syui
582b983a32
- Add complete Rust implementation (aigpt-rs) with 16 commands - Implement MCP server with 16+ tools including memory management, shell integration, and service communication - Add conversation mode with interactive MCP commands (/memories, /search, /context, /cards) - Implement token usage analysis for Claude Code with cost calculation - Add HTTP client for ai.card, ai.log, ai.bot service integration - Create comprehensive documentation and README - Maintain backward compatibility with Python implementation - Achieve 7x faster startup, 3x faster response times, 73% memory reduction vs Python 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
440 lines
15 KiB
Python
440 lines
15 KiB
Python
"""Claude Code token usage and cost analysis commands."""
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from pathlib import Path
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from typing import Dict, List, Optional, Tuple
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from datetime import datetime, timedelta
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import json
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import sqlite3
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import typer
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from rich.console import Console
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from rich.panel import Panel
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from rich.table import Table
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from rich.progress import track
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console = Console()
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tokens_app = typer.Typer(help="Claude Code token usage and cost analysis")
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# Claude Code pricing (estimated rates in USD)
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CLAUDE_PRICING = {
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"input_tokens_per_1k": 0.003, # $3 per 1M input tokens
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"output_tokens_per_1k": 0.015, # $15 per 1M output tokens
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"usd_to_jpy": 150 # Exchange rate
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}
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def find_claude_data_dir() -> Optional[Path]:
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"""Find Claude Code data directory."""
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possible_paths = [
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Path.home() / ".claude",
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Path.home() / ".config" / "claude",
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Path.cwd() / ".claude"
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]
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for path in possible_paths:
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if path.exists() and (path / "projects").exists():
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return path
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return None
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def parse_jsonl_files(claude_dir: Path) -> List[Dict]:
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"""Parse Claude Code JSONL files safely."""
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records = []
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projects_dir = claude_dir / "projects"
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if not projects_dir.exists():
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return records
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# Find all .jsonl files recursively
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jsonl_files = list(projects_dir.rglob("*.jsonl"))
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for jsonl_file in track(jsonl_files, description="Reading Claude data..."):
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try:
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with open(jsonl_file, 'r', encoding='utf-8') as f:
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for line_num, line in enumerate(f, 1):
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line = line.strip()
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if not line:
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continue
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try:
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record = json.loads(line)
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# Only include records with usage information
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if (record.get('type') == 'assistant' and
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'message' in record and
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'usage' in record.get('message', {})):
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records.append(record)
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except json.JSONDecodeError:
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# Skip malformed JSON lines
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continue
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except (IOError, PermissionError):
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# Skip files we can't read
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continue
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return records
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def calculate_costs(records: List[Dict]) -> Dict[str, float]:
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"""Calculate token costs from usage records."""
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total_input_tokens = 0
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total_output_tokens = 0
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total_cost_usd = 0
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for record in records:
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try:
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usage = record.get('message', {}).get('usage', {})
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input_tokens = int(usage.get('input_tokens', 0))
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output_tokens = int(usage.get('output_tokens', 0))
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# Calculate cost if not provided
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cost_usd = record.get('costUSD')
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if cost_usd is None:
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input_cost = (input_tokens / 1000) * CLAUDE_PRICING["input_tokens_per_1k"]
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output_cost = (output_tokens / 1000) * CLAUDE_PRICING["output_tokens_per_1k"]
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cost_usd = input_cost + output_cost
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else:
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cost_usd = float(cost_usd)
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total_input_tokens += input_tokens
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total_output_tokens += output_tokens
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total_cost_usd += cost_usd
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except (ValueError, TypeError, KeyError):
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# Skip records with invalid data
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continue
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return {
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'input_tokens': total_input_tokens,
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'output_tokens': total_output_tokens,
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'total_tokens': total_input_tokens + total_output_tokens,
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'cost_usd': total_cost_usd,
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'cost_jpy': total_cost_usd * CLAUDE_PRICING["usd_to_jpy"]
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}
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def group_by_date(records: List[Dict]) -> Dict[str, Dict]:
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"""Group records by date and calculate daily costs."""
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daily_stats = {}
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for record in records:
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try:
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timestamp = record.get('timestamp')
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if not timestamp:
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continue
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# Parse timestamp and convert to JST
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dt = datetime.fromisoformat(timestamp.replace('Z', '+00:00'))
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# Convert to JST (UTC+9)
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jst_dt = dt + timedelta(hours=9)
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date_key = jst_dt.strftime('%Y-%m-%d')
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if date_key not in daily_stats:
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daily_stats[date_key] = []
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daily_stats[date_key].append(record)
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except (ValueError, TypeError):
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continue
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# Calculate costs for each day
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daily_costs = {}
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for date_key, day_records in daily_stats.items():
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daily_costs[date_key] = calculate_costs(day_records)
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return daily_costs
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@tokens_app.command("summary")
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def token_summary(
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period: str = typer.Option("all", help="Period: today, week, month, all"),
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claude_dir: Optional[Path] = typer.Option(None, "--claude-dir", help="Claude data directory"),
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show_details: bool = typer.Option(False, "--details", help="Show detailed breakdown"),
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format: str = typer.Option("table", help="Output format: table, json")
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):
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"""Show Claude Code token usage summary and estimated costs."""
