This improves the Captain overview by loading reporting metrics and FAQ
stats from separate endpoints. Range changes now refresh only the
metrics, while reopen-rate calculation reuses the resolved conversation
count to avoid redundant database queries.
## What changed
- Split Captain overview metrics and FAQ stats into separate APIs.
- Fetch FAQ stats independently from range-based metrics.
- Reuse resolved conversation totals when calculating reopen rate.
- Skip the reopen query when there are no resolved conversations.
This PR adds a Captain Assistant **Overview** page to show some KPI
metrics (conversations handled, auto-resolution, handoff, hours saved,
reopen-after-resolve, conversation depth) with trend deltas vs the
previous window, a real knowledge card, and a lazily-loaded, cached LLM
welcome summary.
### Highlights
- **Two contextual banners** on the overview:
- **Inbox banner** — prompts the user to connect an inbox when the
assistant has none, so it can actually do work.
- **Coverage banner** — warns when FAQ coverage is below 85% with more
than 100 responses pending review, linking straight to the pending
queue. Dismissal persists per-assistant for 24h via localStorage.
- **Batched stats builder** (`Captain::AssistantStatsBuilder`) computes
both windows in single FILTER-aggregated scans to cut round trips,
behind new `stats`/`summary` endpoints.
- **Cards included but intentionally left dummy / not rendered yet:**
`ResponseQualityCard` (flagged responses) and `CreditUsageCard` (credit
usage + daily chart). Credits are an account-wide counter with no
per-assistant or daily history, so there is no real data to back them
yet; they ship in the codebase but are not wired into the page.
### Index migration
- Replaces `index_messages_on_sender_type_and_sender_id` with
`index_messages_on_sender_and_created` `(sender_type, sender_id,
created_at)`.
- **Why it helps:** the per-assistant windowed lookups filter `sender_*`
*and* a `created_at` range. The old 2-column index matched every
lifetime row for the assistant and filtered the time slice at the heap
(~89% of rows discarded); adding `created_at` as a range column lets
Postgres scan only the window, and fixes the row-count estimate so the
planner picks a hash join over a nested loop on `reporting_events`.
- **Why dropping the old index is safe:** the new index is a left-prefix
superset `(sender_type, sender_id, ...)`, so every query the old one
served is still served. No code references it by name, and dropping it
keeps write amplification on `messages` neutral. Built/dropped with
`CONCURRENTLY` and `if_not_exists`/`if_exists` guards.
## Preview
<img width="2572" height="1754" alt="CleanShot 2026-06-29 at 22 38
51@2x"
src="https://github.com/user-attachments/assets/3798d09e-7850-48e4-b2cd-508533f15cea"
/>
## Banners
#### Inbox connect alert
<img width="2178" height="612" alt="CleanShot 2026-06-30 at 14 26 55@2x"
src="https://github.com/user-attachments/assets/373c371c-bb7d-4291-a0f9-620673078302"
/>
#### Coverage alert
<img width="2178" height="612" alt="CleanShot 2026-06-30 at 14 25 41@2x"
src="https://github.com/user-attachments/assets/e12d6308-11b6-4ba2-88a2-8a3077dd3e8f"
/>
---------
Co-authored-by: Sivin Varghese <64252451+iamsivin@users.noreply.github.com>
Migration Guide: https://chwt.app/v4/migration
This PR imports all the work related to Captain into the EE codebase. Captain represents the AI-based features in Chatwoot and includes the following key components:
- Assistant: An assistant has a persona, the product it would be trained on. At the moment, the data at which it is trained is from websites. Future integrations on Notion documents, PDF etc. This PR enables connecting an assistant to an inbox. The assistant would run the conversation every time before transferring it to an agent.
- Copilot for Agents: When an agent is supporting a customer, we will be able to offer additional help to lookup some data or fetch information from integrations etc via copilot.
- Conversation FAQ generator: When a conversation is resolved, the Captain integration would identify questions which were not in the knowledge base.
- CRM memory: Learns from the conversations and identifies important information about the contact.
---------
Co-authored-by: Vishnu Narayanan <vishnu@chatwoot.com>
Co-authored-by: Sojan <sojan@pepalo.com>
Co-authored-by: iamsivin <iamsivin@gmail.com>
Co-authored-by: Sivin Varghese <64252451+iamsivin@users.noreply.github.com>
