deepwiki-rs 1.3.0

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

pub struct RelationshipsAnalyze {
    prompt_compressor: PromptCompressor,
}

impl RelationshipsAnalyze {
    pub fn new() -> Self {
        Self {
            prompt_compressor: PromptCompressor::new(CompressionConfig::default()),
        }
    }

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

    /// Build optimized analysis parameters, supports intelligent compression
    async fn build_optimized_analysis_params(
        &self,
        context: &GeneratorContext,
        code_insights: &[CodeInsight],
    ) -> Result<AgentExecuteParams> {
        let prompt_sys = "You are a professional software architecture analyst specializing in analyzing project-level code dependency relationship graphs. Based on the provided code insights and dependencies, generate an overall architectural relationship analysis for the project.".to_string();

        // Sort by importance and intelligently select
        let mut sorted_insights: Vec<_> = code_insights.iter().collect();
        sorted_insights.sort_by(|a, b| {
            b.code_dossier
                .importance_score
                .partial_cmp(&a.code_dossier.importance_score)
                .unwrap_or(std::cmp::Ordering::Equal)
        });

        // Build code insights content
        let insights_content = self.build_insights_content(&sorted_insights);

        let compression_result = self
            .prompt_compressor
            .compress_if_needed(context, &insights_content, "Code Insights")
            .await?;

        if compression_result.was_compressed {
            println!(
                "   ✅ Compression complete: {} -> {} tokens",
                compression_result.original_tokens, compression_result.compressed_tokens
            );
        }
        let compressed_insights = compression_result.compressed_content;

        let prompt_user = format!(
            "Please analyze the overall architectural relationship graph of the project based on the following code insights and dependencies:

## Core Code Insights
{}

## Analysis Requirements:
Generate a project-level dependency relationship graph, focusing on:
1. Dependencies between core modules
2. Key data flows
3. Architectural hierarchy
4. Potential circular dependencies",
            compressed_insights
        );

        Ok(AgentExecuteParams {
            prompt_sys,
            prompt_user,
            cache_scope: "ai_relationships_insights".to_string(),
            log_tag: "Dependency Relationship Analysis".to_string(),
        })
    }

    /// Build code insights content
    fn build_insights_content(&self, sorted_insights: &[&CodeInsight]) -> String {
        sorted_insights
            .iter()
            .filter(|insight| insight.code_dossier.importance_score >= 0.6)
            .take(150) // Increase quantity limit
            .map(|insight| {
                let dependencies_introduce = insight
                    .dependencies
                    .iter()
                    .take(20) // Limit number of dependencies per file
                    .map(|r| format!("{}({})", r.name, r.dependency_type))
                    .collect::<Vec<_>>()
                    .join(", ");

                format!(
                    "- {}: {} (path: `{}`, importance: {:.2}, complexity: {:.1}, dependencies: [{}])",
                    insight.code_dossier.name,
                    insight.code_dossier.code_purpose.display_name(),
                    insight.code_dossier.file_path.to_string_lossy(),
                    insight.code_dossier.importance_score,
                    insight.complexity_metrics.cyclomatic_complexity,
                    dependencies_introduce
                )
            })
            .collect::<Vec<_>>()
            .join("\n")
    }
}