iAs/src/core/summary.rs

use crate::core::session::{ChatSession, SummaryEntry, SummaryReason};
use crate::llm::conversation::Summarizer;
use crate::llm::types::Message;
use std::sync::Arc;
use tokio::sync::Mutex;

/// 触发溢出摘要：压缩 checkpoint 到当前位置之间的新消息
pub async fn trigger_overflow_summary(
    session: &Arc<Mutex<ChatSession>>,
    summarizer: Option<&Summarizer>,
) -> bool {
    let mut s = session.lock().await;
    if s.messages.is_empty() {
        return false;
    }

    let prev_checkpoint = s.checkpoint;
    let end = s.messages.len();

    // checkpoint 始终在 user+assistant 对边界，直接用它作为摘要起点
    let start = prev_checkpoint;
    if start >= end {
        return false;
    }

    let to_summarize: Vec<_> = s.messages[start..end]
        .iter()
        .take(40) // 最多 40 条
        .cloned()
        .collect();

    if to_summarize.is_empty() {
        return false;
    }

    let summary_text = generate_summary(&to_summarize, summarizer).await;

    s.summaries.push(SummaryEntry {
        checkpoint: prev_checkpoint,
        text: summary_text.clone(),
        reason: SummaryReason::Overflow,
        created_at: chrono::Utc::now(),
    });

    // 持久化到数据库
    s.save_summary_to_db(&summary_text, "overflow", to_summarize.len() as i32)
        .await;

    s.checkpoint = end;

    // 清理太旧的消息（checkpoint 之前的保留最近 100 条用于调试）
    if s.checkpoint > 200 {
        let keep = s.checkpoint - 100;
        s.messages.drain(0..keep);
        // 调整 checkpoint 和 summary checkpoint
        let shift = keep;
        s.checkpoint -= shift;
        for sum in &mut s.summaries {
            if sum.checkpoint >= shift {
                sum.checkpoint -= shift;
            }
        }
    }

    true
}

/// 触发空闲摘要（不注入，保存到 summaries 供 LLM 工具查询）
pub async fn trigger_idle_summary(
    session: &Arc<Mutex<ChatSession>>,
    summarizer: Option<&Summarizer>,
) {
    let mut s = session.lock().await;
    if s.messages.is_empty() {
        return;
    }

    let summary_text = generate_summary(&s.messages, summarizer).await;
    let cp = s.messages.len();

    s.summaries.push(SummaryEntry {
        checkpoint: cp,
        text: summary_text.clone(),
        reason: SummaryReason::Timeout,
        created_at: chrono::Utc::now(),
    });

    let msg_count = cp as i32;
    s.save_summary_to_db(&summary_text, "timeout", msg_count)
        .await;

    s.checkpoint = s.messages.len();

    // 清理旧消息（checkpoint 之前的全部清除）
    if s.checkpoint > 0 {
        let shift = s.checkpoint;
        s.messages.drain(0..shift);
        s.checkpoint = 0;
        for sum in &mut s.summaries {
            if sum.checkpoint >= shift {
                sum.checkpoint -= shift;
            }
        }
    }
}

/// 生成摘要：优先使用 LLM，不可用时回退到简单截断
async fn generate_summary(messages: &[Message], summarizer: Option<&Summarizer>) -> String {
    if let Some(summarizer) = summarizer
        && messages.len() >= 3 {
            let prompt = build_summary_prompt(messages);
            match summarizer(prompt).await {
                Ok(text) if !text.is_empty() => {
                    tracing::info!("LLM 摘要: {:.100}...", text);
                    return text;
                }
                _ => tracing::warn!("LLM 摘要失败，回退到简单截断"),
            }
        }
    summarize_messages(messages)
}

/// 构建给 LLM 的摘要 prompt
fn build_summary_prompt(messages: &[Message]) -> String {
    let convo: String = messages
        .iter()
        .filter(|m| {
            m.role == crate::llm::types::Role::User
                || m.role == crate::llm::types::Role::Assistant
        })
        .map(|m| {
            let role = if m.role == crate::llm::types::Role::User {
                "用户"
            } else {
                "助手"
            };
            let content: String = m.content.chars().take(200).collect();
            format!("{}: {}", role, content)
        })
        .collect::<Vec<_>>()
        .join("\n");

    format!(
        "请将以下对话压缩为简短摘要，保留关键事实、用户偏好、决定和待办事项。只输出摘要，不要其他内容。\n\n对话：\n{}",
        convo
    )
}

/// 简单的摘要生成（提取最近 N 条消息的关键内容）
fn summarize_messages(messages: &[Message]) -> String {
    // 简单实现：提取用户消息的前 80 个字符作为摘要
    let lines: Vec<String> = messages
        .iter()
        .filter(|m| {
            m.role == crate::llm::types::Role::User
                || m.role == crate::llm::types::Role::Assistant
        })
        .map(|m| {
            let role = match m.role {
                crate::llm::types::Role::User => "用户",
                crate::llm::types::Role::Assistant => "助手",
                _ => "",
            };
            let preview: String = m.content.chars().take(80).collect();
            format!("{}: {}", role, preview)
        })
        .collect();

    if lines.is_empty() {
        "暂无历史对话".to_string()
    } else {
        let result = format!(
            "历史对话摘要（{} 条消息）:\n{}",
            lines.len(),
            lines.join("\n")
        );
        if result.chars().count() > 2000 {
            format!(
                "{}...（已截断）",
                result.chars().take(2000).collect::<String>()
            )
        } else {
            result
        }
    }
}