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spaces-ai-description
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Files changed (5) hide show
  1. .gitignore +1 -0
  2. getDescriptionsAndSave.mjs +75 -0
  3. package-lock.json +770 -0
  4. package.json +17 -0
  5. saveTrendingToJSON.mjs +61 -0
.gitignore ADDED
@@ -0,0 +1 @@
 
 
1
+ node_modules
getDescriptionsAndSave.mjs ADDED
@@ -0,0 +1,75 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import { promises as fs } from "fs";
2
+ import { textGeneration } from "@huggingface/inference";
3
+ import { AutoTokenizer } from "@xenova/transformers";
4
+
5
+ const HF_TOKEN = "";
6
+
7
+ if (!HF_TOKEN) {
8
+ console.error("Please set the HF_TOKEN environment variable");
9
+ process.exit(1);
10
+ }
11
+
12
+ const buildPrompt = (
13
+ appFile
14
+ ) => `Write a short, imperative description of the provided app's purpose. It MUST ALWAYS be under 80 characters and a single-sentence. You can mention some technology names that you extract from the source code.
15
+ Example descriptions: "Remove background from images.", "Generate captions for images using ViT and GPT2.", "Predict the nutritional value of food based on an image of the food." Only answer with the description and nothing else. DON'T ADD ANY EXPLANATIONS.
16
+ The provided app.py file:
17
+ \`\`\`python
18
+ ${appFile}
19
+ \`\`\``;
20
+
21
+ async function readTrendingSpacesFile() {
22
+ const data = await fs.readFile("trendingSpaces.json", "utf8");
23
+ return JSON.parse(data).filter((space) => space.appFile);
24
+ }
25
+
26
+ const extractTextAfterLastInst = (str) => {
27
+ const match = str.match(/\[\/INST\]([^]*?)$/);
28
+ return match ? match[1].replace(/"/g, "").trim() : "";
29
+ };
30
+
31
+ async function processSpaces() {
32
+ const spaces = await readTrendingSpacesFile();
33
+ const tokenizer = await AutoTokenizer.from_pretrained(
34
+ "mistralai/Mistral-7B-Instruct-v0.1"
35
+ );
36
+
37
+ for (const space of spaces) {
38
+ const chat = [{ role: "user", content: buildPrompt(space.appFile) }];
39
+ try {
40
+ const inputs = await tokenizer.apply_chat_template(chat, {
41
+ tokenize: false,
42
+ });
43
+ const result = await textGeneration({
44
+ model: "mistralai/Mixtral-8x7B-Instruct-v0.1",
45
+ accessToken: HF_TOKEN,
46
+ inputs,
47
+ });
48
+ space.ai_description = extractTextAfterLastInst(result.generated_text);
49
+ console.log(
50
+ `Generated text for space ${space.id}: ${space.ai_description}`
51
+ );
52
+ } catch (error) {
53
+ console.error(`Failed to generate text for space ${space.id}: ${error}`);
54
+ }
55
+ }
56
+
57
+ await saveOutputFile(spaces);
58
+ }
59
+
60
+ async function saveOutputFile(spaces) {
61
+ const filteredSpaces = spaces.filter(
62
+ (space) => space.ai_description && space.ai_description.length <= 120
63
+ );
64
+ const sortedSpaces = filteredSpaces.sort((a, b) => b.likes - a.likes);
65
+ const output = sortedSpaces.map(
66
+ ({ id, emoji, likes, ai_description }) =>
67
+ `${id},${emoji},${likes},"${ai_description}"`
68
+ );
69
+ const csvOutput = `id,emoji,likes,ai_description\n${output.join("\n")}`;
70
+ await fs.writeFile("output.csv", csvOutput);
71
+ console.log("CSV output written to file");
72
+ }
73
+
74
+ // Run the process
75
+ processSpaces().catch(console.error);
package-lock.json ADDED
@@ -0,0 +1,770 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ },
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+ }
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package.json ADDED
@@ -0,0 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "dependencies": {
3
+ "@huggingface/inference": "^2.6.6",
4
+ "@xenova/transformers": "^2.16.1"
5
+ },
6
+ "name": "spaces-descriptions",
7
+ "version": "1.0.0",
8
+ "main": "index.js",
9
+ "devDependencies": {},
10
+ "scripts": {
11
+ "fetch-trending": "node saveTrendingToJSON.mjs ",
12
+ "get-descriptions": "node getDescriptionsAndSave.mjs"
13
+ },
14
+ "author": "",
15
+ "license": "ISC",
16
+ "description": ""
17
+ }
saveTrendingToJSON.mjs ADDED
@@ -0,0 +1,61 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import { promises as fs } from "fs";
2
+
3
+ const fetchJson = async (url) => {
4
+ const response = await fetch(url);
5
+ if (!response.ok) throw new Error("Network response was not ok");
6
+ return response.json();
7
+ };
8
+
9
+ const fetchAllPages = async () => {
10
+ const pageNumbers = Array.from({ length: 2 }, (_, i) => i);
11
+ const urls = pageNumbers.map((pageNumber) => {
12
+ const url = new URL("https://huggingface.co/spaces-json");
13
+ url.search = new URLSearchParams({
14
+ p: pageNumber,
15
+ sort: "trending",
16
+ }).toString();
17
+ return url;
18
+ });
19
+ const jsonResponses = await Promise.all(urls.map(fetchJson));
20
+ return jsonResponses.flatMap((json) => json.spaces);
21
+ };
22
+
23
+ const addAppFileToSpaces = async (spaces) => {
24
+ return Promise.all(
25
+ spaces.map(async (space) => {
26
+ try {
27
+ const url = `https://huggingface.co/spaces/${space.id}/resolve/main/app.py`;
28
+ const response = await fetch(url);
29
+ if (response.ok) {
30
+ console.log(`Fetched appFile for space ${space.id}`);
31
+ const appFile = await response.text();
32
+ return { ...space, appFile };
33
+ }
34
+ } catch (error) {
35
+ console.error(
36
+ `Failed to fetch appFile for space ${space.id}: ${error}`
37
+ );
38
+ }
39
+ return space;
40
+ })
41
+ );
42
+ };
43
+
44
+ const saveAllTrendingSpaces = async () => {
45
+ try {
46
+ const spaces = await fetchAllPages();
47
+ const spacesWithAppFile = await addAppFileToSpaces(spaces);
48
+ const publicSpaces = spacesWithAppFile.filter(
49
+ (space) => space.private === false
50
+ );
51
+ await fs.writeFile(
52
+ "trendingSpaces.json",
53
+ JSON.stringify(publicSpaces, null, 2)
54
+ );
55
+ console.log("Data written to file");
56
+ } catch (error) {
57
+ console.error(`An error occurred: ${error}`);
58
+ }
59
+ };
60
+
61
+ saveAllTrendingSpaces();