use std::collections::HashMap;
use crate::data::models::SessionData;
use crate::pricing::calculator::PricingCalculator;
use super::{AgentDetail, AgentSummary, AggregatedTokens, SessionResult, TurnCostBreakdown, TurnDetail};
#[derive(Debug, Clone, Default)]
pub struct AgentMeta {
pub agent_type: String,
pub description: String,
}
pub fn analyze_session(
session: &SessionData,
calc: &PricingCalculator,
agent_meta: &std::collections::HashMap<String, AgentMeta>,
) -> SessionResult {
let all_turns = session.all_responses();
let mut turn_details = Vec::new();
let mut total_tokens = AggregatedTokens::default();
let mut total_cost = 0.0;
let mut stop_reason_counts: HashMap<String, usize> = HashMap::new();
let mut agent_summary = AgentSummary::default();
let mut model_counts: HashMap<&str, usize> = HashMap::new();
let mut max_context: u64 = 0;
let mut prev_context_size: Option<u64> = None;
let mut agent_acc: HashMap<String, (usize, u64, f64)> = HashMap::new();
for (i, turn) in all_turns.iter().enumerate() {
let input = turn.usage.input_tokens.unwrap_or(0);
let output = turn.usage.output_tokens.unwrap_or(0);
let cache_create = turn.usage.cache_creation_input_tokens.unwrap_or(0);
let cache_read = turn.usage.cache_read_input_tokens.unwrap_or(0);
let (cache_write_5m, cache_write_1h) = if let Some(ref detail) = turn.usage.cache_creation {
(
detail.ephemeral_5m_input_tokens.unwrap_or(0),
detail.ephemeral_1h_input_tokens.unwrap_or(0),
)
} else {
(0, 0)
};
let context_size = input + cache_create + cache_read;
let cache_hit_rate = if context_size > 0 {
(cache_read as f64 / context_size as f64) * 100.0
} else {
0.0
};
if context_size > max_context {
max_context = context_size;
}
let is_compaction = match prev_context_size {
Some(prev) => prev > 0 && (context_size as f64) < (prev as f64 * 0.9),
None => false,
};
let context_delta = match prev_context_size {
Some(prev) => context_size as i64 - prev as i64,
None => 0,
};
prev_context_size = Some(context_size);
let pricing_cost = calc.calculate_turn_cost(&turn.model, &turn.usage);
let cost_breakdown = TurnCostBreakdown {
input_cost: pricing_cost.input_cost,
output_cost: pricing_cost.output_cost,
cache_write_5m_cost: pricing_cost.cache_write_5m_cost,
cache_write_1h_cost: pricing_cost.cache_write_1h_cost,
cache_read_cost: pricing_cost.cache_read_cost,
total: pricing_cost.total,
};
if let Some(ref reason) = turn.stop_reason {
*stop_reason_counts.entry(reason.clone()).or_insert(0) += 1;
}
total_tokens.add_usage(&turn.usage);
total_cost += pricing_cost.total;
*model_counts.entry(&turn.model).or_insert(0) += 1;
let is_agent = turn.is_agent;
if is_agent {
agent_summary.total_agent_turns += 1;
agent_summary.agent_output_tokens += output;
agent_summary.agent_cost += pricing_cost.total;
let aid = turn.agent_id.clone().unwrap_or_default();
if !aid.is_empty() {
let entry = agent_acc.entry(aid).or_insert((0usize, 0u64, 0.0f64));
entry.0 += 1;
entry.1 += output;
entry.2 += pricing_cost.total;
}
}
turn_details.push(TurnDetail {
turn_number: i + 1,
timestamp: turn.timestamp,
model: turn.model.clone(),
input_tokens: input,
output_tokens: output,
cache_write_5m_tokens: cache_write_5m,
cache_write_1h_tokens: cache_write_1h,
cache_read_tokens: cache_read,
context_size,
cache_hit_rate,
cost: pricing_cost.total,
cost_breakdown,
stop_reason: turn.stop_reason.clone(),
is_agent,
is_compaction,
context_delta,
user_text: turn.user_text.clone(),
assistant_text: turn.assistant_text.clone(),
tool_names: turn.tool_names.clone(),
});
}
let duration_minutes = match (session.first_timestamp, session.last_timestamp) {
(Some(first), Some(last)) => (last - first).num_seconds() as f64 / 60.0,
_ => 0.0,
};
let compaction_count = turn_details.iter().filter(|t| t.is_compaction).count();
let total_5m = total_tokens.cache_write_5m_tokens;
let total_1h = total_tokens.cache_write_1h_tokens;
let total_cache_write = total_5m + total_1h;
let cache_write_5m_pct = if total_cache_write > 0 {
(total_5m as f64 / total_cache_write as f64) * 100.0
} else {
0.0
};
let cache_write_1h_pct = if total_cache_write > 0 {
(total_1h as f64 / total_cache_write as f64) * 100.0
} else {
0.0
};
let mut agents: Vec<AgentDetail> = agent_acc.into_iter().map(|(aid, (turns, output, cost))| {
let meta = agent_meta.get(&aid);
AgentDetail {
agent_id: aid,
agent_type: meta.map_or_else(|| "unknown".into(), |m| m.agent_type.clone()),
description: meta.map_or_else(|| "".into(), |m| m.description.clone()),
turns,
output_tokens: output,
cost,
}
}).collect();
agents.sort_by(|a, b| b.cost.partial_cmp(&a.cost).unwrap_or(std::cmp::Ordering::Equal));
agent_summary.agents = agents;
let model = model_counts
.into_iter()
.max_by_key(|(_, count)| *count)
.map(|(m, _)| m.to_string())
.unwrap_or_default();
SessionResult {
session_id: session.session_id.clone(),
project: session
.project
.clone()
.unwrap_or_else(|| "(unknown)".to_string()),
turn_details,
agent_summary,
total_tokens,
total_cost,
stop_reason_counts,
duration_minutes,
max_context,
compaction_count,
cache_write_5m_pct,
cache_write_1h_pct,
model,
}
}