// agent.rs — Core agent loop
//
// The simplest possible implementation of the agent pattern:
// send messages + tool definitions to the model, if it responds
// with tool calls then dispatch them and loop, if it responds
// with text then display it and wait for the next prompt.
//
// Uses streaming by default so text tokens appear as they're
// generated. Tool calls are accumulated from stream deltas and
// dispatched after the stream completes.
//
// The DMN (dmn.rs) is the outer loop that decides what prompts
// to send here. This module just handles single turns: prompt
// in, response out, tool calls dispatched.

pub mod api;
pub mod context;
pub mod oneshot;
pub mod tokenizer;
pub mod tools;

use std::sync::Arc;
use anyhow::Result;

use api::{ApiClient, ToolCall};
use api::{ContentPart, Message, MessageContent, Role};
use context::{ConversationEntry, ContextEntry, ContextState};
use tools::{summarize_args, working_stack};

use crate::mind::log::ConversationLog;
use crate::agent::context::ContextSection;

// --- Activity tracking (RAII guards) ---

pub struct ActivityEntry {
    pub id: u64,
    pub label: String,
    pub started: std::time::Instant,
    /// Auto-expires this long after creation (or completion).
    pub expires_at: std::time::Instant,
}

/// RAII guard — marks the activity "(complete)" on drop, starts expiry timer.
pub struct ActivityGuard {
    agent: Arc<tokio::sync::Mutex<Agent>>,
    id: u64,
}

const ACTIVITY_LINGER: std::time::Duration = std::time::Duration::from_secs(5);

impl Drop for ActivityGuard {
    fn drop(&mut self) {
        if let Ok(mut ag) = self.agent.try_lock() {
            if let Some(entry) = ag.activities.iter_mut().find(|a| a.id == self.id) {
                entry.label.push_str(" (complete)");
                entry.expires_at = std::time::Instant::now() + ACTIVITY_LINGER;
            }
        }
    }
}

impl Agent {
    /// Register an activity, returns its ID. Caller creates the guard.
    pub fn push_activity(&mut self, label: impl Into<String>) -> u64 {
        self.expire_activities();
        let id = self.next_activity_id;
        self.next_activity_id += 1;
        self.activities.push(ActivityEntry {
            id, label: label.into(),
            started: std::time::Instant::now(),
            expires_at: std::time::Instant::now() + std::time::Duration::from_secs(3600),
        });
        self.changed.notify_one();
        id
    }

    /// Push a notification — auto-expires after 5 seconds.
    pub fn notify(&mut self, label: impl Into<String>) {
        self.expire_activities();
        let id = self.next_activity_id;
        self.next_activity_id += 1;
        self.activities.push(ActivityEntry {
            id, label: label.into(),
            started: std::time::Instant::now(),
            expires_at: std::time::Instant::now() + ACTIVITY_LINGER,
        });
        self.changed.notify_one();
    }

    /// Remove expired activities.
    pub fn expire_activities(&mut self) {
        let now = std::time::Instant::now();
        self.activities.retain(|a| a.expires_at > now);
    }
}

/// Create an activity guard from outside the lock.
pub fn activity_guard(agent: &Arc<tokio::sync::Mutex<Agent>>, id: u64) -> ActivityGuard {
    ActivityGuard { agent: agent.clone(), id }
}

/// Convenience: lock, push activity, unlock, return guard.
pub async fn start_activity(agent: &Arc<tokio::sync::Mutex<Agent>>, label: impl Into<String>) -> ActivityGuard {
    let id = agent.lock().await.push_activity(label);
    ActivityGuard { agent: agent.clone(), id }
}

/// Result of a single agent turn.
pub struct TurnResult {
    /// The text response (already sent through UI channel).
    #[allow(dead_code)]
    pub text: String,
    /// Whether the model called yield_to_user during this turn.
    pub yield_requested: bool,
    /// Whether any tools (other than yield_to_user) were called.
    pub had_tool_calls: bool,
    /// Number of tool calls that returned errors this turn.
    pub tool_errors: u32,
    /// Model name to switch to after this turn completes.
    pub model_switch: Option<String>,
    /// Agent requested DMN pause (full stop on autonomous behavior).
    pub dmn_pause: bool,
}

