Julian Bilcke
commited on
Commit
·
6b981ec
1
Parent(s):
64dea8b
it works
Browse files- README.md +1 -1
- public/index.html +7 -0
- src/index.mts +11 -6
README.md
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@@ -31,7 +31,7 @@ http://localhost:7860/?prompt=a simple html canvas game where we need to feed ta
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```bash
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nvm use
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npm i
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npm run start
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```
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## Building and running with Docker
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```bash
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nvm use
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npm i
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HF_API_TOKEN=******* HF_END_POINT_URL=https://*******.endpoints.huggingface.cloud npm run start
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```
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## Building and running with Docker
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public/index.html
CHANGED
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@@ -22,6 +22,13 @@
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<p>A space to generate web content using WizardCoder.</p>
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<p>It uses the Hugging Face Endpoints API for inference.</p>
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</div>
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<button
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class="btn disabled:text-stone-400"
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@click="open = true, prompt = promptDraft, state = state === 'stopped' ? 'loading' : 'stopped'"
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<p>A space to generate web content using WizardCoder.</p>
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<p>It uses the Hugging Face Endpoints API for inference.</p>
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</div>
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+
<textarea
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name="promptDraft"
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x-model="promptDraft"
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rows="10"
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placeholder="A simple page to compute the bmi, using kg and meters"
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class="input input-bordered w-full rounded text-lg text-stone-500 bg-stone-300 font-mono h-48"
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></textarea>
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<button
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class="btn disabled:text-stone-400"
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@click="open = true, prompt = promptDraft, state = state === 'stopped' ? 'loading' : 'stopped'"
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src/index.mts
CHANGED
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@@ -4,7 +4,8 @@ import { HfInference } from '@huggingface/inference'
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import { daisy } from "./daisy.mts"
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const hfi = new HfInference(process.env.HF_API_TOKEN)
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-
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const hf = hfi.endpoint(process.env.HF_ENDPOINT_URL)
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// define the CSS and JS dependencies
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@@ -23,9 +24,9 @@ const app = express()
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const port = 7860
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const minPromptSize = 16 // if you change this, you will need to also change in public/index.html
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-
const timeoutInSec =
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console.log("timeout set to
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app.use(express.static("public"))
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@@ -92,12 +93,12 @@ app.get("/app", async (req, res) => {
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const finalPrompt = `# Task
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Generate the following: ${req.query.prompt}
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# API Documentation
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${daisy}
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# Guidelines
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- Never repeat the instruction, instead directly write the final code
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- Use a color scheme consistent with the brief and theme
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- You
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- All the JS code will be written directly inside the page, using <script type="text/javascript">...</script>
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- You MUST use English, not Latin! (I repeat: do NOT write lorem ipsum!)
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- No need to write code comments, so please make the code compact (short function names etc)
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@@ -109,7 +110,7 @@ ${prefix}`
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let result = ''
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for await (const output of hf.textGenerationStream({
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inputs: finalPrompt,
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parameters: { max_new_tokens:
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})) {
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if (!pending.queue.includes(id)) {
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break
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if (result.includes('</html>')) {
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break
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}
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}
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endRequest(id, `normal end of the LLM stream for request ${id}`)
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import { daisy } from "./daisy.mts"
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const hfi = new HfInference(process.env.HF_API_TOKEN)
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console.log('HF_ENDPOINT_URL:', process.env.HF_ENDPOINT_URL)
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const hf = hfi.endpoint(process.env.HF_ENDPOINT_URL)
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// define the CSS and JS dependencies
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const port = 7860
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const minPromptSize = 16 // if you change this, you will need to also change in public/index.html
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const timeoutInSec = 30 * 60
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console.log("timeout set to 30 minutes")
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app.use(express.static("public"))
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const finalPrompt = `# Task
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Generate the following: ${req.query.prompt}
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# API Documentation
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${daisy}
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# Guidelines
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- Never repeat the instruction, instead directly write the final code
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- Use a color scheme consistent with the brief and theme
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- You must use Tailwind CSS and Daisy UI for the CSS classes, vanilla JS and Alpine.js for the JS.
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- All the JS code will be written directly inside the page, using <script type="text/javascript">...</script>
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- You MUST use English, not Latin! (I repeat: do NOT write lorem ipsum!)
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- No need to write code comments, so please make the code compact (short function names etc)
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let result = ''
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for await (const output of hf.textGenerationStream({
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inputs: finalPrompt,
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parameters: { max_new_tokens: 1024 }
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})) {
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if (!pending.queue.includes(id)) {
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break
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if (result.includes('</html>')) {
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break
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}
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if (result.includes('</enbd>') || result.includes('<|assistant|>')) {
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// it ended, but we probably don't have a valid HTML
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break
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}
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}
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endRequest(id, `normal end of the LLM stream for request ${id}`)
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