v1.13.3: cleanup bundle — statement timeout + alpha ordering + stuck-row sweeper + repairToolCall

Four independent items, all owed from prior dispatches.

- statement_timeout at the database level via:
    ALTER DATABASE boocode SET statement_timeout = '30s';
  Applied operationally; documented as a comment at the top of schema.sql
  (ALTER DATABASE can't run inside a DO block, so it's not idempotent
  inside applySchema). Re-apply after a volume reset.

- Tool registry alpha-sorted at module load. llama.cpp's prompt cache
  hits on byte-identical prefixes; any reordering of the tool list near
  the top of the system prompt would invalidate every cached turn.
  Single-source sort at the ALL_TOOLS export so toolJsonSchemas() and
  TOOLS_BY_NAME inherit the order automatically. New tools.test.ts
  asserts the invariant; total tests 173 (was 172).

- Periodic in-process stuck-row sweeper. Runs every 60s, marks
  'streaming' rows older than 5 minutes as 'failed', and publishes
  chat_status='idle' on the user channel so the UI dot drops without a
  refresh. Closes the mid-session crash UX gap; the v1.12.1 boot sweep
  only fires once at startup, so sessions used to stay stuck until next
  reboot. setInterval cleaned up via app.addHook('onClose'). Mirrors
  handleAbortOrError's publish pattern.

- experimental_repairToolCall wired through AI SDK v6 streamText. Pass-
  through implementation: log + return the original toolCall so the
  stream keeps going. executeToolPhase's existing error paths (unknown
  tool name → 'unknown tool: X' result; zod-reject → 'tool X rejected
  — field: required') already surface bad calls to the model; the value
  here is preventing the AI SDK from THROWING on parse errors and
  killing the whole stream. Owed since v1.13.1-A.

Smoke verified:
- statement_timeout = '30s' confirmed via SHOW.
- Tool path normal flow intact (list_dir prompt → tool_call → result
  → final assistant). No malformed tool calls in the test run; repair
  log will surface them when qwen3.6 actually emits one.
- Alpha order verified at runtime via the dist bundle: match: true.
- Sweeper logic not traffic-tested (no stuck rows to find), but the
  SQL UPDATE + broker.publishUser pattern is identical to handleAbort
  and the boot sweep — synthesis-only verification.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

CLAUDE.md

@@ -46,7 +46,9 @@ Tests: `pnpm -C apps/server test` runs the vitest suite. No test harness on `app
 - **Zod** for request validation and config parsing.
 
 Key services:
-- **`services/inference.ts`** — Streams LLM responses, executes tool loops (max depth 15, see `MAX_TOOL_LOOP_DEPTH`), flushes to DB every 500ms. Publishes `InferenceFrame` events through the broker. **`TurnArgs`** is the per-turn state envelope threaded through the `executeToolPhase → runAssistantTurn` recursion (`toolsUsed`, `recentToolCalls`, `assistantMessageId`, `signal`); reset to defaults in `runInference` at the user-message boundary. Cap-hit (`toolsUsed >= budget`) and doom-loop (`detectDoomLoop(recentToolCalls)`) checks both read from this envelope. Add new per-turn state here, not in module-level closures.
+- **`services/inference/`** (v1.12.4 split — was a single `inference.ts` file). Public surface re-exported via `inference/index.ts`; callers import from `./services/inference/index.js`. Layout: `turn.ts` (runAssistantTurn / runInference / createInferenceRunner orchestration, plus `InferenceFrame`, `InferenceContext`, `TurnArgs`, `StreamResult` exported), `stream-phase.ts` (streamCompletion + executeStreamPhase + SSE parsing), `tool-phase.ts` (executeToolPhase; back-edges into turn.ts for the runAssistantTurn recursion — cycle is safe because dereferenced at call time, not module top-level), `sentinel-summaries.ts` (runCapHitSummary + runDoomLoopSummary + their sentinel inserters; two near-clones kept side-by-side until a third sentinel justifies factoring out runWrapUpSummary), `error-handler.ts` (handleAbortOrError, finalizeCompletion), `payload.ts` (buildMessagesPayload, loadContext, maybeFlagForCompaction, `OpenAiMessage`), `sentinels.ts` (`detectDoomLoop`, `DOOM_LOOP_THRESHOLD`, sentinel predicates), `budget.ts` (resolveToolBudget), `xml-parser.ts` (Qwen-coder XML tool-call fallback), `types.ts` (`StreamPhaseState`, `DB_FLUSH_INTERVAL_MS` shared between stream-phase and sentinel-summaries). **`TurnArgs`** is the per-turn state envelope threaded through the `executeToolPhase → runAssistantTurn` recursion (`toolsUsed`, `recentToolCalls`, `assistantMessageId`, `signal`); reset to defaults in `runInference` at the user-message boundary. Cap-hit (`toolsUsed >= budget`) and doom-loop (`detectDoomLoop(recentToolCalls)`) checks both read from this envelope. Add new per-turn state to `TurnArgs` in `turn.ts`, not module-level closures.
+- **`chat_status` frame shape** (published via `broker.publishUser`) — `status: 'streaming' | 'tool_running' | 'waiting_for_input' | 'idle' | 'error'` (widened from `working|idle|error` in v1.12.1). Frontend `useChatStatus` derives `idle_warm` (<30s since idle) vs `idle_cold`. `ChatThroughput` renders inline beside `StatusDot` only when streaming or tool_running, fed by 500ms-throttled `'usage'` WS frames (`completion_tokens` + `ctx_used` + `ctx_max`). The `POST /api/chats/:id/discard_stale` endpoint exists to mark a stuck-streaming row as `failed` when the frontend's 60s no-token-activity timer (`ChatPane` content-length watcher) gives up.
+- **Boot-time stale-streaming sweep** in `apps/server/src/index.ts` after `applySchema()`: any `messages.status='streaming'` older than 5 minutes flips to `'failed'`. Logs only on non-zero count. Recovers from container restart while inference was mid-stream (v1.12.1).
 - **`services/broker.ts`** — In-memory pub/sub with two channel types: per-session (message streaming) and per-user (sidebar updates). No persistence; clients reconnect on restart.
 - **`services/tools.ts`** — Tool registry (`ALL_TOOLS`, `READ_ONLY_TOOL_NAMES`, `TOOLS_BY_NAME`). Filesystem tools (view_file/list_dir/grep/find_files) go through three guard layers: `path_guard.ts` (workspace scope), `secret_guard.ts` (filename deny list), `url_guard.ts` (SSRF/private-IP block for web_fetch). v1.11.8+ web tools (`web_search`, `web_fetch`) are opt-in per chat via `session.web_search_enabled` (resolved with `project.default_web_search_enabled` fallback) and filtered out of the LLM's tool schema when false.
 - **`services/compaction.ts`** + **`services/model-context.ts`** — v1.11.0 anchored rolling summary (single `summary=true` assistant row per chat, supersedes itself on each compaction). Triggered when `chats.needs_compaction` is set after an inference turn exceeds `usable(ctx_max) = ctx_max - 20k`. **`ctx_max` comes from `model-context.getModelContext()` which fetches `${LLAMA_SWAP_URL}/upstream/<model>/props`** — NOT from `parsed.timings.n_ctx` (the stream completion's `timings` doesn't carry n_ctx; that read was dead code until v1.11.3 ripped it out).
@@ -87,15 +89,14 @@ Font / CSS pipeline (apps/web):
 
 ### Multi-pane workspace
 
-Sessions hold 1–5 panes (chat / empty / placeholder terminal+agent). Workspace pane state is **client-side only** (localStorage key `boocode.workspace.panes.<sessionId>`); the legacy `session_panes` table and its REST endpoints are deprecated — no `/api/panes/*` routes exist. Each chat lives in at most one pane; tab strip is per-pane and tracks `chatIds[]` + `activeChatIdx`. Sessions 1:N chats; chats own messages. Tab reorder via native HTML5 drag events.
+Sessions hold 1–5 panes (chat / empty / placeholder terminal+agent). v1.12.1 moved pane state from per-device localStorage to `sessions.workspace_panes jsonb` for cross-device sync. `PATCH /api/sessions/:id/workspace` persists; `session_workspace_updated` user-channel frame broadcasts to every device watching the session. `useWorkspacePanes` debounces saves 300ms and dedups echoes by JSON string. Legacy localStorage key `boocode.workspace.panes.<sessionId>` is read once on first hydrate (one-time seed-and-delete migration when server is empty but localStorage has data); no longer written. The deprecated `session_panes` table was dropped. `validatePanes(validChatIds)` prunes panes referencing chat IDs that no longer exist (called by `useSessionChats` after the chat list fetch lands). Each chat lives in at most one pane; tab strip is per-pane and tracks `chatIds[]` + `activeChatIdx`. Tab reorder via native HTML5 drag events.
 
 ## Database
 
-PostgreSQL 16. Tables: `projects`, `sessions`, `chats`, `messages`, `settings`, `session_panes` (deprecated). Schema applied idempotently on startup via `applySchema()`. Use `clock_timestamp()` (not `NOW()`) inside transactions. CHECK constraints in place: `projects_status_chk` ('open'|'archived'), `sessions_status_chk` (same), `chats_status_chk` (same), `messages_role_chk`, `messages_status_chk` — keep in sync with the `*_STATUSES` const arrays in `apps/server/src/types/api.ts`.
+PostgreSQL 16. Tables: `projects`, `sessions`, `chats`, `messages`, `settings`. (`session_panes` was dropped in v1.12.1; workspace pane state lives in `sessions.workspace_panes jsonb`.) Schema applied idempotently on startup via `applySchema()`. Use `clock_timestamp()` (not `NOW()`) inside transactions. CHECK constraints in place: `projects_status_chk` ('open'|'archived'), `sessions_status_chk` (same), `chats_status_chk` (same), `messages_role_chk`, `messages_status_chk` — keep in sync with the `*_STATUSES` const arrays in `apps/server/src/types/api.ts`. The older anonymous `messages_status_check` (without 'cancelled') and `messages_role_check` (without 'system') were dropped in v1.12.1; only the `_chk` variants remain.
 
 Schema CHECK migration order when renaming allowed values: (1) `ALTER TABLE ... DROP CONSTRAINT IF EXISTS <system_name>` (inline `CREATE TABLE` checks get `<table>_<column>_check`), (2) `UPDATE` rows to new values, (3) wrap new constraint ADD in `DO $$ ... pg_constraint` guard — that block is the only way to get `ADD CONSTRAINT IF NOT EXISTS`.
 
