Files
cc-switch/src-tauri/src/services/session_usage_codex.rs
Jason 2ee7cb4101 fix(usage): prevent double-counting between proxy and session-log sources
Proxy writes and session-log sync wrote to proxy_request_logs with
mismatched request_ids: only Claude on a native Anthropic backend used the
shared `session:{message_id}` key. Codex/Gemini and Claude-through-OpenAI
providers always produced distinct ids, so primary-key dedup never fired
and every real request was recorded twice.

Adds a 7-dim fingerprint dedup (app_type, 4 token counts, 2xx status,
model with case-insensitive match, ±10min window) wired into three layers:

- Write path: should_skip_session_insert() blocks duplicate session rows
  before INSERT, unifying the previously-divergent Claude/Codex/Gemini
  paths through a single DedupKey-based helper.
- Read path: effective_usage_log_filter() excludes already-covered session
  rows from every aggregation query.
- Rollup path: same filter applied so usage_daily_rollups never absorbs
  duplicates.

Also adds a covering index (idx_request_logs_dedup_lookup) so the EXISTS
subquery stays index-only, and a transform.rs regression test that pins
openai_to_anthropic id preservation - the missing piece that lets
Claude+OpenAI-compatible providers reuse the session: id scheme.
2026-04-29 22:41:46 +08:00

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//! Codex 会话日志使用追踪
//!
//! 从 ~/.codex/sessions/ 下的 JSONL 会话文件中提取精确 token 使用数据,
//! 替代原有的 state_5.sqlite 估算方案。
//!
//! ## 数据流
//! ```text
//! ~/.codex/sessions/YYYY/MM/DD/*.jsonl → 增量解析 → delta 计算 → 费用计算 → proxy_request_logs 表
//! ```
//!
//! ## 解析的事件类型
//! - `session_meta` → 提取 session_id
//! - `turn_context` → 提取当前 model
//! - `event_msg` (type=token_count) → 提取累计 token 用量,计算 delta
use crate::codex_config::get_codex_config_dir;
use crate::database::{lock_conn, Database};
use crate::error::AppError;
use crate::proxy::usage::calculator::{CostCalculator, ModelPricing};
use crate::proxy::usage::parser::TokenUsage;
use crate::services::session_usage::SessionSyncResult;
use crate::services::usage_stats::{should_skip_session_insert, DedupKey};
use rust_decimal::Decimal;
use std::fs;
use std::io::{BufRead, BufReader};
use std::path::{Path, PathBuf};
use std::time::SystemTime;
/// 累计 token 用量(跟踪 total_token_usage 字段)
#[derive(Debug, Clone, Default)]
struct CumulativeTokens {
input: u64,
cached_input: u64,
output: u64,
}
/// 单次 API 调用的 token 增量
#[derive(Debug)]
struct DeltaTokens {
input: u32,
cached_input: u32,
output: u32,
}
impl DeltaTokens {
fn is_zero(&self) -> bool {
self.input == 0 && self.cached_input == 0 && self.output == 0
}
}
/// 单文件解析时的运行状态
struct FileParseState {
session_id: Option<String>,
current_model: String,
prev_total: Option<CumulativeTokens>,
event_index: u32,
}
/// 归一化 Codex 模型名
///
/// 处理规则(按顺序):
/// 1. 转小写:`GLM-4.6` → `glm-4.6`
/// 2. 剥离 provider 前缀:`openai/gpt-5.4` → `gpt-5.4`
/// 3. 剥离 ISO 日期后缀:`gpt-5.4-2026-03-05` → `gpt-5.4`
/// 4. 剥离紧凑日期后缀:`gpt-5.4-20260305` → `gpt-5.4`
fn normalize_codex_model(raw: &str) -> String {
// Step 1: 小写
let mut name = raw.to_lowercase();