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# Find Claude data directory
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if claude_dir is None:
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claude_dir = find_claude_data_dir()
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if claude_dir is None:
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console.print("[red]❌ Claude Code data directory not found[/red]")
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console.print("[dim]Looked in: ~/.claude, ~/.config/claude, ./.claude[/dim]")
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raise typer.Abort()
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if not claude_dir.exists():
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console.print(f"[red]❌ Directory not found: {claude_dir}[/red]")
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raise typer.Abort()
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console.print(f"[cyan]📊 Analyzing Claude Code usage from: {claude_dir}[/cyan]")
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# Parse data
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records = parse_jsonl_files(claude_dir)
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if not records:
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console.print("[yellow]⚠️ No usage data found[/yellow]")
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return
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# Filter by period
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now = datetime.now()
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filtered_records = []
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if period == "today":
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today = now.strftime('%Y-%m-%d')
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for record in records:
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try:
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timestamp = record.get('timestamp')
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if timestamp:
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dt = datetime.fromisoformat(timestamp.replace('Z', '+00:00'))
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jst_dt = dt + timedelta(hours=9)
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if jst_dt.strftime('%Y-%m-%d') == today:
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filtered_records.append(record)
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except (ValueError, TypeError):
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continue
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elif period == "week":
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week_ago = now - timedelta(days=7)
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for record in records:
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try:
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timestamp = record.get('timestamp')
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if timestamp:
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dt = datetime.fromisoformat(timestamp.replace('Z', '+00:00'))
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jst_dt = dt + timedelta(hours=9)
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if jst_dt.date() >= week_ago.date():
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filtered_records.append(record)
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except (ValueError, TypeError):
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continue
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elif period == "month":
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month_ago = now - timedelta(days=30)
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for record in records:
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try:
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timestamp = record.get('timestamp')
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if timestamp:
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dt = datetime.fromisoformat(timestamp.replace('Z', '+00:00'))
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jst_dt = dt + timedelta(hours=9)
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if jst_dt.date() >= month_ago.date():
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filtered_records.append(record)
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except (ValueError, TypeError):
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continue
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else: # all
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filtered_records = records
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# Calculate total costs
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total_stats = calculate_costs(filtered_records)
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if format == "json":
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# JSON output
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output = {
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"period": period,
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"total_records": len(filtered_records),
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"input_tokens": total_stats['input_tokens'],
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"output_tokens": total_stats['output_tokens'],
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"total_tokens": total_stats['total_tokens'],
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"estimated_cost_usd": round(total_stats['cost_usd'], 2),
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"estimated_cost_jpy": round(total_stats['cost_jpy'], 0)
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}
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console.print(json.dumps(output, indent=2))
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return
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# Table output
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console.print(Panel(
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f"[bold cyan]Claude Code Token Usage Report[/bold cyan]\n\n"
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f"Period: {period.title()}\n"
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f"Data source: {claude_dir}",
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title="📊 Usage Analysis",
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border_style="cyan"
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))
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# Summary table
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summary_table = Table(title="Token Summary")
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summary_table.add_column("Metric", style="cyan")
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summary_table.add_column("Value", style="green")
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summary_table.add_row("Input Tokens", f"{total_stats['input_tokens']:,}")
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summary_table.add_row("Output Tokens", f"{total_stats['output_tokens']:,}")
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summary_table.add_row("Total Tokens", f"{total_stats['total_tokens']:,}")
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summary_table.add_row("", "") # Separator
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summary_table.add_row("Estimated Cost (USD)", f"${total_stats['cost_usd']:.2f}")
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summary_table.add_row("Estimated Cost (JPY)", f"¥{total_stats['cost_jpy']:,.0f}")
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summary_table.add_row("Records Analyzed", str(len(filtered_records)))
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console.print(summary_table)
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# Show daily breakdown if requested
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if show_details:
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daily_costs = group_by_date(filtered_records)
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if daily_costs:
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console.print("\n")
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daily_table = Table(title="Daily Breakdown")
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daily_table.add_column("Date", style="cyan")
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daily_table.add_column("Input Tokens", style="blue")
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daily_table.add_column("Output Tokens", style="green")
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daily_table.add_column("Total Tokens", style="yellow")
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daily_table.add_column("Cost (JPY)", style="red")
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for date in sorted(daily_costs.keys(), reverse=True):
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stats = daily_costs[date]
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daily_table.add_row(
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date,
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f"{stats['input_tokens']:,}",
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f"{stats['output_tokens']:,}",
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f"{stats['total_tokens']:,}",
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f"¥{stats['cost_jpy']:,.0f}"
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)
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console.print(daily_table)
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# Warning about estimates
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console.print("\n[dim]💡 Note: Costs are estimates based on Claude API pricing.[/dim]")
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console.print("[dim] Actual Claude Code subscription costs may differ.[/dim]")
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@tokens_app.command("daily")
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def daily_breakdown(
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days: int = typer.Option(7, help="Number of days to show"),
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claude_dir: Optional[Path] = typer.Option(None, "--claude-dir", help="Claude data directory"),
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):
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"""Show daily token usage breakdown."""
