Merge pull request #1 from huggingface/julien-openassistant-demo
Browse files- .env.example +8 -0
- README.md +1 -1
- src/lib/Types.ts +30 -0
- src/lib/chat/ChatBox.svelte +3 -1
- src/lib/chat/ChatIntroduction.svelte +31 -21
- src/routes/+page.svelte +51 -28
.env.example
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PUBLIC_HF_TOKEN=
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PUBLIC_ENDPOINT=https://api-inference.huggingface.co/models/OpenAssistant/oasst-sft-1-pythia-12b
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PUBLIC_MODEL_NAME=OpenAssistant/oasst-sft-1-pythia-12b
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PUBLIC_MODEL_TAGLINE=This is the first iteration English supervised-fine-tuning (SFT) model of the <a class="underline" href="https://github.com/LAION-AI/Open-Assistant">Open-Assistant</a> project. It is based on a Pythia 12B that was fine-tuned on ~22k human demonstrations of assistant conversations collected through the <a class="underline" href="https://open-assistant.io/">https://open-assistant.io/</a> human feedback web app before March 7, 2023.
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PUBLIC_DISABLE_INTRO_TILES=true
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PUBLIC_USER_MESSAGE_TOKEN=<|prompter|>
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PUBLIC_ASSISTANT_MESSAGE_TOKEN=<|assistant|>
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PUBLIC_SEP_TOKEN=<|endoftext|>
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README.md
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@@ -1,5 +1,5 @@
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---
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title:
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emoji: 🔥
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colorFrom: purple
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colorTo: purple
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---
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title: oasst-sft-1-pythia-12b
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emoji: 🔥
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colorFrom: purple
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colorTo: purple
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src/lib/Types.ts
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export type Message =
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from: 'user';
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content: string;
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}
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from: 'bot';
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content: string;
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};
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export interface Token {
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id: number;
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text: string;
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logprob: number;
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special: boolean;
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}
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export interface StreamResponse {
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/**
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* Generated token
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*/
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token: Token;
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/**
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* Complete generated text
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* Only available when the generation is finished
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*/
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generated_text?: string;
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}
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src/lib/chat/ChatBox.svelte
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<script lang="ts">
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</script>
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{#if message.from === 'bot'}
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<script lang="ts">
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import type { Message } from '$lib/Types';
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export let message: Message;
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</script>
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{#if message.from === 'bot'}
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src/lib/chat/ChatIntroduction.svelte
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<script lang="ts">
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</script>
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<div class="grid grid-cols-3 gap-3 my-auto">
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<div class="col-span-3 text-center mb-10">
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<h1 class="text-3xl font-bold mb-1.5">{title}</h1>
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<p class="text-lg text-gray-500">
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</div>
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<div class="bg-gray-50 dark:bg-gray-700 rounded-xl text-gray-500 dark:text-gray-400 p-4">
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Overcome
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</div>
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<div class="bg-gray-50 dark:bg-gray-700 rounded-xl text-gray-500 dark:text-gray-400 p-4">
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Create
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</div>
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<div class="bg-gray-50 dark:bg-gray-700 rounded-xl text-gray-500 dark:text-gray-400 p-4">
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Discover
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</div>
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<div class="bg-gray-50 dark:bg-gray-700 rounded-xl text-gray-500 dark:text-gray-400 p-4">
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Overcome
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</div>
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</div>
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<script lang="ts">
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import { PUBLIC_DISABLE_INTRO_TILES, PUBLIC_MODEL_NAME, PUBLIC_MODEL_TAGLINE } from '$env/static/public';
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export let title: string = 'Joi 20B Instruct';
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</script>
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<div class="grid grid-cols-3 gap-3 my-auto">
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<div class="col-span-3 text-center mb-10">
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<h1 class="text-3xl font-bold mb-1.5">{PUBLIC_MODEL_NAME || title}</h1>
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<p class="text-lg text-gray-500">
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{#if PUBLIC_MODEL_TAGLINE}
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{@html PUBLIC_MODEL_TAGLINE}
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{:else}
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Lorem ipsum dolor sit.
