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40878eeba4b3d2ab11edc97fc8e5a0d1f92ba585
847 Commits
| Author | SHA1 | Message | Date | |
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40878eeba4 | feat: add AI provider schema expansion (#25412) | ||
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b7525a9b40 |
feat: add search and filter support to chats endpoint (#25391)
Fixes https://linear.app/codercom/issue/CODAGT-432 Adds structured search/filter capabilities to the `GET /api/experimental/chats/` endpoint via the `q` query parameter. All filters use explicit `key:value` syntax; bare terms are rejected to reserve them for potential future full-text search. > Generated by Coder Agents Co-authored-by: Danielle Maywood <danielle@themaywoods.com> Co-authored-by: Jaayden Halko <jaayden.halko@gmail.com> |
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9b6eadab77 |
fix: drop N+1 db query on template ACL available (#25465)
Fixes [PLAT-149](https://linear.app/codercom/issue/PLAT-149/template-permissions-search-is-extremely-slow-with-many-groups). `/acl/available` ran a db query per group. A deployment with >5,000 groups made this route extremely slow. |
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dd3223451b | feat: add AI providers HTTP CRUD handlers (#24894) | ||
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5a8d0016a5 |
feat: add personal skill storage, API, and SDK (#25363)
> Mux updated this PR on behalf of Mike. ## Stack Context This PR is the storage, permissions, API, and SDK layer for experimental personal skills. #25362 has landed on `main`, so this branch is restacked directly on `main`. Stack order: 1. #25363 storage, permissions, API, and SDK 2. #25365 API test coverage 3. #25366 chattool and chatd integration 4. #25066 settings UI and docs 5. #25386 personal skills slash menu ## What? Adds the `user_skills` database table, generated queries, RBAC resources and scopes, audit resource handling, experimental user-scoped CRUD endpoints, SDK types, and generated API/site types. Follow-up review and restack fixes: - Enforce a bounded personal skill description in parser and database constraints. - Return `403 Forbidden` for unauthorized create and update attempts. - Return explicit conflict responses when soft-deleted users are targeted. - Keep user admins out of personal skills, while site owners can read and delete but not create or update. - Document trigger-raised constraint names and keep schema constants covered by tests. - Reuse `UserSkillMetadata` in the full `UserSkill` SDK response type. - Generate user skill IDs in Go instead of relying on a database default. - Rebase on latest `main` and renumber the user skills migration to `000502_user_skills`. ## Why? Personal skills need durable user-owned storage with owner authorization, limited site-owner moderation, and a hidden API surface before chatd can consume them. ## Validation - `make gen` - `go test ./coderd/database -run '^TestUserSkillSchemaConstants$' -count=1` - `go test ./coderd/database/dbauthz -run '^TestMethodTestSuite/TestUserSkills$' -count=1` - `go test ./coderd -run '^TestPatchUserSkill$' -count=1` - `go test ./codersdk ./coderd/database/db2sdk` - `make lint` - pre-commit hook on `97fd58108d` |
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170a6e1fe9 | feat: add chat sharing foundation (#25041) | ||
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78d4cf9e47 | fix: soft-delete stale workspace agents on new build (#25207) | ||
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238968cfa0 |
feat: add per-group AI budget table and endpoints (#25203)
Closes https://linear.app/codercom/issue/AIGOV-284/add-group-budgets-table-and-crud-api ## Summary Adds the `group_ai_budgets` table and the following endpoints: - `GET /api/v2/groups/{group}/ai/budget` - `PUT /api/v2/groups/{group}/ai/budget` - `DELETE /api/v2/groups/{group}/ai/budget` Each group may have at most one budget row. If no row exists, no budget is enforced. ### Feature gate Added `RequireFeatureMW(FeatureAIBridge)` on the `/ai/budget` sub-route. ## RBAC Authorization reuses `rbac.ResourceGroup` with the existing `.InOrganization(...).WithID(...)` scoping model. The `dbauthz` wrappers load the parent `groups` row and authorize against it. No new resource type is introduced. As a result, anyone with `group:update` permissions (Owner, OrgAdmin, or UserAdmin within the organization) can manage AI budgets for that group. ## Read access for group members `database.Group.RBACObject()` grants `policy.ActionRead` to all members of the group through the group ACL: ```go func (g Group) RBACObject() rbac.Object { return rbac.ResourceGroup.WithID(g.ID). InOrg(g.OrganizationID). // Group members can read the group. WithGroupACL(map[string][]policy.Action{ g.ID.String(): { policy.ActionRead, }, }) } ``` Because the `GET` endpoint authorizes against the same loaded `Group` object, any group member can call: ```text GET /api/v2/groups/{group}/ai/budget ``` `PUT` and `DELETE` remain admin-only. The group ACL grants only `ActionRead`, so write operations continue to require role-based `group:update` permissions. ## Alternative considered A dedicated `rbac.ResourceGroupAiBudget` resource would allow budget management to be separated from general group administration. We decided not to add that complexity for now. |
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9ddfafe2b1 | feat: add chat ACL database foundation (#25080) | ||
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841b777ccd | feat: add ai_providers table, queries, dbauthz, audit, RBAC (#24892) | ||
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25a803221e | feat: add shell tool display mode preference (#25029) | ||
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cb37047dce |
feat: dedicated /prompts endpoint for chat history cycle (#25083)
Follow-up to #25004. The merged change cycles only through messages
already loaded in the in-memory chat store (page size 50). Long chats
and chats whose oldest turns have rolled out of the page lose access to
their earlier prompts in the composer's up/down arrow cycle. This PR
adds a dedicated server endpoint that returns the full prompt history,
newest first, and rewires the composer to use it.
## What changed
### Endpoint
`GET /api/experimental/chats/{chat}/prompts?limit=N`
```go
type ChatPrompt struct { ID int64; Text string }
type ChatPromptsResponse struct { Prompts []ChatPrompt }
```
- `limit`: `0..2000`. `0` (the default) is treated as the server-side
default of 500; out-of-range values return `400`. Negative values are
rejected by the SDK's `PositiveInt32` parser before reaching the
handler.
- Auth: parent-chat read in `dbauthz`, mirroring
`GetChatMessagesByChatID`.
- The SQL filters `role='user'`, `deleted=false`, `visibility IN
('user','both')`, guards the lateral with `jsonb_typeof(content) =
'array'` so legacy V0 scalar-string rows are silently skipped, then
unrolls `content` JSONB with `WITH ORDINALITY` and concatenates only
`type='text'` parts in original order via `string_agg(... ORDER BY
ordinality)`. Messages whose joined text is whitespace-only are dropped
via `HAVING ... ~ '\S'` so cycling never lands on a blank entry.
### Partial index (migration `000494`)
```sql
CREATE INDEX idx_chat_messages_user_prompts
ON chat_messages (chat_id, id DESC)
WHERE deleted = false
AND role = 'user'
AND visibility IN ('user', 'both');
```
The partial WHERE matches the query's filter exactly and the key order
matches `ORDER BY id DESC`, so the planner gets both the filter and the
ordering from the index without a sort step.
`EXPLAIN ANALYZE` on a synthetic 51-chat × 5,000-message dataset (≈260k
rows, 10k user prompts in the target chat, `random_page_cost=1.1`):
| | Plan | Buffers hit | Time |
|---|---|---|---|
| Without index | `Index Scan Backward using chat_messages_pkey`,
**250,848 rows removed by filter** | 6,683 | 32.4 ms |
| With index | `Index Scan using idx_chat_messages_user_prompts`, no
filter | 38 | 1.3 ms |
≈25× faster, 175× fewer buffer hits.
### Frontend
- `chatPromptsKey` / `chatPromptsQuery` factories in
`site/src/api/queries/chats.ts` (`staleTime: 30s`, `enabled: chatId !==
""`, asks the server for 500 prompts).
- `ChatPageContent.tsx` replaces the in-memory derivation with
`useQuery(chatPromptsQuery(chatId ?? ""))`. The composer's existing
`cycleHistorySnapshotRef` anchors the in-flight cycle so a refetch
arriving mid-cycle cannot shift the indexed prompt out from under the
user.
- `getEditableUserMessagePayload` now concatenates user-message text
parts verbatim, mirroring the server's `string_agg(part->>'text', ''
ORDER BY ordinality)`, instead of routing through the streaming-oriented
`parseMessageContent` / `appendText` pipeline (which drops
whitespace-only chunks — correct for assistant streams, wrong for a
user's persisted message). This keeps the cycle and the edit path in
agreement on the same message. File blocks are still pulled separately
via
`parseMessageContent(...).blocks.filter(isEditableUserMessageFileBlock)`.
- Cache invalidation in `createChatMessage.onSuccess`,
`editChatMessage.onSettled`, and `useChatStore.upsertCacheMessages`
(only when an upserted message has `role === "user"`).
- Page-level stories pre-seed `chatPromptsKey(CHAT_ID)` from the same
`messagesData` to keep them offline.
## Tests
- New `TestGetChatUserPrompts` in `coderd/exp_chats_test.go` with five
subtests:
- `NewestFirstFiltering` — multi-part concatenation, non-text parts
skipped, whitespace-only filtered, soft-deleted excluded, `model`-only
visibility excluded, assistant-role excluded by `cm.role = 'user'`,
legacy V0 scalar row silently excluded by the `jsonb_typeof` guard,
ordering newest first.
