// Agent definitions: self-contained files with query + prompt template.
//
// Each agent is a file in the agents/ directory:
//   - First line: JSON header (agent, query, model, schedule)
//   - After blank line: prompt template with {{placeholder}} lookups
//
// Placeholders are resolved at runtime:
//   {{topology}}  — graph topology header
//   {{nodes}}     — query results formatted as node sections
//   {{episodes}}  — alias for {{nodes}}
//   {{health}}    — graph health report
//   {{pairs}}     — interference pairs from detect_interference
//   {{rename}}    — rename candidates
//   {{split}}     — split detail for the first query result
//
// The query selects what to operate on; placeholders pull in context.

use crate::graph::Graph;
use crate::neuro::{consolidation_priority, ReplayItem};
use crate::search;
use crate::store::Store;

use serde::Deserialize;

use std::path::PathBuf;

/// Agent definition: config (from JSON header) + prompt (raw markdown body).
#[derive(Clone, Debug)]
pub struct AgentDef {
    pub agent: String,
    pub query: String,
    pub prompt: String,
    pub model: String,
    pub schedule: String,
    pub tools: Vec<String>,
}

/// The JSON header portion (first line of the file).
#[derive(Deserialize)]
struct AgentHeader {
    agent: String,
    #[serde(default)]
    query: String,
    #[serde(default = "default_model")]
    model: String,
    #[serde(default)]
    schedule: String,
    #[serde(default)]
    tools: Vec<String>,
}

fn default_model() -> String { "sonnet".into() }

/// Parse an agent file: first line is JSON config, rest is the prompt.
fn parse_agent_file(content: &str) -> Option<AgentDef> {
    let (first_line, rest) = content.split_once('\n')?;
    let header: AgentHeader = serde_json::from_str(first_line.trim()).ok()?;
    // Skip optional blank line between header and prompt body
    let prompt = rest.strip_prefix('\n').unwrap_or(rest);
    Some(AgentDef {
        agent: header.agent,
        query: header.query,
        prompt: prompt.to_string(),
        model: header.model,
        schedule: header.schedule,
        tools: header.tools,
    })
}

fn agents_dir() -> PathBuf {
    let repo = PathBuf::from(env!("CARGO_MANIFEST_DIR")).join("agents");
    if repo.is_dir() { return repo; }
    crate::store::memory_dir().join("agents")
}

/// Load all agent definitions.
pub fn load_defs() -> Vec<AgentDef> {
    let dir = agents_dir();
    let Ok(entries) = std::fs::read_dir(&dir) else { return Vec::new() };

    entries
        .filter_map(|e| e.ok())
        .filter(|e| {
            let p = e.path();
            p.extension().map(|x| x == "agent" || x == "md").unwrap_or(false)
        })
        .filter_map(|e| {
            let content = std::fs::read_to_string(e.path()).ok()?;
            parse_agent_file(&content)
        })
        .collect()
}

/// Look up a single agent definition by name.
pub fn get_def(name: &str) -> Option<AgentDef> {
    let dir = agents_dir();
    for ext in ["agent", "md"] {
        let path = dir.join(format!("{}.{}", name, ext));
        if let Ok(content) = std::fs::read_to_string(&path) {
            if let Some(def) = parse_agent_file(&content) {
                return Some(def);
            }
        }
    }
    load_defs().into_iter().find(|d| d.agent == name)
}

/// Result of resolving a placeholder: text + any affected node keys.
struct Resolved {
    text: String,
    keys: Vec<String>,
}

/// Resolve a single {{placeholder}} by name.
/// Returns the replacement text and any node keys it produced (for visit tracking).
fn resolve(
    name: &str,
    store: &Store,
    graph: &Graph,
    keys: &[String],
    count: usize,
) -> Option<Resolved> {
    match name {
        "topology" => Some(Resolved {
            text: super::prompts::format_topology_header(graph),
            keys: vec![],
        }),

        "nodes" | "episodes" => {
            let items = keys_to_replay_items(store, keys, graph);
            Some(Resolved {
                text: super::prompts::format_nodes_section(store, &items, graph),
                keys: vec![], // keys already tracked from query
            })
        }

