//! `/api/agents/{name}/inference` — the model, effort and subagent models the
//! swarm sets for one agent, and what the agent reports running on.
//!
//! Each agent's settings are one value under its own key of `agent-inference`
//! (`swarm_queue_client::agent_inference`), which this daemon alone writes.
//! The agent reads its key and applies each set field over its local value;
//! an unset field leaves the local value in force.
//!
//! What the agent runs on comes from its turn-state header
//! (`$SWARM.agent-state.<agent>`), which [`Reported`] keeps the latest of.
//! Agents publish a header when it changes and re-send it once a minute, and
//! the queue keeps none, so an agent has no entry for up to a minute after
//! this daemon starts.

use std::collections::{BTreeSet, HashMap};
use std::sync::{Arc, Mutex, PoisonError};
use std::time::Duration;

use axum::Json;
use axum::extract::{Path, State};
use axum::http::StatusCode;
use futures_util::StreamExt as _;
use problem_details::ProblemDetails;
use serde::{Deserialize, Serialize};
use swarm_queue_client::agent_inference::{self, AgentInference, Effective, Effort, Source};
use utoipa::ToSchema;

use crate::schedules::{live, queue, read, refused, write};
use crate::{AppState, error_problem, wanted_error_status};

/// How many times a losing writer re-reads and re-applies, as in
/// `wanted::MAX_ATTEMPTS`.
const MAX_ATTEMPTS: usize = 5;

/// One agent's inference settings. An absent field is not set at swarm level,
/// and the agent keeps its own value for it.
#[derive(Debug, Clone, Default, PartialEq, Eq, Serialize, Deserialize, ToSchema)]
#[serde(deny_unknown_fields)]
pub struct InferenceSettings {
    /// The model the agent's turns run on, as claude's `--model` takes it.
    #[serde(default, skip_serializing_if = "Option::is_none")]
    model: Option<String>,
    /// One of `low`, `medium`, `high`, `xhigh`, `max`.
    #[serde(default, skip_serializing_if = "Option::is_none")]
    #[schema(value_type = Option<String>)]
    effort: Option<Effort>,
    /// The models the agent may start its subagents on. At least one.
    #[serde(default, skip_serializing_if = "Option::is_none")]
    subagent_models: Option<Vec<String>>,
}

impl From<AgentInference> for InferenceSettings {
    fn from(v: AgentInference) -> Self {
        Self {
            model: v.model,
            effort: v.effort,
            subagent_models: v.subagent_models,
        }
    }
}

/// A model name as the agent passes it to claude: one non-empty word that
/// cannot be read as a command-line flag.
fn check_model(name: &str, what: &str) -> Result<(), String> {
    if name.is_empty() {
        return Err(format!("the {what} is empty"));
    }
    if name.chars().any(|c| c.is_whitespace() || c.is_control()) {
        return Err(format!("the {what} {name:?} contains whitespace"));
    }
    if name.starts_with('-') {
        return Err(format!("the {what} {name:?} starts with \"-\""));
    }
    Ok(())
}

impl InferenceSettings {
    /// The value to store, or why it is refused.
    fn into_stored(self) -> Result<AgentInference, String> {
        if let Some(model) = &self.model {
            check_model(model, "model")?;
        }
        if let Some(models) = &self.subagent_models {
            if models.is_empty() {
                return Err(
                    "subagent_models is empty; leave it out to keep the agent's own list"
                        .to_owned(),
                );
            }
            let mut seen = BTreeSet::new();
            for model in models {
                check_model(model, "subagent model")?;
                if !seen.insert(model) {
                    return Err(format!("subagent model {model:?} is listed twice"));
                }
            }
        }
        Ok(AgentInference {
            model: self.model,
            effort: self.effort,
            subagent_models: self.subagent_models,
        })
    }
}

/// What `GET` answers for one agent.
#[derive(Debug, Serialize, ToSchema)]
pub struct AgentInferenceView {
    /// The settings the swarm sets; `{}` when none is set.
    configured: InferenceSettings,
    /// What the agent reported running on in its latest turn-state header;
    /// `null` when this daemon has received none with these fields since it
    /// started.
    effective: Option<EffectiveInference>,
}