- `LimitClampsResults` — explicit `limit=2` returns the two newest
prompts.
- `InvalidLimitRejected` — `limit=5000` is `400 Bad Request`.
- `NotFoundForOtherUsers` — a separate user in the same org gets `404`,
not the prompts.
- `EmptyResultIsJSONArray` — zero-message chat and assistant-only chat
both return `Prompts: []` (non-nil, empty).
- New unit test in `messageParsing.test.ts` asserting that
`getEditableUserMessagePayload(["hello", " ", "world"])` returns `"hello
world"`, locking in the agreement with the SQL `string_agg`.
- `dbauthz_test.go` adds the
`MethodTestSuite.TestChats/GetChatUserPromptsByChatID` entry, asserting
parent-chat `policy.ActionRead`.
- `pnpm test src/pages/AgentsPage` — 1159 passed, 2 skipped.
- `make gen` produces no diff.
## Manual verification
Seeded a dev chat with Claude Sonnet 4.6 via the aibridge Anthropic
provider and posted 20 user prompts end-to-end. Verified that the
`/prompts` endpoint returns 20 rows newest-first, that `limit=10` clamps
correctly, that `limit=0` uses the server default of 500, and that the
up/down keyboard cycle in the composer walks the same sequence (and
reverses correctly back to the empty draft).
## Out of scope
- Cross-chat history.
- Per-user opt-out for the cycle.
- File-reference / attachment cycling — the cycle continues to reproduce
plain text only, by design.
<details>
<summary>Implementation plan</summary>
# CODAGT-319 Follow-up — Dedicated `/prompts` endpoint
## Context
The merged feature ([#25004](https://github.com/coder/coder/pull/25004)
/ [
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024132e8a4 |
feat: add theme_mode, theme_light, theme_dark to UserAppearanceSettings (#25076)
Part 1: Backend portion of a change broken into 2 PRs. Part 2: #25077 Adds three new UserAppearanceSettings fields (theme_mode, theme_light, theme_dark) on top of the existing theme_preference and terminal_font. Replaces GetUserThemePreference and GetUserTerminalFont with a single GetUserAppearanceSettings aggregate query. The PUT handler is wrapped in db.InTx so sync-mode's mode + slot writes can never half-apply. |
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341051ceee | fix: exclude service accounts from license seat count (#24401) | ||
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5040ab6fca |
feat: filter chats by diff URL via the q search parameter (#24970)
Adds a `diff_url:` term to the `q` search parameter on `GET /api/experimental/chats` so callers can look up the chat associated with a particular pull request, merge request, or any other URL persisted on the chat's diff status. ``` q=diff_url:"https://github.com/coder/coder/pull/123" ``` Match is case-insensitive. When the URL lives on a delegated sub-agent's diff status, the parent chat is returned so the relationship surfaces from a single lookup. <details> <summary>Design notes</summary> - **Forge-agnostic.** Reuses the existing `chat_diff_statuses.url` column rather than introducing a `pr:` vocabulary, since the SDK already documents the URL as "may point to a pull request or a branch page depending on whether a PR has been opened." Works for GitHub PRs, GitLab MRs, branch pages, etc. - **Composes with `archived:`.** The two terms can be combined: `q=archived:true diff_url:"..."`. - **Case handling.** The parser used to lowercase the entire `q` string up front, which would mangle URL path segments. Switched to lowercasing only the field key inside `searchTerms` (already happens there) and keeping the value as the caller typed it. The SQL comparison lowercases on both sides. - **Validation.** `diff_url` must be a syntactically valid HTTP(S) URL with a non-empty host. No forge-specific validation. - **Index.** Adds `idx_chat_diff_statuses_url_lower` on `LOWER(url)` so the lookup is cheap even on large datasets. - **Sub-agent fan-in.** `EXISTS` clause matches when the URL lives on the chat itself or any chat with `root_chat_id` equal to the chat's id, so a delegated sub-agent's PR pulls in its parent. - **Deferred.** Sentinels like `pr:any` / `pr:none` and a forge-agnostic state filter (`diff_state:open|merged|closed`) were intentionally left out of this change. They couple cleanly to a second forge or a clearer product call, and shipping them now would lock in vocabulary we may want to revisit. </details> ## Tests - `coderd/searchquery`: parser tests for valid URLs, case handling (key insensitive, value preserved), composition with `archived:`, and validation errors (non-HTTP scheme, missing host, malformed URL). - `coderd/exp_chats_test.go`: end-to-end coverage hitting `ListChats`. Verifies a root chat matches its own URL, a parent chat surfaces when only a sub-agent has the URL, lookups are case-insensitive, non-matching URLs return empty, and invalid URLs return `400`. --- _This PR was authored by a Coder Agent on behalf of @kylecarbs._ |
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96333acda3 |
fix(coderd): filter build instance agents in SQL (#25031)
Replaces the per-agent Go-side template-version filter in
`handleAuthInstanceID` with a purpose-built SQL query.
`GetWorkspaceBuildAgentsByInstanceID` joins `workspace_agents ->
workspace_resources -> workspace_builds -> provisioner_jobs ->
workspaces` and excludes:
- non-`workspace_build` provisioner jobs (template-version-import,
dry-run)
- deleted agents and sub-agents
- deleted workspaces
The handler:
- drops the per-candidate `GetWorkspaceResourceByID` /
`GetProvisionerJobByID` lookups
- drops the `provisioner_jobs.input` JSON parsing and the follow-up
`GetWorkspaceBuildByID` call
- compares `latestHistory.ID` against `selected.WorkspaceBuildID`
returned directly from the query
- preserves the existing recycled-instance safety check and matching
response codes
One intentional behavior tightening: agents whose workspace is deleted
now return 404 (previously they could reach the recycled-instance check
and return 400, or 200 if the stale build was still latest). This
matches the existing token-auth path, which already refuses to
authenticate against deleted workspaces.
The original `GetWorkspaceAgentsByInstanceID` query is intentionally
untouched. It remains the generic raw lookup used elsewhere in tests and
helpers.
The dbauthz wrapper for the new query uses the system-read fast path
with `fetchWithPostFilter` for non-system reads, with `RBACObject()`
delegating to the embedded `WorkspaceTable`.
Tests:
- new `TestGetWorkspaceBuildAgentsByInstanceID` covering newest-first
ordering, exclusion of deleted/sub agents, exclusion of template-import
and dry-run jobs, and exclusion of deleted workspaces
- new dbauthz mock test for `GetWorkspaceBuildAgentsByInstanceID`
- new `TestPostWorkspaceAuthAWSInstanceIdentity/RecycledInstanceID`
exercising the recycled-instance rejection branch (HTTP 400 when the
agent's build is no longer latest)
- existing `TestPostWorkspaceAuth{AWS,Azure,Google}InstanceIdentity`
continue to cover the handler end to end (including the template-version
+ workspace-build same-instance-ID scenario via
`setupInstanceIDWorkspace`)
> Mux is acting on Mike's behalf.
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b0b07536fc | feat: add opt-in Coder identity headers for MCP servers (#25153) | ||
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5c3b59151e |
feat: add Cmd/Ctrl+Enter send setting (#25062)
Adds an Agents General setting to require Cmd/Ctrl+Enter before sending
chat messages. When enabled, plain Enter inserts a newline in agent chat
inputs while the send button remains available.
The preference is now persisted server-side through
`/api/v2/users/{user}/preferences`, alongside the existing user
preference settings, and is applied to both the create-agent input and
existing chat composer. Storybook and API coverage verify the setting,
keyboard behavior, validation, and persistence.
<details>
<summary>Coder Agents notes</summary>
Generated by Coder Agents from a Slack request. Dogfooded with
agent-browser against the Storybook settings and chat input stories.