        "health" => Some(Resolved {
            text: super::prompts::format_health_section(store, graph),
            keys: vec![],
        }),

        "pairs" => {
            let mut pairs = crate::neuro::detect_interference(store, graph, 0.5);
            pairs.truncate(count);
            let pair_keys: Vec<String> = pairs.iter()
                .flat_map(|(a, b, _)| vec![a.clone(), b.clone()])
                .collect();
            Some(Resolved {
                text: super::prompts::format_pairs_section(&pairs, store, graph),
                keys: pair_keys,
            })
        }

        "rename" => {
            let (rename_keys, section) = super::prompts::format_rename_candidates(store, count);
            Some(Resolved { text: section, keys: rename_keys })
        }

        "split" => {
            let key = keys.first()?;
            Some(Resolved {
                text: super::prompts::format_split_plan_node(store, graph, key),
                keys: vec![], // key already tracked from query
            })
        }

        "organize" => {
            // Run cluster diagnostic for the query term
            // The query field of the agent def holds the search term
            let term = if keys.is_empty() { "" } else { &keys[0] };
            if term.is_empty() {
                return Some(Resolved { text: "(no term provided)".into(), keys: vec![] });
            }
            let term_lower = term.to_lowercase();
            let skip_prefixes = ["journal#", "daily-", "weekly-", "monthly-", "_",
                                 "deep-index#", "facts-", "irc-history#"];

            let mut cluster: Vec<(String, String)> = Vec::new();
            for (key, node) in &store.nodes {
                if node.deleted { continue; }
                if !key.to_lowercase().contains(&term_lower) { continue; }
                if skip_prefixes.iter().any(|p| key.starts_with(p)) { continue; }
                cluster.push((key.clone(), node.content.clone()));
            }
            cluster.sort_by(|a, b| a.0.cmp(&b.0));

            // Cap cluster size — agent has tools to explore more if needed
            if cluster.len() > 20 {
                cluster.truncate(20);
            }

            // Similarity pairs
            let pairs = crate::similarity::pairwise_similar(&cluster, 0.4);

            let mut text = format!("### Cluster: '{}' ({} nodes)\n\n", term, cluster.len());

            // Similarity report
            if !pairs.is_empty() {
                text.push_str("#### Similarity scores\n\n");
                for (a, b, sim) in &pairs {
                    text.push_str(&format!("  [{:.3}] {} ↔ {}\n", sim, a, b));
                }
                text.push('\n');
            }

            // Connectivity
            let cluster_keys: std::collections::HashSet<&str> = cluster.iter()
                .map(|(k,_)| k.as_str()).collect();
            let mut best_hub: Option<(&str, usize)> = None;
            for key in &cluster_keys {
                let intra = graph.neighbor_keys(key).iter()
                    .filter(|n| cluster_keys.contains(*n))
                    .count();
                if best_hub.is_none() || intra > best_hub.unwrap().1 {
                    best_hub = Some((key, intra));
                }
            }
            if let Some((hub, deg)) = best_hub {
                text.push_str(&format!("#### Hub: {} (intra-cluster degree {})\n\n", hub, deg));
                let hub_nbrs = graph.neighbor_keys(hub);
                for key in &cluster_keys {
                    if *key == hub { continue; }
                    if !hub_nbrs.contains(*key) {
                        text.push_str(&format!("  NOT linked to hub: {}\n", key));
                    }
                }
                text.push('\n');
            }

            // Full node contents
            text.push_str("#### Node contents\n\n");
            let mut result_keys = Vec::new();
            for (key, content) in &cluster {
                let words = content.split_whitespace().count();
                text.push_str(&format!("##### {} ({} words)\n\n{}\n\n---\n\n", key, words, content));
                result_keys.push(key.clone());
            }

            Some(Resolved { text, keys: result_keys })
        }

        "conversations" => {
            let fragments = super::knowledge::select_conversation_fragments(count);
            let text = fragments.iter()
                .map(|(id, text)| format!("### Session {}\n\n{}", id, text))
                .collect::<Vec<_>>()
                .join("\n\n---\n\n");
            Some(Resolved { text, keys: vec![] })
        }