// Step 2: 剥离 "provider/" 前缀(如 openai/, azure/
if let Some(pos) = name.rfind('/') {
name = name[pos + 1..].to_string();
}
// Step 3: 剥离 ISO 日期后缀 -YYYY-MM-DD正好 11 字符)
if name.len() > 11 {
let suffix = &name[name.len() - 11..];
if suffix.as_bytes()[0] == b'-'
&& suffix[1..5].chars().all(|c| c.is_ascii_digit())
&& suffix.as_bytes()[5] == b'-'
&& suffix[6..8].chars().all(|c| c.is_ascii_digit())
&& suffix.as_bytes()[8] == b'-'
&& suffix[9..11].chars().all(|c| c.is_ascii_digit())
{
name.truncate(name.len() - 11);
}
}
// Step 4: 剥离紧凑日期后缀 -YYYYMMDD正好 9 字符)
if name.len() > 9 {
let parts: Vec<&str> = name.rsplitn(2, '-').collect();
if parts.len() == 2 {
if let Some(suffix) = parts.first() {
if suffix.len() == 8 && suffix.chars().all(|c| c.is_ascii_digit()) {
name = parts[1].to_string();
}
}
}
}
name
}
/// 计算两次累计值之间的 delta
fn compute_delta(prev: &Option<CumulativeTokens>, current: &CumulativeTokens) -> DeltaTokens {
match prev {
None => DeltaTokens {
input: current.input as u32,
cached_input: current.cached_input as u32,
output: current.output as u32,
},
Some(p) => DeltaTokens {
input: current.input.saturating_sub(p.input) as u32,
cached_input: current.cached_input.saturating_sub(p.cached_input) as u32,
output: current.output.saturating_sub(p.output) as u32,
},
}
}
/// 从 JSON Value 中提取累计 token 用量
fn parse_cumulative_tokens(total_usage: &serde_json::Value) -> Option<CumulativeTokens> {
if total_usage.is_null() || !total_usage.is_object() {
return None;
}
Some(CumulativeTokens {
input: total_usage
.get("input_tokens")
.and_then(|v| v.as_u64())
.unwrap_or(0),
cached_input: total_usage
.get("cached_input_tokens")
.or_else(|| total_usage.get("cache_read_input_tokens"))
.and_then(|v| v.as_u64())
.unwrap_or(0),
output: total_usage
.get("output_tokens")
.and_then(|v| v.as_u64())
.unwrap_or(0),
})
}
/// 同步 Codex 使用数据(从 JSONL 会话日志)
pub fn sync_codex_usage(db: &Database) -> Result<SessionSyncResult, AppError> {
let codex_dir = get_codex_config_dir();
let files = collect_codex_session_files(&codex_dir);
let mut result = SessionSyncResult {
imported: 0,
skipped: 0,
files_scanned: files.len() as u32,
errors: vec![],
};
if files.is_empty() {
return Ok(result);
}
for file_path in &files {
match sync_single_codex_file(db, file_path) {
Ok((imported, skipped)) => {
result.imported += imported;
result.skipped += skipped;
}
Err(e) => {
let msg = format!("Codex 会话文件解析失败 {}: {e}", file_path.display());
log::warn!("[CODEX-SYNC] {msg}");
result.errors.push(msg);
}
}
}
if result.imported > 0 {
log::info!(
"[CODEX-SYNC] 同步完成: 导入 {} 条, 跳过 {} 条, <20><>描 {} 个文件",
result.imported,
result.skipped,
result.files_scanned
);
}
Ok(result)
}
/// 收集所有 Codex 会话 JSONL 文件
fn collect_codex_session_files(codex_dir: &Path) -> Vec<PathBuf> {
let mut files = Vec::new();
// 1. 扫描 sessions/YYYY/MM/DD/*.jsonl日期分区目录<E79BAE><E5BD95>
let sessions_dir = codex_dir.join("sessions");
if sessions_dir.is_dir() {
collect_jsonl_recursive(&sessions_dir, &mut files, 0, 3);
}
// 2. 扫描 archived_sessions/*.jsonl扁平归档目录
let archived_dir = codex_dir.join("archived_sessions");
if archived_dir.is_dir() {
