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Commit 18d71758 authored by wangsen's avatar wangsen
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Update README.md, requirements, requirements.txt, requirements_wo_ds.txt,... 

Update README.md, requirements, requirements.txt, requirements_wo_ds.txt, test.py, api.py, cli_demo_mp.py, LICENSE.txt, MODEL_LICENSE.txt, finetune_visualglm.py, cli_demo_hf.py, cli_demo.py, web_demo_hf.py, web_demo.py, README_en.md, api_hf.py, temp.json, fewshot-data.zip files
Deleted .gitignore, .gitlab-ci.yml, LICENSE, gatsby-browser.js, gatsby-node.js, gatsby-ssr.js, gatsby-config.js, package-lock.json, package.json, src/components/header.js, src/components/image.js, src/components/layout.css, src/components/layout.js, src/components/seo.js, src/images/gatsby-astronaut.png, src/images/gatsby-icon.png, src/pages/404.js, src/pages/index.js, src/pages/page-2.js files
parent 60c3df39
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Showing with 2570 additions and 887 deletions
requirements.txt 0 → 100644
View file @ 18d71758
SwissArmyTransformer>=0.4.4
#torch>1.10.0
#torchvision
transformers>=4.27.1
mdtex2html
gradio
requirements_wo_ds.txt 0 → 100644
View file @ 18d71758
torch>1.10.0
torchvision
transformers>=4.27.1
mdtex2html
gradio
sentencepiece
tensorboardX
datasets
cpm_kernels
einops
src/components/header.js deleted 100644 → 0
View file @ 60c3df39
import { Link } from "gatsby"
import PropTypes from "prop-types"
import React from "react"
const Header = ({ siteTitle }) => (
<header
style={{
background: `rebeccapurple`,
marginBottom: `1.45rem`,
}}
>
<div
style={{
margin: `0 auto`,
maxWidth: 960,
padding: `1.45rem 1.0875rem`,
}}
>
<h1 style={{ margin: 0 }}>
<Link
to="/"
style={{
color: `white`,
textDecoration: `none`,
}}
>
{siteTitle}
</Link>
</h1>
</div>
</header>
)
Header.propTypes = {
siteTitle: PropTypes.string,
}
Header.defaultProps = {
siteTitle: ``,
}
export default Header
src/components/image.js deleted 100644 → 0
View file @ 60c3df39
import React from "react"
import { useStaticQuery, graphql } from "gatsby"
import Img from "gatsby-image"
/*
* This component is built using `gatsby-image` to automatically serve optimized
* images with lazy loading and reduced file sizes. The image is loaded using a
* `useStaticQuery`, which allows us to load the image from directly within this
* component, rather than having to pass the image data down from pages.
*
* For more information, see the docs:
* - `gatsby-image`: https://gatsby.dev/gatsby-image
* - `useStaticQuery`: https://www.gatsbyjs.org/docs/use-static-query/
*/
const Image = () => {
const data = useStaticQuery(graphql`
query {
placeholderImage: file(relativePath: { eq: "gatsby-astronaut.png" }) {
childImageSharp {
fluid(maxWidth: 300) {
...GatsbyImageSharpFluid
}
}
}
}
`)
return <Img fluid={data.placeholderImage.childImageSharp.fluid} />
}
export default Image
src/components/layout.css deleted 100644 → 0
View file @ 60c3df39
html {
font-family: sans-serif;
-ms-text-size-adjust: 100%;
-webkit-text-size-adjust: 100%;
}
body {
margin: 0;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
}
article,
aside,
details,
figcaption,
figure,
footer,
header,
main,
menu,
nav,
section,
summary {
display: block;
}
audio,
canvas,
progress,
video {
display: inline-block;
}
audio:not([controls]) {
display: none;
height: 0;
}
progress {
vertical-align: baseline;
}
[hidden],
template {
display: none;
}
a {
background-color: transparent;
-webkit-text-decoration-skip: objects;
}
a:active,
a:hover {
outline-width: 0;
}
abbr[title] {
border-bottom: none;
text-decoration: underline;
text-decoration: underline dotted;
}
b,
strong {
font-weight: inherit;
font-weight: bolder;
}
dfn {
font-style: italic;
}
h1 {
font-size: 2em;
margin: 0.67em 0;
}
mark {
background-color: #ff0;
color: #000;
}
small {
font-size: 80%;
}
sub,
sup {
font-size: 75%;
line-height: 0;
position: relative;
vertical-align: baseline;
}
sub {
bottom: -0.25em;
}
sup {
top: -0.5em;
}
img {
border-style: none;
}
svg:not(:root) {
overflow: hidden;
}
code,
kbd,
pre,
samp {
font-family: monospace, monospace;
font-size: 1em;
}
figure {
margin: 1em 40px;
}
hr {
box-sizing: content-box;
height: 0;
overflow: visible;
}
button,
input,
optgroup,
select,
textarea {
font: inherit;
margin: 0;
}
optgroup {
font-weight: 700;
}
button,
input {
overflow: visible;
}
button,
select {
text-transform: none;
}
[type="reset"],
[type="submit"],
button,
html [type="button"] {
-webkit-appearance: button;
}
[type="button"]::-moz-focus-inner,
[type="reset"]::-moz-focus-inner,
