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Made-with: Cursor

openclaw/extensions/openai/embedding-batch.ts

@@ -0,0 +1,261 @@
+import {
+  applyEmbeddingBatchOutputLine,
+  buildBatchHeaders,
+  buildEmbeddingBatchGroupOptions,
+  EMBEDDING_BATCH_ENDPOINT,
+  extractBatchErrorMessage,
+  formatUnavailableBatchError,
+  normalizeBatchBaseUrl,
+  postJsonWithRetry,
+  resolveBatchCompletionFromStatus,
+  resolveCompletedBatchResult,
+  runEmbeddingBatchGroups,
+  throwIfBatchTerminalFailure,
+  type EmbeddingBatchExecutionParams,
+  type EmbeddingBatchStatus,
+  type BatchCompletionResult,
+  type ProviderBatchOutputLine,
+  uploadBatchJsonlFile,
+  withRemoteHttpResponse,
+} from "openclaw/plugin-sdk/memory-core-host-engine-embeddings";
+import type { OpenAiEmbeddingClient } from "./embedding-provider.js";
+
+export type OpenAiBatchRequest = {
+  custom_id: string;
+  method: "POST";
+  url: "/v1/embeddings";
+  body: {
+    model: string;
+    input: string;
+  };
+};
+
+export type OpenAiBatchStatus = EmbeddingBatchStatus;
+export type OpenAiBatchOutputLine = ProviderBatchOutputLine;
+
+export const OPENAI_BATCH_ENDPOINT = EMBEDDING_BATCH_ENDPOINT;
+const OPENAI_BATCH_COMPLETION_WINDOW = "24h";
+const OPENAI_BATCH_MAX_REQUESTS = 50000;
+
+async function submitOpenAiBatch(params: {
+  openAi: OpenAiEmbeddingClient;
+  requests: OpenAiBatchRequest[];
+  agentId: string;
+}): Promise<OpenAiBatchStatus> {
+  const baseUrl = normalizeBatchBaseUrl(params.openAi);
+  const inputFileId = await uploadBatchJsonlFile({
+    client: params.openAi,
+    requests: params.requests,
+    errorPrefix: "openai batch file upload failed",
+  });
+
+  return await postJsonWithRetry<OpenAiBatchStatus>({
+    url: `${baseUrl}/batches`,
+    headers: buildBatchHeaders(params.openAi, { json: true }),
+    ssrfPolicy: params.openAi.ssrfPolicy,
+    fetchImpl: params.openAi.fetchImpl,
+    body: {
+      input_file_id: inputFileId,
+      endpoint: OPENAI_BATCH_ENDPOINT,
+      completion_window: OPENAI_BATCH_COMPLETION_WINDOW,
+      metadata: {
+        source: "openclaw-memory",
+        agent: params.agentId,
+      },
+    },
+    errorPrefix: "openai batch create failed",
+  });
+}
+
+async function fetchOpenAiBatchStatus(params: {
+  openAi: OpenAiEmbeddingClient;
+  batchId: string;
+}): Promise<OpenAiBatchStatus> {
+  return await fetchOpenAiBatchResource({
+    openAi: params.openAi,
+    path: `/batches/${params.batchId}`,
+    errorPrefix: "openai batch status",
+    parse: async (res) => (await res.json()) as OpenAiBatchStatus,
+  });
+}
+
+async function fetchOpenAiFileContent(params: {
+  openAi: OpenAiEmbeddingClient;
+  fileId: string;
+}): Promise<string> {
+  return await fetchOpenAiBatchResource({
+    openAi: params.openAi,
+    path: `/files/${params.fileId}/content`,
+    errorPrefix: "openai batch file content",
+    parse: async (res) => await res.text(),
+  });
+}
+
+async function fetchOpenAiBatchResource<T>(params: {
+  openAi: OpenAiEmbeddingClient;
+  path: string;
+  errorPrefix: string;
+  parse: (res: Response) => Promise<T>;
+}): Promise<T> {
+  const baseUrl = normalizeBatchBaseUrl(params.openAi);
+  return await withRemoteHttpResponse({
+    url: `${baseUrl}${params.path}`,
+    ssrfPolicy: params.openAi.ssrfPolicy,
+    fetchImpl: params.openAi.fetchImpl,
+    init: {
+      headers: buildBatchHeaders(params.openAi, { json: true }),
+    },
+    onResponse: async (res) => {
+      if (!res.ok) {
+        const text = await res.text();
+        throw new Error(`${params.errorPrefix} failed: ${res.status} ${text}`);
+      }
+      return await params.parse(res);
+    },
+  });
+}
+
+function parseOpenAiBatchOutput(text: string): OpenAiBatchOutputLine[] {
+  if (!text.trim()) {
+    return [];
+  }
+  return text
+    .split("\n")
+    .map((line) => line.trim())
+    .filter(Boolean)
+    .map((line) => JSON.parse(line) as OpenAiBatchOutputLine);
+}
+
+async function readOpenAiBatchError(params: {
+  openAi: OpenAiEmbeddingClient;
+  errorFileId: string;
+}): Promise<string | undefined> {
+  try {
+    const content = await fetchOpenAiFileContent({
+      openAi: params.openAi,
+      fileId: params.errorFileId,
+    });
+    const lines = parseOpenAiBatchOutput(content);
+    return extractBatchErrorMessage(lines);
+  } catch (err) {
+    return formatUnavailableBatchError(err);
+  }
+}
+
+async function waitForOpenAiBatch(params: {
+  openAi: OpenAiEmbeddingClient;
+  batchId: string;
+  wait: boolean;
+  pollIntervalMs: number;
+  timeoutMs: number;
+  debug?: (message: string, data?: Record<string, unknown>) => void;
+  initial?: OpenAiBatchStatus;
+}): Promise<BatchCompletionResult> {
+  const start = Date.now();
+  let current: OpenAiBatchStatus | undefined = params.initial;
+  while (true) {
+    const status =
+      current ??
