deepwiki-rs 0.9.7

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::{config::LLMConfig, llm::client::types::TokenUsage};

pub fn evaluate_befitting_model(
    llm_config: &LLMConfig,
    system_prompt: &str,
    user_prompt: &str,
) -> (String, Option<String>) {
    if system_prompt.len() + user_prompt.len() <= 32 * 1024 {
        return (
            llm_config.model_efficient.clone(),
            Some(llm_config.model_powerful.clone()),
        );
    }
    return (llm_config.model_powerful.clone(), None);
}

/// 估算token使用情况（基于文本长度）
pub fn estimate_token_usage(input_text: &str, output_text: &str) -> TokenUsage {
    // 粗略估算：1个token约等于4个字符（英文）或—1.5个字符（中文）
    let input_tokens = estimate_text_tokens(input_text);
    let output_tokens = estimate_text_tokens(output_text);
    TokenUsage::new(input_tokens, output_tokens)
}

/// 估算单个文本的token数量
pub fn estimate_text_tokens(text: &str) -> u64 {
    // 统计中文字符数量
    let chinese_chars = text
        .chars()
        .filter(|c| {
            let code = *c as u32;
            // 中文字符范围（简化）
            (0x4E00..=0x9FFF).contains(&code)
                || (0x3400..=0x4DBF).contains(&code)
                || (0x20000..=0x2A6DF).contains(&code)
        })
        .count();

    let total_chars = text.chars().count();
    let english_chars = total_chars - chinese_chars;

    // 中文字符每个约有1.5个token，英文字符每4个约1个token
    let estimated_tokens = (chinese_chars as f64 * 1.5) + (english_chars as f64 / 4.0);
    estimated_tokens.ceil() as u64
}