otherone_context/

lib.rs

// 作用：otherone-context 模块 — 上下文管理（会话加载 + 压缩触发）
// 关联：被 otherone-agent 的 invoke_agent 调用
// 预期结果：提供 combine_context 核心方法

pub mod compact;
pub mod error;
pub mod types;

use tracing::warn;

use crate::compact::check_threshold::check_threshold;
use crate::compact::compact_messages;
use crate::compact::estimate_tokens::estimate_tokens;
use crate::error::ContextError;
use crate::types::{CombineContextOptions, ContextLoadType};
use otherone_ai::types::{Message, MessageContent};
use otherone_storage::types::SessionData;

/// 提取 MessageContent 中的文本
fn message_content_text(content: &MessageContent) -> &str {
    match content {
        MessageContent::Text(t) => t.as_str(),
        _ => "[非文本内容]",
    }
}

/// 组合 context 配置
/// 作用：根据 session_id 和 load_type 加载历史消息，检查 token 阈值并触发压缩
/// 关联：被 agent loop 调用
/// 预期结果：返回 messages 数组（包含 system prompt），供 AI 调用使用
pub async fn combine_context(
    options: &CombineContextOptions,
) -> Result<Vec<Message>, ContextError> {
    // 参数有效性检查
    if options.session_id.is_empty() {
        return Err(ContextError::ConfigError(
            "session_id is required".to_string(),
        ));
    }
    if options.context_window == 0 {
        return Err(ContextError::ConfigError(
            "context_window is required".to_string(),
        ));
    }

    // 根据 load_type 加载数据
    let session_data = match options.load_type {
        ContextLoadType::Database => {
            let db_config = options.database_config.as_ref().ok_or_else(|| {
                ContextError::ConfigError(
                    "database_config is required when load_type is database".to_string(),
                )
            })?;
            otherone_storage::database::reader::read_session_data_from_database(
                &options.session_id,
                db_config,
            )
            .await
            .map_err(|e| ContextError::StorageError(e.to_string()))?
        }
        ContextLoadType::LocalFile => {
            otherone_storage::localfile::reader::read_session_data(&options.session_id)
                .map_err(|e| ContextError::StorageError(e.to_string()))?
        }
    };

    // 处理压缩记录，找到最新的压缩内容和起始 entry_id
    let (compacted_summary, start_entry_id) = process_compacted_entries(&session_data);

    // 根据 start_entry_id 过滤 entries
    let filtered_entries = filter_entries_from_start(&session_data.entries, &start_entry_id);

    // 更新 session_data 的 entries 为过滤后的结果
    let mut filtered_session = session_data;
    filtered_session.entries = filtered_entries;

    // 根据 provider 类型转换数据格式
    let messages = transform_to_messages(
        &filtered_session,
        &options.provider,
        compacted_summary.as_deref(),
    );

    // 计算 token 用量并检查是否需要压缩
    let mut context_tokens: u32 = 0;

    // 获取最后一条 assistant 消息的 token_consumption
    let assistant_entries: Vec<&otherone_storage::types::Entry> = filtered_session
        .entries
        .iter()
        .rev()
        .filter(|e| e.role == "assistant")
        .collect();

    // 最多检查 3 条 assistant 消息
    let max_attempts = std::cmp::min(3, assistant_entries.len());
    let mut found_token_index: Option<usize> = None;

    for i in 0..max_attempts {
        let entry = assistant_entries[i];
        if let Some(tc) = entry.token_consumption {
            context_tokens = tc;
            if let Some(pos) = filtered_session
                .entries
                .iter()
                .position(|e| e.entry_id == entry.entry_id)
            {
                found_token_index = Some(pos);
            }
            break;
        }
    }

    // 如果没有找到 token_consumption，或者找到后还有新消息，需要估算
    if context_tokens == 0
        || found_token_index.map_or(true, |idx| idx < filtered_session.entries.len() - 1)
    {
        let estimated = estimate_tokens(&messages);

        if context_tokens == 0 {
            let mut extra_tokens: u32 = 0;
            if let Some(ref sp) = options.system_prompt {
                let sys_msg = Message {
                    role: "system".to_string(),
                    content: MessageContent::Text(sp.clone()),
                    name: None,
                    tool_calls: None,
                    tool_call_id: None,
                };
                extra_tokens += estimate_tokens(&[sys_msg]);
            }
            if let Some(ref tools) = options.tools {
                let tools_json = serde_json::to_string(tools).unwrap_or_default();
                let tools_msg = Message {
                    role: "system".to_string(),
                    content: MessageContent::Text(tools_json),
                    name: None,
                    tool_calls: None,
                    tool_call_id: None,
                };
                extra_tokens += estimate_tokens(&[tools_msg]);
            }
            context_tokens = estimated + extra_tokens;
        } else {
            context_tokens += estimated;
        }
    }

    // 检查是否需要压缩
    let should_compress = check_threshold(
        context_tokens,
        options.context_window,
        options.threshold_percentage,
    );

    // 构建最终的 messages
    let mut final_messages = messages;

    if should_compress {
        let has_compacted = final_messages.first().map_or(false, |m| {
            m.role == "user"
                && (message_content_text(&m.content).contains("[压缩")
                    || message_content_text(&m.content).contains("[Compressed"))
        });

        warn!(
            "Context threshold exceeded ({} tokens / {} window). Triggering compaction.",
            context_tokens, options.context_window
        );

