Implements https://linear.app/codercom/issue/AIGOV-285
Follow the structure established in
https://github.com/coder/coder/pull/25203
## Summary
Adds the `user_ai_budget_overrides` table and CRUD API at
`/api/v2/users/{user}/ai/budget`. An override sets a custom per-user
spend cap that supersedes group-budget resolution, attributing spend to
a specific group.
## Schema
```sql
CREATE TABLE user_ai_budget_overrides (
user_id UUID PRIMARY KEY REFERENCES users(id) ON DELETE CASCADE,
group_id UUID NOT NULL REFERENCES groups(id) ON DELETE CASCADE,
spend_limit_micros BIGINT NOT NULL CHECK (spend_limit_micros >= 0),
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);
```
## Membership lifecycle
The membership invariant — a user must be a member of the attributed
group, including when that group is "Everyone" — would naturally be
expressed as a composite FK on `(user_id, group_id) →
group_members_expanded(user_id, group_id)`. PostgreSQL doesn't allow
foreign keys to reference views, so enforcement is split across two
mechanisms:
- **Write-time check.** A CHECK constraint on the table
(`user_ai_budget_overrides_must_be_group_member`) calls a `STABLE`
function `is_group_member(user_id, group_id)` that queries
`group_members_expanded`. The view surfaces both regular group
memberships and the implicit "Everyone" group memberships from
`organization_members`. Any INSERT or UPDATE that violates the predicate
is rejected with a Postgres `check_violation`, which the handler maps to
a 400. `is_group_member` is defined as a general predicate, reusable by
any future table that needs the same check.
- **Cascade on removal.** Two `BEFORE DELETE` triggers handle membership
loss:
- `trigger_delete_user_ai_budget_overrides_on_group_member_delete` on
`group_members` — covers regular group removals (admin action, OIDC
sync).
- `trigger_delete_user_ai_budget_overrides_on_org_member_delete` on
`organization_members` — covers the "Everyone" group, whose membership
lives in `organization_members`.
The single-column FKs on `users(id)` and `groups(id)` remain to cascade
on user or group deletion (those paths don't pass through
`group_members`).
## Authorization
The dbauthz layer gates each operation against the `User` and (for
writes) `Group` resources:
| Operation | User resource | Group resource |
|-----------|----------------|----------------|
| `GET` | `ActionRead` | — |
| `PUT` | `ActionUpdate` | `ActionUpdate` |
| `DELETE` | `ActionUpdate` | `ActionUpdate` |
For `DELETE`, the dbauthz layer fetches the existing override first to
learn the attributed `group_id`, then runs both checks.
### Role matrix
| Role | GET | PUT | DELETE |
|--------------|-----|-----|--------|
| Owner | ✅ | ✅ | ✅ |
| UserAdmin | ✅ | ✅ | ✅ |
| OrgAdmin | ✅ | ❌ | ❌ |
| OrgUserAdmin | ✅ | ❌ | ❌ |
Internal discussion:
https://codercom.slack.com/archives/C096PFVBZKN/p1779392747885359
## Audit logs
Audit logs will be addressed in a follow-up PR.
RFC: [Bridge ↔ Boundaries Correlation
RFC](https://www.notion.so/coderhq/Gateway-and-Firewall-Correlation-RFC-31ad579be592803aa8b3d48348ccdde9)
Register a dedicated `boundary_log` RBAC resource type with `create`,
`read`, and `delete` actions, replacing the placeholder
`rbac.ResourceAuditLog` and `rbac.ResourceSystem` references previously
used in the dbauthz layer.
Create is granted at user-level so workspace agents can only write logs
owned by their workspace owner, preventing cross-workspace log
fabrication. Delete is restricted to `DBPurge` only; no human role
(including owner) can delete boundary logs.
| Subject | Create (own) | Create (other) | Read (all) | Delete |
|---|---|---|---|---|
| Workspace agent | yes | no | no | no |
| Owner (site admin) | yes (via member) | no | yes | no |
| Auditor | no | no | yes | no |
| DBPurge | no | no | no | yes |
### Changes
- **RBAC policy & resource definition**: add `boundary_log` to
`policy.go` and generate `ResourceBoundaryLog` object, scope constants,
and codersdk/TypeScript types.
- **dbauthz authorization**: replace all
`ResourceAuditLog`/`ResourceSystem` placeholders with
`ResourceBoundaryLog`. `InsertBoundaryLog` and `InsertBoundarySession`
derive the workspace owner from the agent and authorize with
`.WithOwner()` for user-scoped create.
- **Role assignments:**
- **Owner (site):** read only. Excluded from `allPermsExcept` wildcard;
create is inherited from member at user-level.
- **Member (user-level):** create. User-scoped so agents can only write
logs they own.
- **Auditor (site):** read.
- `boundary_log` is excluded from org-admin, org-member, and
org-service-account `allPermsExcept` calls for consistency with
`ResourceBoundaryUsage`.
- **System subjects:**
- **DB Purge** (`SubjectTypeDBPurge`): delete. The only subject that can
remove boundary logs.
- **Workspace agent scope**: `ResourceBoundaryLog` with wildcard ID in
the agent scope allow-list (necessary for creation since no pre-existing
ID exists). User-level role scoping prevents deployment-wide access.
