Fix dedicated LLM model list fetching

This commit is contained in:
Youzini-afk
2026-03-28 13:49:06 +08:00
parent b5d8056ae4
commit e58fef240b
2 changed files with 365 additions and 30 deletions

152
llm.js
View File

@@ -486,9 +486,11 @@ function normalizeModelList(items = []) {
id = item.trim();
label = id;
} else if (item && typeof item === "object") {
id = String(item.id || item.name || item.value || item.slug || "").trim();
id = String(
item.id || item.name || item.label || item.value || item.slug || "",
).trim();
label = String(
item.name || item.id || item.value || item.slug || "",
item.label || item.name || item.id || item.value || item.slug || "",
).trim();
}
@@ -500,6 +502,101 @@ function normalizeModelList(items = []) {
return models;
}
function extractModelListPayload(payload = {}) {
if (Array.isArray(payload)) {
return payload;
}
if (!payload || typeof payload !== "object") {
return [];
}
if (Array.isArray(payload.models)) {
return payload.models;
}
if (Array.isArray(payload.data)) {
return payload.data;
}
if (payload.data && typeof payload.data === "object") {
if (Array.isArray(payload.data.models)) {
return payload.data.models;
}
if (Array.isArray(payload.data.data)) {
return payload.data.data;
}
}
return [];
}
function buildDedicatedAuthHeaderString(apiKey = "") {
const normalized = String(apiKey || "").trim();
return normalized ? `Authorization: Bearer ${normalized}` : "";
}
function buildDedicatedStatusRequestVariants(config = getMemoryLLMConfig()) {
const customVariant = {
mode: "custom",
body: {
chat_completion_source: chat_completion_sources.CUSTOM,
custom_url: config.apiUrl,
custom_include_headers: buildDedicatedAuthHeaderString(config.apiKey),
reverse_proxy: config.apiUrl,
proxy_password: "",
},
};
const legacyOpenAiVariant = {
mode: "openai-reverse-proxy",
body: {
chat_completion_source: chat_completion_sources.OPENAI,
reverse_proxy: config.apiUrl,
proxy_password: config.apiKey || "",
},
};
return [customVariant, legacyOpenAiVariant];
}
async function requestDedicatedStatusModels(
variant,
{ timeoutMs = LLM_REQUEST_TIMEOUT_MS } = {},
) {
const response = await fetchWithTimeout(
"/api/backends/chat-completions/status",
{
method: "POST",
headers: getRequestHeaders(),
body: JSON.stringify(variant.body),
},
timeoutMs,
);
const rawText = await response.text().catch(() => "");
let payload = {};
try {
payload = rawText ? JSON.parse(rawText) : {};
} catch {
payload = {};
}
if (!response.ok || payload?.error) {
throw new Error(
extractErrorMessageFromPayload(payload) ||
rawText ||
response.statusText ||
`HTTP ${response.status}`,
);
}
return {
payload,
models: normalizeModelList(extractModelListPayload(payload)),
};
}
function extractContentFromResponsePayload(payload) {
if (typeof payload === "string") {
return payload;
@@ -1508,37 +1605,32 @@ export async function fetchMemoryLLMModels() {
};
}
const variants = buildDedicatedStatusRequestVariants(config);
const errors = [];
try {
const response = await fetch("/api/backends/chat-completions/status", {
method: "POST",
headers: getRequestHeaders(),
body: JSON.stringify({
chat_completion_source: chat_completion_sources.OPENAI,
reverse_proxy: config.apiUrl,
proxy_password: config.apiKey || "",
}),
});
const payload = await response.json().catch(() => ({}));
if (!response.ok) {
const message = payload?.error || payload?.message || response.statusText;
return {
success: false,
models: [],
error: message || `HTTP ${response.status}`,
};
for (const variant of variants) {
try {
const result = await requestDedicatedStatusModels(variant, {
timeoutMs: config.timeoutMs,
});
if (result.models.length > 0) {
return { success: true, models: result.models, error: "" };
}
errors.push(`${variant.mode}:empty`);
} catch (error) {
errors.push(`${variant.mode}:${String(error?.message || error)}`);
}
}
const models = normalizeModelList(payload?.data);
if (models.length === 0) {
return {
success: false,
models: [],
error: "未拉取到可用模型,请检查接口是否支持 /models",
};
}
return { success: true, models, error: "" };
return {
success: false,
models: [],
error:
errors.length > 0
? `未拉取到可用模型。尝试结果: ${errors.join(" | ")}`
: "未拉取到可用模型,请检查接口是否支持模型列表接口",
};
} catch (error) {
return { success: false, models: [], error: String(error) };
}

