Create agent.py

agent.py

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+from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
+import datetime
+import requests
+import pytz
+import yaml
+from tools.final_answer import FinalAnswerTool
+
+from Gradio_UI import GradioUI
+
+# Below is an example of a tool that does nothing. Amaze us with your creativity !
+# @tool
+# def my_custom_tool(arg1:str, arg2:int)-> str: #it's import to specify the return type
+#     #Keep this format for the description / args / args description but feel free to modify the tool
+#     """A tool that does nothing yet 
+#     Args:
+#         arg1: the first argument
+#         arg2: the second argument
+#     """
+#     return "What magic will you build ?"
+
+
+def __init__(self):
+    self.patient_data = {}
+
+@tool
+def collect_symptoms(patient_id: str, symptoms: str) -> str:
+    """
+    Nurse tool to collect symptoms and ask follow-up questions.
+    Args:
+        patient_id: Unique identifier for the patient.
+        symptoms: Initial symptoms provided by the patient.
+    Returns:
+        Follow-up questions based on the symptoms.
+    """
+    try:
+        if not patient_id or not symptoms:
+            raise ValueError("Patient ID and symptoms must be provided.")
+
+        self.patient_data[patient_id] = {"symptoms": symptoms, "additional_info": {}}
+
+        questions = [
+            "How long have you had these symptoms?",
+            "Do you have any allergies?",
+            "Are you taking any medications?",
+            "Have you experienced these symptoms before?",
+            "Have you had any recent illnesses?",
+            "Have you noticed any other unusual changes?",
+            "What is your medical history related to these symptoms?"
+            
+        ]
+
+        return f"Nurse: I have noted the symptoms ({symptoms}). Here are follow-up questions:\n" + "\n".join(questions)
+
+    except ValueError as e:
+        return f"Error: {str(e)}"
+    except Exception as e:
+        return f"Unexpected Error: {str(e)}"
+
+@tool
+def diagnose_patient(patient_id: str) -> str:
+    """
+    Doctor tool to diagnose the patient based on symptoms.
+    
+    Args:
+        patient_id: Unique identifier for the patient.
+        
+    Returns:
+        Diagnosis and recommendations.
+    """
+    try:
+        if patient_id not in CodeAgent.patient_data:
+            raise ValueError("No symptoms found. Nurse must collect symptoms first.")
+
+        symptoms = CodeAgent.patient_data[patient_id]["symptoms"]
+        diagnosis = CodeAgent.fetch_diagnosis(symptoms)
+        medication = CodeAgent.fetch_medication(symptoms)
+        advice = CodeAgent.fetch_treatment_advice(symptoms)
+
+        return (f"Doctor: Based on the symptoms: {symptoms},\n"
+                f"Diagnosis: {diagnosis}\n"
+                f"Medication: {medication}\n"
+                f"Advice: {advice}")
+
+    except ValueError as e:
+        return f"Error: {str(e)}"
+    except Exception as e:
+        return f"Unexpected Error: {str(e)}"
+
+
+@tool
+def fetch_diagnosis(symptoms: str) -> str:
+    """
+    AI tool to retrieve a diagnosis based on symptoms.
+    Args:
+        symptoms: The symptoms provided by the patient.
+    Returns:
+        Detailed Diagnosis information.
+    """
+    search_query = f" A detailed medical diagnosis for this {symptoms}"
+    return search_tool(search_query)
+    try:
+        if not symptoms:
+            raise ValueError("Symptoms must be provided.")
+
+        return f"AI Diagnosis: Potential cause of {symptoms} found."
+
+    except ValueError as e:
+        return f"Error: {str(e)}"
+    except Exception as e:
+        return f"Unexpected Error: {str(e)}"
+
+@tool
+def fetch_medication(symptoms: str) -> str:
+    """
+    AI tool to suggest medications based on symptoms.
+    Args:
+        symptoms: The symptoms provided by the patient.
+    Returns:
+        Suggested medication.
+    """
+    search_query = f" A detailed suggested medication for this {symptoms}"
+    return search_tool(search_query)
+    try:
+        if not symptoms:
+            raise ValueError("Symptoms must be provided.")
+
+        return f"Suggested medication for {symptoms} found."
+
+    except ValueError as e:
+        return f"Error: {str(e)}"
+    except Exception as e:
+        return f"Unexpected Error: {str(e)}"
+
+@tool
+def fetch_treatment_advice(symptoms: str) -> str:
+    """
+    AI tool to provide treatment recommendations.
+    Args:
+        symptoms: The symptoms provided by the patient.
+    Returns:
+        Recommended treatment and advice.
+    """
+    search_query = f" A detailed recommended treatment and advice for this {symptoms}"
+    return search_tool(search_query)
+    try:
+        if not symptoms:
+            raise ValueError("Symptoms must be provided.")
+
+        return f"Treatment advice for {symptoms} retrieved."
+
+    except ValueError as e:
+        return f"Error: {str(e)}"
+    except Exception as e:
+        return f"Unexpected Error: {str(e)}"
+        
+search_tool = DuckDuckGoSearchTool()
+
+@tool
+def get_current_time_in_timezone(timezone: str) -> str:
+    """A tool that fetches the current local time in a specified timezone.
+    Args:
+        timezone: A string representing a valid timezone (e.g., 'America/New_York').
+    """
+    try:
+        # Create timezone object
+        tz = pytz.timezone(timezone)
+        # Get current time in that timezone
+        local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
+        return f"The current local time in {timezone} is: {local_time}"
+    except Exception as e:
+        return f"Error fetching time for timezone '{timezone}': {str(e)}"
+
+
+final_answer = FinalAnswerTool()
+
+# 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:
+# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 
+
+model = HfApiModel(
+max_tokens=2096,
+temperature=0.5,
+model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded
+custom_role_conversions=None,
+)
+
+
+# Import tool from Hub
+image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
+
+with open("prompts.yaml", 'r') as stream:
+    prompt_templates = yaml.safe_load(stream)
+    
+agent = CodeAgent(
+    model=model,
+    tools=[final_answer, collect_symptoms, diagnose_patient, get_current_time_in_timezone], ## add your tools here (don't remove final answer)
+    max_steps=6,
+    verbosity_level=1,
+    grammar=None,
+    planning_interval=None,
+    name="MedicalDoctor",
+    description="A tool that simulates the roles of a medical doctor and a nurse in gathering symptoms, diagnosing, and providing recommendations",
+    prompt_templates=prompt_templates
+)