Some databases contain chat records where 'history' or 'messages' are
stored as lists instead of dicts. This causes an AttributeError
('list' object has no attribute 'items') during the
8452d01d26d7_add_chat_message_table migration.
Add isinstance checks to skip chat records with unexpected data shapes
gracefully, matching the existing pattern used for individual message
validation.
* fix: normalize usage tokens + migration streaming/batching
- Migration: replace .fetchall() with yield_per streaming, replace per-message INSERT+SAVEPOINT with batched inserts (5k/batch) with fallback to row-by-row on error, add progress logging
- Write path: call normalize_usage() in upsert_message() before saving to ensure input_tokens/output_tokens always present
- Read path: analytics queries now COALESCE across input_tokens/prompt_tokens and output_tokens/completion_tokens so historical data with OpenAI-format keys is visible
* fix: restore defensive timestamp conversion in migration
Re-add try/except around int(float(timestamp)) that was accidentally dropped. Without this, a non-numeric timestamp string would cause a TypeError on the subsequent comparison, breaking the entire upgrade.
* revert: remove changes to chat_messages.py
* feat: add LOG_FORMAT env var with JSON formatter for early logging
Introduce LOG_FORMAT environment variable (set to "json" to enable).
When active, logging.basicConfig() uses a JSONFormatter that outputs
single-line JSON objects with fields: ts, level, msg, caller, error,
stacktrace. This covers all log messages emitted during module imports
before Loguru's start_logger() takes over.
* feat: add JSON sink for Loguru when LOG_FORMAT=json
Add _json_sink() as a Loguru sink function that writes single-line JSON
to stdout. In start_logger(), conditionally use the JSON sink instead of
the plain-text stdout_format when LOG_FORMAT is set to "json".
* feat: suppress ASCII banner and fix alembic logging in JSON mode
- Wrap the ASCII art banner print in main.py with a LOG_FORMAT != "json"
guard so JSON output stays machine-parseable.
- Skip alembic's fileConfig() call in migrations/env.py when
LOG_FORMAT=json to prevent it from replacing the JSON log handlers
installed during early startup.
- Add chat_message table for message-level analytics with usage JSON field
- Add migration to backfill from existing chats
- Add /analytics endpoints: summary, models, users, daily
- Support hourly/daily granularity for time-series data
- Fill missing days/hours in date range
- Added sqlcipher3 dependency to requirements.txt for SQLCipher integration.
- Modified database connection handling in wrappers.py to support encrypted SQLite databases using the new sqlite+sqlcipher:// URL protocol.
- Updated db.py to handle SQLCipher URLs for SQLAlchemy connections.
- Enhanced Alembic migration environment to support SQLCipher URLs.
