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import { openAICompletionToTextGenerationStream } from "./openAICompletionToTextGenerationStream";
import {
openAIChatToTextGenerationSingle,
openAIChatToTextGenerationStream,
} from "./openAIChatToTextGenerationStream";
import type { CompletionCreateParamsStreaming } from "openai/resources/completions";
import type {
ChatCompletionCreateParamsNonStreaming,
ChatCompletionCreateParamsStreaming,
} from "openai/resources/chat/completions";
import { buildPrompt } from "$lib/buildPrompt";
import { config } from "$lib/server/config";
import type { Endpoint } from "../endpoints";
import type OpenAI from "openai";
import { createImageProcessorOptionsValidator, makeImageProcessor } from "../images";
import { prepareMessagesWithFiles } from "$lib/server/textGeneration/utils/prepareFiles";
// uuid import removed (no tool call ids)
export const endpointOAIParametersSchema = z.object({
weight: z.number().int().positive().default(1),
model: z.any(),
type: z.literal("openai"),
baseURL: z.string().url().default("https://api.openai.com/v1"),
// Canonical auth token is OPENAI_API_KEY; keep HF_TOKEN as legacy alias
apiKey: z.string().default(config.OPENAI_API_KEY || config.HF_TOKEN || "sk-"),
completion: z
.union([z.literal("completions"), z.literal("chat_completions")])
.default("chat_completions"),
defaultHeaders: z.record(z.string()).optional(),
defaultQuery: z.record(z.string()).optional(),
extraBody: z.record(z.any()).optional(),
multimodal: z
.object({
image: createImageProcessorOptionsValidator({
supportedMimeTypes: [
// Restrict to the most widely-supported formats
"image/png",
"image/jpeg",
],
preferredMimeType: "image/jpeg",
maxSizeInMB: 1,
maxWidth: 1024,
maxHeight: 1024,
}),
})
.default({}),
/* enable use of max_completion_tokens in place of max_tokens */
useCompletionTokens: z.boolean().default(false),
streamingSupported: z.boolean().default(true),
});
export async function endpointOai(
input: z.input<typeof endpointOAIParametersSchema>
): Promise<Endpoint> {
const {
baseURL,
apiKey,
completion,
model,
defaultHeaders,
defaultQuery,
multimodal,
extraBody,
useCompletionTokens,
streamingSupported,
} = endpointOAIParametersSchema.parse(input);
let OpenAI;
try {
OpenAI = (await import("openai")).OpenAI;
} catch (e) {
throw new Error("Failed to import OpenAI", { cause: e });
}
// Store router metadata if captured
let routerMetadata: { route?: string; model?: string; provider?: string } = {};
// Custom fetch wrapper to capture response headers for router metadata
const customFetch = async (url: RequestInfo, init?: RequestInit): Promise<Response> => {
const response = await fetch(url, init);
// Capture router headers if present (fallback for non-streaming)
const routeHeader = response.headers.get("X-Router-Route");
const modelHeader = response.headers.get("X-Router-Model");
const providerHeader = response.headers.get("x-inference-provider");
if (routeHeader && modelHeader) {
routerMetadata = {
route: routeHeader,
model: modelHeader,
provider: providerHeader || undefined,
};
} else if (providerHeader) {
// Even without router metadata, capture provider info
routerMetadata = {
provider: providerHeader,
};
}
return response;
};
const openai = new OpenAI({
apiKey: apiKey || "sk-",
baseURL,
defaultHeaders: {
...(config.PUBLIC_APP_NAME === "HuggingChat" && { "User-Agent": "huggingchat" }),
...defaultHeaders,
},
defaultQuery,
fetch: customFetch,
});
const imageProcessor = makeImageProcessor(multimodal.image);
if (completion === "completions") {
return async ({
messages,
preprompt,
generateSettings,
conversationId,
locals,
abortSignal,
}) => {
const prompt = await buildPrompt({
messages,
preprompt,
model,
});
const parameters = { ...model.parameters, ...generateSettings };
const body: CompletionCreateParamsStreaming = {
model: model.id ?? model.name,
prompt,
stream: true,
max_tokens: parameters?.max_tokens,
stop: parameters?.stop,