if let Ok(entries) = fs::read_dir(&archived_dir) {
for entry in entries.flatten() {
let path = entry.path();
if path.extension().and_then(|e| e.to_str()) == Some("jsonl") {
files.push(path);
}
}
}
}
files
}
/// 递归扫描目录下的 .jsonl 文件(限制最大深度)
fn collect_jsonl_recursive(dir: &Path, files: &mut Vec<PathBuf>, depth: u32, max_depth: u32) {
let entries = match fs::read_dir(dir) {
Ok(e) => e,
Err(_) => return,
};
for entry in entries.flatten() {
let path = entry.path();
if path.is_dir() && depth < max_depth {
collect_jsonl_recursive(&path, files, depth + 1, max_depth);
} else if path.extension().and_then(|e| e.to_str()) == Some("jsonl") {
files.push(path);
}
}
}
/// 同步单<E6ADA5><E58D95> Codex JSONL 文件,返回 (imported, skipped)
fn sync_single_codex_file(db: &Database, file_path: &Path) -> Result<(u32, u32), AppError> {
let file_path_str = file_path.to_string_lossy().to_string();
// 获取文件元数据
let metadata = fs::metadata(file_path)
.map_err(|e| AppError::Config(format!("无法读取文<EFBFBD><EFBFBD><EFBFBD>元数据: {e}")))?;
let file_modified = metadata
.modified()
.ok()
.and_then(|t| t.duration_since(SystemTime::UNIX_EPOCH).ok())
.map(|d| d.as_secs() as i64)
.unwrap_or(0);
// 检查同步状态
let (last_modified, last_offset) = get_sync_state(db, &file_path_str)?;
// 文件未变化则跳过
if file_modified <= last_modified {
return Ok((0, 0));
}
// 打开文件逐行解析
let file =
fs::File::open(file_path).map_err(|e| AppError::Config(format!("无法打开文件: {e}")))?;
let reader = BufReader::new(file);
let mut state = FileParseState {
session_id: None,
current_model: "unknown".to_string(),
prev_total: None,
event_index: 0,
};
let mut line_offset: i64 = 0;
let mut imported: u32 = 0;
let mut skipped: u32 = 0;
for line_result in reader.lines() {
line_offset += 1;
let line = match line_result {
Ok(l) => l,
Err(_) => continue, // 容忍不完整的最后一行
};
if line.trim().is_empty() {
continue;
}
// 快速过滤:在 JSON 反序列化前跳过无关行
let is_event_msg = line.contains("\"event_msg\"");
let is_turn_context = line.contains("\"turn_context\"");
let is_session_meta = line.contains("\"session_meta\"");
if !is_event_msg && !is_turn_context && !is_session_meta {
continue;
}
if is_event_msg && !line.contains("\"token_count\"") {
continue;
}
let value: serde_json::Value = match serde_json::from_str(&line) {
Ok(v) => v,
Err(_) => continue,
};
let event_type = match value.get("type").and_then(|t| t.as_str()) {
Some(t) => t,
None => continue,
};
match event_type {
"session_meta" if state.session_id.is_none() => {
let payload = value.get("payload");
state.session_id = payload
.and_then(|p| {
p.get("session_id")
.or_else(|| p.get("sessionId"))
.or_else(|| p.get("id"))
})
.and_then(|v| v.as_str())
.map(|s| s.to_string());
}
"turn_context" => {
if let Some(payload) = value.get("payload") {
// model 可能在 payload.model 或 payload.info.model
if let Some(model) = payload
.get("model")
.or_else(|| payload.get("info").and_then(|info| info.get("model")))
.and_then(|v| v.as_str())
{
state.current_model = normalize_codex_model(model);
}
}
}
"event_msg" => {
let payload = match value.get("payload") {
Some(p) => p,
None => continue,
};
// 只处理 token_count 类型
if payload.get("type").and_then(|t| t.as_str()) != Some("token_count") {
