ai_agent/
understanding.rs

1//! Understanding Engine - AI-powered task analysis
2
3use crate::types::TaskPlan;
4use crate::models::LanguageModel;
5use crate::errors::AgentError;
6
7/// Understanding engine for analyzing tasks
8pub struct UnderstandingEngine {
9    model: std::sync::Arc<dyn LanguageModel>,
10}
11
12impl UnderstandingEngine {
13    pub fn new(model: std::sync::Arc<dyn LanguageModel>) -> Self {
14        Self { model }
15    }
16
17    /// Understand and analyze a task
18    pub async fn understand(&self, request: &str) -> Result<TaskPlan, AgentError> {
19        let prompt = self.build_understanding_prompt(request);
20        let response = self.model.complete(&prompt).await?;
21
22        self.parse_task_plan(&response.content)
23    }
24
25    fn build_understanding_prompt(&self, request: &str) -> String {
26        format!(
27            "You are an intelligent coding assistant with full autonomy.
28
29TASK TO ANALYZE: {request}
30
31Please analyze this task and provide:
321. Your understanding of what the user wants
332. Your approach to solving it
343. Assessment of complexity (Simple/Moderate/Complex)
354. Any requirements or dependencies you identify
36
37You have complete freedom in how to structure your response. Be thorough but concise."
38        )
39    }
40
41    fn parse_task_plan(&self, response: &str) -> Result<TaskPlan, AgentError> {
42        let complexity = if response.to_lowercase().contains("simple") {
43            crate::types::TaskComplexity::Simple
44        } else if response.to_lowercase().contains("complex") {
45            crate::types::TaskComplexity::Complex
46        } else {
47            crate::types::TaskComplexity::Moderate
48        };
49
50        let estimated_steps = if response.to_lowercase().contains("step") {
51            Some(self.extract_step_count(response))
52        } else {
53            None
54        };
55
56        Ok(TaskPlan {
57            understanding: response.to_string(),
58            approach: "AI-determined approach".to_string(),
59            complexity,
60            estimated_steps,
61            requirements: vec![],
62        })
63    }
64
65    fn extract_step_count(&self, response: &str) -> u32 {
66        // Simple step count extraction logic
67        let words: Vec<&str> = response.split_whitespace().collect();
68        for (i, word) in words.iter().enumerate() {
69            if word.to_lowercase() == "step" && i > 0 {
70                if let Some(num_word) = words.get(i - 1) {
71                    if let Ok(num) = num_word.parse::<u32>() {
72                        return num;
73                    }
74                }
75            }
76        }
77        3 // Default value
78    }
79}
80
81#[cfg(test)]
82mod tests {
83    use super::*;
84    use crate::models::MockModel;
85
86    #[tokio::test]
87    async fn test_understanding_engine() {
88        let model = std::sync::Arc::new(MockModel::new("test".to_string()));
89        let engine = UnderstandingEngine::new(model);
90
91        let plan = engine.understand("Create a simple hello world program").await.unwrap();
92
93        assert!(!plan.understanding.is_empty());
94        assert!(!plan.approach.is_empty());
95    }
96}
ai_agent/understanding.rs

ai_agent/
understanding.rs