        // 实际执行压缩
        let storage_type = match options.load_type {
            ContextLoadType::Database => otherone_storage::types::StorageType::Database,
            ContextLoadType::LocalFile => otherone_storage::types::StorageType::LocalFile,
        };

        match compact_messages(
            &final_messages,
            context_tokens,
            options.context_window,
            None,
            options.ai.as_ref(),
            has_compacted,
            Some(&options.session_id),
            Some(&storage_type),
            options.database_config.as_ref(),
            Some(&filtered_session.entries),
        )
        .await
        {
            Ok(compacted) => {
                final_messages = compacted;
            }
            Err(e) => {
                warn!(
                    "Compaction failed: {}. Continuing with uncompacted messages.",
                    e
                );
            }
        }
    }

    // 在返回前添加 system prompt 到最前面
    if let Some(ref system_prompt) = options.system_prompt {
        final_messages.insert(
            0,
            Message {
                role: "system".to_string(),
                content: MessageContent::Text(system_prompt.clone()),
                name: None,
                tool_calls: None,
                tool_call_id: None,
            },
        );
    }

    Ok(final_messages)
}

/// 处理压缩记录，找到最新的压缩内容和起始 entry_id
fn process_compacted_entries(session_data: &SessionData) -> (Option<String>, Option<String>) {
    if session_data.compacted_entries.is_empty() {
        return (None, None);
    }

    let mut sorted: Vec<&otherone_storage::types::CompactedEntry> =
        session_data.compacted_entries.iter().collect();
    sorted.sort_by(|a, b| b.create_at.cmp(&a.create_at));

    let latest = sorted[0];

    if latest.summary.is_empty() {
        return (None, None);
    }

    let final_entry_id = find_final_trigger_entry_id(
        &latest.trigger_entry_id,
        &session_data.compacted_entries,
        &session_data.entries,
    );

    (Some(latest.summary.clone()), final_entry_id)
}

/// 递归查找最终的 trigger_entry_id
fn find_final_trigger_entry_id(
    trigger_id: &str,
    compacted_entries: &[otherone_storage::types::CompactedEntry],
    entries: &[otherone_storage::types::Entry],
) -> Option<String> {
    let max_depth = 10;
    let mut current_id = trigger_id.to_string();
    let mut visited_ids = std::collections::HashSet::new();

    for _ in 0..max_depth {
        if visited_ids.contains(&current_id) {
            warn!("检测到循环引用: {}", current_id);
            return None;
        }
        visited_ids.insert(current_id.clone());

        if entries.iter().any(|e| e.entry_id == current_id) {
            return Some(current_id);
        }

        if let Some(compacted) = compacted_entries.iter().find(|c| c.entry_id == current_id) {
            current_id = compacted.trigger_entry_id.clone();
        } else {
            warn!("trigger_entry_id 不存在: {}", current_id);
            return None;
        }
    }

    warn!("超过最大递归深度，最后的 ID: {}", current_id);
    None
}

/// 从 start_entry_id 开始过滤 entries
fn filter_entries_from_start(
    entries: &[otherone_storage::types::Entry],
    start_entry_id: &Option<String>,
) -> Vec<otherone_storage::types::Entry> {
    let start_id = match start_entry_id {
        Some(id) => id,
        None => return entries.to_vec(),
    };

    if let Some(start_index) = entries.iter().position(|e| e.entry_id == *start_id) {
        entries[start_index..].to_vec()
    } else {
        warn!("start_entry_id 不存在于 entries 中: {}", start_id);
        entries.to_vec()
    }
}

/// 将 session 数据转换为 AI 请求的 messages 格式
fn transform_to_messages(
    session_data: &SessionData,
    provider: &otherone_ai::types::ProviderType,
    compacted_summary: Option<&str>,
) -> Vec<Message> {
    match provider {
        otherone_ai::types::ProviderType::OpenAI
        | otherone_ai::types::ProviderType::OpenRouter
        | otherone_ai::types::ProviderType::Local
        | otherone_ai::types::ProviderType::Fetch => {
            transform_to_openai_format(session_data, compacted_summary)
        }
        otherone_ai::types::ProviderType::Anthropic => {
            transform_to_anthropic_format(session_data, compacted_summary)
        }
    }
}

/// 转换为 OpenAI 格式的 messages
fn transform_to_openai_format(
    session_data: &SessionData,
    compacted_summary: Option<&str>,
) -> Vec<Message> {
    let mut messages: Vec<Message> = Vec::new();

    if let Some(summary) = compacted_summary {
        messages.push(Message {
            role: "user".to_string(),
            content: MessageContent::Text(summary.to_string()),
            name: None,
            tool_calls: None,
            tool_call_id: None,
        });
    }

    if session_data.entries.is_empty() {
        return messages;
    }

    for entry in &session_data.entries {
        let mut message = Message {
            role: entry.role.clone(),
            content: MessageContent::Text(entry.content.clone()),
            name: None,
            tool_calls: None,
            tool_call_id: None,
        };

        if entry.role == "assistant" {
            if let Some(ref tools) = entry.tools {
                if let Some(tool_calls) = tools.get("tool_calls") {
                    if let Ok(parsed_tool_calls) = serde_json::from_value(tool_calls.clone()) {
                        message.tool_calls = Some(parsed_tool_calls);
                    }
                }
            }
        }

        if entry.role == "tool" {
            if let Some(ref tools) = entry.tools {
                message.tool_call_id = tools
                    .get("tool_call_id")
                    .and_then(|v| v.as_str())
                    .map(|s| s.to_string());
                message.name = tools
                    .get("function_name")
                    .and_then(|v| v.as_str())
                    .map(|s| s.to_string());
            }
        }

        messages.push(message);
    }

    messages
}

/// 转换为 Anthropic 格式的 messages
fn transform_to_anthropic_format(
    session_data: &SessionData,
    compacted_summary: Option<&str>,
) -> Vec<Message> {
    transform_to_openai_format(session_data, compacted_summary)
}