/// Accumulated state across tool dispatches within a single turn.
struct DispatchState {
    yield_requested: bool,
    had_tool_calls: bool,
    tool_errors: u32,
    model_switch: Option<String>,
    dmn_pause: bool,
}

impl DispatchState {
    fn new() -> Self {
        Self {
            yield_requested: false, had_tool_calls: false,
            tool_errors: 0, model_switch: None, dmn_pause: false,
        }
    }
}

pub struct Agent {
    client: ApiClient,
    tools: Vec<tools::Tool>,
    /// Last known prompt token count from the API (tracks context size).
    last_prompt_tokens: u32,
    /// Current reasoning effort level ("none", "low", "high").
    pub reasoning_effort: String,
    /// Sampling parameters — adjustable at runtime from the thalamus screen.
    pub temperature: f32,
    pub top_p: f32,
    pub top_k: u32,
    /// Active activities — RAII guards auto-remove on drop.
    pub activities: Vec<ActivityEntry>,
    next_activity_id: u64,
    /// Control tool flags — set by tool handlers, consumed by turn loop.
    pub pending_yield: bool,
    pub pending_model_switch: Option<String>,
    pub pending_dmn_pause: bool,
    /// Provenance tag for memory operations — identifies who made the change.
    pub provenance: String,
    /// Persistent conversation log — append-only record of all messages.
    pub conversation_log: Option<ConversationLog>,
    /// Mutable context state — personality, working stack, etc.
    pub context: ContextState,
    /// App config — used to reload identity on compaction and model switching.
    pub app_config: crate::config::AppConfig,
    pub prompt_file: String,
    /// Stable session ID for memory-search dedup across turns.
    pub session_id: String,
    /// Incremented on compaction — UI uses this to detect resets.
    pub generation: u64,
    /// Whether incremental memory scoring is currently running.
    pub memory_scoring_in_flight: bool,
    /// Shared active tools — Agent writes, TUI reads.
    pub active_tools: tools::SharedActiveTools,
    /// Fires when agent state changes — UI wakes on this instead of polling.
    pub changed: Arc<tokio::sync::Notify>,
}

impl Agent {
    pub fn new(
        client: ApiClient,
        system_prompt: String,
        personality: Vec<(String, String)>,
        app_config: crate::config::AppConfig,
        prompt_file: String,
        conversation_log: Option<ConversationLog>,
        active_tools: tools::SharedActiveTools,
    ) -> Self {
        let mut system = ContextSection::new("System prompt");
        system.push(ContextEntry::new(
            ConversationEntry::System(Message::system(&system_prompt)), None));

        // Tool definitions — part of the context, tokenized and scored
        let tool_defs: Vec<String> = tools::tools().iter()
            .map(|t| t.to_json()).collect();
        if !tool_defs.is_empty() {
            let tools_text = format!(
                "# Tools\n\nYou have access to the following functions:\n\n<tools>\n{}\n</tools>\n\n\
                If you choose to call a function ONLY reply in the following format with NO suffix:\n\n\
                <tool_call>\n<function=example_function_name>\n\
                <parameter=example_parameter_1>\nvalue_1\n</parameter>\n\
                </function>\n</tool_call>\n\n\
                IMPORTANT: Function calls MUST follow the specified format.",
                tool_defs.join("\n"),
            );
            system.push(ContextEntry::new(
                ConversationEntry::System(Message::system(&tools_text)), None));
        }

        let mut identity = ContextSection::new("Identity");
        for (_name, content) in &personality {
            identity.push(ContextEntry::new(
                ConversationEntry::Message(Message::user(content)), None));
        }
        let context = ContextState {
            system,
            identity,
            journal: ContextSection::new("Journal"),
            conversation: ContextSection::new("Conversation"),
            working_stack: Vec::new(),
        };
        let session_id = format!("consciousness-{}", chrono::Utc::now().format("%Y%m%d-%H%M%S"));
        let mut agent = Self {
            client,
            tools: tools::tools(),
            last_prompt_tokens: 0,
            reasoning_effort: "none".to_string(),
            temperature: 0.6,
            top_p: 0.95,
            top_k: 20,
            activities: Vec::new(),
            next_activity_id: 0,
            pending_yield: false,
            pending_model_switch: None,
            pending_dmn_pause: false,
            provenance: "manual".to_string(),
            conversation_log,
            context,
            app_config,
            prompt_file,
            session_id,
            generation: 0,
            memory_scoring_in_flight: false,
            active_tools,
            changed: Arc::new(tokio::sync::Notify::new()),
        };

        agent.load_startup_journal();
        agent.load_working_stack();
        agent
    }

