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Refactor transformers.js usage

This commit is contained in:
Cohee 2023-09-14 23:12:33 +03:00
parent cb8d9ac71b
commit 0cc048cb64
7 changed files with 167 additions and 171 deletions
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2
default/config.conf
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@ -21,6 +21,8 @@ const extras = {
classificationModel: 'Cohee/distilbert-base-uncased-go-emotions-onnx',
// Image captioning model. HuggingFace ID of a model in ONNX format.
captioningModel: 'Xenova/vit-gpt2-image-captioning',
// Feature extraction model. HuggingFace ID of a model in ONNX format.
embeddingModel: 'Xenova/all-mpnet-base-v2,
};
// Request overrides for additional headers

17
server.js
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@ -5250,21 +5250,18 @@ app.post('/get_character_assets_list', jsonParser, async (request, response) =>
// Stable Diffusion generation
require('./src/stable-diffusion').registerEndpoints(app, jsonParser);
// LLM and SD Horde generation
require('./src/horde').registerEndpoints(app, jsonParser);
// Vector storage DB
require('./src/vectors').registerEndpoints(app, jsonParser);
// Chat translation
require('./src/translate').registerEndpoints(app, jsonParser);
// Emotion classification
import('./src/classify.mjs').then(module => {
module.default.registerEndpoints(app, jsonParser);
}).catch(err => {
console.error(err);
});
require('./src/classify').registerEndpoints(app, jsonParser);
// Image captioning
import('./src/caption.mjs').then(module => {
module.default.registerEndpoints(app, jsonParser);
}).catch(err => {
console.error(err);
});
require('./src/caption').registerEndpoints(app, jsonParser);

29
src/caption.js Normal file
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@ -0,0 +1,29 @@
const TASK = 'image-to-text';
/**
* @param {import("express").Express} app
* @param {any} jsonParser
*/
function registerEndpoints(app, jsonParser) {
app.post('/api/extra/caption', jsonParser, async (req, res) => {
try {
const { image } = req.body;
const module = await import('./transformers.mjs');
const rawImage = module.default.getRawImage(image);
const pipe = await module.default.getPipeline(TASK);
const result = await pipe(rawImage);
const text = result[0].generated_text;
console.log('Image caption:', text);
return res.json({ caption: text });
} catch (error) {
console.error(error);
return res.sendStatus(500);
}
});
}
module.exports = {
registerEndpoints,
};

72
src/caption.mjs
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@ -1,72 +0,0 @@
import { pipeline, env, RawImage } from 'sillytavern-transformers';
import path from 'path';
import { getConfig } from './util.js';
// Limit the number of threads to 1 to avoid issues on Android
env.backends.onnx.wasm.numThreads = 1;
// Use WASM from a local folder to avoid CDN connections
env.backends.onnx.wasm.wasmPaths = path.join(process.cwd(), 'dist') + path.sep;
class PipelineAccessor {
/**
* @type {import("sillytavern-transformers").ImageToTextPipeline}
*/
pipe;
async get() {
if (!this.pipe) {
const cache_dir = path.join(process.cwd(), 'cache');
const model = this.getCaptioningModel();
this.pipe = await pipeline('image-to-text', model, { cache_dir, quantized: true });
}
return this.pipe;
}
getCaptioningModel() {
const DEFAULT_MODEL = 'Xenova/vit-gpt2-image-captioning';
try {
const config = getConfig();
const model = config?.extras?.captioningModel;
return model || DEFAULT_MODEL;
} catch (error) {
console.warn('Failed to read config.conf, using default captioning model.');
return DEFAULT_MODEL;
}
}
}
/**
* @param {import("express").Express} app
* @param {any} jsonParser
*/
function registerEndpoints(app, jsonParser) {
const pipelineAccessor = new PipelineAccessor();
app.post('/api/extra/caption', jsonParser, async (req, res) => {
try {
const { image } = req.body;
// base64 string to blob
const buffer = Buffer.from(image, 'base64');
const byteArray = new Uint8Array(buffer);
const blob = new Blob([byteArray]);
const rawImage = await RawImage.fromBlob(blob);
const pipe = await pipelineAccessor.get();
const result = await pipe(rawImage);
const text = result[0].generated_text;
console.log('Image caption:', text);
return res.json({ caption: text });
} catch (error) {
console.error(error);
return res.sendStatus(500);
}
});
}
export default {
registerEndpoints,
};

53
src/classify.js Normal file
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@ -0,0 +1,53 @@
const TASK = 'text-classification';
/**
* @param {import("express").Express} app
* @param {any} jsonParser
*/
function registerEndpoints(app, jsonParser) {
const cacheObject = {};
app.post('/api/extra/classify/labels', jsonParser, async (req, res) => {
try {
const module = await import('./transformers.mjs');
const pipe = await module.default.getPipeline(TASK);
const result = Object.keys(pipe.model.config.label2id);
return res.json({ labels: result });
} catch (error) {
console.error(error);
return res.sendStatus(500);
}
});
app.post('/api/extra/classify', jsonParser, async (req, res) => {
try {
const { text } = req.body;
async function getResult(text) {
if (cacheObject.hasOwnProperty(text)) {
return cacheObject[text];
} else {
const module = await import('./transformers.mjs');
const pipe = await module.default.getPipeline(TASK);
const result = await pipe(text, { topk: 5 });
result.sort((a, b) => b.score - a.score);
cacheObject[text] = result;
return result;
}
}
console.log('Classify input:', text);
const result = await getResult(text);
console.log('Classify output:', result);
return res.json({ classification: result });
} catch (error) {
console.error(error);
return res.sendStatus(500);
}
});
}
module.exports = {
registerEndpoints,
};