temperature: parameters?.temperature,
top_p: parameters?.top_p,
frequency_penalty: parameters?.frequency_penalty,
presence_penalty: parameters?.presence_penalty,
};
const openAICompletion = await openai.completions.create(body, {
body: { ...body, ...extraBody },
headers: {
"ChatUI-Conversation-ID": conversationId?.toString() ?? "",
"X-use-cache": "false",
...(locals?.token ? { Authorization: `Bearer ${locals.token}` } : {}),
// Bill to organization if configured (HuggingChat only)
...(config.isHuggingChat && locals?.billingOrganization
? { "X-HF-Bill-To": locals.billingOrganization }
: {}),
},
signal: abortSignal,
});
return openAICompletionToTextGenerationStream(openAICompletion);
};
} else if (completion === "chat_completions") {
return async ({
messages,
preprompt,
generateSettings,
conversationId,
isMultimodal,
locals,
abortSignal,
}) => {
// Format messages for the chat API, handling multimodal content if supported
let messagesOpenAI: OpenAI.Chat.Completions.ChatCompletionMessageParam[] =
await prepareMessagesWithFiles(messages, imageProcessor, isMultimodal ?? model.multimodal);
// Normalize preprompt and handle empty values
const normalizedPreprompt = typeof preprompt === "string" ? preprompt.trim() : "";
// Check if a system message already exists as the first message
const hasSystemMessage = messagesOpenAI.length > 0 && messagesOpenAI[0]?.role === "system";
if (hasSystemMessage) {
// Prepend normalized preprompt to existing system content when non-empty
if (normalizedPreprompt) {
const userSystemPrompt =
(typeof messagesOpenAI[0].content === "string"
? (messagesOpenAI[0].content as string)
: "") || "";
messagesOpenAI[0].content =
normalizedPreprompt + (userSystemPrompt ? "\n\n" + userSystemPrompt : "");
}
} else {
// Insert a system message only if the preprompt is non-empty
if (normalizedPreprompt) {
messagesOpenAI = [{ role: "system", content: normalizedPreprompt }, ...messagesOpenAI];
}
}
// Combine model defaults with request-specific parameters
const parameters = { ...model.parameters, ...generateSettings };
const body = {
model: model.id ?? model.name,
messages: messagesOpenAI,
stream: streamingSupported,
// Support two different ways of specifying token limits depending on the model
...(useCompletionTokens
? { max_completion_tokens: parameters?.max_tokens }
: { max_tokens: parameters?.max_tokens }),
stop: parameters?.stop,
temperature: parameters?.temperature,
top_p: parameters?.top_p,
frequency_penalty: parameters?.frequency_penalty,
presence_penalty: parameters?.presence_penalty,
};
// Handle both streaming and non-streaming responses with appropriate processors
if (streamingSupported) {
const openChatAICompletion = await openai.chat.completions.create(
body as ChatCompletionCreateParamsStreaming,
{
body: { ...body, ...extraBody },
headers: {
"ChatUI-Conversation-ID": conversationId?.toString() ?? "",
"X-use-cache": "false",
...(locals?.token ? { Authorization: `Bearer ${locals.token}` } : {}),
// Bill to organization if configured (HuggingChat only)
...(config.isHuggingChat && locals?.billingOrganization
? { "X-HF-Bill-To": locals.billingOrganization }
: {}),
},
signal: abortSignal,
}
);
return openAIChatToTextGenerationStream(openChatAICompletion, () => routerMetadata);
} else {
const openChatAICompletion = await openai.chat.completions.create(
body as ChatCompletionCreateParamsNonStreaming,
{
body: { ...body, ...extraBody },
headers: {
"ChatUI-Conversation-ID": conversationId?.toString() ?? "",
"X-use-cache": "false",
...(locals?.token ? { Authorization: `Bearer ${locals.token}` } : {}),
// Bill to organization if configured (HuggingChat only)
...(config.isHuggingChat && locals?.billingOrganization
? { "X-HF-Bill-To": locals.billingOrganization }
: {}),
},
signal: abortSignal,
}
);
return openAIChatToTextGenerationSingle(openChatAICompletion, () => routerMetadata);
}
};
} else {
throw new Error("Invalid completion type");
}
}
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