- **DB migration** (`000510_boundary_log_scopes`): add `boundary_log:*`,
`boundary_log:create`, `boundary_log:delete`, `boundary_log:read` enum
values to `api_key_scope`.
- **Test coverage**: `BoundaryLogCreate` (user-scoped, only matching
owner succeeds), `BoundaryLogDelete` (all human roles denied),
`BoundaryLogRead` (owner + auditor). dbauthz mock tests set up workspace
agent lookups for owner derivation.
- **Generated docs**: update OpenAPI specs, API reference docs, and
frontend type definitions.
---------
Co-authored-by: Muhammad Danish <mdanishkhdev@gmail.com>
Co-authored-by: Coder Agents <coder-agents-review[bot]@users.noreply.github.com>
## Summary
Routes chatd model calls backed by concrete AI Provider rows through the
in-process aibridge transport by default, with deployment options to use
direct provider routing when AI Gateway is disabled or chat AI Gateway
routing is disabled.
- Splits model routing into common, direct provider, and AI Gateway
paths behind a single deployment-mode entry point.
- Builds chatd models through explicit request, route, and options data.
Active API key attribution is passed explicitly instead of being hidden
inside generic model construction.
- For AI Gateway BYOK routes, resolves the user's provider key in chatd,
forwards it through provider-specific auth headers, and sets
`X-Coder-AI-Governance-Token` to the `delegated` marker so aibridge
preserves those headers while still stripping Coder-specific metadata.
- Keeps central provider credentials and deployment fallback credentials
out of forwarded provider auth headers, so AI Gateway central policy
remains authoritative.
- Redacts delegated provider auth from default string formatting to
avoid accidental plaintext logging of user BYOK credentials.
- Covers selected chat models, advisor overrides, title and quickgen
paths, subagent overrides, computer use model selection, and an
integration-style chat turn through the aibridge transport path.
- Persists initiating API key IDs on chat and queued user messages,
including subagent child messages, and fails closed for AI
Gateway-routed model builds without an active key.
- Removes unused `api_key_id` indexes while keeping the persistence
columns and foreign keys.
- Keeps the deployment option available through config and env parsing,
but hides it from CLI help and generated docs.
- Stabilizes the subagent poll fallback test so background CreateChat
processing cannot win the state transition under slower CI environments.
## Tests
- `go test ./coderd/x/chatd -run
'TestAIGatewayProviderAuthForUser|TestAIGatewayProviderAuthRedactsFormatting|TestResolveModelRouteForConfigAIGatewayProviderAuth|TestAIGatewayModelForwardsProviderAuth|TestProcessChat_AIGatewayRoutingUsesDelegatedAPIKey|TestAwaitSubagentCompletion'
-count=1`
- `go test ./coderd/aibridged -run
'TestServeHTTP_DelegatedAPIKey|TestServeHTTP_StripCoderToken' -count=1`
- `git diff --check HEAD~1..HEAD`
- `make lint`
> Mux working on behalf of Mike.
RFC: [Bridge ↔ Boundaries Correlation
RFC](https://www.notion.so/coderhq/Gateway-and-Firewall-Correlation-RFC-31ad579be592803aa8b3d48348ccdde9)
Add up/down migrations and matching sqlc queries for persisting Boundary
audit events, as specified in the Bridge/Boundaries Correlation RFC.
**Tables:**
- `boundary_sessions`: session metadata with `workspace_agent_id` FK,
`confined_process_name`, and timestamps (`started_at`, `updated_at`). ID
is externally supplied by the Boundary process (no DB-side default).
Created lazily when the first log for a session arrives.
- `boundary_logs`: individual audit events with `session_id` FK,
`sequence_number` (INT, primary ordering key), protocol/method/detail
fields, and `matched_rule` (nullable; non-NULL implies allowed).
**Indexes (per RFC):**
- `(session_id, sequence_number)` for the ordering query path
- `(captured_at)` for the retention purge path
**Queries:**
- `InsertBoundarySession` / `GetBoundarySessionByID`
- `InsertBoundaryLog` / `GetBoundaryLogByID`
- `ListBoundaryLogsBySessionID` with nullable `seq_after`/`seq_before`
exclusive bounds for fetching events between two known interception
sequence numbers
- `DeleteOldBoundaryLogs` with row limit to avoid long-running
transactions
**Also includes:** dbgen helpers (`BoundarySession`, `BoundaryLog`),
dbauthz implementations (reads gated on `ResourceAuditLog`, deletes on
`ResourceSystem`), and all generated wrappers (dbmock, dbmetrics).
No callers yet. A follow-up PR will add the dedicated `boundary_log`
RBAC resource type.
> Generated by Coder Agents
> 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`
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.
Closes https://github.com/coder/internal/issues/965
Recent `pg_dump` patch releases (13.22+ / 14.19+ / 15.14+ / 16.10+ /
17.6+) emit `\restrict` / `\unrestrict` psql meta-commands at the head
and tail of schema dumps. These broke both `sqlc` and our
`scripts/migrate-test` schema-equality check. PR #19696 worked around it
by pinning `pg_dump` to a Docker image.