243
tests/llm-model-fetch.mjs Normal file
View File

@@ -0,0 +1,243 @@
import assert from "node:assert/strict";
import { createRequire, registerHooks } from "node:module";
const extensionsShimSource = [
"export const extension_settings = globalThis.__llmModelFetchExtensionSettings || {};",
"export function getContext() {",
" return null;",
"}",
].join("\n");
const scriptShimSource = [
"export function getRequestHeaders() {",
" return { 'Content-Type': 'application/json' };",
"}",
].join("\n");
const openAiShimSource = [
"export const chat_completion_sources = { CUSTOM: 'custom', OPENAI: 'openai' };",
"export async function sendOpenAIRequest(...args) {",
" if (typeof globalThis.__llmModelFetchSendOpenAIRequest === 'function') {",
" return await globalThis.__llmModelFetchSendOpenAIRequest(...args);",
" }",
" return { choices: [{ message: { content: '{}' } }] };",
"}",
].join("\n");
registerHooks({
resolve(specifier, context, nextResolve) {
if (
specifier === "../../../extensions.js" ||
specifier === "../../../../extensions.js"
) {
return {
shortCircuit: true,
url: `data:text/javascript,${encodeURIComponent(extensionsShimSource)}`,
};
}
if (specifier === "../../../../script.js") {
return {
shortCircuit: true,
url: `data:text/javascript,${encodeURIComponent(scriptShimSource)}`,
};
}
if (specifier === "../../../openai.js") {
return {
shortCircuit: true,
url: `data:text/javascript,${encodeURIComponent(openAiShimSource)}`,
};
}
return nextResolve(specifier, context);
},
});
const require = createRequire(import.meta.url);
const originalRequire = globalThis.require;
const originalExtensionSettings = globalThis.__llmModelFetchExtensionSettings;
const originalSendOpenAIRequest = globalThis.__llmModelFetchSendOpenAIRequest;
globalThis.__llmModelFetchExtensionSettings = {
st_bme: {},
};
globalThis.require = require;
const { createDefaultTaskProfiles } = await import("../prompt-profiles.js");
const llm = await import("../llm.js");
const extensionsApi = await import("../../../../extensions.js");
if (originalRequire === undefined) {
delete globalThis.require;
} else {
globalThis.require = originalRequire;
}
if (originalExtensionSettings === undefined) {
delete globalThis.__llmModelFetchExtensionSettings;
} else {
globalThis.__llmModelFetchExtensionSettings = originalExtensionSettings;
}
if (originalSendOpenAIRequest === undefined) {
delete globalThis.__llmModelFetchSendOpenAIRequest;
} else {
globalThis.__llmModelFetchSendOpenAIRequest = originalSendOpenAIRequest;
}
function buildModelFetchSettings() {
return {
llmApiUrl: "https://example.com/v1",
llmApiKey: "sk-model-secret",
llmModel: "gpt-model-test",
timeoutMs: 5678,
taskProfilesVersion: 3,
taskProfiles: createDefaultTaskProfiles(),
};
}
async function withModelFetchSettings(run) {
const previousSettings = JSON.parse(
JSON.stringify(extensionsApi.extension_settings.st_bme || {}),
);
extensionsApi.extension_settings.st_bme = {
...previousSettings,
...buildModelFetchSettings(),
};
try {
await run();
} finally {
extensionsApi.extension_settings.st_bme = previousSettings;
}
}
async function testFetchMemoryModelsUsesCustomStatusFirst() {
const originalFetch = globalThis.fetch;
const seenBodies = [];
globalThis.fetch = async (_url, options = {}) => {
seenBodies.push(JSON.parse(String(options.body || "{}")));
return new Response(
JSON.stringify({
models: [{ id: "gpt-4.1-mini" }, { id: "gpt-4.1" }],
}),
{
status: 200,
headers: {
"Content-Type": "application/json",
},
},
);
};
try {
await withModelFetchSettings(async () => {
const result = await llm.fetchMemoryLLMModels();
assert.equal(result.success, true);
assert.deepEqual(
result.models.map((item) => item.id),
["gpt-4.1-mini", "gpt-4.1"],
);
assert.equal(seenBodies.length, 1);
assert.equal(seenBodies[0].chat_completion_source, "custom");
assert.equal(seenBodies[0].custom_url, "https://example.com/v1");
assert.match(
String(seenBodies[0].custom_include_headers || ""),
/Authorization:\s+Bearer\s+sk-model-secret/,
);
});
} finally {
globalThis.fetch = originalFetch;
}
}
async function testFetchMemoryModelsFallsBackToLegacyStatus() {
const originalFetch = globalThis.fetch;
const seenBodies = [];
let fetchCount = 0;
globalThis.fetch = async (_url, options = {}) => {
fetchCount += 1;
seenBodies.push(JSON.parse(String(options.body || "{}")));
if (fetchCount === 1) {
return new Response(
JSON.stringify({
error: {
message: "custom source not supported",
},
}),
{
status: 400,
headers: {
"Content-Type": "application/json",
},
},
);
}
return new Response(
JSON.stringify({
data: [{ id: "legacy-openai-model" }],
}),
{
status: 200,
headers: {
"Content-Type": "application/json",
},
},
);
};
try {
await withModelFetchSettings(async () => {
const result = await llm.fetchMemoryLLMModels();
assert.equal(result.success, true);
assert.deepEqual(result.models, [
{ id: "legacy-openai-model", label: "legacy-openai-model" },
]);
assert.equal(fetchCount, 2);
assert.equal(seenBodies[0].chat_completion_source, "custom");
assert.equal(seenBodies[1].chat_completion_source, "openai");
assert.equal(seenBodies[1].reverse_proxy, "https://example.com/v1");
assert.equal(seenBodies[1].proxy_password, "sk-model-secret");
});
} finally {
globalThis.fetch = originalFetch;
}
}
async function testFetchMemoryModelsParsesNestedPayload() {
const originalFetch = globalThis.fetch;
globalThis.fetch = async () =>
new Response(
JSON.stringify({
data: {
models: [{ name: "nested-model-a" }, { label: "nested-model-b" }],
},
}),
{
status: 200,
headers: {
"Content-Type": "application/json",
},
},
);
try {
await withModelFetchSettings(async () => {
const result = await llm.fetchMemoryLLMModels();
assert.equal(result.success, true);
assert.deepEqual(
result.models.map((item) => item.id),
["nested-model-a", "nested-model-b"],
);
});
} finally {
globalThis.fetch = originalFetch;
}
}
await testFetchMemoryModelsUsesCustomStatusFirst();
await testFetchMemoryModelsFallsBackToLegacyStatus();
await testFetchMemoryModelsParsesNestedPayload();
console.log("llm-model-fetch tests passed");