// context.rs — Context window building and management
//
// Pure functions for building the agent's context window from journal
// entries and conversation messages. No mutable state — all functions
// take inputs and return new values. State mutation happens in agent.rs.

// TODO: move Message, ContextState, etc. to thought layer
use crate::agent::journal;
use crate::agent::types::*;
use chrono::{DateTime, Utc};
use tiktoken_rs::CoreBPE;

/// Look up a model's context window size in tokens.
pub fn model_context_window(model: &str) -> usize {
    let m = model.to_lowercase();
    if m.contains("opus") || m.contains("sonnet") {
        200_000
    } else if m.contains("qwen") {
        131_072
    } else {
        128_000
    }
}

/// Context budget in tokens: 60% of the model's context window.
fn context_budget_tokens(model: &str) -> usize {
    model_context_window(model) * 60 / 100
}

/// Allocation plan for the context window.
pub struct ContextPlan {
    header_start: usize,
    full_start: usize,
    entry_count: usize,
    conv_trim: usize,
    _conv_count: usize,
    _full_tokens: usize,
    _header_tokens: usize,
    _conv_tokens: usize,
    _available: usize,
}

/// Build a context window from conversation messages + journal entries.
///
/// Allocation strategy: identity and memory are fixed costs. The
/// remaining budget (minus 25% reserve for model output) is split
/// between journal and conversation. Conversation gets priority —
/// it's what's happening now. Journal fills the rest, newest first.
///
/// Returns (messages, journal_text) — caller stores journal_text in ContextState.
pub fn build_context_window(
    context: &ContextState,
    conversation: &[Message],
    model: &str,
    tokenizer: &CoreBPE,
) -> (Vec<Message>, String) {
    let journal_path = journal::default_journal_path();
    let all_entries = journal::parse_journal(&journal_path);
    dbglog!("[ctx] {} journal entries from {}", all_entries.len(), journal_path.display());
    let count = |s: &str| tokenizer.encode_with_special_tokens(s).len();

    let system_prompt = context.system_prompt.clone();
    let context_message = context.render_context_message();

    // Cap memory to 50% of the context budget so conversation always
    // gets space. Truncate at the last complete section boundary.
    let max_tokens = context_budget_tokens(model);
    let memory_cap = max_tokens / 2;
    let memory_tokens = count(&context_message);
    let context_message = if memory_tokens > memory_cap {
        dbglog!("[ctx] memory too large: {} tokens > {} cap, truncating", memory_tokens, memory_cap);
        truncate_at_section(&context_message, memory_cap, &count)
    } else {
        context_message
    };

    let recent_start = find_journal_cutoff(conversation, all_entries.last());
    dbglog!("[ctx] journal cutoff: {} of {} conversation messages are 'recent'",
        conversation.len() - recent_start, conversation.len());
    let recent = &conversation[recent_start..];

    let plan = plan_context(
        &system_prompt,
        &context_message,
        recent,
        &all_entries,
        model,
        &count,
    );

    let journal_text = render_journal_text(&all_entries, &plan);
    dbglog!("[ctx] plan: header_start={} full_start={} entry_count={} conv_trim={} journal_text={} chars",
        plan.header_start, plan.full_start, plan.entry_count, plan.conv_trim, journal_text.len());

    let messages = assemble_context(
        system_prompt, context_message, &journal_text,
        recent, &plan,
    );
    (messages, journal_text)
}

pub fn plan_context(
    system_prompt: &str,
    context_message: &str,
    recent: &[Message],
    entries: &[journal::JournalEntry],
    model: &str,
    count: &dyn Fn(&str) -> usize,
) -> ContextPlan {
    let max_tokens = context_budget_tokens(model);

    let identity_cost = count(system_prompt);
    let memory_cost = count(context_message);
    let reserve = max_tokens / 4;
    let available = max_tokens
        .saturating_sub(identity_cost)
        .saturating_sub(memory_cost)
        .saturating_sub(reserve);

    let conv_costs: Vec<usize> = recent.iter().map(|m| msg_token_count_fn(m, count)).collect();
    let total_conv: usize = conv_costs.iter().sum();

    let journal_min = available * 15 / 100;
    let journal_budget = available.saturating_sub(total_conv).max(journal_min);

    let full_budget = journal_budget * 70 / 100;
    let header_budget = journal_budget.saturating_sub(full_budget);

