Update app.py

app.py

@@ -1,85 +1,93 @@
-from smolagents import CodeAgent, HfApiModel, tool
+from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool
+import datetime
+import requests
+import pytz
 import yaml
-import gradio as gr
-
-def classify_incident(service_criticity: str, disruption: str, affectation_time: str, magnitude: str, workaround: str) -> str:
-    """Classifies an incident based on predefined rules."""
-    if service_criticity == "High" and disruption == "Full":
-        return "P1"  # Critical issue
-    elif service_criticity == "High" and (disruption == "Degraded" or affectation_time == "Up 15 mins"):
-        return "P2"
-    elif service_criticity == "Low" and magnitude == "Low" and workaround == "Yes":
-        return "P4"
+
+from tools.final_answer import FinalAnswerTool
+from Gradio_UI import GradioUI
+
+ # Herramienta para clasificar alertas P1, P2, P3 basado en criterios de la tabla
+
+
+
+@tool
+def classify_alert(service_criticity: str, disruption: str, affectation_time: str, magnitude: str, business_workaround: str) -> str:
+    """Clasifica una alerta en P1, P2 o P3 según los criterios especificados.
+    Args:
+        service_criticity: 'High' o 'Low'
+        disruption: 'Full', 'Degraded', 'None'
+        affectation_time: 'Up 15 mins' o 'Less 15 mins'
+        magnitude: 'High', 'Low', 'None'
+        business_workaround: 'Yes' o 'No'
+    """
+    if service_criticity == "High" and disruption in ["Full", "Degraded"] and magnitude == "High" and business_workaround == "No":
+        return "P1 - Crítico"
+    elif service_criticity == "High" and (disruption in ["Full", "Degraded"] or affectation_time == "Up 15 mins"):
+        return "P2 - Importante"
     else:
-        return "P3"  # Default priority
+        return "P3 - Menor"
+
+
+
+
 
+ # Herramienta para generar resúmenes de reportes de infraestructura
 @tool
-def diagnose_incident(
-    service_criticity: str, 
-    disruption: str, 
-    affectation_time: str, 
-    magnitude: str, 
-    workaround: str
-) -> str:
-    """Determines the severity priority of an incident.
-    
-    Parameters:
-        service_criticity (str): High or Low.
-        disruption (str): Full, Degraded, or None.
-        affectation_time (str): Up 15 mins, Less 15 mins.
-        magnitude (str): High, Low, or None.
-        workaround (str): Yes or No.
-    
-    Returns:
-        str: The classified priority of the incident.
+def summarize_report(report_text: str) -> str:
+    """Genera un resumen de un reporte sobre la infraestructura de la plataforma.
+    Args:
+        report_text: Texto del reporte.
     """
-    priority = classify_incident(service_criticity, disruption, affectation_time, magnitude, workaround)
-    return f"Incident classified as priority: {priority}"
-
-# Load model with optimized settings
-model = HfApiModel(
-    max_tokens=512,  # Reduce max tokens to improve response time
-    temperature=0.3,  # Lower temperature for more deterministic results
-    model_id='Qwen/Qwen2.5-Coder-32B-Instruct'
+    api_url = "https://api-inference.huggingface.co/models/facebook/bart-large-cnn"
+    headers = {"Authorization": "Bearer YOUR_HF_API_KEY"}
+    payload = {"inputs": report_text}
+    
+    response = requests.post(api_url, headers=headers, json=payload)
+    if response.status_code == 200:
+        return response.json()[0]['summary_text']
+    else:
+        return "Error al generar el resumen."
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ final_answer = FinalAnswerTool()
+
+     custom_role_conversions=None,
 )
 
-# Load prompt templates
-with open("prompts.yaml", 'r') as stream:
-    prompt_templates = yaml.safe_load(stream)
+ image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
 
-# Create agent
+ with open("prompts.yaml", 'r') as stream:
+    prompt_templates = yaml.safe_load(stream)
+    
 agent = CodeAgent(
     model=model,
-    tools=[diagnose_incident],
-    max_steps=3,  # Reduce steps to minimize latency
-    verbosity_level=0,  # Lower verbosity for efficiency
-    name="Incident Diagnosis Agent",
-    description="An agent that classifies incidents based on severity criteria.",
+    tools=[final_answer, classify_alert, summarize_report],
+    max_steps=6,
+    verbosity_level=1,
+    grammar=None,
+    planning_interval=None,
+    name=None,
+    description=None,
     prompt_templates=prompt_templates
 )
 
-def chat_diagnose_incident(service_criticity, disruption, affectation_time, magnitude, workaround):
-    """Diagnoses an incident based on user inputs."""
-    priority = diagnose_incident(service_criticity, disruption, affectation_time, magnitude, workaround)
-    return f"Agent: El incidente se clasifica como prioridad {priority}."
-
-# Gradio UI
-iface = gr.Interface(
-    fn=chat_diagnose_incident,
-    inputs=[
-        gr.Dropdown(["High", "Low"], label="Criticidad del servicio"),
-        gr.Dropdown(["Full", "Degraded", "None"], label="Interrupción"),
-        gr.Dropdown(["Up 15 mins", "Less 15 mins"], label="Tiempo de afectación"),
-        gr.Dropdown(["High", "Low", "None"], label="Magnitud"),
-        gr.Dropdown(["Yes", "No"], label="¿Hay workaround?"),
-    ],
-    outputs=gr.Textbox(),
-    title="Asistente de Diagnóstico de Incidentes",
-    description="Selecciona las opciones para diagnosticar el incidente.",
-    theme="default"
-)
-
-# Lanzar UI
-if __name__ == "__main__":
-    iface.launch()
-
+ GradioUI(agent).launch()