deepwiki-rs 0.9.6

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 crate::generator::{
    step_forward_agent::{
        AgentDataConfig, DataSource, FormatterConfig, LLMCallMode, PromptTemplate, StepForwardAgent,
    }
};
use crate::generator::research::memory::MemoryScope;
use crate::generator::research::types::{AgentType, SystemContextReport};

/// 项目目标调研员 - 负责分析项目的核心目标、功能价值和系统边界
#[derive(Default)]
pub struct SystemContextResearcher;

impl StepForwardAgent for SystemContextResearcher {
    type Output = SystemContextReport;

    fn agent_type(&self) -> String {
        AgentType::SystemContextResearcher.to_string()
    }

    fn memory_scope_key(&self) -> String {
        MemoryScope::STUDIES_RESEARCH.to_string()
    }

    fn data_config(&self) -> AgentDataConfig {
        AgentDataConfig {
            required_sources: vec![DataSource::PROJECT_STRUCTURE, DataSource::CODE_INSIGHTS],
            optional_sources: vec![DataSource::README_CONTENT],
        }
    }

    fn prompt_template(&self) -> PromptTemplate {
        PromptTemplate {
            system_prompt: r#"你是一个专业的软件架构分析师，专注于项目目标和系统边界分析。

你的任务是基于提供的项目信息，分析并确定：
1. 项目的核心目标和业务价值
2. 项目类型和技术特征
3. 目标用户群体和使用场景
4. 外部系统交互
5. 系统边界定义

请以结构化的JSON格式返回分析结果。"#
                .to_string(),

            opening_instruction: "基于以下调研材料，分析项目的核心目标和系统定位：".to_string(),

            closing_instruction: r#"
## 分析要求：
- 准确识别项目类型和技术特征
- 明确定义目标用户和使用场景
- 清晰划定系统边界
- 确保分析结果符合C4架构模型的系统上下文层次"#
                .to_string(),

            llm_call_mode: LLMCallMode::Extract,
            formatter_config: FormatterConfig::default(),
        }
    }
}