continue;
}
let info = match payload.get("info") {
Some(i) if !i.is_null() => i,
_ => continue, // info 为 null 的首个事件跳<E4BBB6><E8B7B3>
};
// 提取模型token_count 事件也可能携带 model
if let Some(model) = info
.get("model")
.or_else(|| info.get("model_name"))
.or_else(|| payload.get("model"))
.and_then(|v| v.as_str())
{
state.current_model = normalize_codex_model(model);
}
// 优先用 total_token_usage累计值fallback 到 last_token_usage增量值
let (cumulative, is_total) = if let Some(total) = info.get("total_token_usage") {
(parse_cumulative_tokens(total), true)
} else if let Some(last) = info.get("last_token_usage") {
(parse_cumulative_tokens(last), false)
} else {
continue;
};
let cumulative = match cumulative {
Some(c) => c,
None => continue,
};
let delta = if is_total {
// 累计值模式:计算与上次的 delta
let d = compute_delta(&state.prev_total, &cumulative);
state.prev_total = Some(cumulative);
d
} else {
// 增量值模式:直接使用 last_token_usage 的值
DeltaTokens {
input: cumulative.input as u32,
cached_input: cumulative.cached_input as u32,
output: cumulative.output as u32,
}
};
// 钳制cached 不应超过 input防护异常数据
let delta = DeltaTokens {
cached_input: delta.cached_input.min(delta.input),
..delta
};
if delta.is_zero() {
continue; // 跳过 task 边界的零 delta 事件
}
state.event_index += 1;
// 跳过已处理的行(但仍需解析以恢复状态)
if line_offset <= last_offset {
continue;
}
// 生成唯一 request_id
let session_id_str = state.session_id.as_deref().unwrap_or("unknown");
let request_id = format!("codex_session:{}:{}", session_id_str, state.event_index);
// 提取时间戳
let timestamp = value
.get("timestamp")
.and_then(|v| v.as_str())
.map(|s| s.to_string());
match insert_codex_session_entry(
db,
&request_id,
&delta,
&state.current_model,
state.session_id.as_deref(),
timestamp.as_deref(),
) {
Ok(true) => imported += 1,
Ok(false) => skipped += 1,
Err(e) => {
log::warn!("[CODEX-SYNC] 插入失败 ({}): {e}", request_id);
skipped += 1;
}
}
}
_ => {}
}
}
// 更新同步状态
update_sync_state(db, &file_path_str, file_modified, line_offset)?;
Ok((imported, skipped))
}
/// 插入单条 Codex 会话记录到 proxy_request_logs
fn insert_codex_session_entry(
db: &Database,
request_id: &str,
delta: &DeltaTokens,
model: &str,
session_id: Option<&str>,
timestamp: Option<&str>,
) -> Result<bool, AppError> {
let conn = lock_conn!(db.conn);
let created_at = timestamp
.and_then(|ts| {
chrono::DateTime::parse_from_rfc3339(ts)
.ok()
.map(|dt| dt.timestamp())
})
.unwrap_or_else(|| {
SystemTime::now()
.duration_since(SystemTime::UNIX_EPOCH)
.map(|d| d.as_secs() as i64)
.unwrap_or(0)
});
let dedup_key = DedupKey {
app_type: "codex",
model,
input_tokens: delta.input,
output_tokens: delta.output,
cache_read_tokens: delta.cached_input,
cache_creation_tokens: 0,
created_at,
};
if should_skip_session_insert(&conn, request_id, &dedup_key)? {
return Ok(false);
}
// 计算费用
let usage = TokenUsage {
input_tokens: delta.input,
output_tokens: delta.output,
cache_read_tokens: delta.cached_input,
cache_creation_tokens: 0,
model: Some(model.to_string()),
message_id: None,
};
let pricing = find_codex_pricing(&conn, model);
let multiplier = Decimal::from(1);
