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# 5. Herramientas adicionales
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@tool
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def get_current_time_in_timezone(timezone: str) -> str:
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"""Obtiene la hora actual en una zona horaria específica"""
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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: {str(e)}"
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# 6. Configuración del agente
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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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custom_role_conversions=None,
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)
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try:
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image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
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except:
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@tool
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def image_generation_tool(prompt: str) -> str:
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return "Image generation disabled in this environment"
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# 7. Carga de plantillas y creación del agente
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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=[
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translate_tool,
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summarize_tool,
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get_current_time_in_timezone,
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image_generation_tool,
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final_answer
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prompt_templates=prompt_templates
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)
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# 8. Iniciar la interfaz
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GradioUI(agent).launch()
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