soma-core 2.0.2

World's first production-ready self-aware development system with meta-cognitive capabilities and cognitive reasoning engine for intelligent development platforms
Documentation 
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// GPT-4 CognitiveAgent implementation for symbolic feedback loop
// All comments in English (US) per coding_guidelines.md

#![allow(dead_code)] // Keep API for future expansion

use crate::dag::Node;
use crate::memory::SymbolicContext;

/// Core edit proposal structure
#[derive(Debug, Clone)]
pub struct ProposedEdit {
    pub file: String,
    pub line_range: (usize, usize), // (start_line, end_line)
    pub new_code: String,
    pub reason: String,
    pub confidence: f64, // 0.0 to 1.0
}

/// Represents an insight or reasoning about code
pub struct Insight {
    pub summary: String,
    pub details: String,
    pub confidence: f64,
}

/// Represents a trace of execution for simulation
pub struct ExecutionTrace {
    pub phase: String,
    pub node_id: String,
    pub result: String,
}

/// Trait for symbolic cognitive agents
pub trait CognitiveAgent {
    fn propose_edit(&self, ctx: &SymbolicContext) -> ProposedEdit;
    fn reason_about_code(&self, file: &str, lines: &[String]) -> Insight;
    fn simulate(&self, phase: &str, dag: &[Node]) -> Vec<ExecutionTrace>;
}

/// Example GPT-4 agent implementation
pub struct GPT4Agent;

impl CognitiveAgent for GPT4Agent {
    fn propose_edit(&self, ctx: &SymbolicContext) -> ProposedEdit {
        // GPT-4 focuses on performance and best practices
        let task = ctx.resolve_or_default("current_task", "general improvement");

        if task.contains("performance") {
            ProposedEdit {
                file: "src/ops.rs".to_string(),
                line_range: (10, 15),
                new_code: "// GPT-4: Optimized implementation for better performance\npub fn optimized_function() {\n    // Use more efficient algorithms\n}".to_string(),
                reason: "Performance optimization suggested by GPT-4 for better runtime efficiency".to_string(),
                confidence: 0.95,
            }
        } else if task.contains("safety") {
            ProposedEdit {
                file: "src/memory.rs".to_string(),
                line_range: (20, 25),
                new_code: "// GPT-4: Added bounds checking for memory safety\nif index < buffer.len() {\n    // Safe access\n}".to_string(),
                reason: "Memory safety improvement with bounds checking".to_string(),
                confidence: 0.92,
            }
        } else {
            ProposedEdit {
                file: "src/ops.rs".to_string(),
                line_range: (10, 12),
                new_code: "// GPT-4: Enhanced error handling and documentation\n/// This function provides improved error handling\npub fn enhanced_function() -> Result<(), Error> {".to_string(),
                reason: "Better error handling and documentation practices".to_string(),
                confidence: 0.88,
            }
        }
    }

    fn reason_about_code(&self, file: &str, lines: &[String]) -> Insight {
        Insight {
            summary: format!("Reasoning about {} ({} lines)", file, lines.len()),
            details: "No issues detected.".to_string(),
            confidence: 0.9,
        }
    }

    fn simulate(&self, phase: &str, dag: &[Node]) -> Vec<ExecutionTrace> {
        dag.iter()
            .map(|node| ExecutionTrace {
                phase: phase.to_string(),
                node_id: node.id.clone(),
                result: "ok".to_string(),
            })
            .collect()
    }
}