let (input_cost, output_cost, cache_read_cost, cache_creation_cost, total_cost) = match pricing
{
Some(p) => {
let cost = CostCalculator::calculate(&usage, &p, multiplier);
(
cost.input_cost.to_string(),
cost.output_cost.to_string(),
cost.cache_read_cost.to_string(),
cost.cache_creation_cost.to_string(),
cost.total_cost.to_string(),
)
}
None => (
"0".to_string(),
"0".to_string(),
"0".to_string(),
"0".to_string(),
"0".to_string(),
),
};
conn.execute(
"INSERT OR IGNORE INTO proxy_request_logs (
request_id, provider_id, app_type, model, request_model,
input_tokens, output_tokens, cache_read_tokens, cache_creation_tokens,
input_cost_usd, output_cost_usd, cache_read_cost_usd, cache_creation_cost_usd, total_cost_usd,
latency_ms, first_token_ms, status_code, error_message, session_id,
provider_type, is_streaming, cost_multiplier, created_at, data_source
) VALUES (?1, ?2, ?3, ?4, ?5, ?6, ?7, ?8, ?9, ?10, ?11, ?12, ?13, ?14, ?15, ?16, ?17, ?18, ?19, ?20, ?21, ?22, ?23, ?24)",
rusqlite::params![
request_id,
"_codex_session", // provider_id
"codex", // app_type
model,
model, // request_model = model
delta.input,
delta.output,
delta.cached_input,
0i64, // cache_creation_tokens: Codex 日志无此数据
input_cost,
output_cost,
cache_read_cost,
cache_creation_cost,
total_cost,
0i64, // latency_ms
Option::<i64>::None, // first_token_ms
200i64, // status_code
Option::<String>::None, // error_message
session_id.map(|s| s.to_string()),
Some("codex_session"), // provider_type
1i64, // is_streaming
"1.0", // cost_multiplier
created_at,
"codex_session", // data_source
],
)
.map_err(|e| AppError::Database(format!("插入 Codex 会话日志失败: {e}")))?;
Ok(true)
}
/// 获取文件的同步状态
fn get_sync_state(db: &Database, file_path: &str) -> Result<(i64, i64), AppError> {
let conn = lock_conn!(db.conn);
let result = conn.query_row(
"SELECT last_modified, last_line_offset FROM session_log_sync WHERE file_path = ?1",
rusqlite::params![file_path],
|row| Ok((row.get::<_, i64>(0)?, row.get::<_, i64>(1)?)),
);
Ok(result.unwrap_or((0, 0)))
}
/// 更新文件的同步状态
fn update_sync_state(
db: &Database,
file_path: &str,
last_modified: i64,
last_offset: i64,
) -> Result<(), AppError> {
let now = SystemTime::now()
.duration_since(SystemTime::UNIX_EPOCH)
.map(|d| d.as_secs() as i64)
.unwrap_or(0);
let conn = lock_conn!(db.conn);
conn.execute(
"INSERT OR REPLACE INTO session_log_sync (file_path, last_modified, last_line_offset, last_synced_at)
VALUES (?1, ?2, ?3, ?4)",
rusqlite::params![file_path, last_modified, last_offset, now],
)
.map_err(|e| AppError::Database(format!("更新同步状态失败: {e}")))?;
Ok(())
}
/// <20><>找 Codex 模型定价(带归一化)
fn find_codex_pricing(conn: &rusqlite::Connection, model_id: &str) -> Option<ModelPricing> {
let normalized = normalize_codex_model(model_id);
// 1. 精确匹配(归一化后的名称)
if let Some(pricing) = try_find_pricing(conn, &normalized) {
return Some(pricing);
}
// 2. LIKE 模糊匹配(兜底)
let pattern = format!("{normalized}%");
conn.query_row(
"SELECT input_cost_per_million, output_cost_per_million,
cache_read_cost_per_million, cache_creation_cost_per_million
FROM model_pricing WHERE model_id LIKE ?1 LIMIT 1",
rusqlite::params![pattern],
|row| {
Ok((
