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Update app.py
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app.py
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from smolagents import CodeAgent,
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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 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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"""
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Args:
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"""
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return f"Error fetching time for timezone '{timezone}': {str(e)}"
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# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
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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, HfApiModel, load_tool, tool
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import yaml
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import datetime
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from tools.final_answer import FinalAnswerTool
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from Gradio_UI import GradioUI
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# Tool to calculate BMI and provide health feedback
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@tool
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def calculate_bmi(weight: float, height: float) -> str:
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"""Calculates BMI and provides a health status.
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Args:
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weight: Weight in kilograms.
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height: Height in meters.
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"""
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if height <= 0 or weight <= 0:
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return "Invalid input. Please enter positive values for weight and height."
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bmi = weight / (height ** 2)
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status = ""
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if bmi < 18.5:
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status = "underweight"
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elif 18.5 <= bmi < 24.9:
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status = "normal weight"
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elif 25 <= bmi < 29.9:
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status = "overweight"
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else:
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status = "obese"
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return f"Your BMI is {bmi:.2f}, which is considered {status}."
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# Tool to analyze symptoms and suggest possible diseases
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@tool
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def analyze_symptoms(symptoms: str) -> str:
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"""Analyzes symptoms and suggests possible diseases.
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Args:
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symptoms: A comma-separated list of symptoms.
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"""
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symptom_disease_mapping = {
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"fever, cough": "Possible Flu or COVID-19",
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"headache, nausea": "Possible Migraine or Food Poisoning",
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"chest pain, shortness of breath": "Possible Heart Disease - Seek immediate medical help!",
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"fatigue, weight loss": "Possible Thyroid Issues or Diabetes",
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"stomach pain, diarrhea": "Possible Food Poisoning or Gastroenteritis"
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}
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for key, disease in symptom_disease_mapping.items():
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if all(symptom in symptoms.lower() for symptom in key.split(", ")):
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return f"Based on your symptoms ({symptoms}), you may have: {disease}. Consult a doctor for a proper diagnosis."
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return "I'm not sure. Please consult a healthcare professional."
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# Load model
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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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)
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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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# Define Agent
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agent = CodeAgent(
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model=model,
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tools=[final_answer, calculate_bmi, analyze_symptoms], # Added tools here
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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="HealthcareBot",
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description="A healthcare assistant that calculates BMI and suggests potential diseases based on symptoms.",
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prompt_templates=prompt_templates
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)
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# Launch Gradio UI
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GradioUI(agent).launch()
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