+      (await fetchOpenAiBatchStatus({
+        openAi: params.openAi,
+        batchId: params.batchId,
+      }));
+    const state = status.status ?? "unknown";
+    if (state === "completed") {
+      return resolveBatchCompletionFromStatus({
+        provider: "openai",
+        batchId: params.batchId,
+        status,
+      });
+    }
+    await throwIfBatchTerminalFailure({
+      provider: "openai",
+      status: { ...status, id: params.batchId },
+      readError: async (errorFileId) =>
+        await readOpenAiBatchError({
+          openAi: params.openAi,
+          errorFileId,
+        }),
+    });
+    if (!params.wait) {
+      throw new Error(`openai batch ${params.batchId} still ${state}; wait disabled`);
+    }
+    if (Date.now() - start > params.timeoutMs) {
+      throw new Error(`openai batch ${params.batchId} timed out after ${params.timeoutMs}ms`);
+    }
+    params.debug?.(`openai batch ${params.batchId} ${state}; waiting ${params.pollIntervalMs}ms`);
+    await new Promise((resolve) => setTimeout(resolve, params.pollIntervalMs));
+    current = undefined;
+  }
+}
+
+export async function runOpenAiEmbeddingBatches(
+  params: {
+    openAi: OpenAiEmbeddingClient;
+    agentId: string;
+    requests: OpenAiBatchRequest[];
+  } & EmbeddingBatchExecutionParams,
+): Promise<Map<string, number[]>> {
+  return await runEmbeddingBatchGroups({
+    ...buildEmbeddingBatchGroupOptions(params, {
+      maxRequests: OPENAI_BATCH_MAX_REQUESTS,
+      debugLabel: "memory embeddings: openai batch submit",
+    }),
+    runGroup: async ({ group, groupIndex, groups, byCustomId }) => {
+      const batchInfo = await submitOpenAiBatch({
+        openAi: params.openAi,
+        requests: group,
+        agentId: params.agentId,
+      });
+      if (!batchInfo.id) {
+        throw new Error("openai batch create failed: missing batch id");
+      }
+      const batchId = batchInfo.id;
+
+      params.debug?.("memory embeddings: openai batch created", {
+        batchId: batchInfo.id,
+        status: batchInfo.status,
+        group: groupIndex + 1,
+        groups,
+        requests: group.length,
+      });
+
+      const completed = await resolveCompletedBatchResult({
+        provider: "openai",
+        status: batchInfo,
+        wait: params.wait,
+        waitForBatch: async () =>
+          await waitForOpenAiBatch({
+            openAi: params.openAi,
+            batchId,
+            wait: params.wait,
+            pollIntervalMs: params.pollIntervalMs,
+            timeoutMs: params.timeoutMs,
+            debug: params.debug,
+            initial: batchInfo,
+          }),
+      });
+
+      const content = await fetchOpenAiFileContent({
+        openAi: params.openAi,
+        fileId: completed.outputFileId,
+      });
+      const outputLines = parseOpenAiBatchOutput(content);
+      const errors: string[] = [];
+      const remaining = new Set(group.map((request) => request.custom_id));
+
+      for (const line of outputLines) {
+        applyEmbeddingBatchOutputLine({ line, remaining, errors, byCustomId });
+      }
+
+      if (errors.length > 0) {
+        throw new Error(`openai batch ${batchInfo.id} failed: ${errors.join("; ")}`);
+      }
+      if (remaining.size > 0) {
+        throw new Error(
+          `openai batch ${batchInfo.id} missing ${remaining.size} embedding responses`,
+        );
+      }
+    },
+  });
+}