89
src/classify.mjs
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@ -1,89 +0,0 @@
import { pipeline, env } from 'sillytavern-transformers';
import path from 'path';
import { getConfig } from './util.js';
// Limit the number of threads to 1 to avoid issues on Android
env.backends.onnx.wasm.numThreads = 1;
// Use WASM from a local folder to avoid CDN connections
env.backends.onnx.wasm.wasmPaths = path.join(process.cwd(), 'dist') + path.sep;
class PipelineAccessor {
/**
* @type {import("sillytavern-transformers").TextClassificationPipeline}
*/
pipe;
async get() {
if (!this.pipe) {
const cache_dir = path.join(process.cwd(), 'cache');
const model = this.getClassificationModel();
this.pipe = await pipeline('text-classification', model, { cache_dir, quantized: true });
}
return this.pipe;
}
getClassificationModel() {
const DEFAULT_MODEL = 'Cohee/distilbert-base-uncased-go-emotions-onnx';
try {
const config = getConfig();
const model = config?.extras?.classificationModel;
return model || DEFAULT_MODEL;
} catch (error) {
console.warn('Failed to read config.conf, using default classification model.');
return DEFAULT_MODEL;
}
}
}
/**
* @param {import("express").Express} app
* @param {any} jsonParser
*/
function registerEndpoints(app, jsonParser) {
const cacheObject = {};
const pipelineAccessor = new PipelineAccessor();
app.post('/api/extra/classify/labels', jsonParser, async (req, res) => {
try {
const pipe = await pipelineAccessor.get();
const result = Object.keys(pipe.model.config.label2id);
return res.json({ labels: result });
} catch (error) {
console.error(error);
return res.sendStatus(500);
}
});
app.post('/api/extra/classify', jsonParser, async (req, res) => {
try {
const { text } = req.body;
async function getResult(text) {
if (cacheObject.hasOwnProperty(text)) {
return cacheObject[text];
} else {
const pipe = await pipelineAccessor.get();
const result = await pipe(text, { topk: 5 });
result.sort((a, b) => b.score - a.score);
cacheObject[text] = result;
return result;
}
}
console.log('Classify input:', text);
const result = await getResult(text);
console.log('Classify output:', result);
return res.json({ classification: result });
} catch (error) {
console.error(error);
return res.sendStatus(500);
}
});
}
export default {
registerEndpoints,
};

76
src/transformers.mjs Normal file
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@ -0,0 +1,76 @@
import { pipeline, env, RawImage } from 'sillytavern-transformers';
import { getConfig } from './util.js';
import path from 'path';
import _ from 'lodash';
configureTransformers();
function configureTransformers() {
// Limit the number of threads to 1 to avoid issues on Android
env.backends.onnx.wasm.numThreads = 1;
// Use WASM from a local folder to avoid CDN connections
env.backends.onnx.wasm.wasmPaths = path.join(process.cwd(), 'dist') + path.sep;
}
const tasks = {
'text-classification': {
defaultModel: 'Cohee/distilbert-base-uncased-go-emotions-onnx',
pipeline: null,
configField: 'extras.classificationModel',
},
'image-to-text': {
defaultModel: 'Xenova/vit-gpt2-image-captioning',
pipeline: null,
configField: 'extras.captioningModel',
},
'feature-extraction': {
defaultModel: 'Xenova/all-mpnet-base-v2',
pipeline: null,
configField: 'extras.embeddingModel',
},
}
async function getRawImage(image) {
const buffer = Buffer.from(image, 'base64');
const byteArray = new Uint8Array(buffer);
const blob = new Blob([byteArray]);
const rawImage = await RawImage.fromBlob(blob);
return rawImage;
}
function getModelForTask(task) {
const defaultModel = tasks[task].defaultModel;
try {
const config = getConfig();
const model = _.get(config, tasks[task].configField, null);
return model || defaultModel;
} catch (error) {
console.warn('Failed to read config.conf, using default classification model.');
return defaultModel;
}
}
function progressCallback() {
// TODO: Implement progress callback
// console.log(arguments);
}
async function getPipeline(task) {
if (tasks[task].pipeline) {
return tasks[task].pipeline;
}
const cache_dir = path.join(process.cwd(), 'cache');
const model = getModelForTask(task);
console.log('Initializing transformers.js pipeline for task', task, 'with model', model);
const instance = await pipeline(task, model, { cache_dir, quantized: true, progress_callback: progressCallback });
tasks[task].pipeline = instance;
return instance;
}
export default {
getPipeline,
getRawImage,
}