row.get::<_, String>(0)?,
row.get::<_, String>(1)?,
row.get::<_, String>(2)?,
row.get::<_, String>(3)?,
))
},
)
.ok()
.and_then(|(i, o, cr, cc)| ModelPricing::from_strings(&i, &o, &cr, &cc).ok())
}
/// 精确匹配定价查询
fn try_find_pricing(conn: &rusqlite::Connection, model_id: &str) -> Option<ModelPricing> {
conn.query_row(
"SELECT input_cost_per_million, output_cost_per_million,
cache_read_cost_per_million, cache_creation_cost_per_million
FROM model_pricing WHERE model_id = ?1",
rusqlite::params![model_id],
|row| {
Ok((
row.get::<_, String>(0)?,
row.get::<_, String>(1)?,
row.get::<_, String>(2)?,
row.get::<_, String>(3)?,
))
},
)
.ok()
.and_then(|(i, o, cr, cc)| ModelPricing::from_strings(&i, &o, &cr, &cc).ok())
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_delta_first_event() {
let prev = None;
let current = CumulativeTokens {
input: 17934,
cached_input: 9600,
output: 454,
};
let delta = compute_delta(&prev, &current);
assert_eq!(delta.input, 17934);
assert_eq!(delta.cached_input, 9600);
assert_eq!(delta.output, 454);
assert!(!delta.is_zero());
}
#[test]
fn test_delta_subsequent_event() {
let prev = Some(CumulativeTokens {
input: 17934,
cached_input: 9600,
output: 454,
});
let current = CumulativeTokens {
input: 36722,
cached_input: 27904,
output: 804,
};
let delta = compute_delta(&prev, &current);
assert_eq!(delta.input, 36722 - 17934);
assert_eq!(delta.cached_input, 27904 - 9600);
assert_eq!(delta.output, 804 - 454);
}
#[test]
fn test_delta_zero_at_task_boundary() {
let prev = Some(CumulativeTokens {
input: 58346,
cached_input: 46976,
output: 1045,
});
// task 边界:相同的累计值
let current = CumulativeTokens {
input: 58346,
cached_input: 46976,
output: 1045,
};
let delta = compute_delta(&prev, &current);
assert!(delta.is_zero());
}
#[test]
fn test_delta_saturating_sub() {
// 异常情况:当前值小于前值(不应发生,但需防护)
let prev = Some(CumulativeTokens {
input: 100,
cached_input: 50,
output: 30,
});
let current = CumulativeTokens {
input: 80,
cached_input: 40,
output: 20,
};
let delta = compute_delta(&prev, &current);
assert_eq!(delta.input, 0);
assert_eq!(delta.cached_input, 0);
assert_eq!(delta.output, 0);
assert!(delta.is_zero());
}
#[test]
fn test_parse_cumulative_tokens_valid() {
let json: serde_json::Value = serde_json::json!({
"input_tokens": 17934,
"cached_input_tokens": 9600,
"output_tokens": 454,
"reasoning_output_tokens": 233,
"total_tokens": 18388
});
let tokens = parse_cumulative_tokens(&json).unwrap();
assert_eq!(tokens.input, 17934);
assert_eq!(tokens.cached_input, 9600);
assert_eq!(tokens.output, 454);
}
#[test]
fn test_parse_cumulative_tokens_null() {
let json = serde_json::Value::Null;
assert!(parse_cumulative_tokens(&json).is_none());
}
#[test]
fn test_parse_cumulative_tokens_alt_field_names() {
// 某些版本可能使用 cache_read_input_tokens 而非 cached_input_tokens
let json: serde_json::Value = serde_json::json!({
"input_tokens": 1000,
"cache_read_input_tokens": 500,
"output_tokens": 200
});
let tokens = parse_cumulative_tokens(&json).unwrap();
assert_eq!(tokens.cached_input, 500);
}
#[test]
fn test_collect_codex_session_files_nonexistent() {