-Position-shift pattern for panes (legacy `session_panes` table): negate-and-restore to avoid UNIQUE(session_id, position) collisions during reorder/insert/delete. Sentinel value -100 for the moving pane.
 
 ## Environment
 
@@ -125,6 +126,7 @@ Required: `DATABASE_URL`, `LLAMA_SWAP_URL`. Optional: `PORT` (3000), `HOST` (0.0
 - TypeScript strict mode. Both apps share `tsconfig.base.json`.
 - Server uses NodeNext module resolution (`.js` extensions in imports).
 - Discriminated unions for type narrowing: `Pane` (by `kind`), `SessionEvent` (by `type`), `InferenceFrame` (by `type`).
+- **Adding a new WS frame type** requires updating BOTH the server's `InferenceFrame` (loose `type:` union + optional fields in `services/inference/turn.ts`) AND the web `WsFrame` (strict discriminated union in `apps/web/src/api/types.ts`). Server publish is permissive; the frontend type is the wire-format gate. The `'usage'` frame added in v1.12.2 needed both sides; missing the web side silently drops the frame at JSON-parse.
 - shadcn primitives live in `components/ui/`. Don't modify them unless adding a new primitive.
 - `inferLanguage()` from `lib/attachments.ts` is the canonical file-extension-to-language map. `CodeBlock.tsx` keeps its own `LANG_MAP` because it also resolves markdown fence names.
 - Two UI event buses: `hooks/sessionEvents.ts` for DB-state events (chat_created, session_updated); `lib/events.ts` for ephemeral UI (`sendToTerminal`, `terminalsRegistry`). Don't merge — different subscriber lifecycles.

apps/server/package.json

@@ -11,8 +11,10 @@
     "test": "vitest run"
   },
   "dependencies": {
+    "@ai-sdk/openai-compatible": "^2.0.47",
     "@fastify/static": "^7.0.4",
     "@fastify/websocket": "^10.0.1",
+    "ai": "^6.0.190",
     "fastify": "^4.28.1",
     "postgres": "^3.4.4",
     "ws": "^8.18.0",

apps/server/src/index.ts

@@ -201,6 +201,46 @@ async function main() {
     app.log.info(`serving static frontend from ${webDist}`);
   }
 
+  // v1.13.3: periodic in-process sweeper for streaming rows orphaned by a
+  // mid-session crash. The boot sweep (above) only fires once at startup;
+  // this loop catches the in-flight case. 60s cadence + 5-min threshold
+  // matches the boot sweep so behavior is consistent. Publishes
+  // chat_status='idle' on the user channel so the UI dot drops without a
+  // refresh — same pattern as handleAbortOrError.
+  const SWEEP_INTERVAL_MS = 60_000;
+  const sweepStaleStreaming = async (): Promise<void> => {
+    try {
+      const rows = await sql<{ id: string; chat_id: string }[]>`
+        UPDATE messages
+        SET status = 'failed', finished_at = clock_timestamp()
+        WHERE status = 'streaming'
+          AND created_at < NOW() - INTERVAL '5 minutes'
+        RETURNING id, chat_id
+      `;
+      if (rows.length === 0) return;
+      app.log.warn(
+        { swept: rows.length, ids: rows.map((r) => r.id) },
+        'swept stale streaming rows',
+      );
+      const seenChats = new Set<string>();
+      const now = new Date().toISOString();
+      for (const row of rows) {
+        if (seenChats.has(row.chat_id)) continue;
+        seenChats.add(row.chat_id);
+        broker.publishUser('default', {
+          type: 'chat_status',
+          chat_id: row.chat_id,
+          status: 'idle',
+          at: now,
+        });
+      }
+    } catch (err) {
+      app.log.error({ err }, 'stuck-row sweeper failed');
+    }
+  };
+  const sweepTimer = setInterval(() => { void sweepStaleStreaming(); }, SWEEP_INTERVAL_MS);
+  app.addHook('onClose', async () => { clearInterval(sweepTimer); });
+
   const shutdown = async (signal: string) => {
     app.log.info(`received ${signal}, shutting down`);
     try {

apps/server/src/routes/chats.ts

@@ -313,6 +313,28 @@ export function registerChatRoutes(
             AND created_at <= ${target.created_at}::timestamptz
             AND status = 'complete'
         `;
+        // v1.13.0: clone message_parts for the forked messages. Source and
+        // destination preserve ordering (the INSERT above orders by created_at,
+        // id) so a ROW_NUMBER pairing maps source.id → dest.id deterministically.
+        await tx`
+          WITH src AS (
+            SELECT id, ROW_NUMBER() OVER (ORDER BY created_at ASC, id ASC) AS rn
+            FROM messages
+            WHERE chat_id = ${source.id}
+              AND created_at <= ${target.created_at}::timestamptz
+              AND status = 'complete'
+          ),
+          dst AS (
+            SELECT id, ROW_NUMBER() OVER (ORDER BY created_at ASC, id ASC) AS rn
+            FROM messages
+            WHERE chat_id = ${chat!.id}
+          )
+          INSERT INTO message_parts (message_id, sequence, kind, payload)
+          SELECT dst.id, p.sequence, p.kind, p.payload
+          FROM message_parts p
+          JOIN src ON p.message_id = src.id
+          JOIN dst ON dst.rn = src.rn
+        `;
         return chat!;
       });
 
@@ -401,11 +423,12 @@ export function registerChatRoutes(
         reply.code(404);
         return { error: 'chat not found' };
       }
+      // v1.13.1-B: reads tool_calls/tool_results via the parts-merged view.
       const rows = await sql<Message[]>`
         SELECT id, session_id, chat_id, role, content, kind, tool_calls, tool_results, status, last_seq,
                tokens_used, ctx_used, ctx_max, started_at, finished_at, created_at, metadata,
                summary, tail_start_id, compacted_at
-        FROM messages
+        FROM messages_with_parts
         WHERE chat_id = ${req.params.id}
         ORDER BY created_at ASC, id ASC
       `;

apps/server/src/routes/messages.ts

@@ -91,11 +91,12 @@ export function registerMessageRoutes(
       // SummaryCard) and shows compacted_at-stamped rows inline for context.
       // Internal inference assembly filters compacted_at IS NULL separately —
       // see services/inference.ts loadContext + services/compaction.ts.
+      // v1.13.1-B: reads tool_calls/tool_results via the parts-merged view.
       const rows = await sql<Message[]>`
         SELECT id, session_id, chat_id, role, content, kind, tool_calls, tool_results, status, last_seq,
                tokens_used, ctx_used, ctx_max, started_at, finished_at, created_at, metadata,
                summary, tail_start_id, compacted_at
-        FROM messages
+        FROM messages_with_parts
         WHERE session_id = ${req.params.id}
         ORDER BY created_at ASC, id ASC
       `;
@@ -469,30 +470,36 @@ export function registerMessageRoutes(
       const chat = chatRows[0]!;
       const sessionId = chat.session_id;
 
-      // Find the assistant message that emitted this tool_call. Scoped by
-      // chat_id + role to avoid cross-chat lookups; ordered by created_at DESC
-      // because the most recent issuance wins when an LLM reuses call IDs
-      // across turns (the older, already-answered one is a different row with
-      // populated tool_results downstream).
-      const callerRows = await sql<{ id: string; tool_calls: ToolCall[] | null }[]>`
-        SELECT id, tool_calls FROM messages
-        WHERE chat_id = ${chat.id}
-          AND role = 'assistant'
-          AND tool_calls IS NOT NULL
-        ORDER BY created_at DESC
+      // v1.13.1-C: find the assistant's tool_call by indexing message_parts
+      // directly on payload->>'id'. Scoped by chat_id + role via the JOIN.
+      // Pre-v1.13.0 history has no parts rows — those tool_calls become
+      // unreachable here (404). Acceptable per the dispatch decision: any
+      // pending elicitation from before v1.13.0 is long timed out by now;
+      // promote to a hotfix with a JSON-column fallback if it ever surfaces.
+      const callerRows = await sql<{
+        message_id: string;
+        payload: { id: string; name: string; args: Record<string, unknown> };
+      }[]>`
+        SELECT p.message_id, p.payload
+        FROM message_parts p
+        JOIN messages m ON m.id = p.message_id
+        WHERE m.chat_id = ${chat.id}
+          AND m.role = 'assistant'
+          AND p.kind = 'tool_call'
+          AND p.payload->>'id' = ${tool_call_id}
+        ORDER BY m.created_at DESC
+        LIMIT 1
       `;
-      let foundCall: ToolCall | null = null;
-      for (const row of callerRows) {
-        const match = row.tool_calls?.find((tc) => tc.id === tool_call_id);
-        if (match) {
-          foundCall = match;
-          break;
-        }
-      }
-      if (!foundCall) {
+      const callerRow = callerRows[0];
+      if (!callerRow) {
         reply.code(404);
         return { error: 'unknown_tool_call_id' };
       }
+      const foundCall: ToolCall = {
+        id: callerRow.payload.id,
+        name: callerRow.payload.name,
+        args: callerRow.payload.args,
+      };
       if (foundCall.name !== 'ask_user_input') {
         reply.code(400);
         return { error: 'tool_call_not_ask_user_input' };
@@ -539,18 +546,21 @@ export function registerMessageRoutes(
         }
       }
 
-      // Find the pending tool row. ORDER BY created_at DESC + LIMIT 1 picks
-      // the most recent row with this tool_call_id; the already-answered
-      // check below guards against UPDATE-ing a stale answer.
+      // v1.13.1-C: find the pending tool row via message_parts on
+      // payload->>'tool_call_id'. Same fallback caveat as the caller lookup
+      // above — pre-v1.13.0 rows are unreachable here.
       const toolRows = await sql<{
-        id: string;
-        tool_results: { tool_call_id: string; output: unknown } | null;
+        message_id: string;
+        payload: { tool_call_id: string; output: unknown };
       }[]>`
-        SELECT id, tool_results FROM messages
-        WHERE chat_id = ${chat.id}
-          AND role = 'tool'
-          AND tool_results->>'tool_call_id' = ${tool_call_id}
-        ORDER BY created_at DESC
+        SELECT p.message_id, p.payload
+        FROM message_parts p
+        JOIN messages m ON m.id = p.message_id
+        WHERE m.chat_id = ${chat.id}
+          AND m.role = 'tool'
+          AND p.kind = 'tool_result'
+          AND p.payload->>'tool_call_id' = ${tool_call_id}
+        ORDER BY m.created_at DESC
         LIMIT 1
       `;
       const toolRow = toolRows[0];
@@ -558,7 +568,7 @@ export function registerMessageRoutes(
         reply.code(404);
         return { error: 'unknown_tool_call_id', detail: 'tool message not found' };
       }
-      if (toolRow.tool_results && toolRow.tool_results.output !== null) {
+      if (toolRow.payload && toolRow.payload.output !== null) {
         reply.code(409);
         return { error: 'tool_call_already_answered' };
       }
@@ -570,11 +580,21 @@ export function registerMessageRoutes(
         truncated: false,
       };
 
