refactor(memory): share batch output parsing

src/memory/batch-openai.ts

@@ -1,5 +1,6 @@
 import type { OpenAiEmbeddingClient } from "./embeddings-openai.js";
 import { retryAsync } from "../infra/retry.js";
+import { applyEmbeddingBatchOutputLine } from "./batch-output.js";
 import { hashText, runWithConcurrency } from "./internal.js";
 
 export type OpenAiBatchRequest = {
@@ -313,32 +314,7 @@ export async function runOpenAiEmbeddingBatches(params: {
     const remaining = new Set(group.map((request) => request.custom_id));
 
     for (const line of outputLines) {
-      const customId = line.custom_id;
-      if (!customId) {
-        continue;
-      }
-      remaining.delete(customId);
-      if (line.error?.message) {
-        errors.push(`${customId}: ${line.error.message}`);
-        continue;
-      }
-      const response = line.response;
-      const statusCode = response?.status_code ?? 0;
-      if (statusCode >= 400) {
-        const message =
-          response?.body?.error?.message ??
-          (typeof response?.body === "string" ? response.body : undefined) ??
-          "unknown error";
-        errors.push(`${customId}: ${message}`);
-        continue;
-      }
-      const data = response?.body?.data ?? [];
-      const embedding = data[0]?.embedding ?? [];
-      if (embedding.length === 0) {
-        errors.push(`${customId}: empty embedding`);
-        continue;
-      }
-      byCustomId.set(customId, embedding);
+      applyEmbeddingBatchOutputLine({ line, remaining, errors, byCustomId });
     }
 
     if (errors.length > 0) {