from openai import OpenAI
from django.conf import settings
from .models import Risk, Control
import time

def extract_organization_details(organization):
    excluded_fields = {"name", "email"}
    risk_data = {}

    for field in organization._meta.get_fields():
        if field.name not in excluded_fields and hasattr(organization, field.name):
            value = getattr(organization, field.name)
            if value:
                help_text = getattr(field, 'help_text', '').strip()
                key = help_text if help_text else field.name
                risk_data[key] = value
    return risk_data

def get_top_risk(organization):
    client = OpenAI(api_key=settings.OPENAI_API_KEY)

    all_risks = Risk.objects.all()

    risk_list = []
    for risk in all_risks:
        risk_list.append(f"""
        Risk ID: {risk.risk_id}
        Category: {risk.category}
        Name: {risk.risk_name}
        Primary Impact: {risk.primary_impact}
        Secondary Impact: {risk.secondary_impact}
        Tertiary Impact: {risk.tretiary_impact}
        Detection Difficulty: {risk.detection_difficulty}
        Recovery Complexity: {risk.recovery_complexity}
        Business Impact Severity: {risk.businnes_impact_severity}
        """)

    organization_details = extract_organization_details(organization)

    prompt = f"""
    You are an AI risk assessor. Based on the following company details and list of known risks,
    identify the 10 most critical risks for this company. Respond only with risk IDs.

    Company Details:
    {organization_details}

    List of Risks:
    {risk_list}

    Provide only the 10 most critical risk IDs in a simple comma-separated format, e.g "1,3,7,12,..."
    """

    response = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[{"role": "system", "content": prompt}]
    )

    risk_ids = response.choices[0].message.content.strip().split(",")
    print(f"Risks: {risk_ids}")

    return [int(risk_id) for risk_id in risk_ids if risk_id.isdigit()]

def get_controls_for_risk(risk, organization):
    client = OpenAI(api_key=settings.OPENAI_API_KEY)
    all_controls = Control.objects.all()
    control_list = []

    organization_details = extract_organization_details(organization)
    valid_control_ids = {control.id for control in all_controls}

    for control in all_controls:
        control_list.append(f"Control ID: {control.id}, Control Name: {control.name}")

    prompt = f"""
    You are an expert in cybersecurity risk management. Given the risk "{risk.risk_name}" and its associated factors "{organization_details}",
    your task is to select **exactly 10 unique controls** from the provided list that best mitigate this risk. Each control should be assigned a weight between **1 and 10** based on its effectiveness in reducing the risk.
    ### Rules:
    1. **Each control ID must be unique** (no duplicates).
    2. **Only return control IDs and weights** in the exact format below.
    3. **Weights must be between 1 and 10** (1 = low impact, 10 = high impact).
    4. **Do NOT add explanations, descriptions, or extra text.**
    5. **Ensure that control IDs are randomly distributed and diverse across different categories.**
    ### Available Controls:
    {control_list}

    ### Expected Response Format (STRICTLY FOLLOW THIS FORMAT):
    ```
    <control_id> : <weight>
    <control_id> : <weight>

    ```

    ### Example Correct Response (NO DUPLICATES):
    ```
     12 : 8
     45 : 7

    ```

    ⚠️ **If you provide duplicate control IDs, your response will be rejected. Ensure all control IDs are unique.**
    ⚠️ **Follow the response format exactly. Any deviation will be considered invalid.**
    """

    for attempt in range(5):
        response = client.chat.completions.create(
            model="gpt-4o-mini",
            messages=[{"role": "system", "content": prompt}]
        )
        result = response.choices[0].message.content.strip()
        print(f"AI Response (Attempt {attempt+1}):\n{result}")

        selected_controls = []
        valid = True
        control_ids_seen = set()

        for line in result.split("\n"):
            line = line.strip()

            parts = line.split(":")
            if len(parts) == 2:
                control_id_str = parts[0].replace("ID:", "").replace("id:", "").replace("Id:", "").strip()
                weight_str = parts[1].strip().replace("Weight:", "").replace("weight:", "").strip()

                control_id_str = ''.join(filter(str.isdigit, control_id_str))
                weight_str = ''.join(filter(str.isdigit, weight_str))

                if control_id_str and weight_str:
                    control_id = int(control_id_str)
                    weight = int(weight_str)

                    if control_id in valid_control_ids and 1 <= weight <= 10:
                        if control_id in control_ids_seen:
                            valid = False
                            break
                        selected_controls.append((control_id, weight))
                        control_ids_seen.add(control_id)
                    else:
                        valid = False
                        break

        if valid and len(selected_controls) == 10:
            return selected_controls

        print("Invalid response or duplicate control IDs found, retrying...\n")
        time.sleep(2)

    print("Failed to get a valid response after multiple attempts.")
    return []