</details>
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b221632615 |
fix: wipe user secrets when user is soft-deleted (#24985)
Extend the delete_deleted_user_resources() trigger so that secrets belonging to a soft-deleted user are removed in the same transaction as the existing api_keys and user_links cleanup. user_secrets.user_id has ON DELETE CASCADE, but Coder soft-deletes users by flipping users.deleted rather than removing the row, so the foreign key cascade never fires and secrets would otherwise survive deletion. Assisted by Coder Agents. |
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4124d1137d |
feat: add ai_model_prices table (#24932)
# Summary Implements https://linear.app/codercom/issue/AIGOV-282/add-ai-model-price-table-and-seed-generator This PR lays the groundwork for AI Bridge cost controls (per the AI Governance RFC). It adds the foundation needed for future cost tracking: a place to store per-model token prices, a way to keep those prices in sync with upstream pricing data, and a startup mechanism that ensures every deployment has prices loaded before AI Bridge starts processing requests. The price data comes from [models.dev](https://models.dev/), a community-maintained catalogue of AI provider pricing. A generator script fetches the latest prices, filters to Anthropic and OpenAI for now, and produces a seed file checked into the repository. On every server startup the seed is applied to the database, so new releases automatically pick up any price corrections that landed since the previous one. Existing rows are overwritten with the latest prices; rows for models no longer in the seed are left untouched. # Batching the AI model price seed: three approaches Context: at server startup we seed the `ai_model_prices` table from an embedded JSON price book (~70 rows today, will grow as we add providers, potentially 4000+). Each row is: ```text (provider, model, input_price, output_price, cache_read_price, cache_write_price) ``` Any of the four price columns can be: - `NULL` → “price unknown for this dimension” - explicit `0` → “free” The batch must be an UPSERT so re-running is idempotent and existing rows pick up new prices. We considered three implementations. --- ## Approach 1 — Per-row UPSERT in a Go loop ```go for _, row := range rows { if err := db.UpsertAIModelPrice(ctx, database.UpsertAIModelPriceParams{ Provider: row.Provider, Model: row.Model, InputPrice: nullInt64(row.InputPrice), // ... }); err != nil { return err } } ``` ### Pros - Trivial. - NULL handling falls out naturally from `sql.NullInt64`. ### Cons - `N` round-trips per seed. - With ~70 rows that means ~70 statement executions on every startup, even inside a transaction. - Doesn't scale gracefully as the price book grows, potentially 4000+. --- ## Approach 2 — `UNNEST` with parallel arrays Pass each column as a separate Go slice. Postgres unnests them in parallel into a virtual table, then `INSERT ... SELECT`. ```sql INSERT INTO ai_model_prices ( provider, model, input_price, output_price, cache_read_price, cache_write_price ) SELECT UNNEST(@providers::text[]), UNNEST(@models::text[]), NULLIF(UNNEST(@input_prices::bigint[]), -1), NULLIF(UNNEST(@output_prices::bigint[]), -1), NULLIF(UNNEST(@cache_read_prices::bigint[]), -1), NULLIF(UNNEST(@cache_write_prices::bigint[]), -1) ON CONFLICT (provider, model) DO UPDATE SET input_price = EXCLUDED.input_price, output_price = EXCLUDED.output_price, cache_read_price = EXCLUDED.cache_read_price, cache_write_price = EXCLUDED.cache_write_price, updated_at = NOW(); ``` Go side: flatten rows into six parallel slices. Use a sentinel (`-1`) for “missing”, since `lib/pq` can't encode `NULL` into a `bigint[]` element. ```go providers := make([]string, len(rows)) models := make([]string, len(rows)) inputs := make([]int64, len(rows)) outputs := make([]int64, len(rows)) cacheR := make([]int64, len(rows)) cacheW := make([]int64, len(rows)) for i, r := range rows { providers[i] = r.Provider models[i] = r.Model inputs[i] = -1 if r.InputPrice != nil { inputs[i] = *r.InputPrice } outputs[i] = -1 if r.OutputPrice != nil { outputs[i] = *r.OutputPrice } cacheR[i] = -1 if r.CacheReadPrice != nil { cacheR[i] = *r.CacheReadPrice } cacheW[i] = -1 if r.CacheWritePrice != nil { cacheW[i] = *r.CacheWritePrice } } return db.UpsertAIModelPrices(ctx, database.UpsertAIModelPricesParams{ Providers: providers, Models: models, InputPrices: inputs, OutputPrices: outputs, CacheReadPrices: cacheR, CacheWritePrices: cacheW, }) ``` ### Pros - Single round-trip. ### Cons - The generated `sqlc` params become plain `[]int64`, which can't represent `NULL`. --- ## Approach 3 — `jsonb_array_elements` over a single `@seed::jsonb` (chosen) Pass the raw seed JSON as one parameter; let Postgres expand and parse it. ```sql INSERT INTO ai_model_prices ( provider, model, input_price, output_price, cache_read_price, cache_write_price ) SELECT elem->>'provider', elem->>'model', (elem->>'input_price')::bigint, (elem->>'output_price')::bigint, (elem->>'cache_read_price')::bigint, (elem->>'cache_write_price')::bigint FROM jsonb_array_elements(@seed::jsonb) AS elem ON CONFLICT (provider, model) DO UPDATE SET input_price = EXCLUDED.input_price, output_price = EXCLUDED.output_price, cache_read_price = EXCLUDED.cache_read_price, cache_write_price = EXCLUDED.cache_write_price, updated_at = NOW(); ``` Go side reduces to: ```go return db.UpsertAIModelPrices(ctx, seedJSON) ``` ### Pros - Single round-trip. - NULLs fall out naturally: - `(elem->>'cache_write_price')::bigint` becomes `NULL` - no sentinels - The seed is already JSON: - Existing precedent: - `jsonb_array_elements` is already used elsewhere in the codebase ### Cons - Less type-safe at the SQL boundary than `UNNEST` - Slightly less standard than `UNNEST` - Readers need familiarity with: - `jsonb_array_elements` - `->>` extraction syntax - Postgres pays JSON parse cost - negligible at our scale --- --- # Decision We picked Approach 3. It collapses the round-trips like `UNNEST` does, but without: - nullable-array workarounds - sentinel values |
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e7958713a9 | feat: add code diff display mode preference (#25027) | ||
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6b0518d051 |
fix: state-aware queued message promotion (#24819)
PromoteQueued now branches on chat status: synth tool results before the user message on requires_action, deferred reorder + Waiting on running so the worker's persist+auto-promote keeps partial output. Stale heartbeat falls through to the synchronous path; GetStaleChats picks up Waiting+queue to recover post-cleanup-crash. Endpoint returns 202. Closes CODAGT-119 |
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0bfb9f6f13 |
feat: show agent turn summary in agents sidebar (#24942)
Persists the agent-generated turn-end summary on `chats` and shows it as the Agents sidebar subtitle when present, falling back to the model name. Errors still take precedence. > Mux is acting on Mike's behalf. ## What changes **Storage.** New nullable `last_turn_summary` column on `chats` (migration `000486`). New `UpdateChatLastTurnSummary` query normalizes blank/whitespace input to `NULL`, preserves `updated_at` (so the chat does not jump to the top of the sidebar on summary writes), and uses an `expected_updated_at` stale-write guard so an older async summary cannot overwrite a newer turn. **Backend.** `coderd/x/chatd/chatd.go` decouples summary generation from webpush. Generated summaries persist for completed parent turns even when webpush is unconfigured or has no subscriptions. The same generated text is reused as the webpush body when webpush is configured, so the summary model is not called twice. Generic fallback push text is no longer persisted; it clears any stale summary instead. Error/interrupt/pending-action terminal paths clear `last_turn_summary` for the latest turn. **Frontend.** `AgentsSidebar.tsx` subtitle priority is now `errorReason || lastTurnSummary || modelName`, normalized via the existing `asNonEmptyString` helper from `blockUtils.ts`. ## Tests - `TestUpdateChatLastTurnSummary` (database): success, whitespace-to-NULL, stale guard rejects, `updated_at` preserved. - `TestUpdateLastTurnSummaryRejectsStaleWrites` (chatd internal): direct stale-`expected_updated_at` test. - `TestSuccessfulChatPersistsTurnSummaryWithoutWebPush`: persistence works without webpush subscriptions. - `TestSuccessfulChatSendsWebPushWithSummary`: same generated text drives both DB and push body. - `TestSuccessfulChatSendsWebPushFallbackWithoutSummaryForEmptyAssistantText`: fallback text is not persisted. - `TestErroredChatClearsLastTurnSummaryAndSendsWebPush`: error path clears the field. - `TestInterruptChatDoesNotSendWebPushNotification`: interrupt path clears the field, no push fires. - `AgentsSidebar.test.tsx`: subtitle priority for summary-present, error-wins, no-summary fallback, whitespace fallback. - `AgentsSidebar.stories.tsx`: `ChatWithTurnSummary` and `ChatWithTurnSummaryAndError`. ## Notes - No backfill. Existing chats keep showing the model name until their next turn completes. - Parent chats only in this iteration; the field is rendered on any `Chat` if a future change extends generation to children. - Decoupling generation from webpush adds quickgen model calls for completed parent turns that previously skipped generation when no subscriptions existed. Existing parent-only, assistant-text-present, `PushSummaryModel` configured, and bounded-timeout gates keep this behavior bounded. |
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2874d4b4cd |
feat: add chat debug retention purge (#24943)
> Mux is acting on Mike's behalf. Adds configurable retention for chat debug data, including the purge query, updated_at index, site config, experimental API, SDK types, frontend lifecycle setting, and docs. The purge deletes debug runs older than the configured retention window and relies on existing cascades to delete steps. The default retention is 30 days, and setting the value to 0 disables the purge. |
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1b2a1af097 |
feat: report user secrets adoption summary in telemetry (#24854)
Add a deployment-wide user secrets summary to the telemetry snapshot so we can track adoption of user secrets The summary reports: - A breakdown of secrets by which injection fields are populated: EnvNameOnly, FilePathOnly, Both, Neither - The distribution of secrets per user (max, p25, p50, p75, p90) All metrics are scoped to active non-system users. Soft-deleted users are excluded. The percentile distribution is computed across the entire active non-system user base, including users with zero secrets, so the percentiles reflect deployment-wide adoption. Assisted by Coder Agents. |
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4751416b29 |
fix!: persist structured chat errors (#24919)
**Breaking change for changelog:**
> `codersdk.Chat.last_error` now returns a structured `ChatError` object
(`{message, kind, provider, retryable, status_code, detail}`) instead of
a plain string. The chats API is experimental
(`/api/experimental/chats`), so this ships without a deprecation cycle;
consumers reading `chat.last_error` as a string must update to read
`chat.last_error.message`. SDK/generated TypeScript terminal error
payloads now use the single `ChatError` type; the live stream error
payload type is renamed from `ChatStreamError` to `ChatError`.