This change unpins the workaround now that `sqlc` handles the
meta-commands:
* Bumps the coder/sqlc fork pin to [`337309b` on
coder/sqlc:main](https://github.com/coder/sqlc/commit/337309bfb9524f38466a5090e310040fc7af0203),
the merge of upstream v1.31.1 (coder/sqlc#6). v1.31.1 includes
[sqlc-dev/sqlc#4390](https://github.com/sqlc-dev/sqlc/pull/4390), the
upstream `\restrict` / `\unrestrict` parser fix. Updated in three places
that pin the fork SHA: `flake.nix` (`sqlc-custom`),
`.github/actions/setup-sqlc/action.yaml`, and the
`dogfood/coder/ubuntu-{22,26}.04` Dockerfiles. The flake's `sha256` /
`vendorHash` are reset to `pkgs.lib.fakeSha256`; Nix will surface the
real hashes on first build, per the existing comment block.
* Reverts #19696's Docker pin in `coderd/database/dbtestutil/db.go`.
Local `pg_dump` (13+) and the `postgres:13` Docker fallback both work
again.
* Strips `\restrict` / `\unrestrict` lines in `normalizeDump` so
`scripts/migrate-test`'s schema comparison is stable across `pg_dump`
versions (the token in those lines is randomized per run).
`TestNormalizeDumpStripsRestrict` locks the behavior in.
* Regenerates with v1.31.1, picking up the version stamp and one
upstream correctness fix in `DeleteLicense`
([sqlc-dev/sqlc#4383](https://github.com/sqlc-dev/sqlc/pull/4383): don't
shadow the input parameter when scanning a single-column return).
# 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
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.
**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
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.
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.
## 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.
> This PR was authored by Mux on behalf of Mike.
Introduce Explore mode, a read-only subagent modality for delegated
discovery and code investigation.
## What
Adds a `spawn_explore_agent` tool that creates child chats restricted to
read-only operations. An admin can optionally configure a
deployment-wide
model override so Explore subagents use a model optimized for large
context
or reasoning without changing the root chat's model.
### Backend
- New `ChatModeExplore` enum value (migration 000471).
- `spawn_explore_agent` tool definition with read-only allowlist:
`read_file`, `execute`, `process_output`, `read_skill`,
`read_skill_file`.
Write tools, file editors, and nested subagent spawning are blocked.
- Deployment config storage for the Explore model override
(`agents_chat_explore_model_override` in `site_configs`).
- Model resolution hierarchy: configured override, then current turn
model,
then global default. Silent fallback with warning log when the override
becomes unavailable.
- RBAC: `AsChatd` for daemon reads, `ActionRead` and `ActionUpdate` on
`ResourceDeploymentConfig` for admin API calls.
- Plan mode root chats can use `spawn_explore_agent` for read-only
research,
matching the planning prompt guidance.
- The Explore override config API now reports malformed saved overrides
as
"treated as unset" so admins can clear them explicitly.
### Frontend
- `ExploreModelOverrideSettings` component in admin agent behavior
settings.
Uses `ModelSelector`, handles unavailable model warnings, and supports
explicit Save and Clear actions.
- Malformed saved overrides show a warning and require an explicit Save
to
clear, instead of Clear auto-submitting behind the scenes.
### Tests
- Integration: `TestExploreSubagentIsReadOnly` (full spawn flow, tool
verification, prompt overlay, DB state).
- Unit: tool allowlist tests for explore, plan, and default modes.
- Internal: model override resolution with valid, invalid UUID,
disabled, and
unconfigured override scenarios.
- RBAC: `dbauthz_test.go` for `GetChatExploreModelOverride` and
`UpsertChatExploreModelOverride`.
- API: admin set and clear, malformed stored override reporting,
disabled
model rejection, non-admin denial.
Add a `chat_client_type` enum (`ui` | `api`) and `client_type` column to
the `chats` table. The column defaults to `api` for new rows so API
callers don't need to set it explicitly. Existing rows are backfilled to
`ui`.
The field flows through `CreateChatRequest`, `chatd.CreateOptions`,
`InsertChat`, and is returned in the `Chat` response via `db2sdk`.
<details>
<summary>Implementation notes (Coder Agents generated)</summary>
### Changes
**Database migration (000469)**
- New enum `chat_client_type` with values `ui`, `api`.
- New `client_type` column, `NOT NULL DEFAULT 'api'`.
- Backfill: `UPDATE chats SET client_type = 'ui'`.
**SQL query** — `InsertChat` now includes `client_type`.
**SDK** — `ChatClientType` type added; `ClientType` field added to both
`CreateChatRequest` (optional, defaults server-side to `api`) and `Chat`
response.
**Handler** — `postChats` maps the request field (defaulting to `api`)
and passes it through `chatd.CreateOptions`.
**Sub-agent** — Child chats inherit their parent's `client_type`.
**db2sdk** — Maps the database value to the SDK type.
### Decision log
- Default is `api` (not `ui`) so existing API integrations get the
correct value without code changes.
- Backfill sets existing rows to `ui` per requirement.
- Child chats inherit `client_type` from parent rather than defaulting.
