kandil_code 2.1.1

Intelligent development platform (CLI + TUI + Multi-Agent System) with cross-platform AI model benchmarking, system diagnostics, and advanced development tools
//! Accessibility (a11y) assistant
//!
//! Assistant for ensuring digital accessibility compliance

use crate::core::adapters::ai::KandilAI;
use crate::core::agents::base::{Agent, AgentState};
use anyhow::Result;
use async_trait::async_trait;
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::sync::Arc;

#[derive(Debug, Clone)]
pub struct A11yAssistant {
    ai: Arc<KandilAI>,
    pub wcag_standards: HashMap<String, String>, // Guidelines reference
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct A11yReport {
    pub issues_found: Vec<A11yIssue>,
    pub compliance_level: ComplianceLevel,
    pub accessibility_score: u8,
    pub recommendations: Vec<String>,
    pub priority_issues: Vec<String>,
    pub overall_status: String,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct A11yIssue {
    pub id: String,
    pub element: String,
    pub description: String,
    pub wcag_level: WcagLevel,
    pub wcag_guidelines: Vec<String>,
    pub severity: Severity,
    pub location: Option<String>, // File or component location
    pub remediation: String,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum WcagLevel {
    A,   // Minimum level
    AA,  // Standard level
    AAA, // Enhanced level
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum ComplianceLevel {
    NonCompliant,
    PartiallyCompliant,
    Compliant,
    ExceedsCompliance,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum Severity {
    Low,
    Medium,
    High,
    Critical,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct WcagGuideline {
    pub id: String,
    pub title: String,
    pub description: String,
    pub techniques: Vec<String>,
    pub failures: Vec<String>,
}

impl A11yAssistant {
    pub fn new(ai: Arc<KandilAI>) -> Self {
        // Add WCAG standards reference
        let mut wcag_standards = HashMap::new();
        wcag_standards.insert(
            "1.1.1".to_string(),
            "Non-text Content: Provide text alternative for non-text content".to_string(),
        );
        wcag_standards.insert(
            "1.2.1".to_string(),
            "Audio-only and Video-only: Provide alternatives for time-based media".to_string(),
        );
        wcag_standards.insert(
            "1.3.1".to_string(),
            "Info and Relationships: Create content that can be presented in different ways"
                .to_string(),
        );
        wcag_standards.insert(
            "1.4.1".to_string(),
            "Use of Color: Don't use color as the only visual means of conveying information"
                .to_string(),
        );
        wcag_standards.insert(
            "2.1.1".to_string(),
            "Keyboard: Make all functionality available from a keyboard".to_string(),
        );
        wcag_standards.insert(
            "2.4.1".to_string(),
            "Bypass Blocks: Provide ways to bypass repetitive content".to_string(),
        );
        wcag_standards.insert(
            "3.1.1".to_string(),
            "Language of Page: Provide language information for the page".to_string(),
        );
        wcag_standards.insert(
            "4.1.1".to_string(),
            "Parsing: Maximize compatibility with assistive technologies".to_string(),
        );

        Self { ai, wcag_standards }
    }

    pub async fn wcag_audit(&self, content: &str, level: WcagLevel) -> Result<A11yReport> {
        let level_str = match level {
            WcagLevel::A => "A",
            WcagLevel::AA => "AA",
            WcagLevel::AAA => "AAA",
        };

        let prompt = format!(
            r#"Perform WCAG {} audit on this content:
            {}

            Check for violations of:
            - Perceivable: Alt text, captions, contrast
            - Operable: Keyboard nav, focus order
            - Understandable: Labels, error messages
            - Robust: Valid HTML, ARIA
            
            Return violations with remediation code.
            "#,
            level_str, content
        );

        let result = self.ai.chat(&prompt).await?;

        // In a real implementation, this would parse the structured response
        // For simulation, return basic data
        let issues = vec![A11yIssue {
            id: "A11Y-001".to_string(),
            element: "img".to_string(),
            description: "Missing alt text".to_string(),
            wcag_level: WcagLevel::A,
            wcag_guidelines: vec!["1.1.1".to_string()],
            severity: Severity::High,
            location: Some("index.html:line 45".to_string()),
            remediation: "Add descriptive alt attribute".to_string(),
        }];

        Ok(A11yReport {
            issues_found: issues,
            compliance_level: ComplianceLevel::PartiallyCompliant,
            accessibility_score: 78,
            recommendations: vec![
                "Add proper alt text to images".to_string(),
                "Improve color contrast ratios".to_string(),
                "Add skip navigation links".to_string(),
            ],
            priority_issues: vec!["Image alt text missing".to_string()],
            overall_status: format!("WCAG {} compliance review completed", level_str),
        })
    }

    pub async fn audit_html(&self, html_content: &str) -> Result<A11yReport> {
        let prompt = format!(
            r#"Audit this HTML for accessibility:
            {}

            Focus on:
            - Semantic HTML usage
            - Proper heading structure
            - Form labels and associations
            - Link text descriptiveness
            - ARIA attributes
            - Color contrast
            - Focus management
            "#,
            html_content
        );

        self.ai.chat(&prompt).await.map(|_| A11yReport {
            issues_found: vec![],
            compliance_level: ComplianceLevel::PartiallyCompliant,
            accessibility_score: 75,
            recommendations: vec!["Improve semantic structure".to_string()],
            priority_issues: vec!["Heading structure issues".to_string()],
            overall_status: "HTML accessibility review completed".to_string(),
        })
    }

    pub async fn generate_a11y_guidelines(&self, component_type: &str) -> Result<String> {
        let prompt = format!(
            r#"Generate accessibility guidelines for {} components.

            Include requirements for:
            - Keyboard navigation
            - Screen reader compatibility
            - Focus management
            - ARIA attributes
            - Color contrast
            - Alternative text
            "#,
            component_type
        );

        self.ai.chat(&prompt).await
    }

    pub async fn remediate_issues(&self, html_content: &str) -> Result<String> {
        let prompt = format!(
            r#"Fix accessibility issues in this HTML:
            {}

            Apply fixes for:
            - Missing alt text
            - Insufficient color contrast
            - Poor heading structure
            - Missing form labels
            - Non-semantic markup
            "#,
            html_content
        );

        self.ai.chat(&prompt).await
    }
}

#[async_trait]
impl Agent for A11yAssistant {
    async fn plan(&self, state: &AgentState) -> Result<String> {
        let prompt = format!(
            "As an accessibility specialist, given this a11y task: {}\n\nPlan the next accessibility activity. Consider WCAG standards, user needs, and implementation feasibility.",
            state.task
        );

        self.ai.chat(&prompt).await
    }

    async fn act(&self, plan: &str) -> Result<String> {
        // Execute the planned accessibility activity
        let prompt = format!(
            "Implement this accessibility plan: {}\n\nAudit content, fix issues, or update accessibility guidelines.",
            plan
        );

        self.ai.chat(&prompt).await
    }

    async fn observe(&self, result: &str) -> Result<String> {
        // Analyze accessibility results
        let prompt = format!(
            "Analyze these accessibility results: {}\n\nHow does this improve digital inclusion and user experience for people with disabilities?",
            result
        );

        self.ai.chat(&prompt).await
    }
}