Persisted chat errors now carry the same provider-specific detail (kind,
provider, retryable, HTTP status, optional detail) as the live stream,
so refreshing a failed chat rehydrates with the full structured error
instead of a one-line headline.
Existing rows are migrated in place: legacy text errors are wrapped into
`{message, kind: "generic"}` so already-errored chats still render, and
rows with `last_error IS NULL` stay NULL. Internally, persisted fallback
decoding now reuses the existing `chaterror.KindGeneric` constant, with
no JSON value change.
Closes CODAGT-239
|
||
|
|
632dcdb63a | feat: add personal chat model overrides (#24715) | ||
|
|
0bb09935bc |
feat: add computer-use provider selection for AI agents (#24772)
Adds a deployment-wide setting to select the computer-use provider (Anthropic or OpenAI) for AI agents, plus the OpenAI computer-use runner needed to honor that selection. The setting is stored in `site_configs` under `agents_computer_use_provider`, defaults to Anthropic when unset, and is exposed via experimental GET/PUT endpoints under `/api/experimental/chats/config/computer-use-provider`. The chatd computer-use tool now dispatches to either `runAnthropicComputerUse` or `runOpenAIComputerUse` based on the resolved provider, with provider-specific result metadata for OpenAI screenshots. Frontend adds a provider dropdown to the Agents Experiments settings page nested under the virtual desktop toggle, with disabled state handling while virtual desktop is off and skeleton loaders while config queries are in flight. Hugo and Codex review follow-up: - Uses shared provider validation and clearer computer-use constant names. - Removes stale OpenAI pending-safety-checks commentary. - Documents why provider result metadata is needed for OpenAI screenshots. - Keeps the computer-use subagent visible when provider credentials are missing, then returns a clear spawn-time configuration error. - Uses OpenAI's recommended 1600x900 screenshot geometry to preserve the native 16:9 aspect ratio. - Moves OpenAI-specific computer-use helpers into `coderd/x/chatd/chatopenai/computeruse` after rebasing onto the provider package refactor in `main`. - Converts OpenAI pixel scroll deltas to Coder desktop wheel-click amounts. - Preserves OpenAI pointer modifiers with key down/up desktop actions and rejects unsupported non-left double-click buttons explicitly. - Maps OpenAI back/forward side-button clicks to browser navigation key actions. - Defaults omitted OpenAI click buttons to left-click. - Retries mouse release cleanup if the final OpenAI drag release fails. - Keeps computer-use subagent availability messages stable when provider config cannot be loaded, while logging the backend error. - Releases remaining OpenAI modifier keys if a synthetic key-up cleanup action fails. - Updates Storybook interaction stories so provider snapshots show the selected final provider. > Mux updated this PR description on behalf of Mike. |
||
|
|
033ed0bb82 |
feat: add admin-configurable chat title generation model (#24838)
Adds an admin-configurable deployment-wide setting that controls which
model is used for chat title generation. Admins can pick any enabled
chat model config from the Agents settings page, or leave the setting
unset to keep the existing fast-models-then-chat-model fallback
algorithm.
When a model is selected, both automatic and manual title generation use
only that model, with no silent fallback. When the configured model is
disabled, missing credentials, or otherwise unusable, automatic title
generation skips entirely (best-effort) and manual title regeneration
returns a clear error, so admins notice the misconfiguration instead of
silently routing title traffic through another provider.
## Surface
- New deployment-wide setting stored as a `site_configs` row
(`agents_chat_title_generation_model_override`).
- New experimental endpoint `GET/PUT
/api/experimental/chats/config/model-override/{context}`.
- Frontend: title generation now appears as a third dropdown on the
Agents admin settings page alongside the existing general and explore
context overrides.
## DRY refactors folded in
Title generation is integrated as a third value of the existing
`ChatModelOverrideContext` type alongside `general` and `explore`,
sharing the parameterized HTTP route, SDK methods, generated types, and
frontend API plumbing rather than introducing a parallel surface. The
`Agent` prefix was dropped from the type and route since title
generation is not a delegated agent.
The chatd model-override resolver is also shared.
`resolveConfiguredModelOverride` now takes a `failureMode` parameter:
- Subagent overrides use soft failure: misconfigured overrides are
logged and the parent model is used.
- Title generation uses hard failure: misconfigured overrides return an
explicit error so manual title regeneration surfaces the
misconfiguration and automatic title generation skips instead of
silently falling back.
> Mux is acting on Mike's behalf.
|
||
|
|
6b9637d85a | feat: replace pgcoordinator pg_notify triggers with app-level Publish() (#24717) | ||
|
|
06bad73df4 |
feat: add admin-configurable advisor API, SDK, and queries (#24621)
## Summary
Add the **admin-configurable advisor configuration**: database-backed storage, SDK types, and the experimental HTTP handlers that back the admin settings UI (later PRs). Follows the same "site-configs" pattern as Virtual Desktop.
## Motivation
The advisor needs runtime-tunable knobs (enable/disable, per-run cap, max output tokens, reasoning effort, optional model override) without a service restart or redeploy. Using the existing `site_configs` K/V table keeps this pattern consistent with other admin features and avoids a bespoke schema.
## Changes
### Database (`coderd/database/queries/siteconfig.sql`)
- `GetChatAdvisorConfig` returns the stored JSON blob (default `'{}'`) under key `agents_advisor_config`.
- `UpsertChatAdvisorConfig` uses the standard `INSERT ... ON CONFLICT` pattern.
- Regenerated via `make gen` (queries.sql.go + mocks).
### SDK (`codersdk/chats.go`)
- `AdvisorConfig` type with `Enabled`, `MaxUsesPerRun`, `MaxOutputTokens`, `ReasoningEffort` (`""` / `low` / `medium` / `high`), `ModelConfigID uuid.UUID`.
- Client methods: `ChatAdvisorConfig(ctx)` / `UpdateChatAdvisorConfig(ctx, cfg)`.
### API (`coderd/exp_chats.go`)
- `GET /api/experimental/chats/config/advisor`: reads current config; relies on `ActorFromContext` validation.
- `PUT /api/experimental/chats/config/advisor`: requires `policy.ActionUpdate` on `rbac.ResourceDeploymentConfig`.
- Handlers unmarshal `{}` to a typed zero value and re-marshal on upsert for schema stability.
- Tests in `exp_chats_test.go` cover empty defaults, round-trip update, unauthorized update, and invalid body.
## Stack context
This is **PR 3 of 6** in the advisor feature stack. Consumed by:
- PR 4 (`feat/advisor-04-chatd-runtime`), which reads this config on every `runChat`.
- PR 6 (`feat/advisor-06-admin-settings-ui`), which renders the admin form.
## Scope / non-goals
- No `chatd` read path (lands in PR 4).
- No UI (lands in PR 6).
- `agents_advisor_config` remains a single-row JSON blob; we intentionally do not shard per-org/per-template yet.
## Validation
- `make gen`
- `go test ./coderd/database/... -run TestChatAdvisor`
- `go test ./coderd/... -run TestChatAdvisorConfig`
- `make lint`
---
<details>
<summary>📋 Implementation Plan (shared across the advisor stack)</summary>
# Plan: Add a Mux-style advisor tool to coder agents/chatd
## Outcome
Add a first-class `advisor` tool to agent chats in `coderd/x/chatd` that feels native to Coder:
- it is a built-in server-side tool, not an MCP/dynamic-tool workaround;
- it performs a nested **tool-less** model call for strategic advice;
- it is exposed only when eligible, and the prompt mentions it only when it is actually available;
- it is treated as a **planning-only** tool so it does not run alongside action tools in the same batch;
- it tracks usage/cost separately enough for operators to reason about it;
- it has a minimally polished UI in the Agents page;
- and it ships with explicit dogfooding evidence, including screenshots and repro videos.
## Design decisions to lock before coding
1. **Primary architecture:** native built-in tool in `chattool/`, backed by a small `chatadvisor` package.
2. **Nested model execution:** reuse chatd's existing model/provider stack for a one-step, tool-less advisor call rather than inventing a new provider pathway.
3. **Execution policy:** treat `advisor` as an exclusive/planning-only tool; mixed batches must return structured policy errors and force the model to retry cleanly.
4. **Availability:** initial rollout is for root agent chats only; disable for child/sub-agent chats until recursion/cost policy is proven.
5. **Prompt sync:** use one eligibility boolean to drive both tool registration and advisor guidance injection.
6. **Persistence/cost split:** MVP should keep advisor usage visible in result metadata and server metrics; only add DB schema if product/billing explicitly needs queryable advisor-specific cost.
7. **UI scope:** generic tool rendering is an acceptable temporary milestone during backend bring-up, but the release candidate should include a dedicated lightweight advisor renderer.
## Delivery model
The work should be executed as coordinated workstreams with one integration owner and parallel contributors for low-conflict areas. The integration owner should own `coderd/x/chatd/chatd.go` because prompt assembly, tool registration, and model resolution all converge there.
## Detailed workstreams
### Repo evidence used for this plan
<details>
<summary>Mux reference and current chatd seams</summary>
**Mux reference implementation**
- `src/node/services/tools/advisor.ts` — native advisor tool implementation.
- `src/common/constants/advisor.ts` — advisor prompt/constants and truncation policy.
- `src/common/utils/tools/tools.ts` — conditional tool registration.
- `src/node/services/streamContextBuilder.ts` — injects advisor guidance only when the tool is available.