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{/if}
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</p>
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</div>
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{#if PUBLIC_DISABLE_INTRO_TILES !== "true"}
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<div class="bg-gray-50 dark:bg-gray-700 rounded-xl text-gray-500 dark:text-gray-400 p-4">
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Create
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</div>
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<div class="bg-gray-50 dark:bg-gray-700 rounded-xl text-gray-500 dark:text-gray-400 p-4">
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Discover
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</div>
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<div class="bg-gray-50 dark:bg-gray-700 rounded-xl text-gray-500 dark:text-gray-400 p-4">
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Overcome
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</div>
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<div class="bg-gray-50 dark:bg-gray-700 rounded-xl text-gray-500 dark:text-gray-400 p-4">
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Create
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</div>
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<div class="bg-gray-50 dark:bg-gray-700 rounded-xl text-gray-500 dark:text-gray-400 p-4">
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Discover
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</div>
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<div class="bg-gray-50 dark:bg-gray-700 rounded-xl text-gray-500 dark:text-gray-400 p-4">
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Overcome
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</div>
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{/if}
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</div>
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src/routes/+page.svelte
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<script lang="ts">
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import { fetchEventSource } from '@microsoft/fetch-event-source';
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import ChatBox from '$lib/chat/ChatBox.svelte';
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import ChatIntroduction from '$lib/chat/ChatIntroduction.svelte';
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-
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-
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content: string;
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}
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from: 'bot';
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content: string;
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};
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let messages: Message[] = [];
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let message = '';
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function onWrite() {
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messages = [...messages, { from: 'user', content: message }];
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message = '';
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let incoming = '';
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const inputs =
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messages
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.map(
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method: 'POST',
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headers: {
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Accept: 'text/event-stream',
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'Content-Type': 'application/json'
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},
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body: JSON.stringify({
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inputs: inputs,
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parameters: {
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-
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}
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}),
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async onopen(response) {
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if (response.ok && response.headers.get('content-type') === 'text/event-stream') {
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messages = [...messages, { from: 'bot', content:
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} else {
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console.error('error opening the SSE endpoint');
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}
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},
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onmessage(msg) {
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const data = JSON.parse(msg.data);
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// console.log(data);
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}
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});
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}
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>
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<div class="flex-none sticky top-0 relative p-3 flex flex-col">
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<button
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class="border px-12 py-2.5 rounded-lg border shadow bg-white dark:bg-gray-700 dark:border-gray-600"
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>New Chat</button
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>
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</div>
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</nav>
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<div class="relative h-screen">
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<div class="overflow-y-auto h-full">
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<div class="max-w-3xl xl:max-w-4xl mx-auto px-5 pt-6 flex flex-col gap-8 h-full">
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{#each messages as message}
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<ChatBox {message} />
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{:else}
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<ChatIntroduction
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{/each}
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<div class="h-32 flex-none" />
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</div>
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<script lang="ts">
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import { afterUpdate } from 'svelte';
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import { fetchEventSource } from '@microsoft/fetch-event-source';
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import ChatBox from '$lib/chat/ChatBox.svelte';
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import ChatIntroduction from '$lib/chat/ChatIntroduction.svelte';
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import type { Message, StreamResponse } from '$lib/Types';
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import {
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PUBLIC_ASSISTANT_MESSAGE_TOKEN,
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PUBLIC_ENDPOINT,
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PUBLIC_HF_TOKEN,
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PUBLIC_SEP_TOKEN,
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PUBLIC_USER_MESSAGE_TOKEN
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} from '$env/static/public';
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const userToken = PUBLIC_USER_MESSAGE_TOKEN || '<|prompter|>';
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const assistantToken = PUBLIC_ASSISTANT_MESSAGE_TOKEN || '<|assistant|>';
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const sepToken = PUBLIC_SEP_TOKEN || '<|endoftext|>';
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let messages: Message[] = [];
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let message = '';
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let messagesContainer: HTMLElement;
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afterUpdate(() => {
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messagesContainer.scrollTo(0, messagesContainer.scrollHeight);
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});
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function onWrite() {
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messages = [...messages, { from: 'user', content: message }];
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message = '';
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const inputs =
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messages
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.map(
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(m) =>
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(m.from === 'user' ? userToken + m.content : assistantToken + m.content) +
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(m.content.endsWith(sepToken) ? '' : sepToken)
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)
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.join('') + assistantToken;
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console.log(inputs);
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fetchEventSource(PUBLIC_ENDPOINT, {
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method: 'POST',
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headers: {
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Accept: 'text/event-stream',
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'Content-Type': 'application/json',
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'user-agent': 'chat-ui/0.0.1',
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...(PUBLIC_HF_TOKEN
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? {
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authorization: `Bearer ${PUBLIC_HF_TOKEN}`
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}
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: {})
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},
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body: JSON.stringify({
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inputs: inputs,
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stream: true,
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parameters: {
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do_sample: false,
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max_new_tokens: 500,
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return_full_text: false,
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stop: [],
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truncate: 1000,
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typical_p: 0.2,
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watermark: false,
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details: true
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}
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}),
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async onopen(response) {
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if (response.ok && response.headers.get('content-type') === 'text/event-stream') {
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messages = [...messages, { from: 'bot', content: '' }];
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} else {
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console.error('error opening the SSE endpoint');
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}
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},
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onmessage(msg) {
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const data = JSON.parse(msg.data) as StreamResponse;
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// console.log(data);
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if (!data.token.special) {
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messages.at(-1)!.content += data.token.text;
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messages = messages;
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}
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}
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});
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}
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>
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<div class="flex-none sticky top-0 relative p-3 flex flex-col">
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<button
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on:click={() => location.reload()}
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class="border px-12 py-2.5 rounded-lg border shadow bg-white dark:bg-gray-700 dark:border-gray-600"
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>New Chat</button
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>
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</div>
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</nav>
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<div class="relative h-screen">
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<div class="overflow-y-auto h-full" bind:this={messagesContainer}>
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<div class="max-w-3xl xl:max-w-4xl mx-auto px-5 pt-6 flex flex-col gap-8 h-full">
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{#each messages as message}
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<ChatBox {message} />
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{:else}
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<ChatIntroduction />
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{/each}
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<div class="h-32 flex-none" />
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</div>
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