        "siblings" | "neighborhood" => {
            let mut seen: std::collections::HashSet<String> = keys.iter().cloned().collect();
            let mut siblings = Vec::new();
            for key in keys {
                for (neighbor, _) in graph.neighbors(key) {
                    if seen.insert(neighbor.clone()) {
                        if let Some(node) = store.nodes.get(neighbor.as_str()) {
                            siblings.push((neighbor.clone(), node.content.clone()));
                        }
                    }
                    if siblings.len() >= count { break; }
                }
                if siblings.len() >= count { break; }
            }
            let text = if siblings.is_empty() {
                String::new()
            } else {
                let mut out = String::from("## Sibling nodes (one hop in graph)\n\n");
                for (key, content) in &siblings {
                    out.push_str(&format!("### {}\n{}\n\n", key, content));
                }
                out
            };
            Some(Resolved { text, keys: vec![] })
        }

        // targets/context: aliases for challenger-style presentation
        "targets" => {
            let items = keys_to_replay_items(store, keys, graph);
            Some(Resolved {
                text: super::prompts::format_nodes_section(store, &items, graph),
                keys: vec![],
            })
        }

        _ => None,
    }
}

/// Resolve all {{placeholder}} patterns in a prompt template.
/// Returns the resolved text and all node keys collected from placeholders.
pub fn resolve_placeholders(
    template: &str,
    store: &Store,
    graph: &Graph,
    keys: &[String],
    count: usize,
) -> (String, Vec<String>) {
    let mut result = template.to_string();
    let mut extra_keys = Vec::new();
    loop {
        let Some(start) = result.find("{{") else { break };
        let Some(end) = result[start + 2..].find("}}") else { break };
        let end = start + 2 + end;
        let name = result[start + 2..end].trim().to_lowercase();
        match resolve(&name, store, graph, keys, count) {
            Some(resolved) => {
                extra_keys.extend(resolved.keys);
                result.replace_range(start..end + 2, &resolved.text);
            }
            None => {
                let msg = format!("(unknown: {})", name);
                result.replace_range(start..end + 2, &msg);
            }
        }
    }
    (result, extra_keys)
}

/// Run a config-driven agent: query → resolve placeholders → prompt.
pub fn run_agent(
    store: &Store,
    def: &AgentDef,
    count: usize,
) -> Result<super::prompts::AgentBatch, String> {
    let graph = store.build_graph();

    // Run the query if present
    let keys = if !def.query.is_empty() {
        let mut stages = search::Stage::parse_pipeline(&def.query)?;
        let has_limit = stages.iter().any(|s|
            matches!(s, search::Stage::Transform(search::Transform::Limit(_))));
        if !has_limit {
            stages.push(search::Stage::Transform(search::Transform::Limit(count)));
        }
        let results = search::run_query(&stages, vec![], &graph, store, false, count);
        if results.is_empty() {
            return Err(format!("{}: query returned no results", def.agent));
        }
        results.into_iter().map(|(k, _)| k).collect::<Vec<_>>()
    } else {
        vec![]
    };

    let (prompt, extra_keys) = resolve_placeholders(&def.prompt, store, &graph, &keys, count);

    // Merge query keys with any keys produced by placeholder resolution
    let mut all_keys = keys;
    all_keys.extend(extra_keys);
    Ok(super::prompts::AgentBatch { prompt, node_keys: all_keys })
}

/// Convert a list of keys to ReplayItems with priority and graph metrics.
pub fn keys_to_replay_items(
    store: &Store,
    keys: &[String],
    graph: &Graph,
) -> Vec<ReplayItem> {
    keys.iter()
        .filter_map(|key| {
            let node = store.nodes.get(key)?;
            let priority = consolidation_priority(store, key, graph, None);
            let cc = graph.clustering_coefficient(key);

            Some(ReplayItem {
                key: key.clone(),
                priority,
                interval_days: node.spaced_repetition_interval,
                emotion: node.emotion,
                cc,
                classification: "unknown",
                outlier_score: 0.0,
            })
        })
        .collect()
}