    /// Create a lightweight agent forked from this one's context.
    ///
    /// The forked agent shares the same conversation prefix (system prompt,
    /// personality, journal, entries) for KV cache sharing. The caller
    /// appends the subconscious prompt as a user message and runs the turn.
    pub fn fork(&self, tools: Vec<tools::Tool>) -> Self {

        Self {
            client: self.client.clone(),
            tools,
            last_prompt_tokens: 0,
            reasoning_effort: "none".to_string(),
            temperature: self.temperature,
            top_p: self.top_p,
            top_k: self.top_k,
            activities: Vec::new(),
            next_activity_id: 0,
            pending_yield: false,
            pending_model_switch: None,
            pending_dmn_pause: false,
            provenance: self.provenance.clone(),
            conversation_log: None,
            context: self.context.clone(),
            app_config: self.app_config.clone(),
            prompt_file: self.prompt_file.clone(),
            session_id: self.session_id.clone(),
            generation: 0,
            memory_scoring_in_flight: false,
            active_tools: tools::shared_active_tools(),
            changed: Arc::new(tokio::sync::Notify::new()),
        }
    }

    /// Assemble the full message list for the API call from typed sources.
    /// System prompt + personality context + journal + conversation messages.
    pub fn assemble_api_messages(&self) -> Vec<Message> {
        let mut msgs = Vec::new();
        // System section
        for e in self.context.system.entries() {
            msgs.push(e.entry.api_message().clone());
        }
        // Identity — render personality files + working stack into one user message
        let ctx = self.context.render_context_message();
        if !ctx.is_empty() {
            msgs.push(Message::user(ctx));
        }
        // Journal — render into one user message
        let jnl = self.context.render_journal();
        if !jnl.is_empty() {
            msgs.push(Message::user(jnl));
        }
        // Conversation entries
        msgs.extend(self.context.conversation.entries().iter()
            .filter(|e| !e.entry.is_log() && !e.entry.is_thinking())
            .map(|e| e.entry.api_message().clone()));
        msgs
    }

    /// Assemble the full prompt as token IDs for the completions API.
    /// System section (includes tools), identity, journal, conversation,
    /// then the assistant prompt suffix.
    pub fn assemble_prompt_tokens(&self) -> Vec<u32> {
        let mut tokens = Vec::new();

        // System section — includes system prompt + tool definitions
        for e in self.context.system.entries() {
            tokens.extend(&e.token_ids);
        }

        // Identity — rendered as one user message
        let ctx = self.context.render_context_message();
        if !ctx.is_empty() {
            tokens.extend(tokenizer::tokenize_entry("user", &ctx));
        }

        // Journal — rendered as one user message
        let jnl = self.context.render_journal();
        if !jnl.is_empty() {
            tokens.extend(tokenizer::tokenize_entry("user", &jnl));
        }

        // Conversation entries — use cached token_ids
        for e in self.context.conversation.entries() {
            if e.entry.is_log() || e.entry.is_thinking() { continue; }
            tokens.extend(&e.token_ids);
        }

        // Prompt the assistant to respond
        tokens.push(tokenizer::IM_START);
        tokens.extend(tokenizer::encode("assistant\n"));

        tokens
    }

    /// Run agent orchestration cycle, returning structured output.
    /// Push a conversation message — stamped and logged.
    pub fn push_message(&mut self, mut msg: Message) {
        msg.stamp();
        let entry = ConversationEntry::Message(msg);
        self.push_entry(entry);
    }

    pub fn push_entry(&mut self, entry: ConversationEntry) {
        if let Some(ref log) = self.conversation_log {
            if let Err(e) = log.append(&entry) {
                eprintln!("warning: failed to log entry: {:#}", e);
            }
        }
        self.context.conversation.push(ContextEntry::new(
            entry, Some(chrono::Utc::now())));

        self.changed.notify_one();
    }

    /// Find the index of the in-progress streaming entry (unstamped assistant message).
    fn streaming_index(&self) -> Option<usize> {
        self.context.conversation.entries().iter().rposition(|ce| {
            if ce.token_ids.is_empty() { return false; }
            let m = ce.entry.message();
            m.role == Role::Assistant && m.timestamp.is_none()
        })
    }

    /// Append streaming text to the last entry (creating a partial
    /// assistant entry if needed). Called by collect_stream per token batch.
    fn append_streaming(&mut self, text: &str) {
        if let Some(idx) = self.streaming_index() {
            assert!(!self.context.conversation.entries()[idx].token_ids.is_empty(),
                "streaming_index returned entry with empty token_ids at {}", idx);
            let mut msg = self.context.conversation.entries()[idx].entry.message().clone();
            msg.append_content(text);
            self.context.conversation.set_message(idx, msg);
        } else {
            self.context.conversation.push(ContextEntry::new(
                ConversationEntry::Message(Message {
                    role: Role::Assistant,
                    content: Some(MessageContent::Text(text.to_string())),
                    tool_calls: None,
                    tool_call_id: None,
                    name: None,
                    timestamp: None,
                }),
                None,
            ));
        }

        self.changed.notify_one();
    }

    /// Finalize the streaming entry with the complete response message.
    /// Finds the unstamped assistant entry, replaces it via set() with proper token count.
    fn finalize_streaming(&mut self, msg: Message) {
        if let Some(i) = self.streaming_index() {
            let mut stamped = msg.clone();
            stamped.stamp();
            self.context.conversation.set(i, ContextEntry::new(
                ConversationEntry::Message(stamped),
                Some(chrono::Utc::now()),
            ));
        } else {
            self.push_message(msg.clone());
        }

        // Log the finalized entry
        if let Some(ref log) = self.conversation_log {
            let entry = ConversationEntry::Message(msg);
            if let Err(e) = log.append(&entry) {
                eprintln!("warning: failed to log finalized entry: {:#}", e);
            }
        }

        self.changed.notify_one();
    }

    /// Send a user message and run the agent loop until the model
    /// produces a text response (no more tool calls). Streams text
    /// and tool activity through the UI channel.
    ///
    /// Takes Arc<Mutex<Agent>> and manages locking internally so the
    /// lock is never held across I/O (API streaming, tool dispatch).
    pub async fn turn(
        agent: Arc<tokio::sync::Mutex<Agent>>,
    ) -> Result<TurnResult> {
        // --- Pre-loop setup (lock 1): collect finished tools ---
        let active_tools = {
            let mut finished = Vec::new();
            let tools = {
                let me = agent.lock().await;

                // Collect completed background tool handles — remove from active list
                // but don't await yet (MutexGuard isn't Send).
                let mut tools = me.active_tools.lock().unwrap();
                let mut i = 0;
                while i < tools.len() {
                    if tools[i].handle.is_finished() {
                        finished.push(tools.remove(i));
                    } else {
                        i += 1;
                    }
                }

                me.active_tools.clone()
            };

            // Await finished handles without holding the agent lock
            let mut bg_results = Vec::new();
            for entry in finished {
                if let Ok((call, output)) = entry.handle.await {
                    bg_results.push((call, output));
                }
            }

            // Re-acquire to apply background tool results
            if !bg_results.is_empty() {
                let mut me = agent.lock().await;
                let mut bg_ds = DispatchState::new();
                for (call, output) in bg_results {
                    me.apply_tool_result(&call, output, &mut bg_ds);
                }
            }

            tools
        };

        let mut overflow_retries: u32 = 0;
        let mut empty_retries: u32 = 0;
        let mut ds = DispatchState::new();

        loop {
            // --- Lock 2: assemble messages, start stream ---
            let _thinking = start_activity(&agent, "thinking...").await;
            let (mut rx, _stream_guard) = {
                let me = agent.lock().await;
                let sampling = api::SamplingParams {
                    temperature: me.temperature,
                    top_p: me.top_p,
                    top_k: me.top_k,
                };
                if tokenizer::is_initialized() {
                    let prompt_tokens = me.assemble_prompt_tokens();
                    me.client.start_stream_completions(
                        &prompt_tokens,
                        sampling,
                        None,
                    )
                } else {
                    let api_messages = me.assemble_api_messages();
                    me.client.start_stream(
                        &api_messages,
                        &me.tools,
                        &me.reasoning_effort,
                        sampling,
                        None,
                    )
                }
            };
            // --- Lock released ---

            // --- Stream loop (no lock) ---
            let sr = api::collect_stream(
                &mut rx, &agent, &active_tools,
            ).await;
            let api::StreamResult {
                content, tool_calls, usage, finish_reason,
                error: stream_error, display_buf, in_tool_call, reasoning,
            } = sr;
            // --- Stream complete ---

            // Push thinking entry if model produced reasoning
            if !reasoning.is_empty() {
                let mut me = agent.lock().await;
                me.push_entry(context::ConversationEntry::Thinking(reasoning));
            }

            // --- Lock 3: process results ---
            let (msg, pending) = {
                let mut me = agent.lock().await;

                // Handle stream errors with retry logic
                if let Some(e) = stream_error {
                    let err = anyhow::anyhow!("{}", e);
                    if crate::agent::context::is_context_overflow(&err) && overflow_retries < 2 {
                        overflow_retries += 1;
                        me.notify(format!("context overflow — retrying ({}/2)", overflow_retries));
                        me.compact();
                        continue;
                    }
                    if crate::agent::context::is_stream_error(&err) && empty_retries < 2 {
                        empty_retries += 1;
                        me.notify(format!("stream error — retrying ({}/2)", empty_retries));
                        drop(me);
                        tokio::time::sleep(std::time::Duration::from_secs(2)).await;
                        continue;
                    }
                    return Err(err);
                }

                if finish_reason.as_deref() == Some("error") {
                    let detail = if content.is_empty() { "no details".into() } else { content };
                    return Err(anyhow::anyhow!("model stream error: {}", detail));
                }

                // Flush remaining display buffer to streaming entry
                if !in_tool_call && !display_buf.is_empty() {
                    me.append_streaming(&display_buf);
                }

                let msg = api::build_response_message(content, tool_calls);

                if let Some(usage) = &usage {
                    me.last_prompt_tokens = usage.prompt_tokens;
                }

                // Empty response — nudge and retry
                let has_content = msg.content.is_some();
                let has_tools = msg.tool_calls.as_ref().map_or(false, |tc| !tc.is_empty());
                if !has_content && !has_tools {
                    if empty_retries < 2 {
                        empty_retries += 1;
                        dbglog!(
                            "empty response, injecting nudge and retrying ({}/2)",
                            empty_retries,
                        );
                        me.push_message(Message::user(
                            "[system] Your previous response was empty. \
                             Please respond with text or use a tool."
                        ));
                        continue;
                    }
                } else {
                    empty_retries = 0;
                }

                // Collect non-background tool calls fired during streaming
                let mut tools_guard = active_tools.lock().unwrap();
                let mut non_bg = Vec::new();
                let mut i = 0;
                while i < tools_guard.len() {
                    if !tools_guard[i].background {
                        non_bg.push(tools_guard.remove(i));
                    } else {
                        i += 1;
                    }
                }
                (msg, non_bg)
            };

            if !pending.is_empty() {
                agent.lock().await.finalize_streaming(msg.clone());

                // Drop lock before awaiting tool handles
                let mut results = Vec::new();
                for entry in pending {
                    if let Ok(r) = entry.handle.await {
                        results.push(r);
                    }
                }
                // Reacquire to apply results
                let mut me = agent.lock().await;
                for (call, output) in results {
                    me.apply_tool_result(&call, output, &mut ds);
                }
                continue;
            }

            // Tool calls (structured API path)
            if let Some(ref tool_calls) = msg.tool_calls {
                if !tool_calls.is_empty() {
                    agent.lock().await.finalize_streaming(msg.clone());
                    let calls: Vec<ToolCall> = tool_calls.clone();
                    // Drop lock before tool dispatch
                    for call in &calls {
                        Agent::dispatch_tool_call_unlocked(
                            &agent, &active_tools, call, &mut ds,
                        ).await;
                    }
                    continue;
                }
            }

            // Genuinely text-only response
            let text = msg.content_text().to_string();
            let mut me = agent.lock().await;
            me.finalize_streaming(msg);

            // Drain pending control flags
            if me.pending_yield { ds.yield_requested = true; me.pending_yield = false; }
            if me.pending_model_switch.is_some() { ds.model_switch = me.pending_model_switch.take(); }
            if me.pending_dmn_pause { ds.dmn_pause = true; me.pending_dmn_pause = false; }

            return Ok(TurnResult {
                text,
                yield_requested: ds.yield_requested,
                had_tool_calls: ds.had_tool_calls,
                tool_errors: ds.tool_errors,
                model_switch: ds.model_switch,
                dmn_pause: ds.dmn_pause,
            });
        }
    }

    /// Dispatch a tool call without holding the agent lock across I/O.
    /// Used by `turn()` which manages its own locking.
    async fn dispatch_tool_call_unlocked(
        agent: &Arc<tokio::sync::Mutex<Agent>>,
        active_tools: &tools::SharedActiveTools,
        call: &ToolCall,
        ds: &mut DispatchState,
    ) {
        let args: serde_json::Value = match serde_json::from_str(&call.function.arguments) {
            Ok(v) => v,
            Err(e) => {
                let err = format!("Error: malformed tool call arguments: {e}");
                let _act = start_activity(agent, format!("rejected: {} (bad args)", call.function.name)).await;
                let mut me = agent.lock().await;
                me.apply_tool_result(call, err, ds);
                return;
            }
        };

        let args_summary = summarize_args(&call.function.name, &args);
        let _calling = start_activity(agent, format!("calling: {}", call.function.name)).await;

        // Spawn tool, track it
        let call_clone = call.clone();
        let agent_handle = agent.clone();
        let handle = tokio::spawn(async move {
            let output = tools::dispatch_with_agent(&call_clone.function.name, &args, Some(agent_handle)).await;
            (call_clone, output)
        });
        active_tools.lock().unwrap().push(
            tools::ActiveToolCall {
                id: call.id.clone(),
                name: call.function.name.clone(),
                detail: args_summary,
                started: std::time::Instant::now(),
                background: false,
                handle,
            }
        );

        // Pop it back and await — no agent lock held
        let entry = {
            let mut tools = active_tools.lock().unwrap();
            tools.pop().unwrap()
        };
        if let Ok((call, output)) = entry.handle.await {
            // Brief lock to apply result
            let mut me = agent.lock().await;
            me.apply_tool_result(&call, output, ds);
        }
    }

    /// Apply a completed tool result to conversation state.
    fn apply_tool_result(
        &mut self,
        call: &ToolCall,
        output: String,
        ds: &mut DispatchState,
    ) {
        let args: serde_json::Value =
            serde_json::from_str(&call.function.arguments).unwrap_or_default();

        ds.had_tool_calls = true;
        if output.starts_with("Error:") {
            ds.tool_errors += 1;
        }

        self.active_tools.lock().unwrap().retain(|t| t.id != call.id);

        // Tag memory_render results for context deduplication
        if call.function.name == "memory_render" && !output.starts_with("Error:") {
            if let Some(key) = args.get("key").and_then(|v| v.as_str()) {
                let mut msg = Message::tool_result(&call.id, &output);
                msg.stamp();
                self.push_entry(ConversationEntry::Memory { key: key.to_string(), message: msg, score: None });
                return;
            }
        }

        self.push_message(Message::tool_result(&call.id, &output));
    }


    /// Context state sections — just returns references to the live data.
    pub fn context_sections(&self) -> [&ContextSection; 4] {
        self.context.sections()
    }

    /// Conversation entries from `from` onward — used by the
    /// subconscious debug screen to show forked agent conversations.
    pub fn conversation_entries_from(&self, from: usize) -> &[ContextEntry] {
        let entries = self.context.conversation.entries();
        if from < entries.len() { &entries[from..] } else { &[] }
    }

    /// Load recent journal entries at startup for orientation.
    /// Uses the same budget logic as compaction but with empty conversation.
    /// Only parses the tail of the journal file (last 64KB) for speed.
    fn load_startup_journal(&mut self) {
        let store = match crate::store::Store::load() {
            Ok(s) => s,
            Err(_) => return,
        };

        // Find oldest message timestamp in conversation log
        let oldest_msg_ts = self.conversation_log.as_ref()
            .and_then(|log| log.oldest_timestamp());

        // Get journal entries from the memory graph
        let mut journal_nodes: Vec<_> = store.nodes.values()
            .filter(|n| n.node_type == crate::store::NodeType::EpisodicSession)
            .collect();
        let mut dbg = std::fs::OpenOptions::new().create(true).append(true)
                .open("/tmp/poc-journal-debug.log").ok();
        macro_rules! dbg_log {
            ($($arg:tt)*) => {
                if let Some(ref mut f) = dbg { use std::io::Write; let _ = writeln!(f, $($arg)*); }
            }
        }
        dbg_log!("[journal] {} nodes, oldest_msg={:?}", journal_nodes.len(), oldest_msg_ts);

        journal_nodes.sort_by_key(|n| n.created_at);
        if let Some(first) = journal_nodes.first() {
            dbg_log!("[journal] first created_at={}", first.created_at);
        }
        if let Some(last) = journal_nodes.last() {
            dbg_log!("[journal] last created_at={}", last.created_at);
        }

        // Find the cutoff index — entries older than conversation, plus one overlap
        let cutoff_idx = if let Some(cutoff) = oldest_msg_ts {
            let cutoff_ts = cutoff.timestamp();
            dbg_log!("[journal] cutoff timestamp={}", cutoff_ts);
            let mut idx = journal_nodes.len();
            for (i, node) in journal_nodes.iter().enumerate() {
                if node.created_at >= cutoff_ts {
                    idx = i + 1;
                    break;
                }
            }
            idx
        } else {
            journal_nodes.len()
        };
        dbg_log!("[journal] cutoff_idx={}", cutoff_idx);

        // Walk backwards from cutoff, accumulating entries within 15% of context
        let context_window = crate::agent::context::context_window();
        let journal_budget = context_window * 15 / 100;
        dbg_log!("[journal] budget={} tokens ({}*15%)", journal_budget, context_window);

        let mut journal_entries = Vec::new();
        let mut total_tokens = 0;

        for node in journal_nodes[..cutoff_idx].iter().rev() {
            let msg = Message::user(&node.content);
            let ce = ContextEntry::new(
                ConversationEntry::Message(msg),
                chrono::DateTime::from_timestamp(node.created_at, 0),
            );
            if total_tokens + ce.tokens() > journal_budget && !journal_entries.is_empty() {
                break;
            }
            total_tokens += ce.tokens();
            journal_entries.push(ce);
        }
        journal_entries.reverse();
        dbg_log!("[journal] loaded {} entries, {} tokens", journal_entries.len(), total_tokens);

        if journal_entries.is_empty() {
            dbg_log!("[journal] no entries!");
            return;
        }

        self.context.journal.clear();
        for entry in journal_entries {
            self.context.journal.push(entry);
        }
        dbg_log!("[journal] context.journal now has {} entries", self.context.journal.len());
    }

    /// Called after any change to context state (working stack, etc).
    /// Load working stack from disk.
    fn load_working_stack(&mut self) {
        if let Ok(data) = std::fs::read_to_string(working_stack::file_path()) {
            if let Ok(stack) = serde_json::from_str::<Vec<String>>(&data) {
                self.context.working_stack = stack;
            }
        }
    }

    /// Replace base64 image data in older messages with text placeholders.
    /// Keeps the 2 most recent images live (enough for motion/comparison).
    /// The tool result message before each image records what was loaded.
    pub fn age_out_images(&mut self) {
        // Find image entries newest-first, skip 1 (caller is about to add another)
        let to_age: Vec<usize> = self.context.conversation.entries().iter().enumerate()
            .rev()
            .filter(|(_, ce)| {
                if let Some(MessageContent::Parts(parts)) = &ce.entry.message().content {
                    parts.iter().any(|p| matches!(p, ContentPart::ImageUrl { .. }))
                } else { false }
            })
            .map(|(i, _)| i)
            .skip(1) // keep 1 existing + 1 about to be added = 2 live
            .collect();

        for i in to_age {
            // Build replacement entry with image data stripped
            let old = &self.context.conversation.entries()[i];
            let msg = old.entry.message();
            if let Some(MessageContent::Parts(parts)) = &msg.content {
                let mut replacement = String::new();
                for part in parts {
                    match part {
                        ContentPart::Text { text } => {
                            if !replacement.is_empty() { replacement.push('\n'); }
                            replacement.push_str(text);
                        }
                        ContentPart::ImageUrl { .. } => {
                            if !replacement.is_empty() { replacement.push('\n'); }
                            replacement.push_str("[image aged out]");
                        }
                    }
                }
                let mut new_msg = msg.clone();
                new_msg.content = Some(MessageContent::Text(replacement));
                self.context.conversation.set(i, ContextEntry::new(
                    ConversationEntry::Message(new_msg),
                    old.timestamp,
                ));
            }
        }
        self.generation += 1;
    }

    /// Strip ephemeral tool calls from the conversation history.
    ///
    /// Last prompt token count reported by the API.
    pub fn last_prompt_tokens(&self) -> u32 {
        self.last_prompt_tokens
    }

    /// Rebuild the context window: reload identity, dedup, trim, reload journal.
    pub fn compact(&mut self) {
        // Reload identity from config
        match crate::config::reload_for_model(&self.app_config, &self.prompt_file) {
            Ok((system_prompt, personality)) => {
                self.context.system.clear();
                self.context.system.push(ContextEntry::new(
                    ConversationEntry::System(Message::system(&system_prompt)), None));
                self.context.identity.clear();
                for (_name, content) in &personality {
                    self.context.identity.push(ContextEntry::new(
                        ConversationEntry::Message(Message::user(content)), None));
                }
            }
            Err(e) => {
                eprintln!("warning: failed to reload identity: {:#}", e);
            }
        }

        let before = self.context.conversation.len();
        let before_mem = self.context.conversation.entries().iter()
            .filter(|e| e.entry.is_memory()).count();
        let before_conv = before - before_mem;

        // Age out images before trimming — they're huge in the request payload
        self.age_out_images();

        // Load journal BEFORE trimming so trim accounts for journal cost
        self.load_startup_journal();

        // Dedup memory, trim to budget
        let fixed = self.context.system.tokens() + self.context.identity.tokens()
            + self.context.journal.tokens();
        self.context.conversation.trim(fixed);

        let after = self.context.conversation.len();
        let after_mem = self.context.conversation.entries().iter()
            .filter(|e| e.entry.is_memory()).count();
        let after_conv = after - after_mem;

        dbglog!("[compact] entries: {} → {} (mem: {} → {}, conv: {} → {})",
            before, after, before_mem, after_mem, before_conv, after_conv);
        self.generation += 1;
        self.last_prompt_tokens = 0;

        dbglog!("[compact] budget: {}", self.context.format_budget());
    }

    /// Restore from the conversation log. Builds the context window
    /// the same way compact() does — journal summaries for old messages,
    /// raw recent messages. This is the unified startup path.
    /// Returns true if the log had content to restore.
    pub fn restore_from_log(&mut self) -> bool {
        let entries = match &self.conversation_log {
            Some(log) => match log.read_tail(64 * 1024 * 1024) {
                Ok(entries) if !entries.is_empty() => entries,
                _ => return false,
            },
            None => return false,
        };

        // Load extra — compact() will dedup, trim, reload identity + journal
        let all: Vec<ContextEntry> = entries.into_iter()
            .filter(|e| !e.is_log() && !e.is_thinking() && e.message().role != Role::System)
            .map(|e| {
                let timestamp = if e.is_log() || e.is_thinking() { None } else {
                    e.message().timestamp.as_ref().and_then(|ts| {
                        chrono::DateTime::parse_from_rfc3339(ts).ok()
                            .map(|dt| dt.with_timezone(&chrono::Utc))
                    })
                };
                ContextEntry::new(e, timestamp)
            })
            .collect();
        let mem_count = all.iter().filter(|e| e.entry.is_memory()).count();
        let conv_count = all.len() - mem_count;
        dbglog!("[restore] loaded {} entries from log (mem: {}, conv: {})",
            all.len(), mem_count, conv_count);
        self.context.conversation.set_entries(all);
        self.compact();
        // Estimate prompt tokens so status bar isn't 0 on startup
        self.last_prompt_tokens = self.context.total_tokens() as u32;
        true
    }

    /// Replace the API client (for model switching).
    pub fn swap_client(&mut self, new_client: ApiClient) {
        self.client = new_client;
    }

    /// Get the model identifier.
    pub fn model(&self) -> &str {
        &self.client.model
    }

    /// Get the conversation entries.
    pub fn entries(&self) -> &[ContextEntry] {
        self.context.conversation.entries()
    }

    /// Mutable access to conversation entries (for /retry).
    pub fn client_clone(&self) -> ApiClient {
        self.client.clone()
    }



}