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Added optional llm summerization (#498)
Browse files* Added optional llm summerization
* set summery as first 5 words
Co-authored-by: Nathan Sarrazin <sarrazin.nathan@gmail.com>
* delete unused file
* Pass stop sequences properly to TGI (#499)
* Pass stop sequences properly to TGI
* fix types
* Add a job in release action that updates the .env in prod (#493)
* Add a workflow that updates the .env in prod
* move update env to release workflow
* version bumps on actons
* flipped config
* black
* Save user message on request (#337) (#492)
Closes #337
* bump inference version
* lint
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Co-authored-by: Nathan Sarrazin <sarrazin.nathan@gmail.com>
- .env +1 -0
- src/lib/server/summarize.ts +4 -0
.env
CHANGED
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@@ -87,6 +87,7 @@ PUBLIC_APP_ASSETS=chatui # used to find logos & favicons in static/$PUBLIC_APP_A
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PUBLIC_APP_COLOR=blue # can be any of tailwind colors: https://tailwindcss.com/docs/customizing-colors#default-color-palette
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PUBLIC_APP_DATA_SHARING=#set to 1 to enable options & text regarding data sharing
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PUBLIC_APP_DISCLAIMER=#set to 1 to show a disclaimer on login page
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# PUBLIC_APP_NAME=HuggingChat
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# PUBLIC_APP_ASSETS=huggingchat
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PUBLIC_APP_COLOR=blue # can be any of tailwind colors: https://tailwindcss.com/docs/customizing-colors#default-color-palette
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PUBLIC_APP_DATA_SHARING=#set to 1 to enable options & text regarding data sharing
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PUBLIC_APP_DISCLAIMER=#set to 1 to show a disclaimer on login page
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LLM_SUMMERIZATION=true
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# PUBLIC_APP_NAME=HuggingChat
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# PUBLIC_APP_ASSETS=huggingchat
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src/lib/server/summarize.ts
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@@ -1,8 +1,12 @@
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import { buildPrompt } from "$lib/buildPrompt";
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import { generateFromDefaultEndpoint } from "$lib/server/generateFromDefaultEndpoint";
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import { defaultModel } from "$lib/server/models";
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export async function summarize(prompt: string) {
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const userPrompt = `Please summarize the following message: \n` + prompt;
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const summaryPrompt = await buildPrompt({
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import { buildPrompt } from "$lib/buildPrompt";
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import { generateFromDefaultEndpoint } from "$lib/server/generateFromDefaultEndpoint";
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import { defaultModel } from "$lib/server/models";
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import { LLM_SUMMERIZATION } from "$env/static/private";
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export async function summarize(prompt: string) {
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if (!LLM_SUMMERIZATION) {
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return prompt.split(/\s+/g).slice(0, 5).join(" ");
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}
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const userPrompt = `Please summarize the following message: \n` + prompt;
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const summaryPrompt = await buildPrompt({
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