**Current chatd seams**
- `coderd/x/chatd/chatd.go`
- `processChat()` — tool assembly, prompt assembly, and chatloop invocation.
- `resolveChatModel()` — current model/provider/key resolution seam.
- `type Config struct` — server-level chatd configuration surface.
- `coderd/x/chatd/chatloop/chatloop.go`
- `Run()` — main streaming/model loop.
- `executeTools()` — built-in tool execution/batching seam.
- `coderd/x/chatd/chattool/` — built-in tool implementations.
- `site/src/pages/AgentsPage/components/ChatElements/tools/Tool.tsx` — tool renderer dispatch.
- `site/src/pages/AgentsPage/components/ChatConversation/messageParsing.ts` and `ConversationTimeline.tsx` — tool/result merge and rendering flow.
</details>
### Workstream map and ownership
| Workstream | Primary owner | Main files | Can run in parallel? | Done when |
|---|---|---|---|---|
| 0. Integration + gating | Integration lead | `coderd/x/chatd/chatd.go` | No; central merge lane | Tool registration, prompt sync, and model selection are wired together |
| 1. Advisor runtime + tool | Backend agent | new `coderd/x/chatd/chatadvisor/`, new `coderd/x/chatd/chattool/advisor.go` | Yes | Tool can perform a tool-less advisor call in memory and return structured results |
| 2. Planning-only execution policy | Chatloop agent | `coderd/x/chatd/chatloop/chatloop.go`, related tests | Yes | Mixed `advisor` + action-tool batches are rejected cleanly and deterministically |
| 3. Metrics/usage/config | Backend/telemetry agent | `chatd.go`, `chatloop/metrics.go`, optional config plumbing | Partially; coordinate with integration lead | Advisor usage is separately visible in metadata/metrics and limits are enforced |
| 4. Frontend rendering | Frontend agent | `site/.../tools/Tool.tsx`, new `AdvisorTool.tsx`, stories | Yes after result schema stabilizes | Advisor renders as a readable card and story tests pass |
| 5. Dogfood + QA evidence | QA agent | dev server, Storybook, dogfood output | After backend + UI are usable | Repro videos, screenshots, and a concise QA report exist |
### Parallelization rules
- **Do not split `coderd/x/chatd/chatd.go` across multiple execution agents without an integration lead.** That file owns prompt building, tool registration, model resolution, and cost persistence.
- Workstreams 1 and 2 can be developed in parallel and then stacked onto the integration branch.
- Workstream 4 should begin once the backend result schema is agreed on, even if the backend is still behind a feature flag.
- Any agent that needs to re-check Mux behavior should clone `coder/mux` into a temporary directory (for example, `$(mktemp -d)/mux`) and inspect it read-only; do not vendor or copy code from Mux directly.
## Phase 0 — Preflight and guardrails
### Goals
- Align the team on the smallest shippable architecture.
- Prevent scope creep into MCP/dynamic-tool/sub-agent variants.
- Decide upfront what is MVP vs. follow-up.
### Tasks
1. **Confirm the MVP boundary.**
- Ship a built-in advisor tool first.
- Do **not** make MCP, dynamic tools, or sub-agents the primary implementation.
- Do **not** add transient streaming phases in the first backend PR unless they fall out almost for free.
2. **Confirm local workflow hygiene before coding.**
- Ensure the repo is using the project git hooks from `scripts/githooks`.
- Do not bypass hooks with `--no-verify`.
- Use `./scripts/develop.sh` for the full dev server rather than manual build/run commands.
3. **Lock the model-selection policy.**
- **Recommended MVP:** advisor uses the same resolved provider/model/cost config as the current chat, with advisor-specific max-output and usage caps.
- **Follow-up only if required:** add a separate `AdvisorModelConfigID`-style override that resolves through the existing `configCache`/model-config path. Do not invent a new free-form `provider:model` parser if chatd already stores provider/model separately.
4. **Lock the persistence policy.**
- **Recommended MVP:** no DB migration. Persist advisor-visible metadata in the tool result and record separate metrics in memory/Prometheus.
- **Only if product/billing explicitly asks for queryable advisor cost:** add a later DB migration or usage table, following the normal `queries/*.sql` + `make gen` workflow.
5. **Create an execution ADR note in the work item or tracking doc.**
- Capture: built-in tool, tool-less nested call, root-chat-only rollout, exclusive execution policy, MVP no-DB-migration default.
### Quality gate
- Everyone on the team can state the same answers to these questions:
- Is advisor a built-in tool? **Yes.**
- Can advisor run with action tools in the same batch? **No.**
- Does advisor get tools of its own? **No.**
- Is a DB migration required for MVP? **No, unless billing insists.**
## Phase 1 — Build the advisor runtime and tool wrapper
### Goals
Create the core advisor implementation in a way that is easy to test and keeps `chattool/` thin.
### Files to add
- `coderd/x/chatd/chatadvisor/types.go`
- `coderd/x/chatd/chatadvisor/guidance.go`
- `coderd/x/chatd/chatadvisor/handoff.go`
- `coderd/x/chatd/chatadvisor/runtime.go`
- `coderd/x/chatd/chatadvisor/runner.go`
- `coderd/x/chatd/chattool/advisor.go`
### Responsibilities by file
1. **`types.go`**
- Define the input/result schema used by the tool and UI.
- Keep the result shape close to Mux so the UI and model both have predictable cases.
- Recommended result variants:
- `advice`
- `limit_reached`
- `error`
Recommended shape:
```go
type AdvisorArgs struct {
Question string `json:"question"`
}
type AdvisorResult struct {
Type string `json:"type"`
Advice string `json:"advice,omitempty"`
Error string `json:"error,omitempty"`
AdvisorModel string `json:"advisor_model,omitempty"`
RemainingUses int `json:"remaining_uses,omitempty"`
Usage *AdvisorUsageResult `json:"usage,omitempty"`
}
```
2. **`guidance.go`**
- Hold two strings:
- the nested advisor system prompt;
- the parent-agent guidance block to inject into the outer system prompt.
- The nested advisor prompt must say, in plain language:
- you are advising the parent agent;
- you do not address the end user directly;
- you do not claim actions happened;
- you return concise strategic guidance and tradeoffs.
3. **`runtime.go`**
- Define the per-run runtime state.
- Recommended fields:
- resolved model + model config;
- provider keys/options reused from the outer chat;
- `MaxUsesPerRun`;
- `MaxOutputTokens`;
- atomic/current call counter;
- callback(s) to obtain the current prompt snapshot and current-step snapshot;
- optional metrics/usage hook.
- Add fail-fast validation for impossible config: nil model, non-positive limits, empty prompt builders, etc.
4. **`handoff.go`**
- Build the advisor handoff message from:
- the explicit question;
- the exact prompt/messages the parent model just used;
- the current step's text/reasoning snapshot, if available;
- the most recent relevant tool outputs, if they are already in the prompt snapshot.
- **Important:** use the already-prepared outer prompt tail, not a fresh DB reload. That keeps the advisor aligned with compaction and the exact context the outer model saw.
- Apply hard truncation budgets with recent-context bias.
5. **`runner.go`**
- Execute the nested advisor call.
- **Recommended implementation:** call `chatloop.Run()` in an in-memory, one-step mode:
- `Tools: nil`
- `ProviderTools: nil`
- `MaxSteps: 1`
- `PersistStep`: capture the assistant output in memory instead of writing DB rows
- Reuse the existing provider/model/cost path instead of building a second provider runner.
- Assert that no tool definitions are passed to the nested call.
6. **`chattool/advisor.go`**
- Keep this file thin and consistent with other built-ins.
- Responsibilities:
- decode `AdvisorArgs`;
- validate `Question` is non-empty and bounded;
- call the `chatadvisor` runner;
- return a structured tool response.
### Defensive programming requirements
- Assert `Question` is non-empty after trimming.
- Assert runtime limits are positive.
- Assert the nested advisor call runs with zero tools/provider tools.
- Assert `AdvisorResult.Type` is one of the known variants before returning.
- Assert remaining uses never goes negative.
### Acceptance criteria
- A unit test can call the advisor tool with a fake model and receive a stable `advice` result.
- The nested advisor call is impossible to run with tools accidentally attached.
- The core logic lives in `chatadvisor/`, not embedded inside `chatd.go`.
## Phase 2 — Wire advisor into chatd and keep prompt/tool availability in sync
### Goals
Register the tool in the right place, expose it only when eligible, and inject system guidance only when the tool is present.
### Files to modify
- `coderd/x/chatd/chatd.go`
- optionally a small helper file if `chatd.go` becomes too crowded
### Tasks
1. **Compute one eligibility boolean in `processChat()`.**
Recommended inputs:
- server-level advisor enabled flag;
- root chat only (`chat.ParentChatID == uuid.Nil` or equivalent existing root/child check);
- a usable resolved model/provider exists;
- optional experiment/workspace/org gate if product wants staged rollout.
2. **Create the runtime once per outer chat run.**
- Use the model/config/keys resolved by `resolveChatModel()`.
- Reuse provider options from the current chat's `ChatModelCallConfig`.
- Set `MaxUsesPerRun` and `MaxOutputTokens` from advisor config defaults.
3. **Register the tool in the built-in tool block.**
- Insert after the skill tools and before MCP tools in `processChat()`.
- Record `builtinToolNames["advisor"] = true` so metrics stay bounded.