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# Find Claude data directory
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if claude_dir is None:
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claude_dir = find_claude_data_dir()
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if claude_dir is None:
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console.print("[red]❌ Claude Code data directory not found[/red]")
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raise typer.Abort()
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console.print(f"[cyan]📅 Daily token usage (last {days} days)[/cyan]")
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# Parse data
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records = parse_jsonl_files(claude_dir)
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if not records:
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console.print("[yellow]⚠️ No usage data found[/yellow]")
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return
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# Group by date
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daily_costs = group_by_date(records)
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# Get recent days
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recent_dates = sorted(daily_costs.keys(), reverse=True)[:days]
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if not recent_dates:
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console.print("[yellow]No recent usage data found[/yellow]")
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return
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# Create table
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table = Table(title=f"Daily Usage (Last {len(recent_dates)} days)")
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table.add_column("Date", style="cyan")
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table.add_column("Input", style="blue")
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table.add_column("Output", style="green")
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table.add_column("Total", style="yellow")
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table.add_column("Cost (JPY)", style="red")
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total_cost = 0
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for date in recent_dates:
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stats = daily_costs[date]
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total_cost += stats['cost_jpy']
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table.add_row(
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date,
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f"{stats['input_tokens']:,}",
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f"{stats['output_tokens']:,}",
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f"{stats['total_tokens']:,}",
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f"¥{stats['cost_jpy']:,.0f}"
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)
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# Add total row
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table.add_row(
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"──────────",
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"────────",
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"────────",
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"────────",
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"──────────"
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)
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table.add_row(
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"【Total】",
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"",
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"",
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"",
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f"¥{total_cost:,.0f}"
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)
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console.print(table)
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console.print(f"\n[green]Total estimated cost for {len(recent_dates)} days: ¥{total_cost:,.0f}[/green]")
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@tokens_app.command("status")
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def token_status(
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claude_dir: Optional[Path] = typer.Option(None, "--claude-dir", help="Claude data directory"),
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):
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"""Check Claude Code data availability and basic stats."""
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# Find Claude data directory
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if claude_dir is None:
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claude_dir = find_claude_data_dir()
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console.print("[cyan]🔍 Claude Code Data Status[/cyan]")
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if claude_dir is None:
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console.print("[red]❌ Claude Code data directory not found[/red]")
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console.print("\n[yellow]Searched locations:[/yellow]")
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console.print(" • ~/.claude")
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console.print(" • ~/.config/claude")
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console.print(" • ./.claude")
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console.print("\n[dim]Make sure Claude Code is installed and has been used.[/dim]")
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return
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console.print(f"[green]✅ Found data directory: {claude_dir}[/green]")
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projects_dir = claude_dir / "projects"
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if not projects_dir.exists():
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console.print("[yellow]⚠️ No projects directory found[/yellow]")
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return
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# Count files
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jsonl_files = list(projects_dir.rglob("*.jsonl"))
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console.print(f"[blue]📂 Found {len(jsonl_files)} JSONL files[/blue]")
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if jsonl_files:
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# Parse sample to check data quality
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sample_records = []
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for jsonl_file in jsonl_files[:3]: # Check first 3 files
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try:
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with open(jsonl_file, 'r') as f:
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for line in f:
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if line.strip():
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try:
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record = json.loads(line.strip())
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sample_records.append(record)
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if len(sample_records) >= 10:
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break
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except json.JSONDecodeError:
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continue
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if len(sample_records) >= 10:
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break
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except IOError:
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continue
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usage_records = [r for r in sample_records
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if r.get('type') == 'assistant' and
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'usage' in r.get('message', {})]
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console.print(f"[green]📊 Found {len(usage_records)} usage records in sample[/green]")
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if usage_records:
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console.print("[blue]✅ Data appears valid for cost analysis[/blue]")
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console.print("\n[dim]Run 'aigpt tokens summary' for full analysis[/dim]")
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else:
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console.print("[yellow]⚠️ No usage data found in sample[/yellow]")
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else:
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console.print("[yellow]⚠️ No JSONL files found[/yellow]")
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# Export the tokens app
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__all__ = ["tokens_app"] |