+      const toolMessageId = toolRow.message_id;
       const result = await sql.begin(async (tx) => {
         await tx`
           UPDATE messages
           SET tool_results = ${tx.json(newToolResults as never)}
-          WHERE id = ${toolRow.id}
+          WHERE id = ${toolMessageId}
+        `;
+        // v1.13.0: replace the pending tool_result part inserted at message
+        // creation (tool-phase.ts) with the answered one. Delete-then-insert
+        // is simpler than UPDATE because parts are append-style elsewhere;
+        // the UNIQUE (message_id, sequence) constraint blocks plain insert.
+        await tx`DELETE FROM message_parts WHERE message_id = ${toolMessageId} AND kind = 'tool_result'`;
+        await tx`
+          INSERT INTO message_parts (message_id, sequence, kind, payload)
+          VALUES (${toolMessageId}, 0, 'tool_result', ${tx.json(newToolResults as never)})
         `;
         const [assistantMsg] = await tx<{ id: string }[]>`
           INSERT INTO messages (session_id, chat_id, role, content, status, created_at)
@@ -584,7 +604,7 @@ export function registerMessageRoutes(
         await tx`UPDATE sessions SET updated_at = clock_timestamp() WHERE id = ${sessionId}`;
         await tx`UPDATE chats SET updated_at = clock_timestamp() WHERE id = ${chat.id}`;
         return {
-          tool_message_id: toolRow.id,
+          tool_message_id: toolMessageId,
           assistant_message_id: assistantMsg!.id,
         };
       });

apps/server/src/routes/skills.ts

@@ -90,11 +90,26 @@ export function registerSkillsRoutes(
           VALUES (${sessionId}, ${chat.id}, 'assistant', '', ${sql.json(toolCalls as never)}, 'complete', clock_timestamp())
           RETURNING id
         `;
+        // v1.13.0: dual-write the synthetic assistant message's tool_call.
+        // Single skill_use tool_call, no text content, so one part at seq 0.
+        await tx`
+          INSERT INTO message_parts (message_id, sequence, kind, payload)
+          VALUES (${synthAssistant!.id}, 0, 'tool_call', ${tx.json({
+            id: toolCallId,
+            name: 'skill_use',
+            args: { name: skill_name },
+          } as never)})
+        `;
         const [toolMsg] = await tx<{ id: string }[]>`
           INSERT INTO messages (session_id, chat_id, role, content, tool_results, status, created_at)
           VALUES (${sessionId}, ${chat.id}, 'tool', '', ${sql.json(toolResults as never)}, 'complete', clock_timestamp())
           RETURNING id
         `;
+        // v1.13.0: dual-write the synthetic tool result (the skill body).
+        await tx`
+          INSERT INTO message_parts (message_id, sequence, kind, payload)
+          VALUES (${toolMsg!.id}, 0, 'tool_result', ${tx.json(toolResults as never)})
+        `;
         const [userMsg] = await tx<{ id: string }[]>`
           INSERT INTO messages (session_id, chat_id, role, content, status, created_at)
           VALUES (${sessionId}, ${chat.id}, 'user', ${userText}, 'complete', clock_timestamp())

apps/server/src/routes/ws.ts

@@ -23,11 +23,12 @@ export function registerWebSocket(
 
       // v1.11: snapshot includes compaction fields so MessageBubble can
       // render the SummaryCard for summary=true rows on first connect.
+      // v1.13.1-B: reads tool_calls/tool_results via the parts-merged view.
       const messages = await sql<Message[]>`
         SELECT id, session_id, chat_id, role, content, kind, tool_calls, tool_results, status, last_seq,
                tokens_used, ctx_used, ctx_max, started_at, finished_at, created_at, metadata,
                summary, tail_start_id, compacted_at
-        FROM messages
+        FROM messages_with_parts
         WHERE session_id = ${sessionId}
         ORDER BY created_at ASC, id ASC
       `;

apps/server/src/schema.sql

@@ -1,3 +1,10 @@
+-- v1.13.3: statement_timeout is set at database level via:
+--   ALTER DATABASE boocode SET statement_timeout = '30s';
+-- ALTER DATABASE can't run inside a DO block, so this is an operational
+-- step rather than schema. Re-apply after a volume reset (the setting
+-- lives in pg_db which survives `docker compose up --build` but NOT a
+-- `docker volume rm boocode_pgdata`).
+
 CREATE TABLE IF NOT EXISTS projects (
   id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
   name TEXT NOT NULL,
@@ -32,6 +39,59 @@ CREATE TABLE IF NOT EXISTS messages (
 
 CREATE INDEX IF NOT EXISTS idx_messages_session ON messages(session_id, created_at);
 
+-- v1.13.0: granular message parts table for AI SDK migration. Old
+-- messages.content / tool_calls / tool_results columns stay authoritative
+-- for reads in v1.13.0; this table is dual-written so the swap can happen
+-- in a later dispatch without a backfill window. ON DELETE CASCADE means
+-- removing a message removes its parts in one go.
+CREATE TABLE IF NOT EXISTS message_parts (
+  id uuid PRIMARY KEY DEFAULT gen_random_uuid(),
+  message_id uuid NOT NULL REFERENCES messages(id) ON DELETE CASCADE,
+  sequence int NOT NULL,
+  kind text NOT NULL,
+  payload jsonb NOT NULL,
+  created_at timestamptz NOT NULL DEFAULT clock_timestamp(),
+  CONSTRAINT message_parts_kind_chk CHECK (kind IN ('text', 'tool_call', 'tool_result', 'reasoning', 'step_start')),
+  CONSTRAINT message_parts_seq_uniq UNIQUE (message_id, sequence)
+);
+CREATE INDEX IF NOT EXISTS message_parts_msg_seq_idx ON message_parts (message_id, sequence);
+
+-- v1.13.1-B: read-path view. Read sites SELECT FROM messages_with_parts
+-- instead of messages so tool_calls / tool_results / reasoning_parts come
+-- from the granular message_parts table. The COALESCE means pre-v1.13.0
+-- history (no parts rows) still resolves via the legacy JSON columns; the
+-- dual-write from v1.13.0 keeps both in sync for all rows written since.
+-- Writes continue to target `messages` directly — the view is read-only.
+-- Shapes match the in-memory ToolCall / ToolResult types: tool_calls is a
+-- jsonb array of {id, name, args}, tool_results is a single jsonb object
+-- {tool_call_id, output, truncated, error?}. reasoning_parts is new — only
+-- consumed by the inference history fetch (payload.ts) so v1.13.1-C can
+-- wire reasoning into the model payload. Not surfaced in external APIs yet.
+CREATE OR REPLACE VIEW messages_with_parts AS
+SELECT
+  m.id, m.session_id, m.chat_id, m.role, m.content, m.kind, m.status,
+  m.last_seq, m.tokens_used, m.ctx_used, m.ctx_max,
+  m.started_at, m.finished_at, m.created_at, m.metadata,
+  m.summary, m.tail_start_id, m.compacted_at,
+  COALESCE(
+    (SELECT jsonb_agg(p.payload ORDER BY p.sequence)
+       FROM message_parts p
+      WHERE p.message_id = m.id AND p.kind = 'tool_call'),
+    m.tool_calls
+  ) AS tool_calls,
+  COALESCE(
+    (SELECT p.payload
+       FROM message_parts p
+      WHERE p.message_id = m.id AND p.kind = 'tool_result'
+      ORDER BY p.sequence
+      LIMIT 1),
+    m.tool_results
+  ) AS tool_results,
+  (SELECT jsonb_agg(p.payload ORDER BY p.sequence)
+     FROM message_parts p
+    WHERE p.message_id = m.id AND p.kind = 'reasoning') AS reasoning_parts
+FROM messages m;
+
 ALTER TABLE messages ADD COLUMN IF NOT EXISTS tokens_used INTEGER;
 ALTER TABLE messages ADD COLUMN IF NOT EXISTS ctx_used INTEGER;
 ALTER TABLE messages ADD COLUMN IF NOT EXISTS ctx_max INTEGER;