4. **Inject advisor guidance into the outer system prompt using the same boolean.**
- Use `chatprompt.InsertSystem()` in the same prompt assembly path that already injects user/system instructions.
- Place the block near the existing instruction insertion, before plan-path/skill context blocks.
- Wrap the guidance in an explicit tag like `<advisor-guidance>` so it is easy to spot in tests and future refactors.
5. **Keep advisor out of child chats for the first release.**
- That avoids recursion/cost blowups with `spawn_agent` / `wait_agent` flows.
- Document this explicitly in the rollout notes and tests.
### Acceptance criteria
- If advisor is disabled, neither the tool nor the prompt guidance appears.
- If advisor is enabled, both the tool and the prompt guidance appear.
- Root chats can use advisor; child chats cannot.
- Built-in tool names include `advisor` so metrics do not collapse it into the generic `mcp` label.
## Phase 3 — Enforce planning-only execution policy in `chatloop`
### Goals
Prevent the model from calling `advisor` and action tools in the same execution batch.
### Files to modify
- `coderd/x/chatd/chatloop/chatloop.go`
- related chatloop tests
### Recommended implementation
Keep the MVP small; do **not** build a general policy engine yet.
1. Add a minimal field to `chatloop.RunOptions`, for example:
```go
ExclusiveToolName *string
```
2. In `Run()` / `executeTools()`, detect the case where the exclusive tool appears in the same local-tool batch as any other locally executed tool.
3. When that happens, synthesize structured tool-result errors for the affected calls instead of executing anything in the batch.
- `advisor` should receive a clear error like: _advisor must be called by itself before action tools_.
- The sibling action tools should receive a paired policy error like: _this tool was skipped because advisor must run alone_.
4. Let the outer model see those tool errors and retry cleanly.
- This is simpler and safer than partial execution or hidden deferral.
- It preserves deterministic transcript history for debugging.
5. Pass the just-finished step snapshot into the tool execution context.
- The advisor runtime should be able to see the current step's text/reasoning content, because that is often the best hint about what the outer model is trying to decide.
### Why this is the right fit
- It matches the intended semantics: advisor is consulted **before** taking action.
- It avoids subtle race conditions caused by concurrent built-in tool execution.
- It keeps the behavior easy to test with fake models.
### Acceptance criteria
- A model-emitted batch containing only `advisor` succeeds.
- A model-emitted batch containing `advisor` plus any other locally executed tool returns deterministic policy errors and executes nothing.
- Non-advisor tool execution stays unchanged for normal chats.
## Phase 4 — Usage limits, metrics, and configuration
### Goals
Make advisor safe to operate without over-designing billing/storage in the first release.
### Files to modify
- `coderd/x/chatd/chatd.go`
- `coderd/x/chatd/chatloop/metrics.go` as needed
- `coderd/x/chatd/chatd.go` `Config` struct and constructor path
- optional follow-up config/db files only if a separate advisor model or persistent billing is required
### Tasks
1. **Add explicit server config knobs for MVP.**
Recommended fields on `chatd.Config` or a nested advisor config struct:
- `AdvisorEnabled bool`
- `AdvisorMaxUsesPerRun int`
- `AdvisorMaxOutputTokens int64`
2. **Track usage per outer run.**
- Reset the counter for each `processChat()` invocation.
- Return `remaining_uses` in the tool result.
- Return `limit_reached` when the cap is exhausted.
3. **Expose advisor usage metadata in the tool result.**
- Include model name and token/cost summary if available.
- Use the same `callConfig.Cost` calculation path as the outer chat for MVP if advisor reuses the same model.
4. **Record server-side metrics.**
- Count advisor invocations, failures, and latency.
- Ensure they show up under the built-in tool label `advisor`.
5. **Optional decision gate: separate advisor model.**
- If product insists on a stronger/different advisor model, add a follow-up config hook that resolves another existing chat model config through the same `configCache` path.
- Keep that out of the first landing PR unless it is required for acceptance.
6. **Optional decision gate: queryable advisor cost.**
- If this becomes required, spin a follow-up DB task:
- update `coderd/database/queries/*.sql`;
- add migration files;
- run `make gen`;
- update audit mappings if a new auditable type/field is introduced.
### Acceptance criteria
- Advisor calls are capped per outer run.
- Limit exhaustion is user-visible in the tool result.
- Metrics distinguish advisor calls from other built-in tools.
- MVP does not require a schema migration unless explicitly approved.
## Phase 5 — Frontend rendering and Storybook coverage
### Goals
Make advisor feel intentional in the Agents UI without blocking the backend on fancy streaming UI.
### Files to modify
- `site/src/pages/AgentsPage/components/ChatElements/tools/Tool.tsx`
- new `site/src/pages/AgentsPage/components/ChatElements/tools/AdvisorTool.tsx`
- Storybook story file(s) in the same tools directory
### Delivery strategy
1. **Intermediate milestone during backend bring-up:** rely on the existing generic tool renderer if needed.
- This is acceptable only as a short-lived integration checkpoint.
2. **Release milestone:** add a dedicated lightweight `AdvisorTool` renderer.
- Reuse existing primitives:
- `ToolCollapsible`
- `ToolIcon`
- `Response` for markdown/prose rendering
- `ScrollArea` if the advice can be long
- Keep styling light and consistent with the Agents page.
- Do not add unnecessary React memoization in `site/src/pages/AgentsPage/`; that area is already React-Compiler aware.
3. **Render the structured result states cleanly.**
- `advice` — readable prose/markdown with optional metadata footer.
- `limit_reached` — warning-style message.
- `error` — error state with visible fallback text.
- `running` — existing tool loading state/spinner is enough for MVP.
4. **Add Storybook coverage instead of ad-hoc component tests.**
Recommended stories:
- successful advice;
- running/loading;
- limit reached;
- error.
5. **Keep the UI contract narrow.**
- Prefer one text field like `advice` plus small metadata rather than a deeply nested schema.
- That keeps the UI resilient to prompt iteration.
### Acceptance criteria
- The advisor tool card renders readable content rather than raw quoted JSON in the final release branch.
- Running, limit, and error states are visibly distinct.
- Storybook stories and play assertions cover the new states.
- Existing tool rendering flows remain unchanged.
## Phase 6 — Automated tests and validation gates
### Backend tests to add
1. **Advisor runtime/tool tests**
- question validation;
- tool-less nested execution assertion;
- success result shaping;
- limit-reached result shaping;
- error result shaping.
2. **Prompt/gating tests in chatd**
- advisor disabled ⇒ no tool, no guidance;
- advisor enabled/root chat ⇒ tool + guidance;
- child chat ⇒ advisor absent.
3. **Chatloop policy tests**
- advisor alone runs;
- advisor + action tool mixed batch returns deterministic policy errors;
- non-advisor tools still execute normally.
4. **Usage/metrics tests**
- per-run cap resets correctly;
- builtin tool labeling includes `advisor`;
- returned metadata includes model/usage summary when available.
### Frontend tests to add
- Storybook `play()` assertions for the advisor renderer states.
- Verify expand/collapse behavior and visible fallback text.
- Verify the message timeline still renders adjacent tools correctly.
### Recommended command sequence
Run these as the implementation matures, not only at the end:
1. Backend-focused gate after phases 1–4:
- `make test RUN=TestAdvisor`
- `make test RUN=TestChatloopAdvisor`
- `make lint`
2. Frontend-focused gate after phase 5:
- `pnpm test:storybook src/pages/AgentsPage/components/ChatElements/tools/AdvisorTool.stories.tsx`
- `pnpm lint`
- `pnpm format`
3. Final repo gate before handoff:
- `make pre-commit`
- run any additional targeted `make test RUN=...` selections covering touched chatd paths
> Use the exact new test names the implementing agents create; the names above are recommended anchors, not existing tests.
## Dogfooding plan
### Principle
Dogfood the change as a real agent feature, not just a unit-tested backend. Per the dogfood and `agent-browser` skills, the reviewer should get **watchable repro videos** plus screenshots that make the behavior obvious without reading logs.
### Required setup
1. Start the full dev environment with:
- `./scripts/develop.sh`
2. If the frontend renderer changes, also start Storybook from `site/` with:
- `pnpm storybook --no-open`
3. Use `agent-browser` directly — **never `npx agent-browser`**.
4. Use named browser sessions and an output folder such as:
- `./dogfood-output/advisor/`
- with subfolders `screenshots/` and `videos/`
### Evidence protocol
For every interactive scenario below:
1. Start video recording **before** the action.
2. Capture step-by-step screenshots at human pace.
3. Capture one annotated screenshot of the final state.
4. Stop the recording.
5. Note the exact pass/fail observation in the QA report.
For static UI states (for example Storybook error/limit cards), an annotated screenshot is sufficient; video is optional but still encouraged by this project’s review preference.
### Dogfood scenarios
#### Scenario A — Happy path in the real Agents UI
**Goal:** prove that a root agent chat can invoke advisor and produce a readable recommendation before taking further action.
Steps:
1. Open the Agents page with an advisor-enabled root chat.
2. Start a repro video.
3. Send a prompt that should reasonably trigger strategic planning, such as an architecture or multi-tradeoff question.
4. Capture screenshots of:
- the prompt before send;
- the running advisor state;
- the completed advisor card and the assistant’s follow-up response.
5. Stop recording.
Pass criteria:
- advisor appears in the timeline;
- the rendered result is readable;
- the assistant can continue after consuming the advisor output.