let files = collect_codex_session_files(Path::new("/nonexistent/path"));
assert!(files.is_empty());
}
#[test]
fn test_insert_codex_session_skips_matching_proxy_log() -> Result<(), AppError> {
let db = Database::memory()?;
{
let conn = lock_conn!(db.conn);
conn.execute(
"INSERT INTO proxy_request_logs (
request_id, provider_id, app_type, model, request_model,
input_tokens, output_tokens, cache_read_tokens, cache_creation_tokens,
total_cost_usd, latency_ms, status_code, created_at, data_source
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
rusqlite::params![
"codex-proxy",
"openai",
"codex",
"gpt-5.4",
"gpt-5.4",
10,
2,
1,
7,
"0.01",
100,
200,
1000,
"proxy"
],
)?;
}
let delta = DeltaTokens {
input: 10,
cached_input: 1,
output: 2,
};
let inserted = insert_codex_session_entry(
&db,
"codex-session-dup",
&delta,
"gpt-5.4",
Some("session-1"),
Some("1970-01-01T00:16:45Z"),
)?;
assert!(!inserted);
let conn = lock_conn!(db.conn);
let count: i64 = conn.query_row("SELECT COUNT(*) FROM proxy_request_logs", [], |row| {
row.get(0)
})?;
assert_eq!(count, 1);
Ok(())
}
// ── 模型名归一化测试 ──
#[test]
fn test_normalize_codex_model_lowercase() {
assert_eq!(normalize_codex_model("GLM-4.6"), "glm-4.6");
assert_eq!(normalize_codex_model("DeepSeek-Chat"), "deepseek-chat");
assert_eq!(normalize_codex_model("GPT-5.4"), "gpt-5.4");
}
#[test]
fn test_normalize_codex_model_strip_prefix() {
assert_eq!(normalize_codex_model("openai/gpt-5.4"), "gpt-5.4");
assert_eq!(
normalize_codex_model("azure/gpt-5.2-codex"),
"gpt-5.2-codex"
);
assert_eq!(normalize_codex_model("OPENAI/GPT-5.4"), "gpt-5.4");
}
#[test]
fn test_normalize_codex_model_strip_iso_date() {
assert_eq!(normalize_codex_model("gpt-5.4-2026-03-05"), "gpt-5.4");
assert_eq!(
normalize_codex_model("gpt-5.4-pro-2026-03-05"),
"gpt-5.4-pro"
);
}
#[test]
fn test_normalize_codex_model_strip_compact_date() {
assert_eq!(normalize_codex_model("gpt-5.4-20260305"), "gpt-5.4");
assert_eq!(
normalize_codex_model("claude-opus-4-6-20260206"),
"claude-opus-4-6"
);
}
#[test]
fn test_normalize_codex_model_no_change() {
assert_eq!(normalize_codex_model("gpt-5.4"), "gpt-5.4");
assert_eq!(normalize_codex_model("gpt-5.2-codex"), "gpt-5.2-codex");
assert_eq!(normalize_codex_model("o3"), "o3");
assert_eq!(normalize_codex_model("deepseek-chat"), "deepseek-chat");
}
#[test]
fn test_normalize_codex_model_combined() {
// prefix + uppercase + ISO date
assert_eq!(
normalize_codex_model("openai/GPT-5.4-2026-03-05"),
"gpt-5.4"
);
// prefix + compact date
assert_eq!(normalize_codex_model("openai/gpt-5.4-20260305"), "gpt-5.4");
}
#[test]
fn test_cached_clamped_to_input() {
// cached > input 的异常场景应被 min() 钳制
let prev = Some(CumulativeTokens {
input: 100,
cached_input: 0,
output: 50,
});
let current = CumulativeTokens {
input: 110, // delta = 10
cached_input: 80, // delta = 80异常大于 input delta
output: 60,
};
let delta = compute_delta(&prev, &current);
// 钳制前cached_input = 80, input = 10
assert_eq!(delta.cached_input, 80);
assert_eq!(delta.input, 10);
// 实际钳制在调用侧delta.cached_input.min(delta.input)
let clamped = delta.cached_input.min(delta.input);
assert_eq!(clamped, 10);
}
}