apps/server/src/services/__tests__/parts.test.ts

@@ -0,0 +1,121 @@
+import { describe, it, expect } from 'vitest';
+import { partsFromAssistantMessage, partsFromToolMessage } from '../inference/parts.js';
+import type { ToolCall, ToolResult } from '../../types/api.js';
+
+describe('partsFromAssistantMessage', () => {
+  it('emits one text part for content-only assistant', () => {
+    const parts = partsFromAssistantMessage({ content: 'hello world', tool_calls: null });
+    expect(parts).toHaveLength(1);
+    expect(parts[0]).toEqual({
+      sequence: 0,
+      kind: 'text',
+      payload: { text: 'hello world' },
+    });
+  });
+
+  it('emits one tool_call part for empty-content + single tool_call', () => {
+    const tc: ToolCall = { id: 'call_1', name: 'view_file', args: { path: 'src/a.ts' } };
+    const parts = partsFromAssistantMessage({ content: '', tool_calls: [tc] });
+    expect(parts).toHaveLength(1);
+    expect(parts[0]).toEqual({
+      sequence: 0,
+      kind: 'tool_call',
+      payload: { id: 'call_1', name: 'view_file', args: { path: 'src/a.ts' } },
+    });
+  });
+
+  it('emits text then tool_call parts in order when both present', () => {
+    const tc: ToolCall = { id: 'call_2', name: 'grep', args: { pattern: 'foo' } };
+    const parts = partsFromAssistantMessage({ content: 'let me search', tool_calls: [tc] });
+    expect(parts.map((p) => [p.sequence, p.kind])).toEqual([
+      [0, 'text'],
+      [1, 'tool_call'],
+    ]);
+  });
+
+  it('preserves tool_call order with multiple calls', () => {
+    const calls: ToolCall[] = [
+      { id: 'a', name: 'list_dir', args: { path: '.' } },
+      { id: 'b', name: 'view_file', args: { path: 'x.ts' } },
+      { id: 'c', name: 'grep', args: { pattern: 'y' } },
+    ];
+    const parts = partsFromAssistantMessage({ content: '', tool_calls: calls });
+    expect(parts).toHaveLength(3);
+    expect(parts.map((p) => p.payload)).toEqual([
+      { id: 'a', name: 'list_dir', args: { path: '.' } },
+      { id: 'b', name: 'view_file', args: { path: 'x.ts' } },
+      { id: 'c', name: 'grep', args: { pattern: 'y' } },
+    ]);
+    expect(parts.map((p) => p.sequence)).toEqual([0, 1, 2]);
+  });
+
+  it('returns empty array for empty content + null tool_calls', () => {
+    expect(partsFromAssistantMessage({ content: '', tool_calls: null })).toEqual([]);
+  });
+
+  it('v1.13.1-C: reasoning lands at sequence 0 before text + tool_calls', () => {
+    const tc: ToolCall = { id: 'call_r', name: 'view_file', args: { path: 'x.ts' } };
+    const parts = partsFromAssistantMessage({
+      content: 'inspecting now',
+      tool_calls: [tc],
+      reasoning: 'user asked about x.ts; I should view it',
+    });
+    expect(parts.map((p) => [p.sequence, p.kind])).toEqual([
+      [0, 'reasoning'],
+      [1, 'text'],
+      [2, 'tool_call'],
+    ]);
+    expect(parts[0]!.payload).toEqual({
+      text: 'user asked about x.ts; I should view it',
+    });
+  });
+
+  it('v1.13.1-C: reasoning + empty content + tool_calls preserves seq 0 reasoning', () => {
+    const tc: ToolCall = { id: 'call_r2', name: 'grep', args: { pattern: 'foo' } };
+    const parts = partsFromAssistantMessage({
+      content: '',
+      tool_calls: [tc],
+      reasoning: 'jumping straight to grep',
+    });
+    expect(parts.map((p) => [p.sequence, p.kind])).toEqual([
+      [0, 'reasoning'],
+      [1, 'tool_call'],
+    ]);
+  });
+});
+
+describe('partsFromToolMessage', () => {
+  it('emits a single tool_result part at sequence 0', () => {
+    const tr: ToolResult = {
+      tool_call_id: 'call_1',
+      output: { contents: 'console.log(1)' },
+      truncated: false,
+    };
+    const parts = partsFromToolMessage({ tool_results: tr });
+    expect(parts).toHaveLength(1);
+    expect(parts[0]).toEqual({
+      sequence: 0,
+      kind: 'tool_result',
+      payload: {
+        tool_call_id: 'call_1',
+        output: { contents: 'console.log(1)' },
+        truncated: false,
+      },
+    });
+  });
+
+  it('includes error in payload when present', () => {
+    const tr: ToolResult = {
+      tool_call_id: 'call_2',
+      output: null,
+      truncated: false,
+      error: 'permission denied',
+    };
+    const parts = partsFromToolMessage({ tool_results: tr });
+    expect(parts[0]!.payload).toMatchObject({ error: 'permission denied' });
+  });
+
+  it('returns empty array when tool_results is null', () => {
+    expect(partsFromToolMessage({ tool_results: null })).toEqual([]);
+  });
+});

apps/server/src/services/__tests__/tools.test.ts

@@ -0,0 +1,14 @@
+import { describe, it, expect } from 'vitest';
+import { ALL_TOOLS } from '../tools.js';
+
+describe('ALL_TOOLS registry', () => {
+  // v1.13.3: tools must be alpha-sorted at module load. llama.cpp's prompt
+  // cache hits on byte-identical prefixes; the tool list lives near the
+  // top of the system prompt, so any order drift invalidates every cached
+  // turn. The registry sort is the single source of truth; downstream
+  // helpers (toolJsonSchemas, TOOLS_BY_NAME, buildAiTools) inherit it.
+  it('exports tools in alphabetical order by name', () => {
+    const names = ALL_TOOLS.map((t) => t.name);
+    expect(names).toEqual([...names].sort((a, b) => a.localeCompare(b)));
+  });
+});

apps/server/src/services/compaction.ts

@@ -342,9 +342,11 @@ export async function process(input: ProcessInput): Promise<void> {
   // 2. All currently-active messages in this chat (compacted_at IS NULL).
   // ORDER BY (created_at, id) matches loadContext in inference.ts so the
   // turns() boundary logic sees the same sequence the LLM will.
+  // v1.13.1-B: reads tool_calls/tool_results via the parts-merged view so
+  // the compaction payload matches what the LLM saw on the original turn.
   const messages = await sql<CompactionMessage[]>`
     SELECT id, role, content, kind, summary, status, tool_calls, tool_results, metadata, created_at
-    FROM messages
+    FROM messages_with_parts
     WHERE chat_id = ${chatId} AND compacted_at IS NULL
     ORDER BY created_at ASC, id ASC
   `;

apps/server/src/services/inference/error-handler.ts

@@ -1,6 +1,7 @@
 import type { MessageMetadata, Session } from '../../types/api.js';
 import * as modelContext from '../model-context.js';
 import { maybeFlagForCompaction } from './payload.js';
+import { insertParts, partsFromAssistantMessage } from './parts.js';
 import type { InferenceContext, StreamResult, TurnArgs } from './turn.js';
 
 export async function handleAbortOrError(
@@ -112,6 +113,24 @@ export async function finalizeCompletion(
     WHERE id = ${assistantMessageId}
     RETURNING tokens_used, ctx_used, ctx_max, finished_at
   `;
+  // v1.13.0: dual-write the text part. finalizeCompletion is the terminal
+  // path for text-only assistant turns (no tool calls); tool_calls are null
+  // here by construction (the tool-bearing path goes through executeToolPhase).
+  // v1.13.1-C: include result.reasoning so reasoning-channel models capture
+  // a kind='reasoning' part alongside the text.
+  // TODO(v1.13.1): wrap the UPDATE above and this insertParts in a single
+  // sql.begin before flipping read authority to message_parts.
+  await insertParts(
+    ctx.sql,
+    partsFromAssistantMessage({
+      content,
+      tool_calls: null,
+      reasoning: result.reasoning,
+    }).map((p) => ({
+      ...p,
+      message_id: assistantMessageId,
+    })),
+  );
   // v1.11: flag for compaction on the terminal turn too. Catches the common
   // case of a turn that hit the limit without invoking tools.
   await maybeFlagForCompaction(ctx, chatId, updated);

apps/server/src/services/inference/parts.ts

@@ -0,0 +1,95 @@
+import type { Sql } from '../../db.js';
+import type { ToolCall, ToolResult } from '../../types/api.js';
+
+// v1.13.0: dual-write helper. Every site that writes the legacy
+// messages.tool_calls / messages.tool_results JSON columns calls into here
+// to mirror the same data into message_parts rows. Reads still go to the
+// JSON columns; the swap to parts-as-source-of-truth happens in a later
+// v1.13 dispatch alongside the AI SDK streamText migration.
+
+export type PartKind = 'text' | 'tool_call' | 'tool_result' | 'reasoning' | 'step_start';
+
+export interface PartInsert {
+  message_id: string;
+  sequence: number;
+  kind: PartKind;
+  payload: unknown;
+}
+
+export async function insertParts(sql: Sql, parts: PartInsert[]): Promise<void> {
+  if (parts.length === 0) return;
+  // postgres-js fans out an array of objects to a multi-row INSERT. Each
+  // payload field needs sql.json() so jsonb storage receives a JSON value
+  // rather than a quoted string.
+  await sql`
+    INSERT INTO message_parts ${sql(
+      parts.map((p) => ({
+        message_id: p.message_id,
+        sequence: p.sequence,
+        kind: p.kind,
+        payload: sql.json(p.payload as never),
+      })),
+      'message_id',
+      'sequence',
+      'kind',
+      'payload',
+    )}
+  `;
+}
+
+// Derive parts from the canonical messages row for an assistant message.
+// reasoning (when non-empty) becomes a 'reasoning' part at sequence 0 —
+// it precedes user-visible content logically. content (when non-empty)
+// becomes a 'text' part next; each tool_call becomes a 'tool_call' part
+// with payload { id, name, args } where args is the parsed object (we
+// use the in-memory ToolCall shape, not the OpenAI stringified one).
+export function partsFromAssistantMessage(args: {
+  content: string;
+  tool_calls: ToolCall[] | null;
+  // v1.13.1-C: optional reasoning text streamed alongside the answer.
+  // Most rows have none — only models with separate reasoning channels
+  // (qwen3.6 etc.) populate this.
+  reasoning?: string;
+}): Omit<PartInsert, 'message_id'>[] {
+  const out: Omit<PartInsert, 'message_id'>[] = [];
+  let seq = 0;
+  if (args.reasoning && args.reasoning.length > 0) {
+    out.push({ sequence: seq, kind: 'reasoning', payload: { text: args.reasoning } });
+    seq += 1;
+  }
+  if (args.content && args.content.length > 0) {
+    out.push({ sequence: seq, kind: 'text', payload: { text: args.content } });
+    seq += 1;
+  }
+  for (const tc of args.tool_calls ?? []) {
+    out.push({
+      sequence: seq,
+      kind: 'tool_call',
+      payload: { id: tc.id, name: tc.name, args: tc.args },
+    });
+    seq += 1;
+  }
+  return out;
+}
+
+// Derive a single tool_result part from a tool message's tool_results JSON.
+// The payload includes the same shape that buildMessagesPayload reads from
+// later: tool_call_id, output, optional error/truncated metadata.
+export function partsFromToolMessage(args: {
+  tool_results: ToolResult | null;
+}): Omit<PartInsert, 'message_id'>[] {
+  if (!args.tool_results) return [];
+  const tr = args.tool_results;
+  return [
+    {
+      sequence: 0,
+      kind: 'tool_result',
+      payload: {
+        tool_call_id: tr.tool_call_id,
+        output: tr.output,
+        truncated: tr.truncated,
+        ...(tr.error ? { error: tr.error } : {}),
+      },
+    },
+  ];
+}

apps/server/src/services/inference/payload.ts

@@ -19,6 +19,12 @@ export interface OpenAiMessage {
     function: { name: string; arguments: string };
   }>;
   tool_call_id?: string;
+  // v1.13.1-C: reasoning text from a prior assistant turn, sourced from
+  // message_parts kind='reasoning' rows joined in via reasoning_parts on
+  // the messages_with_parts view. stream-phase.ts/toModelMessages threads
+  // this into the AI SDK ReasoningPart when forwarding to the model so
+  // reasoning models can resume mid-thought across tool-call boundaries.
+  reasoning?: string;
 }
 