/// The model and effort an agent runs on, and where each comes from.
#[derive(Debug, PartialEq, Eq, Serialize, ToSchema)]
pub struct EffectiveInference {
    model: String,
    effort: String,
    /// `swarm`, `agent_nix`, `local_file` or `default`.
    #[schema(value_type = String)]
    model_source: Source,
    /// As `model_source`.
    #[schema(value_type = String)]
    effort_source: Source,
}

impl From<Effective> for EffectiveInference {
    fn from(v: Effective) -> Self {
        Self {
            model: v.model,
            effort: v.effort,
            model_source: v.model_source,
            effort_source: v.effort_source,
        }
    }
}

/// The latest [`Effective`] each agent reported, by agent.
#[derive(Debug, Default)]
pub(crate) struct Reported {
    latest: Mutex<HashMap<String, Effective>>,
}

impl Reported {
    /// Start recording every agent's turn-state headers from `client`.
    pub(crate) fn spawn(client: async_nats::Client) -> Arc<Self> {
        let reported = Arc::new(Self::default());
        let recording = Arc::clone(&reported);
        tokio::spawn(async move { recording.follow(&client).await });
        reported
    }

    /// Subscribe to every agent's header, and subscribe again if the
    /// subscription ends.
    async fn follow(&self, client: &async_nats::Client) {
        const RETRY: Duration = Duration::from_secs(5);
        let subject = swarm_queue_client::agent_state_subject_wildcard();
        loop {
            match client.subscribe(subject.clone()).await {
                Ok(mut headers) => {
                    tracing::info!(%subject, "inference: following agent turn-state headers");
                    while let Some(msg) = headers.next().await {
                        self.record(&msg.subject, &msg.payload);
                    }
                    tracing::warn!(%subject, "inference: header subscription ended");
                }
                Err(e) => tracing::warn!(%subject, error = %e, "inference: subscribe failed"),
            }
            tokio::time::sleep(RETRY).await;
        }
    }

    /// Keep one header's inference fields. A header without them, from an
    /// agent that does not report them, removes what was kept.
    fn record(&self, subject: &str, payload: &[u8]) {
        let Some(agent) = swarm_queue_client::agent_from_state_subject(subject) else {
            return;
        };
        let mut latest = self.latest.lock().unwrap_or_else(PoisonError::into_inner);
        match serde_json::from_slice::<Effective>(payload) {
            Ok(effective) => {
                latest.insert(agent.to_owned(), effective);
            }
            Err(e) => {
                tracing::debug!(%agent, error = %e, "inference: header has no inference fields");
                latest.remove(agent);
            }
        }
    }

    fn get(&self, agent: &str) -> Option<Effective> {
        self.latest
            .lock()
            .unwrap_or_else(PoisonError::into_inner)
            .get(agent)
            .cloned()
    }
}

fn agent_name(name: &str) -> Result<String, (StatusCode, String)> {
    hive_types::Ident::parse(name)
        .map(hive_types::Ident::into_string)
        .map_err(|reason| (StatusCode::BAD_REQUEST, reason.to_owned()))
}

fn queue_problem(e: &anyhow::Error) -> ProblemDetails {
    tracing::warn!(error = %format!("{e:#}"), "inference: queue failure");
    error_problem(wanted_error_status(e), &format!("{e:#}"))
}

async fn open(
    client: &async_nats::Client,
) -> Result<async_nats::jetstream::kv::Store, ProblemDetails> {
    agent_inference::open_or_create(client)
        .await
        .map_err(|e| queue_problem(&anyhow::Error::new(e)))
}

#[utoipa::path(
    get,
    path = "/api/agents/{name}/inference",
    params(("name" = String, Path, description = "agent name")),
    responses(
        (status = 200, description = "the settings the swarm sets for the agent, and what \
            it reported running on", body = AgentInferenceView),
        (status = 400, description = "not an identifier (problem+json)", body = String),
        (status = 503, description = "no swarm queue is configured on this host, or it is \
            not connected (problem+json)", body = String),
        (status = 500, description = "the settings could not be read (problem+json)",
            body = String),
    ),
    tag = "agents"
)]
pub(crate) async fn get_agent_inference(
    State(state): State<AppState>,
    Path(name): Path<String>,
) -> Result<Json<AgentInferenceView>, ProblemDetails> {
    let agent = agent_name(&name).map_err(refused)?;
    let client = queue(&state).map_err(refused)?;
    let store = open(&client).await?;
    let (current, _) = read::<AgentInference>(&store, &agent)
        .await
        .map_err(|e| queue_problem(&e))?;
    Ok(Json(AgentInferenceView {
        configured: current.into(),
        effective: state
            .reported_inference
            .as_ref()
            .and_then(|r| r.get(&agent))
            .map(Into::into),
    }))
}