    // Phase 1: Full entries (newest first)
    let mut full_used = 0;
    let mut n_full = 0;
    for entry in entries.iter().rev() {
        let cost = count(&entry.content) + 10;
        if full_used + cost > full_budget {
            break;
        }
        full_used += cost;
        n_full += 1;
    }
    let full_start = entries.len().saturating_sub(n_full);

    // Phase 2: Header-only entries (continuing backward)
    let mut header_used = 0;
    let mut n_headers = 0;
    for entry in entries[..full_start].iter().rev() {
        let first_line = entry
            .content
            .lines()
            .find(|l| !l.trim().is_empty())
            .unwrap_or("(empty)");
        let cost = count(first_line) + 10;
        if header_used + cost > header_budget {
            break;
        }
        header_used += cost;
        n_headers += 1;
    }
    let header_start = full_start.saturating_sub(n_headers);

    // Trim oldest conversation if it exceeds budget
    let journal_used = full_used + header_used;
    let mut conv_trim = 0;
    let mut trimmed_conv = total_conv;
    while trimmed_conv + journal_used > available && conv_trim < recent.len() {
        trimmed_conv -= conv_costs[conv_trim];
        conv_trim += 1;
    }
    // Walk forward to user message boundary
    while conv_trim < recent.len() && recent[conv_trim].role != Role::User {
        conv_trim += 1;
    }

    dbglog!("[plan] model={} max_tokens={} available={} (identity={} memory={} reserve={})",
        model, max_tokens, available, identity_cost, memory_cost, reserve);
    dbglog!("[plan] conv: {} msgs, {} tokens total, trimming {} msgs → {} tokens",
        recent.len(), total_conv, conv_trim, trimmed_conv);
    dbglog!("[plan] journal: {} full entries ({}t) + {} headers ({}t)",
        n_full, full_used, n_headers, header_used);

    ContextPlan {
        header_start,
        full_start,
        entry_count: entries.len(),
        conv_trim,
        _conv_count: recent.len(),
        _full_tokens: full_used,
        _header_tokens: header_used,
        _conv_tokens: trimmed_conv,
        _available: available,
    }
}

pub fn render_journal_text(
    entries: &[journal::JournalEntry],
    plan: &ContextPlan,
) -> String {
    let has_journal = plan.header_start < plan.entry_count;
    if !has_journal {
        return String::new();
    }

    let mut text = String::from("[Earlier in this conversation — from your journal]\n\n");

    for entry in &entries[plan.header_start..plan.full_start] {
        let first_line = entry
            .content
            .lines()
            .find(|l| !l.trim().is_empty())
            .unwrap_or("(empty)");
        text.push_str(&format!(
            "## {} — {}\n",
            entry.timestamp.format("%Y-%m-%dT%H:%M"),
            first_line,
        ));
    }

    let n_headers = plan.full_start - plan.header_start;
    let n_full = plan.entry_count - plan.full_start;
    if n_headers > 0 && n_full > 0 {
        text.push_str("\n---\n\n");
    }

    for entry in &entries[plan.full_start..] {
        text.push_str(&format!(
            "## {}\n\n{}\n\n",
            entry.timestamp.format("%Y-%m-%dT%H:%M"),
            entry.content
        ));
    }

    text
}

fn assemble_context(
    system_prompt: String,
    context_message: String,
    journal_text: &str,
    recent: &[Message],
    plan: &ContextPlan,
) -> Vec<Message> {
    let mut messages = vec![Message::system(system_prompt)];
    if !context_message.is_empty() {
        messages.push(Message::user(context_message));
    }

