chat-ui_test / src /lib /buildPrompt.ts
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nsarrazin HF staff
Add support for tgi multimodal models (#531)
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import type { BackendModel } from "./server/models";
import type { Message } from "./types/Message";
import { format } from "date-fns";
import type { WebSearch } from "./types/WebSearch";
import { downloadFile } from "./server/files/downloadFile";
import type { Conversation } from "./types/Conversation";
interface buildPromptOptions {
messages: Pick<Message, "from" | "content" | "files">[];
id?: Conversation["_id"];
model: BackendModel;
locals?: App.Locals;
webSearch?: WebSearch;
preprompt?: string;
files?: File[];
}
export async function buildPrompt({
messages,
model,
webSearch,
preprompt,
id,
}: buildPromptOptions): Promise<string> {
if (webSearch && webSearch.context) {
const lastMsg = messages.slice(-1)[0];
const messagesWithoutLastUsrMsg = messages.slice(0, -1);
const previousUserMessages = messages.filter((el) => el.from === "user").slice(0, -1);
const previousQuestions =
previousUserMessages.length > 0
? `Previous questions: \n${previousUserMessages
.map(({ content }) => `- ${content}`)
.join("\n")}`
: "";
const currentDate = format(new Date(), "MMMM d, yyyy");
messages = [
...messagesWithoutLastUsrMsg,
{
from: "user",
content: `I searched the web using the query: ${webSearch.searchQuery}. Today is ${currentDate} and here are the results:
=====================
${webSearch.context}
=====================
${previousQuestions}
Answer the question: ${lastMsg.content}
`,
},
];
}
// section to handle potential files input
if (model.multimodal) {
messages = await Promise.all(
messages.map(async (el) => {
let content = el.content;
if (el.from === "user") {
if (el?.files && el.files.length > 0 && id) {
const markdowns = await Promise.all(
el.files.map(async (hash) => {
try {
const { content: image, mime } = await downloadFile(hash, id);
const b64 = image.toString("base64");
return `![](data:${mime};base64,${b64})})`;
} catch (e) {
console.error(e);
}
})
);
content += markdowns.join("\n ");
} else {
// if no image, append an empty white image
content +=
"\n![](data:image/png;base64,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)";
}
}
return { ...el, content };
})
);
}
return (
model
.chatPromptRender({ messages, preprompt })
// Not super precise, but it's truncated in the model's backend anyway
.split(" ")
.slice(-(model.parameters?.truncate ?? 0))
.join(" ")
);
}