deepwiki-rs 0.9.8

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::agent_executor::{AgentExecuteParams, extract};
use crate::types::code::CodeInsight;
use crate::{
    generator::context::GeneratorContext,
    types::{code_releationship::RelationshipAnalysis, project_structure::ProjectStructure},
};

pub struct RelationshipsAnalyze;

impl RelationshipsAnalyze {
    pub fn new() -> Self {
        Self
    }

    pub async fn execute(
        &self,
        context: &GeneratorContext,
        code_insights: &Vec<CodeInsight>,
        _project_structure: &ProjectStructure,
    ) -> Result<RelationshipAnalysis> {
        let agent_params = self.build_simple_analysis_params(code_insights);
        extract::<RelationshipAnalysis>(context, agent_params).await
    }

    /// 构建简单分析参数
    fn build_simple_analysis_params(&self, code_insights: &[CodeInsight]) -> AgentExecuteParams {
        let prompt_sys = "你是一个专业的软件架构分析师，专门分析项目级别的代码依赖关系图谱。基于提供的代码洞察和依赖关系，生成项目的整体架构关系分析。".to_string();

        let prompt_user = format!(
            "请基于以下代码洞察和依赖关系，分析项目的整体架构关系图谱：

## 核心代码洞察 ({} 个)
{}

## 分析要求：
生成项目级别的依赖关系图谱",
            code_insights.len(),
            code_insights
                .iter()
                .filter(|insight| insight.code_dossier.importance_score > 0.6)
                .map(|insight| {
                    {
                        let dependencies_introduce = insight
                            .dependencies
                            .iter()
                            .map(|r| r.to_string())
                            .collect::<Vec<_>>()
                            .join(",");

                        format!(
                            "- {}: {} (文件路径：`{}`，重要性: {:.1}, 复杂度: {:.1}, 依赖: [{}])",
                            insight.code_dossier.name,
                            insight.code_dossier.file_path.to_string_lossy(),
                            insight.code_dossier.code_purpose.display_name(),
                            insight.code_dossier.importance_score,
                            insight.complexity_metrics.cyclomatic_complexity,
                            dependencies_introduce
                        )
                    }
                })
                .collect::<Vec<_>>()
                .join("\n")
        );

        AgentExecuteParams {
            prompt_sys,
            prompt_user,
            cache_scope: "ai_relationships_insights".to_string(),
            log_tag: String::new(),
        }
    }
}