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✨ Add preprompt (#124)
Browse files- .env +1 -0
- src/lib/buildPrompt.ts +6 -1
- src/routes/conversation/[id]/summarize/+server.ts +1 -1
.env
CHANGED
@@ -13,6 +13,7 @@ PUBLIC_DISABLE_INTRO_TILES=false
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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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# [{"endpoint": "https://api-inference.huggingface.co/models/...", authorization: "Bearer hf_<token>", weight: 1}] to load balance
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# Eg if one endpoint has weight 2 and the other has weight 1, the first endpoint will be called twice as often
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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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+
PUBLIC_PREPROMPT="Below are a series of dialogues between various people and an AI assistant. The AI tries to be helpful, polite, honest, sophisticated, emotionally aware, and humble-but-knowledgeable. The assistant is happy to help with almost anything, and will do its best to understand exactly what is needed. It also tries to avoid giving false or misleading information, and it caveats when it isn't entirely sure about the right answer. That said, the assistant is practical and really does its best, and doesn't let caution get too much in the way of being useful."
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# [{"endpoint": "https://api-inference.huggingface.co/models/...", authorization: "Bearer hf_<token>", weight: 1}] to load balance
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# Eg if one endpoint has weight 2 and the other has weight 1, the first endpoint will be called twice as often
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src/lib/buildPrompt.ts
CHANGED
@@ -1,6 +1,7 @@
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import {
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PUBLIC_ASSISTANT_MESSAGE_TOKEN,
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PUBLIC_MAX_INPUT_TOKENS,
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PUBLIC_SEP_TOKEN,
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PUBLIC_USER_MESSAGE_TOKEN,
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} from "$env/static/public";
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@@ -24,5 +25,9 @@ export function buildPrompt(messages: Message[]): string {
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.join("") + PUBLIC_ASSISTANT_MESSAGE_TOKEN;
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// Not super precise, but it's truncated in the model's backend anyway
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-
return
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}
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import {
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PUBLIC_ASSISTANT_MESSAGE_TOKEN,
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PUBLIC_MAX_INPUT_TOKENS,
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PUBLIC_PREPROMPT,
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PUBLIC_SEP_TOKEN,
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PUBLIC_USER_MESSAGE_TOKEN,
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} from "$env/static/public";
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.join("") + PUBLIC_ASSISTANT_MESSAGE_TOKEN;
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// Not super precise, but it's truncated in the model's backend anyway
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return (
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PUBLIC_PREPROMPT +
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"\n-----\n" +
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prompt.split(" ").slice(-parseInt(PUBLIC_MAX_INPUT_TOKENS)).join(" ")
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);
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}
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src/routes/conversation/[id]/summarize/+server.ts
CHANGED
@@ -21,7 +21,7 @@ export async function POST({ params, locals, fetch }) {
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const firstMessage = conversation.messages.find((m) => m.from === "user");
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const userPrompt =
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`
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firstMessage?.content;
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const prompt = buildPrompt([{ from: "user", content: userPrompt }]);
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const firstMessage = conversation.messages.find((m) => m.from === "user");
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const userPrompt =
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`Please summarize the following message as a single sentence of less than 5 words:\n` +
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firstMessage?.content;
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const prompt = buildPrompt([{ from: "user", content: userPrompt }]);
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