use anyhow::Result;
use clap::Args;
use std::path::PathBuf;
use systemprompt_analytics::RequestAnalyticsRepository;
use systemprompt_logging::CliService;
use systemprompt_runtime::{AppContext, DatabaseContext};
use super::{ModelUsageRow, ModelsOutput};
use crate::CliConfig;
use crate::commands::analytics::shared::{export_to_csv, parse_time_range, resolve_export_path};
use crate::shared::{CommandResult, RenderingHints};
#[derive(Debug, Args)]
pub struct ModelsArgs {
#[arg(
long,
alias = "from",
default_value = "24h",
help = "Time range (e.g., '1h', '24h', '7d')"
)]
pub since: Option<String>,
#[arg(long, alias = "to", help = "End time for range")]
pub until: Option<String>,
#[arg(
long,
short = 'n',
default_value = "20",
help = "Maximum number of models"
)]
pub limit: i64,
#[arg(long, help = "Export results to CSV file")]
pub export: Option<PathBuf>,
}
pub async fn execute(args: ModelsArgs, _config: &CliConfig) -> Result<CommandResult<ModelsOutput>> {
let ctx = AppContext::new().await?;
let repo = RequestAnalyticsRepository::new(ctx.db_pool())?;
execute_internal(args, &repo).await
}
pub async fn execute_with_pool(
args: ModelsArgs,
db_ctx: &DatabaseContext,
_config: &CliConfig,
) -> Result<CommandResult<ModelsOutput>> {
let repo = RequestAnalyticsRepository::new(db_ctx.db_pool())?;
execute_internal(args, &repo).await
}
async fn execute_internal(
args: ModelsArgs,
repo: &RequestAnalyticsRepository,
) -> Result<CommandResult<ModelsOutput>> {
let (start, end) = parse_time_range(args.since.as_ref(), args.until.as_ref())?;
let rows = repo.list_models(start, end, args.limit).await?;
let total_requests: i64 = rows.iter().map(|r| r.request_count).sum();
let models: Vec<ModelUsageRow> = rows
.into_iter()
.map(|row| {
let percentage = if total_requests > 0 {
(row.request_count as f64 / total_requests as f64) * 100.0
} else {
0.0
};
ModelUsageRow {
provider: row.provider,
model: row.model,
request_count: row.request_count,
total_tokens: row.total_tokens.unwrap_or(0),
total_cost_microdollars: row.total_cost.unwrap_or(0),
avg_latency_ms: row.avg_latency.map_or(0, |v| v as i64),
percentage,
}
})
.collect();
let output = ModelsOutput {
period: format!(
"{} to {}",
start.format("%Y-%m-%d %H:%M"),
end.format("%Y-%m-%d %H:%M")
),
models,
total_requests,
};
if let Some(ref path) = args.export {
let resolved_path = resolve_export_path(path)?;
export_to_csv(&output.models, &resolved_path)?;
CliService::success(&format!("Exported to {}", resolved_path.display()));
return Ok(CommandResult::table(output).with_skip_render());
}
if output.models.is_empty() {
CliService::warning("No models found in the specified time range");
return Ok(CommandResult::table(output).with_skip_render());
}
let hints = RenderingHints {
columns: Some(vec![
"provider".to_string(),
"model".to_string(),
"request_count".to_string(),
"total_tokens".to_string(),
"total_cost_microdollars".to_string(),
]),
..Default::default()
};
Ok(CommandResult::table(output)
.with_title("Model Usage")
.with_hints(hints))
}