#[utoipa::path(
    put,
    path = "/api/agents/{name}/inference",
    params(("name" = String, Path, description = "agent name")),
    request_body = InferenceSettings,
    responses(
        (status = 200, description = "the settings as stored; they replace the previous \
            ones whole", body = InferenceSettings),
        (status = 400, description = "not an identifier, not declared on any hive, or a \
            model name is empty, has whitespace, starts with `-`, or is listed twice \
            (problem+json)",
            body = String),
        (status = 422, description = "an unknown field, or an effort that is not one of \
            the five levels"),
        (status = 503, description = "no swarm queue is configured on this host, or it is \
            not connected (problem+json)", body = String),
        (status = 500, description = "the settings could not be written (problem+json)",
            body = String),
    ),
    tag = "agents"
)]
pub(crate) async fn put_agent_inference(
    State(state): State<AppState>,
    Path(name): Path<String>,
    Json(req): Json<InferenceSettings>,
) -> Result<Json<InferenceSettings>, ProblemDetails> {
    let agent = agent_name(&name).map_err(refused)?;
    let value = req
        .into_stored()
        .map_err(|why| error_problem(StatusCode::BAD_REQUEST, &why))?;
    let client = queue(&state).map_err(refused)?;
    if !live(&state).await?.contains(&agent) {
        return Err(error_problem(
            StatusCode::BAD_REQUEST,
            &format!("no hive's wanted state declares an agent {agent:?} that is not destroyed"),
        ));
    }
    let store = open(&client).await?;
    for _ in 0..MAX_ATTEMPTS {
        let (current, revision) = read::<AgentInference>(&store, &agent)
            .await
            .map_err(|e| queue_problem(&e))?;
        if current == value
            || write(&store, &agent, &value, revision)
                .await
                .map_err(|e| queue_problem(&e))?
        {
            tracing::info!(%agent, ?value, "set inference settings");
            return Ok(Json(value.into()));
        }
    }
    Err(queue_problem(&anyhow::anyhow!(
        "gave up writing the inference settings of {agent} after {MAX_ATTEMPTS} conflicting \
         writes"
    )))
}

#[utoipa::path(
    delete,
    path = "/api/agents/{name}/inference",
    params(("name" = String, Path, description = "agent name")),
    responses(
        (status = 204, description = "cleared; the agent goes back to its own values"),
        (status = 400, description = "not an identifier (problem+json)", body = String),
        (status = 503, description = "no swarm queue is configured on this host, or it is \
            not connected (problem+json)", body = String),
        (status = 500, description = "the settings could not be cleared (problem+json)",
            body = String),
    ),
    tag = "agents"
)]
pub(crate) async fn delete_agent_inference(
    State(state): State<AppState>,
    Path(name): Path<String>,
) -> Result<StatusCode, ProblemDetails> {
    let agent = agent_name(&name).map_err(refused)?;
    let client = queue(&state).map_err(refused)?;
    let store = open(&client).await?;
    store
        .delete(&agent)
        .await
        .map_err(|e| queue_problem(&anyhow::Error::new(e)))?;
    tracing::info!(%agent, "cleared inference settings");
    Ok(StatusCode::NO_CONTENT)
}

#[cfg(test)]
mod tests {
    use super::*;

    fn settings(json: &str) -> serde_json::Result<InferenceSettings> {
        serde_json::from_str(json)
    }

    #[test]
    fn a_full_put_is_stored_as_sent() {
        let stored = settings(r#"{"model":"opus","effort":"high","subagent_models":["haiku"]}"#)
            .unwrap()
            .into_stored()
            .unwrap();
        assert_eq!(
            stored,
            AgentInference {
                model: Some("opus".to_owned()),
                effort: Some(Effort::High),
                subagent_models: Some(vec!["haiku".to_owned()]),
            }
        );
        assert_eq!(
            serde_json::to_value(InferenceSettings::from(stored)).unwrap(),
            serde_json::json!({"model": "opus", "effort": "high", "subagent_models": ["haiku"]})
        );
    }

    /// Each field is optional, and one left out stays out of the stored value.
    #[test]
    fn a_partial_put_leaves_the_other_fields_unset() {
        let stored = settings(r#"{"effort":"max"}"#)
            .unwrap()
            .into_stored()
            .unwrap();
        assert_eq!(
            stored,
            AgentInference {
                effort: Some(Effort::Max),
                ..AgentInference::default()
            }
        );
    }

    #[test]
    fn an_unknown_field_or_effort_does_not_decode() {
        for json in [
            r#"{"modle":"opus"}"#,
            r#"{"available_models":["opus"]}"#,
            r#"{"effort":"extreme"}"#,
            r#"{"effort":"HIGH"}"#,
        ] {
            assert!(settings(json).is_err(), "{json}");
        }
        // Control: the same shape with a known field and level decodes.
        assert!(settings(r#"{"model":"opus","effort":"xhigh"}"#).is_ok());
    }

    const NEW_HEADER: &[u8] = br#"{"turn_state":"idle","model":"opus","effort":"high",
        "model_source":"swarm","effort_source":"local_file"}"#;

    /// A header from an agent that does not report effort or sources.
    const OLD_HEADER: &[u8] = br#"{"turn_state":"idle","model":"sonnet"}"#;

    fn iris() -> String {
        swarm_queue_client::agent_state_subject("iris")
    }

    #[test]
    fn a_header_is_kept_under_its_agent() {
        let reported = Reported::default();
        reported.record(&iris(), NEW_HEADER);
        assert_eq!(
            reported.get("iris"),
            Some(Effective {
                model: "opus".to_owned(),
                effort: "high".to_owned(),
                model_source: Source::Swarm,
                effort_source: Source::LocalFile,
            })
        );
        assert_eq!(reported.get("atlas"), None);
    }

    #[test]
    fn a_header_without_the_inference_fields_leaves_no_entry() {
        let reported = Reported::default();
        reported.record(&iris(), NEW_HEADER);
        reported.record(&iris(), OLD_HEADER);
        assert_eq!(reported.get("iris"), None);
    }

    #[test]
    fn a_subject_naming_no_agent_is_skipped() {
        let reported = Reported::default();
        reported.record("$SWARM.agent-state.iris.sub.scout", NEW_HEADER);
        reported.record("$SWARM.term.iris", NEW_HEADER);
        assert!(reported.latest.lock().unwrap().is_empty());
    }

    #[test]
    fn the_view_answers_both_halves() {
        let view = |effective: Option<Effective>| {
            serde_json::to_value(AgentInferenceView {
                configured: InferenceSettings::default(),
                effective: effective.map(Into::into),
            })
            .unwrap()
        };
        assert_eq!(
            view(None),
            serde_json::json!({"configured": {}, "effective": null})
        );
        let reported = Reported::default();
        reported.record(&iris(), NEW_HEADER);
        assert_eq!(
            view(reported.get("iris"))["effective"],
            serde_json::json!({"model": "opus", "effort": "high",
                "model_source": "swarm", "effort_source": "local_file"})
        );
    }

    #[test]
    fn bad_model_names_are_refused() {
        for json in [
            r#"{"model":""}"#,
            r#"{"model":"opus 4"}"#,
            r#"{"subagent_models":[]}"#,
            r#"{"subagent_models":["haiku",""]}"#,
            r#"{"subagent_models":["haiku","haiku"]}"#,
            r#"{"model":"--dangerously-skip-permissions"}"#,
            r#"{"model":"-x"}"#,
            r#"{"subagent_models":["haiku","--print"]}"#,
        ] {
            assert!(settings(json).unwrap().into_stored().is_err(), "{json}");
        }
    }

    /// Control for the leading-dash refusal: full model ids have dashes inside.
    #[test]
    fn a_dash_inside_a_model_name_is_accepted() {
        let json = r#"{"model":"claude-opus-4-8","subagent_models":["claude-haiku-4-5"]}"#;
        assert!(settings(json).unwrap().into_stored().is_ok());
    }
}