</details>
> This PR was authored by Mux on behalf of Mike.
## Summary
- add persistent plan mode for chats and the chat-specific plan file
flow
- add structured planning tools such as `ask_user_question` and
`propose_plan`
- keep `write_file` and `edit_files` constrained to the chat-specific
plan file during plan turns
- allow shell exploration in plan mode, including subagents, via
`execute` and `process_output`
- block implementation-oriented, provider-native, MCP, dynamic, and
computer-use tools during plan turns
- update the chat UI, tests, and docs for the new planning flow
Fixes https://github.com/coder/internal/issues/1436
* Adds organization_id to chats with backfill (workspace org → user org membership → default org)
* No support yet for ACLs (follow-up issue)
- Cross-org workspace binding rejected (both in `CreateChatRequest` and in `create_workspace` tool
- Adds `OrganizationAutocomplete` to `AgentCreateForm`
- Docs updated with `organization_id` in chats-api.md
> 🤖 Written by a Coder Agent. Reviewed by many humans and many agents.
---------
Co-authored-by: Mathias Fredriksson <mafredri@gmail.com>
## Summary
Adds `credential_kind` and `credential_hint` columns to
`aibridge_interceptions` to record how each LLM request was
authenticated and provide a masked credential identifier for audit
purposes.
This enables admins to distinguish between centralized API keys,
personal API keys, and subscription-based credentials in the
interceptions audit log.
## Changes
- New migration adding `credential_kind`and `credential_hint` to
`aibridge_interceptions`
- Updated `InsertAIBridgeInterception` query and proto definition to
carry the new fields
- Wired proto fields through `translator.go` and `aibridgedserver.go` to
the database
Depends on https://github.com/coder/aibridge/pull/239
Adds client-executed dynamic tools to the chat API. Dynamic tools are
declared by the client at chat creation time, presented to the LLM
alongside built-in tools, but executed by the client rather than chatd.
This enables external systems (Slack bots, IDE extensions, Discord bots,
CI/CD integrations) to plug custom tools into the LLM chat loop without
modifying chatd's built-in tool set.
Modeled after OpenAI's Assistants API: the chat pauses with
`requires_action` status when the LLM calls a dynamic tool, the client
POSTs results back via `POST /chats/{id}/tool-results`, and the chat
resumes.
See [this example](https://github.com/coder/coder-slackbot-poc) as a
reference for how this is used. It's highly-configurable, which would
enable creating chats from webhooks, periodically polling, or running as
a Slackbot.
<details>
<summary>Design context</summary>
### Architecture
The chatloop **exits** when it encounters dynamic tools and
**re-enters** when results arrive. No blocking channels, no pubsub for
tool results, no in-memory registry. The DB is the only coordination
mechanism.
```
Phase 1 (chatloop):
LLM response → execute built-in tools only →
Persist(assistant + built-in results) →
status = requires_action → chatloop exits
Phase 2 (POST /tool-results):
Persist(dynamic tool results) →
status = pending → wakeCh → chatloop re-enters
```
### Validation (POST /tool-results)
1. Chat status must be `requires_action` (409 if not)
2. Read chat's `dynamic_tools` → set of dynamic tool names
3. Read last assistant message → extract tool-call parts matching
dynamic tool names
4. Submitted tool_call_ids must match exactly (400 for missing/extra)
5. Persist tool-result message parts, set status to `pending`, signal
wake
### Idempotency
Tool call IDs scoped per LLM step. State machine (`requires_action` →
`pending`) is the guard. First POST wins, subsequent get 409.
### Mixed tool calls
When the LLM calls both built-in and dynamic tools in one step, built-in
tools execute immediately. Their results are persisted in phase 1.
Dynamic tool results arrive via POST in phase 2. The LLM sees all
results when the chatloop resumes.
</details>
> 🤖 Generated by Coder Agents
Needed by #23833
Adds a `chat_file_links` association table to track which files are
associated with each chat.
- `AppendChatFileIDs` query links a file to a chat with deduplication
- `GetChatFileMetadataByIDs` query returns lightweight file metadata by
IDs
- Tool-created files (e.g. `propose_plan`) are linked to the chat after
insert
- User-uploaded files are linked to the chat when the referencing
message is sent
- Single-chat GET endpoint hydrates `files: ChatFileMetadata[]` on the
response
> 🤖 Created by Coder Agents and massaged into shape by a human.
Two new columns added to aibridge_token_usages:
- cache_read_input_tokens (BIGINT, default 0)
- cache_write_input_tokens (BIGINT, default 0)
Migration backfills existing rows by extracting values from the metadata
JSONB column (cache_read_input, input_cached, prompt_cached for reads
(max value selected since only 1 should be set), cache_creation_input
for writes).
All references to data from metadata were updated to reference new
columns. No other changes then changing where data is extracted from.
Requires aibridge library version bump to include:
https://github.com/coder/aibridge/pull/229
Fixes: https://github.com/coder/aibridge/issues/150
Add a nullable `value_key_id` column to the `user_secrets` table with a
foreign key to `dbcrypt_keys`. This is the column dbcrypt uses to track
which encryption key encrypted a given secret's value. This is required
for encryption of user secret values.
