Files
openclaw/src/memory/batch-openai.ts
2026-02-22 21:19:09 +00:00

259 lines
8.2 KiB
TypeScript

import { extractBatchErrorMessage, formatUnavailableBatchError } from "./batch-error-utils.js";
import { postJsonWithRetry } from "./batch-http.js";
import { applyEmbeddingBatchOutputLine } from "./batch-output.js";
import {
EMBEDDING_BATCH_ENDPOINT,
type EmbeddingBatchStatus,
type ProviderBatchOutputLine,
} from "./batch-provider-common.js";
import {
buildEmbeddingBatchGroupOptions,
runEmbeddingBatchGroups,
type EmbeddingBatchExecutionParams,
} from "./batch-runner.js";
import { uploadBatchJsonlFile } from "./batch-upload.js";
import { buildBatchHeaders, normalizeBatchBaseUrl } from "./batch-utils.js";
import type { OpenAiEmbeddingClient } from "./embeddings-openai.js";
import { withRemoteHttpResponse } from "./remote-http.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: `${baseUrl}/batches`,
headers: buildBatchHeaders(params.openAi, { json: true }),
ssrfPolicy: params.openAi.ssrfPolicy,
body: {
input_file_id: inputFileId,
endpoint: OPENAI_BATCH_ENDPOINT,
completion_window: OPENAI_BATCH_COMPLETION_WINDOW,
metadata: {
source: "openclaw-memory",
agent: params.agentId,
},
},
errorPrefix: "openai batch create failed",
});
}
async function fetchOpenAiBatchStatus(params: {
openAi: OpenAiEmbeddingClient;
batchId: string;
}): Promise<OpenAiBatchStatus> {
const baseUrl = normalizeBatchBaseUrl(params.openAi);
return await withRemoteHttpResponse({
url: `${baseUrl}/batches/${params.batchId}`,
ssrfPolicy: params.openAi.ssrfPolicy,
init: {
headers: buildBatchHeaders(params.openAi, { json: true }),
},
onResponse: async (res) => {
if (!res.ok) {
const text = await res.text();
throw new Error(`openai batch status failed: ${res.status} ${text}`);
}
return (await res.json()) as OpenAiBatchStatus;
},
});
}
async function fetchOpenAiFileContent(params: {
openAi: OpenAiEmbeddingClient;
fileId: string;
}): Promise<string> {
const baseUrl = normalizeBatchBaseUrl(params.openAi);
return await withRemoteHttpResponse({
url: `${baseUrl}/files/${params.fileId}/content`,
ssrfPolicy: params.openAi.ssrfPolicy,
init: {
headers: buildBatchHeaders(params.openAi, { json: true }),
},
onResponse: async (res) => {
if (!res.ok) {
const text = await res.text();
throw new Error(`openai batch file content failed: ${res.status} ${text}`);
}
return await res.text();
},
});
}
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<{ outputFileId: string; errorFileId?: string }> {
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") {
if (!status.output_file_id) {
throw new Error(`openai batch ${params.batchId} completed without output file`);
}
return {
outputFileId: status.output_file_id,
errorFileId: status.error_file_id ?? undefined,
};
}
if (["failed", "expired", "cancelled", "canceled"].includes(state)) {
const detail = status.error_file_id
? await readOpenAiBatchError({ openAi: params.openAi, errorFileId: status.error_file_id })
: undefined;
const suffix = detail ? `: ${detail}` : "";
throw new Error(`openai batch ${params.batchId} ${state}${suffix}`);
}
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");
}
params.debug?.("memory embeddings: openai batch created", {
batchId: batchInfo.id,
status: batchInfo.status,
group: groupIndex + 1,
groups,
requests: group.length,
});
if (!params.wait && batchInfo.status !== "completed") {
throw new Error(
`openai batch ${batchInfo.id} submitted; enable remote.batch.wait to await completion`,
);
}
const completed =
batchInfo.status === "completed"
? {
outputFileId: batchInfo.output_file_id ?? "",
errorFileId: batchInfo.error_file_id ?? undefined,
}
: await waitForOpenAiBatch({
openAi: params.openAi,
batchId: batchInfo.id,
wait: params.wait,
pollIntervalMs: params.pollIntervalMs,
timeoutMs: params.timeoutMs,
debug: params.debug,
initial: batchInfo,
});
if (!completed.outputFileId) {
throw new Error(`openai batch ${batchInfo.id} completed without output file`);
}
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`,
);
}
},
});
}