 // v1.12: buildSystemPrompt lives in services/system-prompt.ts. It awaits the
@@ -83,6 +89,12 @@ export async function buildMessagesPayload(
           function: { name: tc.name, arguments: JSON.stringify(tc.args) },
         }));
       }
+      // v1.13.1-C: collapse reasoning_parts into a single string. The view
+      // returns them ordered by sequence; multiple reasoning parts on one
+      // message are rare but concat preserves ordering. Skip when absent.
+      if (m.reasoning_parts && m.reasoning_parts.length > 0) {
+        msg.reasoning = m.reasoning_parts.map((p) => p.text ?? '').join('');
+      }
       out.push(msg);
       continue;
     }
@@ -116,10 +128,14 @@ export async function loadContext(
   // /api/sessions/:id/messages endpoint still returns everything (so the UI
   // can show history with the summary card inline); only LLM payloads skip
   // compacted rows. compacted_at IS NULL keeps the active summary + tail.
+  // v1.13.1-B: reads tool_calls/tool_results via the parts-merged view.
+  // v1.13.1-C: also pull reasoning_parts so assistant messages from
+  // reasoning models can be replayed with their reasoning context preserved.
   const history = await sql<Message[]>`
     SELECT id, session_id, chat_id, role, content, kind, tool_calls, tool_results, status, last_seq,
-           tokens_used, ctx_used, ctx_max, started_at, finished_at, created_at, metadata
-    FROM messages
+           tokens_used, ctx_used, ctx_max, started_at, finished_at, created_at, metadata,
+           reasoning_parts
+    FROM messages_with_parts
     WHERE chat_id = ${chatId} AND compacted_at IS NULL
     ORDER BY created_at ASC, id ASC
   `;

apps/server/src/services/inference/provider.ts

@@ -0,0 +1,26 @@
+import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
+import type { LanguageModel } from 'ai';
+
+// v1.13.1-A: AI SDK provider against llama-swap. baseURL is threaded from
+// config.LLAMA_SWAP_URL at call time (not module-load) so tests can stub the
+// upstream without touching env vars. No apiKey — llama-swap is unauth in our
+// Tailscale topology and exposing it over the public internet is gated by
+// Authelia at the Caddy layer, not by API keys.
+
+const cache = new Map<string, ReturnType<typeof createOpenAICompatible>>();
+
+function getProvider(baseURL: string): ReturnType<typeof createOpenAICompatible> {
+  let provider = cache.get(baseURL);
+  if (!provider) {
+    provider = createOpenAICompatible({
+      name: 'llama-swap',
+      baseURL: baseURL.endsWith('/v1') ? baseURL : `${baseURL}/v1`,
+    });
+    cache.set(baseURL, provider);
+  }
+  return provider;
+}
+
+export function upstreamModel(baseURL: string, modelId: string): LanguageModel {
+  return getProvider(baseURL).chatModel(modelId);
+}

apps/server/src/services/inference/stream-phase.ts

@@ -18,29 +18,15 @@ import type {
   StreamResult,
   TurnArgs,
 } from './turn.js';
-
-interface ChatCompletionDelta {
-  role?: string;
-  content?: string | null;
-  tool_calls?: Array<{
-    index: number;
-    id?: string;
-    type?: 'function';
-    function?: { name?: string; arguments?: string };
-  }>;
-}
-
-interface ChatCompletionChunk {
-  choices?: Array<{
-    delta: ChatCompletionDelta;
-    finish_reason: string | null;
-  }>;
-  usage?: {
-    prompt_tokens?: number;
-    completion_tokens?: number;
-    total_tokens?: number;
-  };
-}
+import { upstreamModel } from './provider.js';
+import {
+  jsonSchema,
+  streamText,
+  tool,
+  type JSONValue,
+  type ModelMessage,
+  type ToolCallRepairFunction,
+} from 'ai';
 
 interface StreamOptions {
   // null = omit tools entirely (compact phase); [] = caller stripped all tools
@@ -49,44 +35,113 @@ interface StreamOptions {
   temperature?: number;
 }
 
-async function* sseLines(stream: ReadableStream<Uint8Array>): AsyncGenerator<string> {
-  const reader = stream.getReader();
-  const decoder = new TextDecoder('utf-8');
-  let buffer = '';
-  try {
-    while (true) {
-      const { value, done } = await reader.read();
-      if (done) break;
-      buffer += decoder.decode(value, { stream: true });
-      let idx;
-      while ((idx = buffer.indexOf('\n')) >= 0) {
-        const line = buffer.slice(0, idx).replace(/\r$/, '');
-        buffer = buffer.slice(idx + 1);
-        if (line.length === 0) continue;
-        yield line;
+// v1.13.1-A: convert BooCode's OpenAI-shaped history into AI SDK
+// ModelMessage[]. Tool result messages need a `toolName` field that the
+// OpenAI shape doesn't carry; we look it up by scanning earlier assistant
+// `tool_calls` entries for a matching id.
+function toModelMessages(messages: OpenAiMessage[]): ModelMessage[] {
+  const toolNameById = new Map<string, string>();
+  for (const m of messages) {
+    if (m.role === 'assistant' && m.tool_calls) {
+      for (const tc of m.tool_calls) {
+        toolNameById.set(tc.id, tc.function.name);
       }
     }
-    if (buffer.length > 0) yield buffer;
-  } finally {
-    reader.releaseLock();
   }
+  const out: ModelMessage[] = [];
+  for (const m of messages) {
+    if (m.role === 'system' || m.role === 'user') {
+      out.push({ role: m.role, content: m.content ?? '' });
+      continue;
+    }
+    if (m.role === 'assistant') {
+      const hasTools = m.tool_calls && m.tool_calls.length > 0;
+      const hasReasoning = typeof m.reasoning === 'string' && m.reasoning.length > 0;
+      if (!hasTools && !hasReasoning) {
+        // Bare text assistant (string content). null content + no tool_calls
+        // is degenerate but harmless to forward.
+        out.push({ role: 'assistant', content: m.content ?? '' });
+        continue;
+      }
+      // v1.13.1-C: AI SDK ReasoningPart precedes text + tool-calls in the
+      // assistant content array. Reasoning models (qwen3.6) consume their
+      // prior reasoning context to resume mid-thought across tool boundaries.
+      const parts: Array<
+        | { type: 'reasoning'; text: string }
+        | { type: 'text'; text: string }
+        | { type: 'tool-call'; toolCallId: string; toolName: string; input: unknown }
+      > = [];
+      if (hasReasoning) {
+        parts.push({ type: 'reasoning', text: m.reasoning! });
+      }
+      if (m.content && m.content.length > 0) {
+        parts.push({ type: 'text', text: m.content });
+      }
+      for (const tc of m.tool_calls ?? []) {
+        let input: unknown = {};
+        try {
+          input = tc.function.arguments.length > 0 ? JSON.parse(tc.function.arguments) : {};
+        } catch {
+          // Malformed args from a prior turn: pass through as a raw blob so
+          // the model sees the same shape it emitted. Wraps the string under
+          // _raw to match the buildMessagesPayload upstream convention.
+          input = { _raw: tc.function.arguments };
+        }
+        parts.push({ type: 'tool-call', toolCallId: tc.id, toolName: tc.function.name, input });
+      }
+      out.push({ role: 'assistant', content: parts });
+      continue;
+    }
+    if (m.role === 'tool') {
+      const toolCallId = m.tool_call_id ?? '';
+      const toolName = toolNameById.get(toolCallId) ?? 'unknown';
+      const raw = m.content ?? '';
+      let output: { type: 'text'; value: string } | { type: 'json'; value: JSONValue };
+      try {
+        // JSON.parse returns `any`; cast to JSONValue since the upstream
+        // tool_results column is already JSON-serializable by construction.
+        output = { type: 'json', value: JSON.parse(raw) as JSONValue };
+      } catch {
+        output = { type: 'text', value: raw };
+      }
+      out.push({
+        role: 'tool',
+        content: [{ type: 'tool-result', toolCallId, toolName, output }],
+      });
+      continue;
+    }
+  }
+  return out;
+}
+
+// Build the AI SDK tools record from BooCode's JSON-schema tool definitions.
+// No `execute` field: BooCode runs tools itself in tool-phase.ts; streamText
+// surfaces the tool-call parts via fullStream and we capture them for the
+// outer loop to dispatch.
+function buildAiTools(schemas: ToolJsonSchema[]): Record<string, ReturnType<typeof tool>> {
+  const out: Record<string, ReturnType<typeof tool>> = {};
+  for (const s of schemas) {
+    out[s.function.name] = tool({
+      description: s.function.description,
+      inputSchema: jsonSchema(s.function.parameters),
+    });
+  }
+  return out;
 }
 
 // v1.10.5 Qwen-coder XML fallback. Some local models (notably qwen3-coder via
 // llama-swap) emit tool calls as inline XML inside delta.content rather than
-// the structured delta.tool_calls field. The XML shape is:
+// the structured tool_calls field. We extract them out of the streamed text
+// before flushing it to the client, mirroring the pre-AI-SDK behavior.
+//
+// XML shape:
 //   <tool_call>
 //   <function=NAME>
-//   <parameter=KEY>
-//   VALUE
-//   </parameter>
-//   ...more parameters...
+//   <parameter=KEY>VALUE</parameter>
+//   ...
 //   </function>
 //   </tool_call>
 // Multiple <tool_call> blocks may appear back-to-back; they never nest.
-// streamCompletion buffers delta.content, extracts complete blocks, parses
-// them via parseXmlToolCall, and pushes synthetic entries into the existing
-// toolCallsBuffer alongside any native JSON-format tool calls.
 export async function streamCompletion(
   ctx: InferenceContext,
   model: string,
@@ -96,152 +151,196 @@ export async function streamCompletion(
   onUsage: ((prompt: number | null, completion: number | null) => void) | undefined,
   signal?: AbortSignal
 ): Promise<StreamResult> {
-  const body: Record<string, unknown> = {
-    model,
-    messages,
-    stream: true,
-    stream_options: { include_usage: true },
-  };
-  if (opts.tools && opts.tools.length > 0) {
-    body['tools'] = opts.tools;
-    body['tool_choice'] = 'auto';
-  }
-  if (typeof opts.temperature === 'number') {
-    body['temperature'] = opts.temperature;
-  }
+  const aiMessages = toModelMessages(messages);
+  const hasTools = opts.tools !== null && opts.tools.length > 0;
+  const aiTools = hasTools ? buildAiTools(opts.tools!) : undefined;
 
