Add a GET endpoint at `/api/v2/agent-firewall/sessions/{id}` that
returns agent firewall session metadata (`id`, `workspace_id`,
`owner_id`, `confined_process`, `started_at`). The handler authorizes
against the `boundary_log` resource with `ActionRead` via dbauthz.
The endpoint is enterprise-only, gated behind the `FeatureBoundary`
entitlement.
The `GetBoundarySessionByID` SQL query JOINs through `workspace_agents`
→ `workspace_resources` → `workspace_builds` → `workspaces` to return
`workspace_id` and `workspace_owner_id` directly, avoiding a separate
query.
Also adds an `owner_id` column to the `boundary_logs` table (migration
000526) with a FK to `users(id)` and a backfill from
`boundary_sessions`. This enables user-scoped RBAC authorization for
`InsertBoundaryLogs` via `.WithOwner()`, ensuring workspace agents can
only insert logs for their own owner.
Depends on #24810
**RBAC behaviour:**
| Role | Result |
|---------|--------|
| Owner | read |
| Auditor | read |
| Member | 404 |
> [!NOTE]
> This PR was authored by Coder Agents.
Adds chat_context_resources: a per-chat pinned copy of the agent context
resources a chat is hydrated against. The agent-side table
(workspace_agent_context_resources) is last-writer-wins with no history,
so a chat copies its resources at hydration/refresh to keep a stable view
while the agent drifts.
Schema foundation only (no queries/dbauthz/prepareGeneration/SDK yet).
chat_id FK ON DELETE CASCADE for cleanup parity; no agent FK so the pin
survives agent replacement; PK (chat_id, source); reuses the 000522 enum
types.
Implements
https://linear.app/codercom/issue/AIGOV-286/add-interception-cost-calculation-to-aibridge-token-usages
Adds spend attribution to AI Gateway. After the upstream response, each
token-usage record now captures the user's effective group, the
per-token prices in effect at that moment, and a computed cost — so
spend is recorded as an immutable, point-in-time snapshot.
Concretely, `aibridge_token_usages` gains `effective_group_id`,
`input_price_micros`, `output_price_micros`, `cache_read_price_micros`,
`cache_write_price_micros`, and `cost_micros`. When a usage record is
written, the effective group is resolved (per-user override, else the
deployment budget policy), the `(provider, model)` price is looked up
and snapshotted onto the row, and cost is computed from the
provider-reported token counts. A model that isn't in the price table
records its tokens with a `NULL` cost; any *other* resolution failure
fails the write, so a `NULL` cost unambiguously means "model not priced"
rather than "lookup errored."
All values are stored in micro-units (1 unit = 1,000,000 micro-units;
Phase 1 assumes USD, so 1 micro-unit = $0.000001). Prices are quoted per
million tokens.
This also grants the AI Bridge RBAC subject `read` on `ai_model_prices`
(the per-interception price lookup needs it; it previously only had
`update` for the startup seeder).
## Cost precision
Cost is computed per token category as `tokens × price / 1_000_000` with
integer division, then the four categories are summed. The division is
done **per category** (not once over the summed numerator) on purpose:
it keeps the per-category line items summing exactly to the stored total
— no "the parts don't add up to the whole" in reporting).
Integer division truncates sub-micro-unit fractions. For example, a
cheap model at $0.10 per million tokens is a price of `100_000`; 9
tokens cost `9 × 100_000 / 1_000_000 = 900_000 / 1_000_000 = 0` (the
true 0.9 micro-units floors to 0). At real list prices this rarely bites
— $3/M input is a price of `3_000_000`, so even a single token is 3
micro-units. The per-record under-count is bounded below 1 micro-unit
per category, so under $0.000004 total across the four categories, which
is acceptable for list-price-based cost approximation.
## Overflow safety
`cost_micros` is a `BIGINT` (int64), and the largest intermediate value
is a single category's `tokens × price` before division. int64's ceiling
is ≈ `9.223e18`.
- At a steep $75/M model (price `75_000_000`), overflow would require
~123 billion tokens in one response: `123e9 × 75e6 = 9.225e18`, just
over the limit. `122e9` stays under at `9.15e18`.
- A realistically maxed-out Opus 4.8 response (≈1M input + 128K output
at list prices) costs about $15, with a numerator around `1.5e13` —
roughly six orders of magnitude below the ceiling.
So overflow is unreachable from real token counts.
