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, Serialize, Deserialize)]
pub struct PairProgrammingSession {
pub participants: Vec<String>,
pub code_file: String,
pub current_task: String,
pub session_notes: Vec<String>,
pub bugs_found: Vec<Bug>,
pub features_implemented: Vec<String>,
pub duration_minutes: u32,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct Bug {
pub id: String,
pub description: String,
pub severity: Severity,
pub location: String,
pub fix_suggestion: String,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum Severity {
Low,
Medium,
High,
Critical,
}
impl std::fmt::Display for Severity {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
match self {
Severity::Low => write!(f, "Low"),
Severity::Medium => write!(f, "Medium"),
Severity::High => write!(f, "High"),
Severity::Critical => write!(f, "Critical"),
}
}
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ImplementationProgress {
pub completed_features: Vec<String>,
pub in_progress_features: Vec<String>,
pub blocked_features: Vec<String>,
pub code_coverage: f32,
pub bugs_found: u32,
pub estimated_completion: String,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CodeReviewFeedback {
pub reviewer: String,
pub file_reviewed: String,
pub comments: Vec<ReviewComment>,
pub overall_rating: u8,
pub recommendations: Vec<String>,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ReviewComment {
pub line_number: Option<u32>,
pub comment: String,
pub severity: Severity,
pub suggestion: String,
}
pub struct DeveloperSimulation {
pub ai: Arc<KandilAI>,
pub current_project: String,
pub session_history: HashMap<String, PairProgrammingSession>,
pub implementation_progress: HashMap<String, ImplementationProgress>,
}
impl DeveloperSimulation {
pub fn new(ai: Arc<KandilAI>, project_name: String) -> Self {
Self {
ai,
current_project: project_name,
session_history: HashMap::new(),
implementation_progress: HashMap::new(),
}
}
pub async fn implement_feature(
&mut self,
feature_spec: &str,
file_path: &str,
) -> Result<String> {
let prompt = format!(
r#"Implement the following feature in {}:
{}
Requirements:
1. Follow best practices for the language/framework
2. Include error handling
3. Add appropriate logging
4. Include unit tests if applicable
5. Add documentation
Return the implementation code.
"#,
file_path, feature_spec
);
let implementation = self.ai.chat(&prompt).await?;
let progress = self
.implementation_progress
.entry(file_path.to_string())
.or_insert_with(|| ImplementationProgress {
completed_features: vec![],
in_progress_features: vec![],
blocked_features: vec![],
code_coverage: 0.0,
bugs_found: 0,
estimated_completion: "Unknown".to_string(),
});
progress.in_progress_features.push(feature_spec.to_string());
Ok(implementation)
}
pub async fn start_pair_programming(
&mut self,
partner: &str,
task: &str,
file: &str,
) -> Result<String> {
let session_id = format!("PPS-{}", self.session_history.len() + 1);
let session = PairProgrammingSession {
participants: vec!["Developer Simulation".to_string(), partner.to_string()],
code_file: file.to_string(),
current_task: task.to_string(),
session_notes: vec![],
bugs_found: vec![],
features_implemented: vec![],
duration_minutes: 0,
};
self.session_history.insert(session_id.clone(), session);
Ok(format!("Started pair programming session: {}", session_id))
}
pub async fn find_bugs(&self, code: &str, file_path: &str) -> Result<Vec<Bug>> {
let prompt = format!(
r#"Analyze this code for bugs and issues:
File: {}
Code:
{}
Identify potential bugs, logic errors, and code smells. Rate their severity.
"#,
file_path, code
);
let findings = self.ai.chat(&prompt).await?;
Ok(vec![Bug {
id: "BUG-001".to_string(),
description: "Potential null pointer access".to_string(),
severity: Severity::High,
location: format!("{}:line 25", file_path),
fix_suggestion: "Add null check before access".to_string(),
}])
}
pub async fn generate_unit_tests(&self, function_name: &str, language: &str) -> Result<String> {
let prompt = format!(
r#"Generate unit tests for the function '{}'.
Language: {}
Create comprehensive tests covering:
- Happy path
- Edge cases
- Error conditions
- Boundary values
"#,
function_name, language
);
self.ai.chat(&prompt).await
}
pub fn get_session(&self, session_id: &str) -> Option<&PairProgrammingSession> {
self.session_history.get(session_id)
}
pub fn get_progress(&self, file_path: &str) -> Option<&ImplementationProgress> {
self.implementation_progress.get(file_path)
}
}
#[async_trait]
impl Agent for DeveloperSimulation {
async fn plan(&self, state: &AgentState) -> Result<String> {
let prompt = format!(
"As a Software Developer, given this development task: {}\n\nPlan the next implementation step. Consider code structure, dependencies, and testing approach.",
state.task
);
self.ai.chat(&prompt).await
}
async fn act(&self, plan: &str) -> Result<String> {
let prompt = format!(
"Implement this development plan: {}\n\nWrite code, fix issues, or refactor as needed.",
plan
);
self.ai.chat(&prompt).await
}
async fn observe(&self, result: &str) -> Result<String> {
let prompt = format!(
"Analyze this development output: {}\n\nHow does this implementation meet the requirements? What improvements are needed?",
result
);
self.ai.chat(&prompt).await
}
}