#### Scenario B — Advisor unavailable path
**Goal:** prove the feature is truly gated.
Suggested variants (at least one is required, both are better):
- feature flag/config off;
- child/sub-agent chat.
Evidence:
- annotated screenshot of the chat/tool state showing advisor is absent;
- short video if toggling the gate live is part of the repro.
Pass criteria:
- no advisor tool is available;
- no advisor-specific prompt behavior leaks through.
#### Scenario C — UI states in Storybook
**Goal:** prove the renderer handles non-happy states cleanly.
Required story states:
- success/advice;
- running;
- limit reached;
- error.
Evidence:
- one screenshot per state;
- at least one short video showing collapse/expand behavior.
Pass criteria:
- success renders readable advice;
- limit/error have visible fallback text;
- the component behaves like the other tool cards.
#### Scenario D — Regression sweep of nearby tools
**Goal:** ensure advisor does not break the surrounding chat timeline.
Check at minimum:
- another existing built-in tool still renders correctly near advisor;
- sub-agent/tool cards still expand/collapse normally;
- no obvious console errors appear in the Agents page during the advisor flow.
Evidence:
- screenshots of adjacent tool cards;
- console/error capture if anything suspicious appears.
### `agent-browser` usage notes for the QA agent
- Prefer `agent-browser batch` for 2+ sequential commands when no intermediate parsing is needed.
- Use `snapshot -i` to discover interactive refs.
- Re-snapshot after navigation or major DOM changes.
- Avoid `wait --load networkidle` unless the page is known to go idle; prefer explicit element/text waits or short fixed waits.
- Record videos at human pace and include pauses that a reviewer can follow.
## Rollout plan
### Initial rollout
- Gate behind a server-side advisor-enabled flag.
- Enable only for selected internal/root agent chats first.
- Watch metrics for:
- invocation count;
- failure rate;
- latency;
- obvious retry loops.
### Expansion conditions
Expand beyond the initial rollout only after the following are true:
- mixed-batch policy behavior is stable;
- cost impact is understood;
- frontend UX is readable in production-like dogfood;
- no recursion surprises have appeared with sub-agent flows.
### Explicit non-goals for the first release
- advisor inside child/sub-agent chats;
- provider-agnostic streaming phase UI;
- MCP-based external advisor implementation;
- mandatory DB-backed advisor cost reporting.
## Final acceptance checklist
- [ ] `advisor` is a built-in chatd tool, not an MCP/dynamic-tool substitute.
- [ ] The nested advisor call is tool-less and bounded to one in-memory step.
- [ ] One eligibility boolean controls both tool registration and prompt guidance injection.
- [ ] Root chats can use advisor; child chats cannot in the initial rollout.
- [ ] Mixed advisor/action batches produce deterministic policy errors instead of partial execution.
- [ ] Per-run usage caps and limit-reached behavior work.
- [ ] Advisor usage is visible in metadata/metrics without forcing a DB migration for MVP.
- [ ] The Agents UI has a readable advisor card and Storybook coverage.
- [ ] Dogfooding produced screenshots and repro videos for the required scenarios.
- [ ] Validation commands (`make lint`, targeted `make test`, Storybook tests, `make pre-commit`) passed before handoff.
## Suggested PR split
1. **PR 1 — Backend foundation**
- `chatadvisor/` package
- `chattool/advisor.go`
- `chatloop` exclusive policy
- chatd gating/prompt sync
- backend tests
2. **PR 2 — Frontend + QA**
- advisor renderer
- stories/play assertions
- dogfood artifacts and QA notes
3. **PR 3 — Optional follow-ups only if demanded by stakeholders**
- separate advisor model override
- persistent advisor billing/queryability
- transient phase-stream UX
</details>
---
_Generated with [`mux`](https://github.com/coder/mux) • Model: `anthropic:claude-opus-4-7` • Thinking: `max`_
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be57af5ff0 |
feat: add exit code and status to workspace agent scripts (#24505)
For scripts that have not finished or in dry run cases these will be omitted. |
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1c30d52b2b |
feat: audit user secret create, update, and delete (#24756)
Emit user secret audit log entries for create/update/delete operations. Reads stay un-audited, matching every other resource. Audit log entries record changes in user secret name, environment variable name, file path, and value. The secret value column is marked `ActionSecret` so the diff records the change without showing the ciphertext or plaintext. Closes a TOCTOU window on delete to ensure no phantom audit logs for a delete of a non-existent secret. Secret update accepts a small TOCTOU window matching the other audited resources (templates, workspaces, chats). The two-query pattern is wrapped in a transaction so audit state can't leak from a failed mutation. |
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5222db86c7 | feat: add after_id pagination for chat messages (#24531) | ||
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70d6efa311 |
feat: chat auto-archive owner digest notifications (#24643)
Depends on #24642 Adds per-owner digest notifications onto the chat auto-archive subsystem. Each tick's archived rows are grouped by owner, the top 25 titles per owner are rendered into a new `Chats Auto-Archived` notification template, and any remainder surfaces as `and N more`. Each digest is per-tick, so users with large amounts of purgeable data may get multiple notifications in sequence (one per user per tick). The template body branches on `retention_days`: when retention is disabled (`retention_days=0`), users are told archived chats are kept indefinitely rather than falsely claiming imminent deletion. ### Changes - migration `000XXX_chat_auto_archive_notification_template` adds new notification template - `dbpurge`: threads `notifications.Enqueuer` through `New`; and enqueues notification message. - `cli/server.go`: passes `options.NotificationsEnqueuer` into `dbpurge.New`. - `coderd/notifications/events.go`: new `TemplateChatAutoArchiveDigest` UUID. - `coderd/inboxnotifications.go`: inbox registration. - Docs: adds a `Notifications` section to `chat-auto-archive.md`. > 🤖 |
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069223ae26 | fix: recover web push subscriptions after PWA reinstall (#24720) | ||
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c7cac9debe |
fix: persist per-turn model on chats and queued messages (#24688)
Previously, `chats.last_model_config_id` was not updated when a user sent a mid-chat message with a different model, and queued messages did not store their own per-turn model, so promotion ran against whatever the chat row said at promote time. Chat watch events also did not merge `last_model_config_id` into the site's root, child, and per-chat caches, so sidebar labels stayed stale after direct sends and queued promotions. - Add nullable `chat_queued_messages.model_config_id`, backfilled from `chats.last_model_config_id`. Queued inserts round-trip the effective model id at enqueue time. - In `coderd/x/chatd`, direct sends update `chats.last_model_config_id` inside the same transaction that inserts the admitted user message. Manual promotion and auto-promotion use the queued row's stored `model_config_id`, with a fallback to `chats.last_model_config_id` for legacy NULL rows during rollout. `PromoteQueuedOptions.ModelConfigID` is now ignored. - On the site, extract `mergeWatchedChatSummary` and `mergeWatchedChatIntoCaches` in `site/src/api/queries/chats.ts` so status-change watch events merge `last_model_config_id` into the root infinite chat list, the parent-embedded child entry, and the per-chat `chatKey(chatId)` cache. `updated_at` guards against stale watch payloads clobbering newer cached state, while diff status events still merge their PR metadata because they are timestamped outside the chat row. Watch timestamps are compared as instants so variable fractional precision does not make fresh events look stale. - Queued promotion validates stored model config IDs before admission. Invalid legacy queued IDs fall back to the chat's current model config instead of dropping the queued message during auto-promotion. - Backend and frontend regression coverage added for admission, queue promotion (including FIFO across mixed models, legacy NULL fallback, and invalid queued model IDs), and chat watch cache merging. > Mux is acting on Mike's behalf. |
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a876287d36 |
feat: auto-archive inactive chats with audit trail (#24642)
Adds a background job in `dbpurge` that periodically archives chats inactive beyond a configurable threshold. Each archived root chat gets a background audit entry tagged `chat_auto_archive`. Disabled by default. * New `AutoArchiveInactiveChats` SQL query with LATERAL last-activity subquery and partial index on archive candidates * `site_configs`-backed `auto_archive_days` setting with admin-only PUT, any-authenticated-user GET * Cascade archive via `root_chat_id`; pinned chats and active threads exempt * Root-only audit dispatch on detached context, matching manual archive (`patchChat`) behavior * 11 subtests covering disabled no-op, boundary, deleted messages, child activity, pinned exemption, multi-owner, idempotency, and batch pagination PR #24643 adds per-owner digest notifications. PR #24704 adds the requisite UI controls. > 🤖 |
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3a9a60dff8 | feat: add collapsible thinking blocks with configurable display mode (#24635) | ||
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3d90546aae |
feat: add general subagent model override (#24610)
Adds a deployment-wide admin override for general delegated subagents.
## What changed
- store the general override in `site_configs` and expose it through the
shared `agent-model-override/{context}` API
- apply the general override when spawning delegated general subagents,
while preserving the existing Explore override behavior
- reuse a shared Agents settings form for the general and Explore
override sections
## Validation
- `make gen`
- `go test ./coderd -run 'TestChatModelOverrides'`
- `go test ./coderd/x/chatd -run
'TestSpawnAgent_(GeneralUsesConfiguredModelOverride|GeneralOverrideLogsAndFallsBackWhenCredentialsUnavailable|GeneralOverrideLogsAndFallsBackWhenProviderDisabled)'`
- `pnpm -C site lint:types`
- `pnpm -C site test:storybook --
AgentSettingsAgentsPageView.stories.tsx`
- `make lint`
- `make pre-commit`
> Mux is acting on Mike's behalf.
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f8fe5d680b |
fix(coderd): reject API operations on archived chats (#24633)
Archived chats accept mutations (messages, edits, queued-message promotions, tool-result submissions) via the API, causing them to re-enter the processing pipeline. This violates the hard-stop design intent from PR #23758. Add archived checks at three layers: - HTTP handlers (postChatMessages, patchChatMessage, promoteChatQueuedMessage, postChatToolResults): return 400 after auth so callers get a clear error. - Daemon functions (SendMessage, EditMessage, PromoteQueued, SubmitToolResults): return ErrChatArchived after row lock, guarding against future callers that bypass the handler. - AcquireChats SQL: filter out archived chats so they are never acquired for processing. Fixes CODAGT-245 |
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c23abc691f |
feat: sort AI sessions by last prompt time (#24440)
Previously, the sessions list sorted by `MIN(started_at)` across interceptions, so sessions with old start times but recent activity would sink to the bottom of the list regardless of how recently they were used. `ListAIBridgeSessions` now sorts by `COALESCE(MAX(prompt.created_at), MIN(started_at)) DESC`, exposed as the non-nullable `last_active_at` field. Sessions with prompts surface by last activity; sessions with no prompts fall back to their start time. The original implementation used two separate columns (`last_active_at` as a nullable prompt timestamp and `sort_at` as the non-nullable cursor key). This revision collapses them into a single `last_active_at` that is always set — simplifying the SQL, the Go conversion, the API type, and the frontend. 🤖 Generated with [Claude Code](https://claude.ai/claude-code) --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> |
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ad1906589d |
fix(coderd): allow deleting chat providers used in historical chats (#24568)
Drop the `chat_model_configs.provider -> chat_providers.provider` foreign key and soft-delete model configs when their provider is removed. The provider row is now hard-deleted inside a transaction that also tombstones its model configs and promotes a replacement default when needed. Historical chats and messages keep pointing at the soft-deleted model config rows, which are hidden from live/admin queries but still resolve for read. The runtime chat path already falls back to the default model config when a soft-deleted config is looked up. Replaces the lost FK validation in the create/update model-config handlers with an explicit provider lookup that returns the existing `Chat provider is not configured.` 400. ## UX **Admin deleting a chat provider that has historical usage** - Before: blocked with 400 `Provider models are still referenced by existing chats.` Admins had no in-product way to remove a provider that had ever been used. - After: delete succeeds (204). Any model configs under that provider are soft-deleted. If the removed provider owned the default model config, one of the remaining live configs is auto-promoted to the new default. The promotion is deterministic (`ensureDefaultChatModelConfig` picks the first live config by `provider ASC, model ASC, updated_at DESC, id DESC`); there is no picker, and no toast or response detail names which config became the new default. **End users with chats that used a deleted provider's model** - Old chats still open and their history still renders unchanged. - Sending a new turn in such a chat silently falls back to the current default model. No banner or warning tells the user the original model is gone. - The model picker no longer lists the deleted model. - If no default model config exists at all after the delete, sending a new turn fails with `no default chat model config is available`. **Admin creating or updating a model config against a provider that is not configured** - Same as before: 400 `Chat provider is not configured.` Only the detection mechanism changed (explicit `FOR UPDATE` lookup inside the transaction, which also serializes against a concurrent provider delete). **Admin updating a model config whose row disappears mid-transaction** - Now returns the standard 404 `Resource not found or you do not have access to this resource` instead of the previous 500 that leaked `sql: no rows in result set` in the detail. Unrelated internal races (for example a race on the promoted default candidate) are still reported as 500 so they are not misclassified as "your target is gone". Closes CODAGT-23 |
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9d0469fc4c |
feat: allow approved external MCP tools in root plan mode (#24509)
## Summary
Allow root plan-mode chats to use MCP tools from external servers that
an admin has explicitly approved for plan mode. Workspace MCP and
plan-mode subagents remain blocked.
## Problem
`chatd.go` excluded every MCP tool when `isPlanModeTurn` was true, so
planning had no access to tools like docs search, ticketing, etc.
Lifting that guard wholesale was unsafe: `mcp_server_configs` already
has centralized admin governance, but workspace-local MCP (discovered
from agent `.mcp.json`) does not, and subagents use a narrower trust
boundary.
## Fix
Add an admin-controlled per-server `allow_in_plan_mode` flag (default
`false`) and gate plan-mode MCP access on it.
### Backend / schema
- New migration `000472_mcp_server_allow_in_plan_mode.{up,down}.sql` and
matching fixture update.
- `mcpserverconfigs.sql` + generated code: persist and read the new
column.
- `codersdk/mcp.go`: thread the field through `MCPServerConfig`,
`Create*`, and `Update*` request types.
- `coderd/mcp.go`: validate, persist, and return the flag in
get/list/create/update handlers.
### chatd
- `coderd/x/chatd/chatd.go`: pre-filter selected external MCP configs by
`AllowInPlanMode` before calling `mcpclient.ConnectAll` on plan-mode
root turns. Workspace MCP discovery is skipped entirely on plan-mode
turns.
- Single helper decides whether a tool is available in plan mode, used
both at construction and for active-tool filtering (defense in depth).
Plan-mode subagents, dynamic tools, provider-native tools, computer-use,
and workspace MCP stay unchanged.
- `coderd/x/chatd/prompt.go`: update the root plan-mode overlay text to
match the new boundary.
### UI
- `MCPServerAdminPanel.tsx`: add an explicit toggle ("Allow all tools
from this MCP server in root plan mode") next to the existing governance
controls.
- Regenerated `site/src/api/typesGenerated.ts`.
### Docs
- `docs/ai-coder/agents/architecture.md`: replace the blanket "MCP is
unavailable in plan mode" note with the new root-only, external-only,
admin-approved policy. Explicitly call out that workspace MCP and
plan-mode subagents are still excluded.
### Tests
- Plan-mode visibility (approved vs non-approved external server).
- Plan-mode invocation of an approved external MCP tool.
- End-to-end plan-mode workflow that uses an approved MCP tool and then
reaches `propose_plan`.
- Regressions: workspace MCP still excluded in plan mode; plan-mode
subagents still on the restricted tool boundary; existing tool
allow/deny list filtering still applies.
## Policy precedence
`allow_in_plan_mode` is an **additional** requirement on top of existing
`enabled`, availability, chat-selected / forced server IDs, and tool
allow/deny lists. It approves **all tools on that server** for root plan
mode; a per-tool plan allowlist is deliberately deferred.
## Follow-ups (explicitly out of scope)
- Whether plan-mode subagents should inherit approved external MCP
tools.
- Workspace-local MCP safety model (agent-side `.mcp.json` schema vs. a
coderd-managed workspace MCP config).
## Validation
- `go vet ./coderd/x/chatd/...`
- `go test ./coderd/x/chatd -run 'TestPlan.*|TestMCP.*' -count=1`
- `go test ./coderd/x/chatd -count=1 -timeout 5m` (full chatd suite)
- `make fmt` (no diff)
> Mux opened this PR on Mike's behalf.
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410f9a5e19 |
feat: allow renaming of agent chat title (#24489)
Co-authored-by: Coder Agents <noreply@coder.com> |
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467430d8fa |
fix: sort child chats newest-first and prepend on creation (#24524)
GetChildChatsByParentIDs sorted created_at ASC, but the cache helper appended new children to the end. On refetch the API and cache agreed on oldest-first, putting the just-created child at the bottom. Users expect newest first, matching the root-chat sidebar convention. - SQL: change child sort to created_at DESC, id DESC. - Cache: prepend instead of append in addChildToParentInCache (renamed from appendChildToParentInCache to avoid leaking position semantics). - Test: update ordering assertion to expect newest-first. Refs #24404 |
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df7e838c21 | feat(coderd): wire debug logging into chat lifecycle (#23917) | ||
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fc2493780f |
fix: exclude subagent chats from sidebar pagination (#24404)
GetChats now returns only root chats (parent_chat_id IS NULL). A new GetChildChatsByParentIDs query fetches children for visible roots and embeds them in each parent's Children field. The singular getChat endpoint does the same. Archive invariant is one-way: parent archived implies child archived. Parent archive/unarchive cascades via root_chat_id. Individual child archive is permitted; child unarchive while the parent is archived is rejected atomically (row lock on child, re-read parent inside the transaction). Embedded children are filtered by the caller's archive state so individually-archived children stay hidden from active-parent views. Gitsync MarkStale uses GetChatsByWorkspaceIDs directly; MarkStaleParams.OwnerID removed (dead after the switch). Frontend: buildChatTree reads from the embedded children field, WebSocket handlers route child events into the parent's children array, and archiving a child strips it from the parent cache. |
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e19b21b7d5 |
chore: add GetLatestWorkspaceBuildWithStatusByWorkspaceID query (#24441)
<!-- If you have used AI to produce some or all of this PR, please ensure you have read our [AI Contribution guidelines](https://coder.com/docs/about/contributing/AI_CONTRIBUTING) before submitting. --> relates to GRU-18 Adds new database query supporting the Agent Connection Watch we will add. |
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91f9de27a1 | feat(coderd): add chat debug service and summary aggregation (#23916) |