### Multi-currency support
In the future, we may encounter issues with multi-currency support,
especially when dealing with currencies that have very large exchange
rates relative to USD, for example:
IRR: ~1,300,000 IRR ≈ 1 USD
VND: ~26,000 VND ≈ 1 USD
For currencies with such large denominations, numeric overflow is
technically possible, considering that we have only about six orders of
magnitude of headroom before reaching the limit (see above).
## `effective_group_id` has no foreign key
`effective_group_id` records the group a spend was attributed to, as an
immutable historical fact. It is intentionally **not** a foreign key, so
the record survives deletion of the group.
Alternatives were considered and rejected:
- **`ON DELETE SET NULL`** would mutate an "immutable" record — deleting
a group silently erases that interception's attribution and under-counts
the group's historical spend.
- **`RESTRICT` / `NO ACTION`** would block group deletion entirely
(groups are hard-deleted).
- **`CASCADE`** would delete spend history when a group is deleted — the
worst outcome for an audit record.
There is also no insert-time check that the group still exists: the id
comes from a budget that was just resolved, meaning it was valid at some
point.
## Open question: group name snapshotting
Should we also snapshot the group *name* onto each record? Two options:
- **Denormalize it now** — readable in historical reports even after a
group is deleted, but the snapshot can drift from the current name on
rename, raising a "show point-in-time vs. current name" question.
- **Postpone until needed** — it's a purely additive column later, and
the name is display-only (not correctness-bearing like the price). The
cost: names of groups deleted before the column is added can't be
backfilled.
Leaning toward postponing until a concrete reporting need settles the
drift question.
Adds `ai` to sqlc's `gen.go.initialisms` in `coderd/database/sqlc.yaml`
so the generated DB code follows Go's initialism convention. Adds the
matching `ai` -> `AI` case to the dbgen PascalCase helper
(`scripts/dbgen/main.go`) so the corresponding `dbmem` / mock
identifiers stay in sync. `make gen` regenerates the rest; hand-written
call sites that consume DB-generated identifiers
(`enterprise/audit/table.go`, `coderd/database/modelmethods.go`,
`enterprise/coderd/aigatewaykeys.go`, `coderd/database/dbauthz/*`, etc.)
are updated to match.
Scope is deliberately limited to the database layer:
- `coderd/rbac/*` (resource and scope generators) is untouched —
`ResourceAi*` / `ScopeAi*` constants stay on main's casing.
- `codersdk/*` (Go SDK) is untouched — `codersdk.ResourceAi*` /
`codersdk.APIKeyScopeAi*` constants stay on main's casing, so external
Go SDK consumers see no source-level break.
- `Aibridge*` identifiers (one SQL token `aibridge`, not `ai_bridge`)
are out of scope.
On-the-wire values are unchanged: enum strings, RBAC resource type
strings, API key scope strings, and JSON tags all stay the same. The
HTTP/JSON surface is unaffected.
Refs:
[AIGOV-369](https://linear.app/codercom/issue/AIGOV-369/change-ai-references-in-coderddatabasemodelsgo-to-ai)
🤖 Generated with [Coder Agents](https://coder.com)
Foundation for the Workspace Context Sources RFC (phase 3). The agent
push (#25983) and coderd snapshot storage (#26145) already persist
per-agent context snapshots; this PR lands the **chat-side storage**
plus the **`agentapi` push trigger** that a follow-up will use to read
them. It does **not** touch `chatd` and changes no behavior — nothing
wires an implementation yet.
## What changed
- Adds four nullable columns to `chats` — `context_aggregate_hash`,
`context_dirty_since`, `context_dirty_resources`, and `context_error` —
and rebuilds the `chats_expanded` view.
- Adds three queries — `SetChatContextSnapshot`,
`HydrateAgentChatsContext`, `MarkChatsContextDirtyByAgent` — with
`dbauthz` wrappers and `audit` entries. They are store-interface methods
covered by a Postgres test (`TestChatContextHydration`).
- Adds the `agentapi.ContextDirtyMarker` interface and invokes it inside
the `PushContextState` transaction, publishing collected events only
after commit.
## Intentionally inert
There are **no production callers** of the three queries and **no
implementation** wired for `ContextDirtyMarker`, so the push trigger is
dormant. This is deliberate: the PR is the durable storage/query
foundation only.
The actual integration — the `chatd` implementation that
hydrates/dirties chats and backs a refresh endpoint, consuming the
pinned context in prompt building, the rich SDK types + UI, and retiring
the live per-turn pull — lands as a single follow-up PR. Splitting this
way keeps the schema/query layer reviewable on its own and keeps the
integration whole in one place.
Refs #25983, #26145.
