deepwiki-rs 1.2.0

deepwiki-rs(also known as Litho) is a high-performance automatic generation engine for C4 architecture documentation, developed using Rust. It can intelligently analyze project structures, identify core components, parse dependency relationships, and leverage large language models (LLMs) to automatically generate professional architecture documentation.
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use anyhow::Result;

use crate::generator::context::GeneratorContext;
use crate::generator::research::agents::architecture_researcher::ArchitectureResearcher;
use crate::generator::research::agents::boundary_analyzer::BoundaryAnalyzer;
use crate::generator::research::agents::domain_modules_detector::DomainModulesDetector;
use crate::generator::research::agents::key_modules_insight::KeyModulesInsight;
use crate::generator::research::agents::system_context_researcher::SystemContextResearcher;
use crate::generator::research::agents::workflow_researcher::WorkflowResearcher;
use crate::generator::step_forward_agent::StepForwardAgent;

/// 多智能体研究编排器
#[derive(Default)]
pub struct ResearchOrchestrator;

impl ResearchOrchestrator {
    /// 执行所有智能体的分析流程
    pub async fn execute_research_pipeline(&self, context: &GeneratorContext) -> Result<()> {
        println!("🚀 开始执行Litho Studies Research调研流程...");

        // 第一层：宏观分析（C1）
        self.execute_agent("SystemContextResearcher", &SystemContextResearcher, context)
            .await?;

        // 第二层：中观分析（C2）
        self.execute_agent("DomainModulesDetector", &DomainModulesDetector, context)
            .await?;
        self.execute_agent("ArchitectureResearcher", &ArchitectureResearcher, context)
            .await?;
        self.execute_agent("WorkflowResearcher", &WorkflowResearcher, context)
            .await?;

        // 第三层：微观分析（C3-C4）
        self.execute_agent("KeyModulesInsight", &KeyModulesInsight, context)
            .await?;

        // 边界接口分析
        self.execute_agent("BoundaryAnalyzer", &BoundaryAnalyzer::default(), context)
            .await?;

        println!("✓ Litho Studies Research流程执行完毕");

        Ok(())
    }

    /// 执行单个智能体
    async fn execute_agent<T>(
        &self,
        name: &str,
        agent: &T,
        context: &GeneratorContext,
    ) -> Result<()>
    where
        T: StepForwardAgent + Send + Sync,
    {
        println!("🤖 执行 {} 智能体分析...", name);

        agent.execute(context).await?;
        println!("✓ {} 分析完成", name);
        Ok(())
    }
}