Files
boocode/apps/server/src/services/inference/parts.ts
indifferentketchup ac1a71f583 v1.13.1-C: port ask_user_input correlation to parts + wire reasoning_parts end-to-end
Pass 1 — ask_user_input correlation port (messages.ts:478, :549):

- The two correlation queries that backed the elicitation flow used to scan
  messages.tool_calls and messages.tool_results JSON columns directly. They
  now JOIN message_parts on payload->>'id' (for the caller assistant) and
  payload->>'tool_call_id' (for the pending tool row). Semantics preserved:
  ORDER BY m.created_at DESC LIMIT 1 still picks the latest issuance, the
  already-answered 409 guard now reads payload.output, and the UPDATE +
  parts replace inside sql.begin is unchanged from v1.13.0.
- Pre-v1.13.0 history has no parts rows and is unreachable to this lookup
  path (404). Acceptable per dispatch decision — no pending elicitation
  from before v1.13.0 will still be open. JSON-column fallback can land as
  a hotfix if it ever surfaces.

Pass 2 — reasoning_parts wired end-to-end:

- types.ts/StreamResult gains `reasoning: string`. stream-phase.ts accumulates
  reasoning-delta text per stream (replacing the v1.13.1-A counter-only
  diagnostic) and returns it on the result.
- parts.ts/partsFromAssistantMessage gains an optional `reasoning` param.
  When present it emits a kind='reasoning' part at sequence 0, ahead of
  the text and tool_call parts.
- error-handler.ts/finalizeCompletion and tool-phase.ts/executeToolPhase
  both thread result.reasoning into the dual-write call so reasoning-channel
  models (qwen3.6) get persistent reasoning rows.
- payload.ts: loadContext SELECT pulls reasoning_parts from the v1.13.1-B
  view; OpenAiMessage gains an optional `reasoning` field; buildMessagesPayload
  collapses reasoning_parts into a single string per assistant message.
- stream-phase.ts/toModelMessages converts assistant messages with reasoning
  into an AI SDK ModelMessage content array starting with a ReasoningPart,
  matching the @ai-sdk/provider-utils AssistantContent union. Reasoning
  models can now replay prior reasoning context across tool-call boundaries.
- types/api.ts and apps/web/src/api/types.ts Message interface gain
  reasoning_parts (optional, nullable). Frontend doesn't render this yet —
  field reserved for a v1.14 UI surface.

Tests: 2 new in parts.test.ts cover reasoning-at-sequence-0 with and
without text content. 172 tests pass (170 prior + 2 new).

Smoke verified against the live container:
- A reasoning-prompt ("walk through 17 × 23 step by step") produced one
  message with kind='reasoning' (361 chars) at sequence 0 and kind='text'
  (429 chars) at sequence 1. Adapter log confirmed reasoning capture.
- The new correlation SQL was validated against existing tool_call /
  tool_result parts: returns the expected message_id + payload shape with
  pending state correctly identified via payload.output IS NULL.
- ask_user_input end-to-end through the UI is Sam's smoke — the Prompt
  Builder agent does not always trigger ask_user_input for these prompts,
  so synthetic verification via SQL substituted for traffic-driven cover.

Annotation: the v1.13.1-A abort-throw site in stream-phase.ts got a
one-liner comment ("AI SDK v6 fullStream returns normally on abort; check
signal explicitly.") to prevent a future refactor removing it.

v1.13.2 drops the dual-write + the JSON columns + collapses the view.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-22 06:34:10 +00:00

96 lines
3.2 KiB
TypeScript

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 } : {}),
},
},
];
}