<details>
<summary>Decision log</summary>
- **Columns over a side table.** The four `chats` columns are the
durable model (accepting the one-time `chats_expanded` view/CTE churn).
`last_injected_context` is deliberately left untouched — it is
load-bearing for the live per-turn context pull.
- **Keep `agentapi`, drop `chatd`.** The earlier revision wired the
hydrate/dirty implementation through `chatd` and added a `PUT
/chats/{chat}/context` refresh endpoint. Those were removed so this PR
is pure foundation; `agentapi` defines the trigger + interface (it does
not import `chatd`), and the `chatd` implementation arrives with the
full integration.
- **No new experiment flag.** The columns are dark and unread by prompt
building.
- **Authz.** The new query wrappers authorize chat updates under the
chat RBAC object / `ResourceChat`, consistent with the existing system
chat mutators.
</details>
---
🤖 Generated by Coder Agents on behalf of @kylecarbs.
Replaces the v2.10 `PushContextState` stub with a real coderd write
path. Phase 1 of the chat-side persistence story; nothing reads these
rows yet.
Follows [#25983](https://github.com/coder/coder/pull/25983) and unblocks
[CODAGT-569](https://linear.app/codercom/issue/CODAGT-569/enable-agent-api-v210-pushcontextstate-bump-currentminor-wire-coderd).
## What ships
### Schema (`000517_workspace_agent_context.{up,down}.sql`)
Two new tables plus `api_key_scope` enum extensions:
- `workspace_agent_context_snapshots` (PK `workspace_agent_id` to
`workspace_agents(id) ON DELETE CASCADE`): one row per agent,
overwritten per push. Holds `version`, `schema_version`,
`aggregate_hash`, `snapshot_error`, `received_at`.
- `workspace_agent_context_resources` (PK `(workspace_agent_id,
source)`): per-resource state. `body_kind` and `status` are `TEXT` +
`CHECK` so adding new wire kinds (the RFC's reserved
PLUGIN/HOOK/SUBAGENT/COMMAND) is a one-line CHECK update plus a Go
switch case.
### SQLC queries (`coderd/database/queries/workspaceagentcontext.sql`)
- `UpsertWorkspaceAgentContextSnapshot`
- `UpsertWorkspaceAgentContextResource`
- `DeleteStaleWorkspaceAgentContextResources`
(delete-where-source-not-in)
- `GetLatestWorkspaceAgentContextSnapshot`
- `ListWorkspaceAgentContextResources`
### Handler (`coderd/agentapi/context.go`)
`ContextAPI` is a new sub-API. `PushContextState`:
1. Rejects `schema_version > 1` with a non-`Unimplemented` error so a
forward-incompatible agent fails loudly during rollout instead of
slipping into the permanent fallback path the `Unimplemented`
translation reserves for old coderd deployments.
2. Validates resources: no empty/duplicate sources, every variant maps
to a known body kind, every status maps to a known enum value, the
`Body` oneof is set (even when status is non-OK, mirroring the wire
guarantee so coderd can attribute failures to a known kind).
3. Inside `Database.InTx`, reads the existing snapshot. If the push is
not `initial` and `version` is not strictly greater, returns `accepted =
false` and leaves stored state untouched. Otherwise upserts the snapshot
row, upserts each resource, then runs the stale-source prune so the
snapshot and resource rows always agree.
4. Returns `accepted = true` on success.
Resource bodies are stored as `protojson(body oneof variant)` in `body
JSONB` with `body_kind` as the discriminator. Adding a new field to an
existing variant is zero work since `protojson` tolerates new fields;
adding a new variant is a CHECK + switch case.
### RBAC + dbauthz
- New `ResourceWorkspaceAgentContext` (Create/Read/Update/Delete).
- New `SubjectTypeAgentContext` plus `subjectAgentContext` system role
and `dbauthz.AsAgentContext` helper. The push handler elevates to this
subject; the agent's own role does not get direct write access to the
table.
- New `workspace_agent_context:*` API key scopes registered in the enum
migration; internal-only (not added to `externalLowLevel`).
### Audit
These rows are agent-pushed state, not user-authored. They are
intentionally not added to `AuditActionMap` and not enumerated in
`enterprise/audit/table.go`, matching `boundary_logs`,
`workspace_agent_memory_resource_monitor`, etc. `enterprise/audit` tests
pass unchanged.
## Tests
- `coderd/agentapi/context_test.go`: 12 subtests covering
accepts/rejects (schema version, empty/duplicate source, unknown status,
missing body), version semantics (stale dropped, same-version replay
dropped, `initial=true` overwrites lower version), variant coverage,
non-OK status persistence, and the empty-active-set prune case.