-  const res = await fetch(`${ctx.config.LLAMA_SWAP_URL}/v1/chat/completions`, {
-    method: 'POST',
-    headers: { 'Content-Type': 'application/json' },
-    body: JSON.stringify(body),
-    signal,
+  const startedAt = Date.now();
+  // v1.13.1-C: accumulate reasoning text across reasoning-delta parts.
+  // qwen3.6 emits these on a separate channel from text content; we capture
+  // them per stream so finalizeCompletion can dual-write a 'reasoning' part.
+  // Replaces the v1.13.1-A counter-only diagnostic.
+  let reasoningAccumulated = '';
+
+  // v1.13.3: experimental_repairToolCall keeps the stream alive when the
+  // model emits a malformed tool call (bad JSON args, unknown name, etc.).
+  // Without a repair function streamText throws and the WHOLE stream dies;
+  // with one, the SDK invokes us and we route the bad call through normally.
+  // Strategy: pass through unmodified. executeToolPhase's existing error
+  // path (unknown tool name → "unknown tool: X" result; zod-reject → tool
+  // 'X' rejected — fieldname: required) already gives the model a clean
+  // recovery surface on the next turn. Logging gives us visibility into
+  // how often qwen3.6 actually emits broken calls.
+  const repairToolCall: ToolCallRepairFunction<NonNullable<typeof aiTools>> = async ({
+    toolCall,
+    error,
+  }) => {
+    ctx.log.warn(
+      {
+        toolCallId: toolCall.toolCallId,
+        toolName: toolCall.toolName,
+        error: error.message,
+      },
+      'malformed tool call surfaced via repairToolCall',
+    );
+    return toolCall;
+  };
+
+  const result = streamText({
+    model: upstreamModel(ctx.config.LLAMA_SWAP_URL, model),
+    messages: aiMessages,
+    ...(aiTools
+      ? { tools: aiTools, toolChoice: 'auto' as const, experimental_repairToolCall: repairToolCall }
+      : {}),
+    ...(typeof opts.temperature === 'number' ? { temperature: opts.temperature } : {}),
+    abortSignal: signal,
   });
-  if (!res.ok || !res.body) {
-    const text = await res.text().catch(() => '');
-    throw new Error(`llama-swap returned ${res.status}: ${text.slice(0, 200)}`);
-  }
 
   let content = '';
-  // v1.10.5: holds delta.content bytes that may contain a partial XML tool
-  // call. Anything not part of a (possibly forming) <tool_call>…</tool_call>
-  // pair is flushed to content + onDelta as soon as we know it's safe.
   let pendingBuffer = '';
   let finishReason: string | null = null;
-  let promptTokens: number | null = null;
-  let completionTokens: number | null = null;
-  const toolCallsBuffer = new Map<number, { id: string; name: string; argsText: string }>();
+  // v1.13.1-A: AI SDK emits one `tool-call` part per fully-aggregated call,
+  // so we no longer need the OpenAI-index reassembly map the manual SSE
+  // parser used. XML tool calls extracted from text content go into the
+  // same flat list and keep the v1.10.5 synthetic id convention.
+  const toolCalls: ToolCall[] = [];
 
-  for await (const line of sseLines(res.body)) {
-    if (!line.startsWith('data:')) continue;
-    const payload = line.slice(5).trim();
-    if (payload === '[DONE]') break;
-    let parsed: ChatCompletionChunk;
-    try {
-      parsed = JSON.parse(payload);
-    } catch {
-      continue;
-    }
-
-    if (parsed.usage) {
-      if (typeof parsed.usage.prompt_tokens === 'number') {
-        promptTokens = parsed.usage.prompt_tokens;
-      }
-      if (typeof parsed.usage.completion_tokens === 'number') {
-        completionTokens = parsed.usage.completion_tokens;
-      }
-      onUsage?.(promptTokens, completionTokens);
-    }
-    // v1.11.3: removed dead `parsed.timings.n_ctx` read. llama-server's
-    // streaming completion does NOT emit n_ctx in timings (verified
-    // empirically); the authoritative source is llama-swap's
-    // /upstream/<model>/props endpoint, fetched per-turn via
-    // model-context.getModelContext() at the finalization sites below.
-
-    const choice = parsed.choices?.[0];
-    if (!choice) continue;
-    const delta = choice.delta ?? {};
-    if (typeof delta.content === 'string' && delta.content.length > 0) {
-      // v1.10.5 XML fallback. Append, then extract any complete tool_call
-      // blocks before deciding what's safe to flush as visible content.
-      pendingBuffer += delta.content;
-      while (true) {
-        const startIdx = pendingBuffer.indexOf(XML_TOOL_OPEN);
-        if (startIdx === -1) break;
-        const closeIdx = pendingBuffer.indexOf(XML_TOOL_CLOSE, startIdx);
-        if (closeIdx === -1) break;
-        const blockEnd = closeIdx + XML_TOOL_CLOSE.length;
-        const block = pendingBuffer.slice(startIdx, blockEnd);
-        // Any text before the opener is plain content — flush it now.
-        if (startIdx > 0) {
-          const before = pendingBuffer.slice(0, startIdx);
-          content += before;
-          onDelta(before);
+  for await (const part of result.fullStream) {
+    switch (part.type) {
+      case 'text-delta': {
+        pendingBuffer += part.text;
+        // Extract any complete <tool_call>...</tool_call> blocks before
+        // flushing visible text.
+        while (true) {
+          const startIdx = pendingBuffer.indexOf(XML_TOOL_OPEN);
+          if (startIdx === -1) break;
+          const closeIdx = pendingBuffer.indexOf(XML_TOOL_CLOSE, startIdx);
+          if (closeIdx === -1) break;
+          const blockEnd = closeIdx + XML_TOOL_CLOSE.length;
+          const block = pendingBuffer.slice(startIdx, blockEnd);
+          if (startIdx > 0) {
+            const before = pendingBuffer.slice(0, startIdx);
+            content += before;
+            onDelta(before);
+          }
+          const parsedCall = parseXmlToolCall(block);
+          if (parsedCall) {
+            const synthIdx = toolCalls.length;
+            toolCalls.push({
+              id: `xml_call_${synthIdx}`,
+              name: parsedCall.name,
+              args: parsedCall.args,
+            });
+          }
+          // Parse failures still drop the block — leaking <tool_call> XML to
+          // the chat would look worse than silently swallowing the bad block.
+          pendingBuffer = pendingBuffer.slice(blockEnd);
         }
-        const parsedCall = parseXmlToolCall(block);
-        if (parsedCall) {
-          const synthIdx = toolCallsBuffer.size;
-          toolCallsBuffer.set(synthIdx, {
-            id: `xml_call_${synthIdx}`,
-            name: parsedCall.name,
-            argsText: JSON.stringify(parsedCall.args),
-          });
+        // Hold back any (partial or full) unclosed opener; flush the rest.
+        const partialIdx = partialXmlOpenerStart(pendingBuffer);
+        if (partialIdx >= 0) {
+          if (partialIdx > 0) {
+            const flush = pendingBuffer.slice(0, partialIdx);
+            content += flush;
+            onDelta(flush);
+          }
+          pendingBuffer = pendingBuffer.slice(partialIdx);
+        } else if (pendingBuffer.length > 0) {
+          content += pendingBuffer;
+          onDelta(pendingBuffer);
+          pendingBuffer = '';
         }
-        // If parsing failed we still drop the block — emitting unparseable
-        // XML to the chat would look worse than silently swallowing it.
-        pendingBuffer = pendingBuffer.slice(blockEnd);
+        break;
       }
-      // After all complete blocks are out, hold back any (partial or full)
-      // unclosed opener; flush the rest.
-      const partialIdx = partialXmlOpenerStart(pendingBuffer);
-      if (partialIdx >= 0) {
-        if (partialIdx > 0) {
-          const flush = pendingBuffer.slice(0, partialIdx);
-          content += flush;
-          onDelta(flush);
+      case 'tool-call': {
+        // AI SDK has already parsed the input into an object. Match the
+        // ToolCall shape BooCode passes around in toolCallsBuffer downstream.
+        toolCalls.push({
+          id: part.toolCallId,
+          name: part.toolName,
+          args: (part.input ?? {}) as Record<string, unknown>,
+        });
+        break;
+      }
+      case 'reasoning-delta': {
+        // v1.13.1-C: accumulate; finalizeCompletion / executeToolPhase
+        // dual-write the resulting text as a kind='reasoning' part.
+        if (typeof part.text === 'string') {
+          reasoningAccumulated += part.text;
         }
-        pendingBuffer = pendingBuffer.slice(partialIdx);
-      } else if (pendingBuffer.length > 0) {
-        content += pendingBuffer;
-        onDelta(pendingBuffer);
-        pendingBuffer = '';
+        break;
       }
-    }
-    if (Array.isArray(delta.tool_calls)) {
-      for (const tc of delta.tool_calls) {
-        const idx = tc.index;
-        const existing = toolCallsBuffer.get(idx) ?? { id: '', name: '', argsText: '' };
-        if (tc.id) existing.id = tc.id;
-        if (tc.function?.name) existing.name = tc.function.name;
-        if (typeof tc.function?.arguments === 'string') existing.argsText += tc.function.arguments;
-        toolCallsBuffer.set(idx, existing);
+      case 'finish': {
+        if (typeof part.finishReason === 'string') {
+          finishReason = part.finishReason;
+        }
+        break;
       }
+      case 'error': {
+        const err = part.error;
+        throw err instanceof Error ? err : new Error(String(err));
+      }
+      // Intentional no-op: start, start-step, text-start, text-end,
+      // reasoning-start, reasoning-end, source, file, tool-input-start,
+      // tool-input-delta, tool-input-end, tool-result, tool-error,
+      // finish-step, raw. We only care about the aggregated tool-call and
+      // text-delta paths above; the rest are AI SDK lifecycle/streaming
+      // breadcrumbs that don't change BooCode's persistence or WS contract.
+      default:
+        break;
     }
-    if (choice.finish_reason) finishReason = choice.finish_reason;
   }
 
