The chat table has no computed columns (no DEFAULT, SERIAL/IDENTITY,
or TRIGGER that populate server-side values on UPDATE), and every
column modified by update_chat_by_id is set explicitly from Python
values earlier in the function. db.refresh therefore issues a SELECT
that replaces those just-written Python values with the round-tripped
database representation of the same values, which is a no-op for
functional purposes but pulls the entire chat.chat JSON blob back over
the network and through the driver's JSON decoder.
On large, active chats where chat.chat can reach tens of megabytes,
skipping the refresh measurably reduces latency and eliminates one
~JSON-sized transient allocation per write.
Avoid loading the full Chat row (including the potentially large `chat`
JSON column) just to read tag IDs from `meta.tags`. Issue a narrow
SELECT on `Chat.meta` instead, which is much cheaper for chats with
large message histories.
Co-authored-by: Claude <noreply@anthropic.com>
Convert chat_message_file_ids from list to set so the membership test
in the comprehension is O(1) instead of O(m), turning the dedupe from
O(n*m) into O(n+m). Also replace the redundant set([...]) with a set
comprehension.
https://claude.ai/code/session_01Le3NnqNhcgaJvFrDZGqmwe
Co-authored-by: Claude <noreply@anthropic.com>
Add Chat.id as a secondary sort key to all paginated chat queries
that use offset/limit pagination. When multiple chats share the same
updated_at timestamp, the database does not guarantee a stable order
across page boundaries, causing chats to appear on multiple pages.
This produces duplicate keys in the Svelte sidebar each-block
(each_key_duplicate error). Adding Chat.id as a tiebreaker ensures
fully deterministic ordering.
Extends the fix from #22383 (which addressed get_chat_ids_by_model_id)
to all remaining paginated chat queries.
* perf: eliminate 2 redundant full chat deserialization on every message send (#162)
Problem:
Every message send triggered get_chat_by_id_and_user_id which loads the
entire Chat row — including the potentially massive JSON blob containing
the full conversation history — even when the caller only needed a
simple yes/no ownership check or a single column value.
Two call sites in the message-send hot path were doing this:
1. main.py ownership verification: loaded the entire chat object including
all message history JSON, then checked `if chat is None`. The JSON blob
was immediately discarded — only the existence of the row mattered.
2. middleware.py folder check: loaded the entire chat object including all
message history JSON, then read only `chat.folder_id` — a plain column
on the chat table that requires zero JSON parsing.
Fix:
- Added `chat_exists_by_id_and_user_id()`: uses SQL EXISTS subquery which
returns a boolean without loading any row data. The database can satisfy
this from the primary key index alone.
- Added `get_chat_folder_id()`: queries only the `folder_id` column via
`db.query(Chat.folder_id)`, which tells SQLAlchemy to SELECT only that
single column instead of the entire row.
Both new methods preserve the same error handling semantics (return
False/None on exception) and user_id filtering (ownership check) as
the original get_chat_by_id_and_user_id.
Impact:
- Best case (typical): eliminates deserializing 2 full chat JSON blobs per
message send. For long conversations (hundreds of messages with tool
calls, images, file attachments), this blob can be multiple megabytes.
- Worst case: no regression — the new queries are strictly cheaper than
the old ones (less data transferred, less Python object construction,
no Pydantic model_validate overhead).
- The 3 remaining full chat loads in process_chat_payload (load_messages_from_db,
add_file_context, chat_image_generation_handler) are left untouched as
they genuinely need the full history and require separate analysis.
* Address maintainer feedback: rename method and inline call (#166)
- Rename chat_exists_by_id_and_user_id -> is_chat_owner
- Remove intermediate chat_owned variable; call is_chat_owner directly in if condition
Previously loaded the entire ChatModel (including the full conversation JSON
blob) just to extract the title string. Now queries only the Chat.title
column directly, which is already a top-level DB column.
The GET /chats/shared endpoint was loading full Chat rows including
the entire conversation history JSON blob, only to discard it and
return SharedChatResponse (id, title, share_id, timestamps). Now
uses with_entities() to select only the 5 needed columns, avoiding
deserialization of potentially large chat JSON for every shared chat.
- 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
Add null check after db.get(Chat, chat_id) before accessing chat.share_id. Returns None instead of crashing with AttributeError when chat doesn't exist.