- `coderd/database/dbauthz/dbauthz_test.go`: 5 `MethodTestSuite` cases
covering the new queries.
- `coderd/rbac/roles_test.go`: `WorkspaceAgentContext` permission row
asserting no human role currently has access.
-
`coderd/database/migrations/testdata/fixtures/000517_workspace_agent_context.up.sql`:
one snapshot + one resource per known body kind plus a non-OK status, so
the migration test suite never lands with these tables empty.
## Out of scope (later phases)
- Chat hydration (`chats.context_aggregate_hash`,
`last_injected_context`).
- Dirty-bit fan-out and `PUT /chats/{id}/context`.
- Agent-side `POST /api/v0/context/resync` barrier and the `coder exp
chat context` CLI.
- `codersdk` chat-context wire types and the dashboard Sources drawer.
- Removal of the chatd per-turn pull fallback.
## Compat property
This is a pure write path. If anything here returns errors the agent's
`RunPush` loop backs off, no chat behavior changes, and the workspace
keeps behaving exactly like it did before v2.10.
<details>
<summary>Implementation plan and decision log</summary>
Key design calls:
1. **Concurrency**: Accept iff `req.Initial || req.Version >
existing.Version`. The strict RFC reading ("version comparison is
authoritative") locks restarted agents out because their per-process
counter resets to 1; honoring `initial=true` reflects the real reboot
reality while still rejecting steady-state replays/out-of-order pushes.
2. **Body encoding**: `protojson` over the oneof variant body proto,
stored in JSONB with `body_kind` discriminator. Structured at the API/Go
layer, schema-tolerant at the storage layer, and Phase 2 readers
round-trip back via `protojson.Unmarshal`.
3. **Schema version rejection**: returns a normal error, not
`Unimplemented`. The agent's `RunPush` loop only short-circuits on
`Unimplemented`; that escape hatch is reserved for old coderd
deployments. A forward-incompatible agent should retry-and-back-off, not
flip the connection into permanent fallback.
4. **Validation strictness**: empty sources, duplicate sources,
`STATUS_UNSPECIFIED`, and missing `Body` oneof variants are rejected
before any write so a misbehaving agent cannot poison the snapshot
table. Phase 2 readers can trust every row maps to a known proto
variant.
</details>
_This PR was authored by Coder Agents on Kyle Carberry's behalf._
Add `agent_firewall_session_id` (UUID NULL) and
`agent_firewall_sequence_number` (INT NULL) to `aibridge_interceptions`
with a partial index on `agent_firewall_session_id`. No FK to
`boundary_sessions` (soft reference, resolved at query time).
`RecordInterception` reads the new fields from the proto request (merged
in #25884) via `parseOptionalUUID` / `parseOptionalInt32` helpers.
> This PR was authored by Coder Agents.
Relates to
https://linear.app/codercom/issue/AIGOV-285/add-user-budget-overrides-table-and-crud-api
Adds audit-log support for `user_ai_budget_override` mutations. Without
it, an admin could quietly change a user's per-user spend cap (e.g. from
`$500` to `$50`), reassign it to a different group, or delete it
entirely with no record of who did it.
Both write (`create-or-update`) and delete actions now generate audit
log entries. Unlike group AI budgets, which only track `spend_limit`,
overrides also track `group_name`: an override can be reassigned to a
different attributed group, so that change needs to show up in the diff.
The raw `spend_limit_micros`, IDs, and timestamps are ignored in favor
of the human-readable `spend_limit` and `group_name`.
Depends on #25439.
## Screenshot
<img width="1343" height="514" alt="image"
src="https://github.com/user-attachments/assets/aee30f58-6e81-435e-9bca-5bc98f49d8d3"
/>
Refs #25936.
Adds a configurable per-org default member role set. Unioned into each member's effective roles at read time.
<sub>with Coder Agents on behalf of @Emyrk.</sub>
Adds an optional dbcrypt wrapper around gitsshkeys.private_key. The
column is encrypted on insert and update through enterprise/dbcrypt when
external token encryption is configured, and decrypted on read.
A new private_key_key_id column references
dbcrypt_keys(active_key_digest) so revocation safety is enforced by the
existing foreign key. Rows with a NULL key_id stay plaintext and remain
readable. Existing plaintext rows can be backfilled by running `coder
server dbcrypt rotate`.
Generated with assistance from Coder Agents.
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 ._
Jon Ayers