-  // v1.10.5: if the stream ended mid-XML (e.g. model truncated, no closer
-  // ever arrived), flush whatever was buffered as plain content so it isn't
-  // silently dropped. Better to show a stray `<tool_call>` than vanish text.
+  // v1.13.1-A: drain any buffered partial XML opener as plain text. The
+  // pre-AI-SDK path did this on stream end too — better to leak `<tool_c`
+  // than vanish the text.
   if (pendingBuffer.length > 0) {
     content += pendingBuffer;
     onDelta(pendingBuffer);
     pendingBuffer = '';
   }
 
-  const toolCalls: ToolCall[] = [];
-  for (const [, t] of [...toolCallsBuffer.entries()].sort(([a], [b]) => a - b)) {
-    let args: Record<string, unknown> = {};
-    if (t.argsText.length > 0) {
-      try {
-        args = JSON.parse(t.argsText);
-      } catch {
-        args = { _raw: t.argsText };
-      }
-    }
-    toolCalls.push({ id: t.id || `call_${toolCalls.length}`, name: t.name, args });
+  // AI SDK v6 fullStream returns normally on abort; check signal explicitly.
+  // Without this throw the row would land as status='complete' with partial
+  // content instead of going through handleAbortOrError → status='cancelled'.
+  // Smoke D caught this in v1.13.1-A — don't refactor it away.
+  if (signal?.aborted) {
+    const abortErr = new Error('aborted');
+    abortErr.name = 'AbortError';
+    throw abortErr;
   }
 
-  return { finishReason, content, toolCalls, promptTokens, completionTokens };
+  // Usage lands as a promise on the result; awaiting after fullStream is
+  // drained is safe. AI SDK v6 names: `inputTokens` / `outputTokens`.
+  let promptTokens: number | null = null;
+  let completionTokens: number | null = null;
+  try {
+    const usage = await result.usage;
+    if (typeof usage.inputTokens === 'number') promptTokens = usage.inputTokens;
+    if (typeof usage.outputTokens === 'number') completionTokens = usage.outputTokens;
+  } catch {
+    // Some providers omit usage on partial streams; leave both null.
+  }
+
+  if (onUsage && (promptTokens !== null || completionTokens !== null)) {
+    onUsage(promptTokens, completionTokens);
+  }
+
+  if (reasoningAccumulated.length > 0) {
+    ctx.log.debug(
+      { reasoningChars: reasoningAccumulated.length, model, elapsed_ms: Date.now() - startedAt },
+      'streamCompletion: captured reasoning',
+    );
+  }
+
+  return {
+    finishReason,
+    content,
+    toolCalls,
+    promptTokens,
+    completionTokens,
+    reasoning: reasoningAccumulated,
+  };
 }
 
 export async function executeStreamPhase(
@@ -313,9 +412,12 @@ export async function executeStreamPhase(
   const mctxForStream = await modelContext.getModelContext(session.model);
   const nCtxForStream = mctxForStream?.n_ctx ?? null;
 
-  // v1.12.2: throttle live usage publishes to ~500ms. The model can land
-  // dozens of usage frames per second; without a throttle the WS turns into
-  // a firehose for a few KB savings on each render.
+  // v1.12.2 → v1.13.1-A: live usage publishes were throttled to ~500ms when
+  // the manual SSE parser saw `parsed.usage` per chunk. AI SDK v6 surfaces
+  // usage only at stream end (result.usage promise), so the throttle is
+  // effectively a single trailing publish. ChatThroughput will tick once at
+  // stream completion rather than mid-stream — known regression vs v1.12.2,
+  // recovered if a future dispatch interpolates from delta cadence.
   const USAGE_THROTTLE_MS = 500;
   let lastUsageAt = 0;
   let pendingUsage: { p: number | null; c: number | null } | null = null;

apps/server/src/services/inference/tool-phase.ts

@@ -3,6 +3,7 @@ import * as modelContext from '../model-context.js';
 import { PathScopeError } from '../path_guard.js';
 import { TOOLS_BY_NAME } from '../tools.js';
 import { maybeFlagForCompaction } from './payload.js';
+import { insertParts, partsFromAssistantMessage, partsFromToolMessage } from './parts.js';
 import type {
   InferenceContext,
   StreamResult,
@@ -97,6 +98,26 @@ export async function executeToolPhase(
     WHERE id = ${assistantMessageId}
     RETURNING tokens_used, ctx_used, ctx_max, finished_at
   `;
+  // v1.13.0: dual-write to message_parts. v1.13.1-B made parts authoritative
+  // for reads via the messages_with_parts view; the JSON column write above
+  // remains for v1.13.1 fallback compatibility (dropped in v1.13.2).
+  // v1.13.1-C: include result.reasoning so models with separate reasoning
+  // channels (qwen3.6) get a kind='reasoning' part at sequence 0.
+  // TODO(v1.13.1): wrap the UPDATE above and this insertParts in a single
+  // sql.begin before flipping read authority to message_parts. Without the
+  // transaction, a crash between the two leaves an orphan message that
+  // becomes invisible in the parts-authoritative read path.
+  await insertParts(
+    ctx.sql,
+    partsFromAssistantMessage({
+      content,
+      tool_calls: toolCalls,
+      reasoning: result.reasoning,
+    }).map((p) => ({
+      ...p,
+      message_id: assistantMessageId,
+    })),
+  );
   // v1.11: flag for compaction if this turn pushed us over the usable budget.
   // We never compact mid-loop (the recursive runAssistantTurn keeps tools
   // flowing); the flag fires on the NEXT turn's pre-fetch hook above.
@@ -150,6 +171,18 @@ export async function executeToolPhase(
           SET tool_results = ${ctx.sql.json(sentinel as never)}
           WHERE id = ${toolMessageId}
         `;
+        // v1.13.0: mirror the pending sentinel into message_parts. The
+        // answer-endpoint UPDATE later (messages.ts:576) will delete and
+        // re-insert this part when the user submits their answer.
+        // TODO(v1.13.1): wrap the INSERT + UPDATE + insertParts triple in
+        // a per-iteration sql.begin before flipping read authority.
+        await insertParts(
+          ctx.sql,
+          partsFromToolMessage({ tool_results: sentinel }).map((p) => ({
+            ...p,
+            message_id: toolMessageId,
+          })),
+        );
         return;
       }
       const tres = await executeToolCall(projectRoot, tc);
@@ -164,6 +197,16 @@ export async function executeToolPhase(
         SET tool_results = ${ctx.sql.json(stored as never)}
         WHERE id = ${toolMessageId}
       `;
+      // v1.13.0: dual-write the tool_result part.
+      // TODO(v1.13.1): wrap the INSERT + UPDATE + insertParts triple in a
+      // per-iteration sql.begin before flipping read authority.
+      await insertParts(
+        ctx.sql,
+        partsFromToolMessage({ tool_results: stored }).map((p) => ({
+          ...p,
+          message_id: toolMessageId,
+        })),
+      );
       ctx.publish(sessionId, {
         type: 'tool_result',
         tool_message_id: toolMessageId,

apps/server/src/services/inference/turn.ts

@@ -118,6 +118,9 @@ export interface StreamResult {
   toolCalls: ToolCall[];
   promptTokens: number | null;
   completionTokens: number | null;
+  // v1.13.1-C: reasoning text accumulated across reasoning-delta parts.
+  // Empty string when the model doesn't emit reasoning (most cases).
+  reasoning: string;
 }
 
 

apps/server/src/services/tools.ts

@@ -527,6 +527,11 @@ export const askUserInput: ToolDef<AskUserInputInputT> = {
   },
 };
 
+// v1.13.3: alpha-sorted by tool.name at module load. llama.cpp's prompt
+// cache hits on byte-identical prefixes; the tool list lives near the top
+// of the system prompt, so any order drift would invalidate every cached
+// turn. Single source of truth for ordering lives here — toolJsonSchemas()
+// and TOOLS_BY_NAME inherit it.
 export const ALL_TOOLS: ReadonlyArray<ToolDef<unknown>> = [
   viewFile as ToolDef<unknown>,
   listDir as ToolDef<unknown>,
@@ -553,7 +558,7 @@ export const ALL_TOOLS: ReadonlyArray<ToolDef<unknown>> = [
   watchChanges as ToolDef<unknown>,
   getSemanticNeighborhoods as ToolDef<unknown>,
   getFrameworkAnalysis as ToolDef<unknown>,
-];
+].sort((a, b) => a.name.localeCompare(b.name));
 
 // v1.8.2: forward-compatible read-only whitelist. An agent whose `tools` is
 // fully contained in this set gets a generous default tool budget (30);

apps/server/src/types/api.ts

@@ -186,6 +186,11 @@ export interface Message {
   // v1.8.2: per-message metadata. See MessageMetadata for the discriminated
   // shapes currently in use.
   metadata: MessageMetadata | null;
+  // v1.13.1-C: reasoning content captured from the model's reasoning stream
+  // (qwen3.6 etc.). Populated from message_parts via the messages_with_parts
+  // view's reasoning_parts column. Optional — most rows have no reasoning
+  // and the API may omit the field on legacy responses.
+  reasoning_parts?: Array<{ text: string }> | null;
   // v1.11: anchored rolling compaction. Optional so consumers that SELECT
   // the pre-v1.11 column set still type-check. See compaction.ts +
   // schema.sql for semantics.