The column was missing from the original migration (000357).
## Description
Adds `provider_name` to aibridge interceptions to store the provider
instance name alongside the provider type. This allows distinguishing
between multiple instances of the same provider type (e.g. `copilot` vs
`copilot-business`).
## Changes
* Add `provider_name` column to `aibridge_interceptions` table with
backfill from `provider`.
* Add `provider_name` field to the proto `RecordInterceptionRequest`
message.
* Add `ProviderName` to the `codersdk.AIBridgeInterception` API
response.
_Disclaimer: initially produced by Claude Opus 4.6, modified and
reviewed by @ssncferreira ._
Adds a nullable JSONB column `last_injected_context` to the `chats`
table that stores the most recently persisted injected context parts
(AGENTS.md context-file and skill message parts). The column is updated
only when `persistInstructionFiles()` runs — on first workspace attach
or when the agent changes — so there are no redundant writes on
subsequent turns.
Internal fields (`ContextFileContent`, `ContextFileOS`,
`ContextFileDirectory`, `SkillDir`) are stripped at write time so the
column only holds small metadata. No stripping needed on the read path.
<details>
<summary>Implementation notes</summary>
- New migration `000456` adds nullable `last_injected_context JSONB`
column.
- New SQL query `UpdateChatLastInjectedContext` writes the column
without touching `updated_at`.
- `persistInstructionFiles()` strips internal fields from parts via
`StripInternal()` before persisting.
- Sentinel path (no AGENTS.md) persists skill-only parts when skills
exist.
- `codersdk.Chat` exposes `LastInjectedContext []ChatMessagePart`
(omitempty).
- `db2sdk.Chat()` passes through the already-clean data.
</details>
## Summary
Adds read/unread tracking for chats so users can see which agent
conversations have new assistant messages they haven't viewed.
## Backend Changes
- Adds `last_read_message_id` column to the `chats` table (migration
000439).
- Computes `has_unread` as a virtual column in `GetChatsByOwnerID` using
an `EXISTS` subquery checking for assistant messages beyond the read
cursor.
- Exposes `has_unread` on the `codersdk.Chat` struct and auto-generated
TypeScript types.
- Updates `last_read_message_id` on stream connect/disconnect in
`streamChat`, avoiding per-message API calls during active streaming.
- Uses `context.WithoutCancel` for the deferred disconnect write so the
DB update succeeds even after the client disconnects.
## Frontend Changes
- Bold title (`font-semibold`) for unread chats in the sidebar.
- Small blue dot indicator next to the relative timestamp.
- Suppresses unread indicator for the currently active chat via
`isActive` from NavLink.
## Design Decisions
- Only `assistant` messages count as unread — the user's own messages
don't trigger the indicator.
- No foreign key on `last_read_message_id` since messages can be deleted
(via rollback/truncation) and the column is just a high-water mark.
- Zero API calls during streaming: exactly 2 DB writes per stream
session (connect + disconnect).
- Unread state refreshes on chat list load and window focus. The
`watchChats` WebSocket optimistically marks non-active chats as unread
on `status_change` events, but does not carry a server-computed
`has_unread` field. Navigating to a chat optimistically clears its
unread indicator in the cache.
Add a per-MCP-server `model_intent` toggle that wraps tool schemas with
a
`model_intent` field, requiring the LLM to provide a human-readable
description of each tool call's purpose. The intent string is shown as a
status label in the UI instead of opaque tool names, and is
transparently
stripped before the call reaches the remote MCP server.
Built-in tools have rich specialized renderers (terminal blocks, file
diffs,
etc.) and don't need this. MCP tools hit `GenericToolRenderer` which
only
shows raw tool names and JSON — that's where model_intent adds value.
The model learns what to provide via the JSON Schema `description` on
the
`model_intent` property itself — no system prompt changes needed.
<details>
<summary>Implementation details</summary>
### Architecture
Inspired by the `withModelIntent()` pattern from `coder/blink`, adapted
for
Go + React. The wrapping is entirely in the `mcpclient` layer — tool
implementations never see `model_intent`.
**Schema wrapping** (`mcpToolWrapper.Info()`): When enabled, wraps the
original tool parameters under a `properties` key and adds a
`model_intent`
string field with a rich description that teaches the model inline.
**Input unwrapping** (`mcpToolWrapper.Run()`): Strips `model_intent` and
unwraps `properties` before forwarding to the remote MCP server. Handles
three input shapes models may produce:
1. `{ model_intent, properties: {...} }` — correct format
2. `{ model_intent, key: val, ... }` — flat, no wrapper
3. Malformed — falls through gracefully
**Frontend extraction**: `streamState.ts` extracts `model_intent` from
incrementally parsed streaming JSON. `messageParsing.ts` extracts it
from
persisted tool call args.
**UI rendering**: `GenericToolRenderer` shows the capitalized intent
string
as the primary label when available, falling back to the raw tool name.
### Changes
- Database: `model_intent` boolean column on `mcp_server_configs`
- SDK: `ModelIntent` field on config/create/update types
- API: pass-through in create/update handlers + converter
- mcpclient: schema wrapping in `Info()`, input unwrapping in `Run()`
- Frontend: extraction from streaming + persisted args
- UI: intent label in `GenericToolRenderer`, toggle in admin panel
- Tests: 6 new tests (schema wrapping, unwrapping, passthrough,
fallback)
### Decision log
- **Option lives on MCPServerConfig, not model config**: Built-in tools
already have rich renderers; only MCP tools benefit from model_intent.
- **No system prompt changes**: The JSON Schema `description` on the
`model_intent` property teaches the model inline.
- **Pointer bool on update request**: Follows existing pattern (`*bool`)
so PATCH requests don't reset the value when omitted.
</details>
https://github.com/user-attachments/assets/bd5d12a1-61b3-4b7d-83b6-317bdfb60b3c
## Summary
Adds pinned chats to the agents page sidebar with server-side
persistence and drag-to-reorder. Users can pin/unpin chats via the
context menu, and pinned chats appear in a dedicated "Pinned" section
above the time-grouped list.
## Database
Migration `000453_chat_pin_order`: adds `pin_order integer DEFAULT 0 NOT
NULL` column on `chats` (0 = unpinned, 1+ = pinned in display order).
Three SQL queries handle pin operations server-side using CTEs with
`ROW_NUMBER()`:
- `PinChatByID`: normalizes existing orders and appends to end
- `UnpinChatByID`: sets target to 0 and compacts remaining pins
- `UpdateChatPinOrder`: shifts neighbors, clamps to `[1, pinned_count]`
All queries exclude archived chats. `ArchiveChatByID` clears `pin_order`
on archive. The handler rejects pinning archived chats with 400.
## Backend
Pin/unpin/reorder go through the existing `PATCH
/api/experimental/chats/{chat}` via the `pin_order` field on
`UpdateChatRequest`. The handler routes based on current pin state:
`pin_order == 0` unpins, `> 0` on an already-pinned chat reorders, `> 0`
on an unpinned chat appends to end.
## Frontend
- `pinChat` / `unpinChat` / `reorderPinnedChat` optimistic mutations
using shared `isChatListQuery` predicate
- Sidebar renders Pinned section above time groups, excludes pinned
chats from time groups
- Pin/Unpin context menu items (hidden for child/delegated chats)
- `@dnd-kit/core` + `@dnd-kit/sortable` for drag-to-reorder with
`MouseSensor`, `TouchSensor`, and `KeyboardSensor`
- Local pin-order override prevents flash on drop; click blocker
prevents NavLink navigation after drag
---
*PR generated with Coder Agents*
## Summary
This change removes the steady-state "resolve the latest workspace
agent" query from chat execution.
Instead of asking the database for the latest build's agent on every
turn, a chat now persists the workspace/build/agent binding it actually
uses and reuses that binding across subsequent turns. The common path
becomes "load the bound agent by ID and dial it", with fallback paths to
repair the binding when it is missing, stale, or intentionally changed.
## What changes
- add `workspace_id`, `build_id`, and `agent_id` binding fields to
`chats`
- expose those fields through the chat API / SDK so the execution
context is explicit
- load the persisted binding first in chatd, instead of always resolving
the latest build's agent
- persist a refreshed binding when chatd has to re-resolve the workspace
agent
- keep child / subagent chats on the same bound workspace context by
inheriting the parent binding
- leave `build_id` / `agent_id` unset for flows like `create_workspace`,
then bind them lazily on the next agent-backed turn
## Runtime behavior
The binding is treated as an optimistic cache of the agent a chat should
use:
- if the bound agent still exists and dials successfully, we use it
without a latest-build lookup
- if the bound agent is missing or no longer reachable, chatd
re-resolves against the latest build and persists the new binding
- if a workspace mutation changes the chat's target workspace, the
binding is updated as part of that mutation
To avoid reintroducing a hot-path query, dialing uses lazy validation:
- start dialing the cached agent immediately
- only validate against the latest build if the dial is still pending
after a short delay
- if validation finds a different agent, cancel the stale dial, switch
to the current agent, and persist the repaired binding
## Result
The hot path stops issuing
`GetWorkspaceAgentsInLatestBuildByWorkspaceID` for every user message,
which is the source of the DB pressure this PR is addressing. At the
same time, chats still converge to the correct workspace agent when the
binding becomes stale due to rebuilds or explicit workspace changes.
## Summary
Adds a general-purpose `map[string]string` label system to chats, stored
as jsonb with a GIN index for efficient containment queries.
This is a standalone foundational feature that will be used by the
upcoming Automations feature for session identity (matching webhook
events to existing chats), replacing the need for bespoke session-key
tables.
## Changes
### Database
- **Migration 000451**: Adds `labels jsonb NOT NULL DEFAULT '{}'` column
to `chats` table with a GIN index (`idx_chats_labels`)
- **`InsertChat`**: Accepts labels on creation via `COALESCE(@labels,
'{}')`
- **`UpdateChatByID`**: Supports partial update —
`COALESCE(sqlc.narg('labels'), labels)` preserves existing labels when
NULL is passed
- **`GetChats`**: New `has_labels` filter using PostgreSQL `@>`
containment operator
- **`GetAuthorizedChats`**: Synced with generated `GetChats` (new column
scan + query param)
### API
- **Create chat** (`POST /chats`): Accepts optional `labels` field,
validated before creation
- **Update chat** (`PATCH /chats/{chat}`): Supports `labels` field for
atomic label replacement
- **List chats** (`GET /chats`): Supports `?label=key:value` query
parameters (multiple are AND-ed)
### SDK
- `Chat`, `CreateChatRequest`, `UpdateChatRequest`, `ListChatsOptions`
all gain `Labels` fields
- `UpdateChatRequest.Labels` is a pointer (`*map[string]string`) so
`nil` means "don't change" vs empty map means "clear all"
### Validation (`coderd/httpapi/labels.go`)
- Max 50 labels per chat
- Key: 1–64 chars, must match `[a-zA-Z0-9][a-zA-Z0-9._/-]*` (supports
namespaced keys like `github.repo`, `automation/pr-number`)
- Value: 1–256 chars
- 13 test cases covering all edge cases
### Chat runtime
- `chatd.CreateOptions` gains `Labels` field, threaded through to
`InsertChat`
- Existing `UpdateChatByID` callers (e.g., quickgen title updates) are
unaffected — NULL labels preserve existing values via COALESCE
OpenAI Responses follow-up turns were replaying full assistant/tool
history even when `store=true`, which breaks after reasoning +
provider-executed `web_search` output.
This change persists the OpenAI response ID on assistant messages, then
in `coderd/x/chatd` switches `store=true` follow-ups to
`previous_response_id` chaining with a system + new-user-only prompt.
`store=false` and missing-ID cases still fall back to manual replay.
It also updates the fake OpenAI server and integration coverage for the
chaining contract, and carries the rebased path move to `coderd/x/chatd`
plus the migration renumber needed after rebasing onto `main`.
<!--
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_Disclaimer:_ _initially_ _produced_ _by_ _Claude_ _Opus_ _4\.6,_ _heavily_ _modified_ _and_ _reviewed_ _by_ _me._
Closes https://github.com/coder/internal/issues/1360
Adds a new `/api/v2/aibridge/sessions` API which returns "sessions".
Sessions, as defined in the [RFC](https://www.notion.so/coderhq/AI-Bridge-Sessions-Threads-2ccd579be59280f28021d3baf7472fbe?source=copy_link), are a set of interceptions logically grouped by a session key issued by the client.
The API design for this endpoint was done in [this doc](https://github.com/coder/internal/issues/1360).
If the client has not provided a session ID, we will revert to the thread root ID, and if that's not present we use the interception's own ID (i.e. a session of a single interception - which is effectively what we show currently in our `/api/v2/aibridge/interceptions` API).
The SQL query looks gnarly but it's relatively simple, and seems to perform well (~200ms) even when I import dogfood's `aibridge_*` tables into my workspace. If we need to improve performance on this later we can investigate materialized views, perhaps, but for now I don't think it's warranted.
---
_The PR looks large but it's got a lot of generated code; the actual changes aren't huge._
## Summary
Adds the database schema, API endpoints, SDK types, and encryption
wrappers for admin-managed MCP (Model Context Protocol) server
configurations that chatd can consume. This is the backend foundation
for allowing external MCP tools (Sentry, Linear, GitHub, etc.) to be
used during AI chat sessions.
## Database
Two new tables:
- **`mcp_server_configs`**: Admin-managed server definitions with URL,
transport (Streamable HTTP / SSE), auth config (none / OAuth2 / API key
/ custom headers), tool allow/deny lists, and an availability policy
(`force_on` / `default_on` / `default_off`). Includes CHECK constraints
on transport, auth_type, and availability values.
- **`mcp_server_user_tokens`**: Per-user OAuth2 tokens for servers
requiring individual authentication. Cascades on user/config deletion.
New column on `chats` table:
- **`mcp_server_ids UUID[]`**: Per-chat MCP server selection, following
the same pattern as `model_config_id` — passed at chat creation,
changeable per-message with nil-means-no-change semantics.
## API Endpoints
All routes are under `/api/experimental/mcp/servers/` and gated behind
the `agents` experiment.
**Admin endpoints** (`ResourceDeploymentConfig` auth):
- `POST /` — Create MCP server config
- `PATCH /{id}` — Update MCP server config (full-replace)
- `DELETE /{id}` — Delete MCP server config
**Authenticated endpoints** (all users, enabled servers only for
non-admins):
- `GET /` — List configs (admins see all, members see enabled-only with
admin fields redacted)
- `GET /{id}` — Get config by ID (with `auth_connected` populated
per-user)
**OAuth2 per-user auth flow:**
- `GET /{id}/oauth2/connect` — Initiate OAuth2 flow (state cookie CSRF
protection)
- `GET /{id}/oauth2/callback` — Handle OAuth2 callback, store tokens
- `DELETE /{id}/oauth2/disconnect` — Remove stored OAuth2 tokens
## Security
- **Secrets never returned**: `OAuth2ClientSecret`, `APIKeyValue`, and
`CustomHeaders` are never in API responses — only boolean indicators
(`has_oauth2_secret`, `has_api_key`, `has_custom_headers`).
- **Field redaction for non-admins**: `convertMCPServerConfigRedacted`
strips `OAuth2ClientID`, auth URLs, scopes, and `APIKeyHeader` from
non-admin responses.
- **dbcrypt encryption at rest**: All 5 secret fields use `dbcrypt_keys`
encryption with full encrypt-on-write / decrypt-on-read wrappers (11
dbcrypt method overrides + 2 helpers), following the same pattern as
`chat_providers.api_key`.
- **OAuth2 CSRF protection**: State parameter stored in `HttpOnly`
cookie with `HTTPCookies.Apply()` for correct `Secure`/`SameSite` behind
TLS-terminating proxies.
- **dbauthz authorization**: All 18 querier methods have authorization
wrappers. Read operations use `ActionRead`, write operations use
`ActionUpdate` on `ResourceDeploymentConfig`.
## Governance Model
| Control | Implementation |
|---------|---------------|
| **Global kill switch** | `enabled` defaults to `false` |
| **Availability policy** | `force_on` (always injected), `default_on`
(pre-selected), `default_off` (opt-in) |
| **Per-chat selection** | `mcp_server_ids` on `CreateChatRequest` /
`CreateChatMessageRequest` |
| **Auth gate** | OAuth2 servers require per-user auth before tools are
injected |
| **Tool-level allow/deny** | Arrays on `mcp_server_configs` for
granular tool filtering |
| **Secrets encrypted at rest** | Uses `dbcrypt_keys` (same pattern as
`chat_providers.api_key`) |
## Tests
8 test functions covering:
- Full CRUD lifecycle (create, list, update, delete)
- Non-admin visibility filtering (enabled-only, field redaction)
- `auth_connected` population for OAuth2 vs non-OAuth2 servers
- Availability policy validation (valid values + invalid rejection)
- Unique slug enforcement (409 Conflict)
- OAuth2 disconnect idempotency
- Chat creation with `mcp_server_ids` persistence
## Known Limitations (Deferred)
These are documented and intentional for an experimental feature:
- **Audit logging** not yet wired — will add when feature stabilizes
- **Cross-field validation** (e.g., OAuth2 fields required when
`auth_type=oauth2`) — admin-only endpoint, will add when stabilizing
- **`force_on` auto-injection** — query exists but not yet wired into
chatd tool injection (follow-up)
- **Additional test coverage** — 403 auth tests, GET-by-ID tests,
callback CSRF tests planned for follow-up
## What's NOT in this PR
- Frontend UI (admin panel + chat picker)
- Actual MCP client connections (`chatd/chatmcp/` manager)
- Tool injection into `chatloop/`
Adds a `deleted` boolean column to the `chat_messages` table. Messages
are never physically deleted from the database — instead they are marked
as deleted so that usage and cost data is preserved.
## Changes
### Migration
- New migration (000444) adds `deleted boolean NOT NULL DEFAULT false`
to `chat_messages`
### SQL queries
- `DeleteChatMessagesAfterID` → `SoftDeleteChatMessagesAfterID` (UPDATE
SET deleted=true instead of DELETE)
- New `SoftDeleteChatMessageByID` query for single-message soft-delete
- All read queries now filter `deleted = false`:
- `GetChatMessageByID`
- `GetChatMessagesByChatID`
- `GetChatMessagesByChatIDDescPaginated`
- `GetChatMessagesForPromptByChatID` (both CTE and main query)
- `GetLastChatMessageByRole`
- Cost/usage queries (`GetChatCostSummary`, `GetChatCostPerModel`, etc.)
intentionally still include deleted messages to preserve accurate spend
tracking
### EditMessage behavior
- Previously: updated the message content in-place + hard-deleted
subsequent messages
- Now: soft-deletes the original message + soft-deletes subsequent
messages + inserts a new message with the updated content
- This preserves the original message data (tokens, cost, content) in
the database
## Summary
Adds a `runtime_ms` column to `chat_messages` that records the
wall-clock duration (in milliseconds) of each LLM step. This covers LLM
streaming, tool execution, and retries — the full time the agent is
"alive" for a step.
This is the foundation for billing by agent alive time. The column
follows the same pattern as `total_cost_micros`: stored per assistant
message, aggregatable with `SUM()` over time periods by user.
## Changes
- **Migration**: adds nullable `runtime_ms bigint` to `chat_messages`.
- **chatloop**: adds `Runtime time.Duration` field to `PersistedStep`,
measures `time.Since(stepStart)` at the beginning of each step (covering
stream + tool execution + retries).
- **chatd**: passes `step.Runtime.Milliseconds()` to the assistant
message `InsertChatMessage` call; all other message types (system, user,
tool) get `NULL`.
- **Tests**: adds `runtime > 0` assertion in chatloop tests.
## Billing query pattern
Once ready, aggregation mirrors the existing cost queries:
```sql
SELECT COALESCE(SUM(cm.runtime_ms), 0)::bigint AS total_runtime_ms
FROM chat_messages cm
JOIN chats c ON c.id = cm.chat_id
WHERE c.owner_id = @user_id
AND cm.created_at >= @start_time
AND cm.created_at < @end_time
AND cm.runtime_ms IS NOT NULL;
```
Paweł Banaszewski