kandil_code 2.1.1

//! Test execution agent
//!
//! Specialized agent for generating and executing tests

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::sync::Arc;

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct TestResult {
    pub passed: u32,
    pub failed: u32,
    pub skipped: u32,
    pub duration_ms: u64,
    pub details: Vec<TestDetail>,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct TestDetail {
    pub name: String,
    pub status: TestStatus,
    pub message: Option<String>,
    pub duration_ms: u64,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum TestStatus {
    Passed,
    Failed,
    Skipped,
    Error,
}

pub struct TestAgent {
    ai: Arc<KandilAI>,
}

impl TestAgent {
    pub fn new(ai: Arc<KandilAI>) -> Self {
        Self { ai }
    }

    pub async fn generate_tests(&self, source_file: &str, target_language: &str) -> Result<String> {
        let source_code = std::fs::read_to_string(source_file)?;

        let prompt = format!(
            "Generate comprehensive unit tests for this {} code:\n\n{}\n\nCreate tests that cover:\n1. All public functions/methods\n2. Edge cases\n3. Error handling\n4. Boundary conditions\n5. Happy path scenarios\n\nFollow the testing conventions of {}.",
            target_language, source_code, target_language
        );

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

    pub async fn execute_tests(&self, test_file: &str, test_framework: &str) -> Result<TestResult> {
        // In a real implementation, this would actually execute the tests
        // For simulation, we'll return a mock result

        println!("Executing tests using {} framework...", test_framework);
        println!("Test file: {}", test_file);

        // Mock test execution result
        Ok(TestResult {
            passed: 8,
            failed: 1,
            skipped: 1,
            duration_ms: 1250,
            details: vec![
                TestDetail {
                    name: "test_user_creation".to_string(),
                    status: TestStatus::Passed,
                    message: None,
                    duration_ms: 50,
                },
                TestDetail {
                    name: "test_invalid_input".to_string(),
                    status: TestStatus::Failed,
                    message: Some("Expected validation error not thrown".to_string()),
                    duration_ms: 80,
                },
                TestDetail {
                    name: "test_edge_case".to_string(),
                    status: TestStatus::Skipped,
                    message: Some("Feature not yet implemented".to_string()),
                    duration_ms: 0,
                },
            ],
        })
    }

    pub async fn analyze_test_coverage(
        &self,
        source_file: &str,
        test_file: &str,
    ) -> Result<String> {
        let source_code = std::fs::read_to_string(source_file)?;
        let test_code = std::fs::read_to_string(test_file)?;

        let prompt = format!(
            "Analyze test coverage for this source code:\n\n{}\n\nAgainst these tests:\n\n{}\n\nIdentify:\n1. Untested functions/methods\n2. Missing edge cases\n3. Suggested additional tests\n4. Test quality assessment",
            source_code, test_code
        );

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

#[async_trait]
impl Agent for TestAgent {
    async fn plan(&self, state: &AgentState) -> Result<String> {
        let prompt = format!(
            "Given this testing task: {}\n\nPlan the next testing step. What should we test or analyze next?",
            state.task
        );

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

    async fn act(&self, plan: &str) -> Result<String> {
        // Execute the planned testing action
        let prompt = format!(
            "Execute this testing plan: {}\n\nGenerate test results or perform test analysis.",
            plan
        );

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

    async fn observe(&self, result: &str) -> Result<String> {
        // Analyze test results
        let prompt = format!(
            "Analyze these test results: {}\n\nWhat do these results tell us about code quality and test coverage?",
            result
        );

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