apps/web/src/api/types.ts

@@ -161,6 +161,11 @@ export interface Message {
   // v1.8.2: per-message metadata; see MessageMetadata. null for the vast
   // majority of messages.
   metadata: MessageMetadata | null;
+  // v1.13.1-C: reasoning content captured from models that stream reasoning
+  // tokens separately (qwen3.6 etc.). Backend populates from message_parts;
+  // optional on the wire — frontend doesn't render this yet (reserved for
+  // a v1.14 UI surface).
+  reasoning_parts?: Array<{ text: string }> | null;
   // v1.11: anchored rolling compaction fields. Optional on the wire so that
   // older API responses (or test fixtures) parse without explicit nulls.
   //   summary       — true on the assistant row that holds the active

pnpm-lock.yaml

@@ -48,12 +48,18 @@ importers:
 
   apps/server:
     dependencies:
+      '@ai-sdk/openai-compatible':
+        specifier: ^2.0.47
+        version: 2.0.47(zod@3.25.76)
       '@fastify/static':
         specifier: ^7.0.4
         version: 7.0.4
       '@fastify/websocket':
         specifier: ^10.0.1
         version: 10.0.1
+      ai:
+        specifier: ^6.0.190
+        version: 6.0.190(zod@3.25.76)
       fastify:
         specifier: ^4.28.1
         version: 4.29.1
@@ -179,6 +185,28 @@ importers:
 
 packages:
 
+  '@ai-sdk/gateway@3.0.119':
+    resolution: {integrity: sha512-VAhfRWC+JexZakkVfmjaJKaTj00x7/UHdE8kMWL3NhuQAlf8oXtg9r4dfvFZrByXxchGRBvYE3biEUyibkg0xg==}
+    engines: {node: '>=18'}
+    peerDependencies:
+      zod: ^3.25.76 || ^4.1.8
+
+  '@ai-sdk/openai-compatible@2.0.47':
+    resolution: {integrity: sha512-Enm5UlL0zUCrW3792opk5h7hRWxZOZzDe6eQYVFqX9LUOGGCe1h8MZWAGim765nwzgnjlpeYOsuzZmLtRsTPlg==}
+    engines: {node: '>=18'}
+    peerDependencies:
+      zod: ^3.25.76 || ^4.1.8
+
+  '@ai-sdk/provider-utils@4.0.27':
+    resolution: {integrity: sha512-ubkAJ+xODouwtmN1tYlvTPphH1hPOBfZaEQe8U7skGvFAnIRs9PPpsq57bC2+Ky/MB4yzhd6YOsxTAx9sGpazw==}
+    engines: {node: '>=18'}
+    peerDependencies:
+      zod: ^3.25.76 || ^4.1.8
+
+  '@ai-sdk/provider@3.0.10':
+    resolution: {integrity: sha512-Q3BZ27qfpYqnCYGvE3vt+Qi6LGOF9R5Nmzn+9JoM1lCRsD9mYaIhfJLkSunN48nfGXJ6n+XNV0J/XVpqGQl7Dw==}
+    engines: {node: '>=18'}
+
   '@alloc/quick-lru@5.2.0':
     resolution: {integrity: sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==}
     engines: {node: '>=10'}
@@ -789,6 +817,10 @@ packages:
   '@open-draft/until@2.1.0':
     resolution: {integrity: sha512-U69T3ItWHvLwGg5eJ0n3I62nWuE6ilHlmz7zM0npLBRvPRd7e6NYmg54vvRtP5mZG7kZqZCFVdsTWo7BPtBujg==}
 
+  '@opentelemetry/api@1.9.1':
+    resolution: {integrity: sha512-gLyJlPHPZYdAk1JENA9LeHejZe1Ti77/pTeFm/nMXmQH/HFZlcS/O2XJB+L8fkbrNSqhdtlvjBVjxwUYanNH5Q==}
+    engines: {node: '>=8.0.0'}
+
   '@pinojs/redact@0.4.0':
     resolution: {integrity: sha512-k2ENnmBugE/rzQfEcdWHcCY+/FM3VLzH9cYEsbdsoqrvzAKRhUZeRNhAZvB8OitQJ1TBed3yqWtdjzS6wJKBwg==}
 
@@ -1646,6 +1678,9 @@ packages:
     resolution: {integrity: sha512-tlqY9xq5ukxTUZBmoOp+m61cqwQD5pHJtFY3Mn8CA8ps6yghLH/Hw8UPdqg4OLmFW3IFlcXnQNmo/dh8HzXYIQ==}
     engines: {node: '>=18'}
 
+  '@standard-schema/spec@1.1.0':
+    resolution: {integrity: sha512-l2aFy5jALhniG5HgqrD6jXLi/rUWrKvqN/qJx6yoJsgKhblVd+iqqU4RCXavm/jPityDo5TCvKMnpjKnOriy0w==}
+
   '@tailwindcss/node@4.3.0':
     resolution: {integrity: sha512-aFb4gUhFOgdh9AXo4IzBEOzBkkAxm9VigwDJnMIYv3lcfXCJVesNfbEaBl4BNgVRyid92AmdviqwBUBRKSeY3g==}
 
@@ -1811,6 +1846,10 @@ packages:
   '@ungap/structured-clone@1.3.1':
     resolution: {integrity: sha512-mUFwbeTqrVgDQxFveS+df2yfap6iuP20NAKAsBt5jDEoOTDew+zwLAOilHCeQJOVSvmgCX4ogqIrA0mnyr08yQ==}
 
+  '@vercel/oidc@3.2.0':
+    resolution: {integrity: sha512-UycprH3T6n3jH0k44NHMa7pnFHGu/N05MjojYr+Mc6I7obkoLIJujSWwin1pCvdy/eOxrI/l3uDLQsmcrOb4ug==}
+    engines: {node: '>= 20'}
+
   '@vitejs/plugin-react@4.7.0':
     resolution: {integrity: sha512-gUu9hwfWvvEDBBmgtAowQCojwZmJ5mcLn3aufeCsitijs3+f2NsrPtlAWIR6OPiqljl96GVCUbLe0HyqIpVaoA==}
     engines: {node: ^14.18.0 || >=16.0.0}
@@ -1878,6 +1917,12 @@ packages:
     resolution: {integrity: sha512-MnA+YT8fwfJPgBx3m60MNqakm30XOkyIoH1y6huTQvC0PwZG7ki8NacLBcrPbNoo8vEZy7Jpuk7+jMO+CUovTQ==}
     engines: {node: '>= 14'}
 
+  ai@6.0.190:
+    resolution: {integrity: sha512-T+ixHbWZ6jmHRREpVVJTkFyWJeCekCdzLPan7lp1F32jG5OUw4+odlVYjtMRXVzogU+pWzpMmXdRiHUmdL/q0w==}
+    engines: {node: '>=18'}
+    peerDependencies:
+      zod: ^3.25.76 || ^4.1.8
+
   ajv-formats@2.1.1:
     resolution: {integrity: sha512-Wx0Kx52hxE7C18hkMEggYlEifqWZtYaRgouJor+WMdPnQyEK13vgEWyVNup7SoeeoLMsr4kf5h6dOW11I15MUA==}
     peerDependencies:
@@ -2694,6 +2739,9 @@ packages:
   json-schema-typed@8.0.2:
     resolution: {integrity: sha512-fQhoXdcvc3V28x7C7BMs4P5+kNlgUURe2jmUT1T//oBRMDrqy1QPelJimwZGo7Hg9VPV3EQV5Bnq4hbFy2vetA==}
 
+  json-schema@0.4.0:
+    resolution: {integrity: sha512-es94M3nTIfsEPisRafak+HDLfHXnKBhV3vU5eqPcS3flIWqcxJWgXHXiey3YrpaNsanY5ei1VoYEbOzijuq9BA==}
+
   json5@2.2.3:
     resolution: {integrity: sha512-XmOWe7eyHYH14cLdVPoyg+GOH3rYX++KpzrylJwSW98t3Nk+U8XOl8FWKOgwtzdb8lXGf6zYwDUzeHMWfxasyg==}
     engines: {node: '>=6'}
@@ -3966,6 +4014,30 @@ packages:
 
 snapshots:
 
+  '@ai-sdk/gateway@3.0.119(zod@3.25.76)':
+    dependencies:
+      '@ai-sdk/provider': 3.0.10
+      '@ai-sdk/provider-utils': 4.0.27(zod@3.25.76)
+      '@vercel/oidc': 3.2.0
+      zod: 3.25.76
+
+  '@ai-sdk/openai-compatible@2.0.47(zod@3.25.76)':
+    dependencies:
+      '@ai-sdk/provider': 3.0.10
+      '@ai-sdk/provider-utils': 4.0.27(zod@3.25.76)
+      zod: 3.25.76
+
+  '@ai-sdk/provider-utils@4.0.27(zod@3.25.76)':
+    dependencies:
+      '@ai-sdk/provider': 3.0.10
+      '@standard-schema/spec': 1.1.0
+      eventsource-parser: 3.0.8
+      zod: 3.25.76
+
+  '@ai-sdk/provider@3.0.10':
+    dependencies:
+      json-schema: 0.4.0
+
   '@alloc/quick-lru@5.2.0': {}
 
   '@babel/code-frame@7.29.0':
@@ -4516,6 +4588,8 @@ snapshots:
 
   '@open-draft/until@2.1.0': {}
 
+  '@opentelemetry/api@1.9.1': {}
+
   '@pinojs/redact@0.4.0': {}
 
   '@pkgjs/parseargs@0.11.0':
@@ -5386,6 +5460,8 @@ snapshots:
 
   '@sindresorhus/merge-streams@4.0.0': {}
 
+  '@standard-schema/spec@1.1.0': {}
+
   '@tailwindcss/node@4.3.0':
     dependencies:
       '@jridgewell/remapping': 2.3.5
@@ -5548,6 +5624,8 @@ snapshots:
 
   '@ungap/structured-clone@1.3.1': {}
 
+  '@vercel/oidc@3.2.0': {}
+
   '@vitejs/plugin-react@4.7.0(vite@5.4.21(@types/node@20.19.41)(lightningcss@1.32.0))':
     dependencies:
       '@babel/core': 7.29.0
@@ -5628,6 +5706,14 @@ snapshots:
 
   agent-base@7.1.4: {}
 
+  ai@6.0.190(zod@3.25.76):
+    dependencies:
+      '@ai-sdk/gateway': 3.0.119(zod@3.25.76)
+      '@ai-sdk/provider': 3.0.10
+      '@ai-sdk/provider-utils': 4.0.27(zod@3.25.76)
+      '@opentelemetry/api': 1.9.1
+      zod: 3.25.76
+
   ajv-formats@2.1.1(ajv@8.20.0):
     optionalDependencies:
       ajv: 8.20.0
@@ -6453,6 +6539,8 @@ snapshots:
 
   json-schema-typed@8.0.2: {}
 
+  json-schema@0.4.0: {}
+
   json5@2.2.3: {}
 
   jsonfile@6.2.1: