use anyhow::Result;
use clap::Args;
use std::sync::Arc;
use systemprompt_logging::{AiRequestFilter, TraceQueryService};
use super::{RequestListRow, build_request_list};
use crate::commands::infrastructure::logs::duration::parse_since;
use crate::shared::CommandOutput;
use systemprompt_models::text::truncate_with_ellipsis;
#[derive(Debug, Args)]
pub struct ListArgs {
#[arg(
long,
short = 'n',
default_value = "20",
help = "Maximum number of requests to return"
)]
pub limit: i64,
#[arg(
long,
help = "Only show requests since this duration (e.g., '1h', '24h', '7d')"
)]
pub since: Option<String>,
#[arg(long, help = "Filter by model name (partial match)")]
pub model: Option<String>,
#[arg(long, help = "Filter by provider (e.g., 'openai', 'anthropic')")]
pub provider: Option<String>,
#[arg(long, help = "Filter by user id (exact match)")]
pub user: Option<String>,
}
crate::define_pool_command!(ListArgs => CommandOutput, no_config);
async fn execute_with_pool_inner(
args: ListArgs,
pool: &Arc<sqlx::PgPool>,
) -> Result<CommandOutput> {
let mut filter = AiRequestFilter::new(args.limit);
if let Some(since) = parse_since(args.since.as_ref())? {
filter = filter.with_since(since);
}
if let Some(model) = args.model.as_ref() {
filter = filter.with_model(format!("%{model}%"));
}
if let Some(provider) = args.provider.as_ref() {
filter = filter.with_provider(format!("%{provider}%"));
}
if let Some(user) = args.user {
filter = filter.with_user(user);
}
let service = TraceQueryService::new(Arc::clone(pool));
let rows = service.list_ai_requests(&filter).await?;
let requests: Vec<RequestListRow> = rows
.into_iter()
.map(|r| {
let input = r.input_tokens.unwrap_or(0);
let output = r.output_tokens.unwrap_or(0);
let cost_dollars = r.cost_microdollars as f64 / 1_000_000.0;
RequestListRow {
request_id: truncate_with_ellipsis(r.id.as_str(), 12),
timestamp: r.created_at.format("%Y-%m-%d %H:%M:%S").to_string(),
user_id: r.user_id,
actor: format!("{}:{}", r.actor_kind, r.actor_id),
provider: r.provider.unwrap_or_else(|| "-".to_owned()),
model: r.model.unwrap_or_else(|| "-".to_owned()),
tokens: format!("{input}/{output}"),
cost: format!("${cost_dollars:.6}"),
latency_ms: r.latency_ms.map(i64::from),
status: r.status,
}
})
.collect();
Ok(build_request_list(&requests))
}