feat(v0.7.0): implement cost tracking and token usage

[dongkoony]

Phase 1: Basic token tracking and cost calculation

Changes:

• Add token usage fields to llm_logs table (input/output/cached/reasoning)
• Add cost tracking fields (cost_input_usd, cost_output_usd, cost_total_usd)
• Create llm_model_pricing table for model pricing configuration
• Implement cost calculation logic in cost_utils.py
• Update llm_client.py to extract token information from API responses
• Modify /chat endpoint to save token and cost data
• Add architecture design document for v0.7.0
• Add AI agent documentation (agent/ directory)

Database:

• Migration script: scripts/migrate_v0.7.0.sql
• New table: llm_model_pricing with 7 initial models
• New columns in llm_logs: 8 fields (5 token + 3 cost)

API Changes:

• ChatResponse now includes usage and cost fields (optional)
• Backwards compatible: existing API calls work without changes

Docs:

• docs/ARCHITECTURE_v0.7.0.md: Complete v0.7.0 design document
• agent/: AI agent documentation for Claude Code and OpenAI Codex

Related:

• Issue: Cost tracking feature request
• Roadmap: v0.7.0 milestone