    let final_recent = &recent[plan.conv_trim..];

    if !journal_text.is_empty() {
        messages.push(Message::user(journal_text.to_string()));
    } else if !final_recent.is_empty() {
        messages.push(Message::user(
            "Your context was just rebuilt. Memory files have been \
             reloaded. Your recent conversation continues below. \
             Earlier context is in your journal and memory files."
                .to_string(),
        ));
    }

    messages.extend(final_recent.iter().cloned());
    messages
}

fn truncate_at_section(text: &str, max_tokens: usize, count: &dyn Fn(&str) -> usize) -> String {
    let mut boundaries = vec![0usize];
    for (i, line) in text.lines().enumerate() {
        if line.trim() == "---" || line.starts_with("## ") {
            let offset = text.lines().take(i).map(|l| l.len() + 1).sum::<usize>();
            boundaries.push(offset);
        }
    }
    boundaries.push(text.len());

    let mut best = 0;
    for &end in &boundaries[1..] {
        let slice = &text[..end];
        if count(slice) <= max_tokens {
            best = end;
        } else {
            break;
        }
    }

    if best == 0 {
        best = text.len().min(max_tokens * 3);
    }

    let truncated = &text[..best];
    dbglog!("[ctx] truncated memory from {} to {} chars ({} tokens)",
        text.len(), truncated.len(), count(truncated));
    truncated.to_string()
}

fn find_journal_cutoff(
    conversation: &[Message],
    newest_entry: Option<&journal::JournalEntry>,
) -> usize {
    let cutoff = match newest_entry {
        Some(entry) => entry.timestamp,
        None => return 0,
    };

    let mut split = conversation.len();
    for (i, msg) in conversation.iter().enumerate() {
        if let Some(ts) = parse_msg_timestamp(msg) {
            if ts > cutoff {
                split = i;
                break;
            }
        }
    }
    while split > 0 && split < conversation.len() && conversation[split].role != Role::User {
        split -= 1;
    }
    split
}

fn msg_token_count_fn(msg: &Message, count: &dyn Fn(&str) -> usize) -> usize {
    let content = msg.content.as_ref().map_or(0, |c| match c {
        MessageContent::Text(s) => count(s),
        MessageContent::Parts(parts) => parts
            .iter()
            .map(|p| match p {
                ContentPart::Text { text } => count(text),
                ContentPart::ImageUrl { .. } => 85,
            })
            .sum(),
    });
    let tools = msg.tool_calls.as_ref().map_or(0, |calls| {
        calls
            .iter()
            .map(|c| count(&c.function.arguments) + count(&c.function.name))
            .sum()
    });
    content + tools
}

/// Count the token footprint of a message using BPE tokenization.
pub fn msg_token_count(tokenizer: &CoreBPE, msg: &Message) -> usize {
    msg_token_count_fn(msg, &|s| tokenizer.encode_with_special_tokens(s).len())
}

/// Detect context window overflow errors from the API.
pub fn is_context_overflow(err: &anyhow::Error) -> bool {
    let msg = err.to_string().to_lowercase();
    msg.contains("context length")
        || msg.contains("token limit")
        || msg.contains("too many tokens")
        || msg.contains("maximum context")
        || msg.contains("prompt is too long")
        || msg.contains("request too large")
        || msg.contains("input validation error")
        || msg.contains("content length limit")
        || (msg.contains("400") && msg.contains("tokens"))
}

/// Detect model/provider errors delivered inside the SSE stream.
pub fn is_stream_error(err: &anyhow::Error) -> bool {
    err.to_string().contains("model stream error")
}

fn parse_msg_timestamp(msg: &Message) -> Option<DateTime<Utc>> {
    msg.timestamp
        .as_ref()
        .and_then(|ts| DateTime::parse_from_rfc3339(ts).ok())
        .map(|dt| dt.with_timezone(&Utc))
}