[type="submit"]::-moz-focus-inner,
button::-moz-focus-inner {
border-style: none;
padding: 0;
}
[type="button"]:-moz-focusring,
[type="reset"]:-moz-focusring,
[type="submit"]:-moz-focusring,
button:-moz-focusring {
outline: 1px dotted ButtonText;
}
fieldset {
border: 1px solid silver;
margin: 0 2px;
padding: 0.35em 0.625em 0.75em;
}
legend {
box-sizing: border-box;
color: inherit;
display: table;
max-width: 100%;
padding: 0;
white-space: normal;
}
textarea {
overflow: auto;
}
[type="checkbox"],
[type="radio"] {
box-sizing: border-box;
padding: 0;
}
[type="number"]::-webkit-inner-spin-button,
[type="number"]::-webkit-outer-spin-button {
height: auto;
}
[type="search"] {
-webkit-appearance: textfield;
outline-offset: -2px;
}
[type="search"]::-webkit-search-cancel-button,
[type="search"]::-webkit-search-decoration {
-webkit-appearance: none;
}
::-webkit-input-placeholder {
color: inherit;
opacity: 0.54;
}
::-webkit-file-upload-button {
-webkit-appearance: button;
font: inherit;
}
html {
font: 112.5%/1.45em georgia, serif;
box-sizing: border-box;
overflow-y: scroll;
}
* {
box-sizing: inherit;
}
*:before {
box-sizing: inherit;
}
*:after {
box-sizing: inherit;
}
body {
color: hsla(0, 0%, 0%, 0.8);
font-family: georgia, serif;
font-weight: normal;
word-wrap: break-word;
font-kerning: normal;
-moz-font-feature-settings: "kern", "liga", "clig", "calt";
-ms-font-feature-settings: "kern", "liga", "clig", "calt";
-webkit-font-feature-settings: "kern", "liga", "clig", "calt";
font-feature-settings: "kern", "liga", "clig", "calt";
}
img {
max-width: 100%;
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
}
h1 {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
color: inherit;
font-family: -apple-system, BlinkMacSystemFont, Segoe UI, Roboto, Oxygen,
Ubuntu, Cantarell, Fira Sans, Droid Sans, Helvetica Neue, sans-serif;
font-weight: bold;
text-rendering: optimizeLegibility;
font-size: 2.25rem;
line-height: 1.1;
}
h2 {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
color: inherit;
font-family: -apple-system, BlinkMacSystemFont, Segoe UI, Roboto, Oxygen,
Ubuntu, Cantarell, Fira Sans, Droid Sans, Helvetica Neue, sans-serif;
font-weight: bold;
text-rendering: optimizeLegibility;
font-size: 1.62671rem;
line-height: 1.1;
}
h3 {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
color: inherit;
font-family: -apple-system, BlinkMacSystemFont, Segoe UI, Roboto, Oxygen,
Ubuntu, Cantarell, Fira Sans, Droid Sans, Helvetica Neue, sans-serif;
font-weight: bold;
text-rendering: optimizeLegibility;
font-size: 1.38316rem;
line-height: 1.1;
}
h4 {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
color: inherit;
font-family: -apple-system, BlinkMacSystemFont, Segoe UI, Roboto, Oxygen,
Ubuntu, Cantarell, Fira Sans, Droid Sans, Helvetica Neue, sans-serif;
font-weight: bold;
text-rendering: optimizeLegibility;
font-size: 1rem;
line-height: 1.1;
}
h5 {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
color: inherit;
font-family: -apple-system, BlinkMacSystemFont, Segoe UI, Roboto, Oxygen,
Ubuntu, Cantarell, Fira Sans, Droid Sans, Helvetica Neue, sans-serif;
font-weight: bold;
text-rendering: optimizeLegibility;
font-size: 0.85028rem;
line-height: 1.1;
}
h6 {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
color: inherit;
font-family: -apple-system, BlinkMacSystemFont, Segoe UI, Roboto, Oxygen,
Ubuntu, Cantarell, Fira Sans, Droid Sans, Helvetica Neue, sans-serif;
font-weight: bold;
text-rendering: optimizeLegibility;
font-size: 0.78405rem;
line-height: 1.1;
}
hgroup {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
}
ul {
margin-left: 1.45rem;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
list-style-position: outside;
list-style-image: none;
}
ol {
margin-left: 1.45rem;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
list-style-position: outside;
list-style-image: none;
}
dl {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
}
dd {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
}
p {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
}
figure {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
}
pre {
margin-left: 0;
margin-right: 0;
margin-top: 0;
margin-bottom: 1.45rem;
font-size: 0.85rem;
line-height: 1.42;
background: hsla(0, 0%, 0%, 0.04);
border-radius: 3px;
overflow: auto;
word-wrap: normal;
padding: 1.45rem;
}
table {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
font-size: 1rem;
line-height: 1.45rem;
border-collapse: collapse;
width: 100%;
}
fieldset {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
}
blockquote {
margin-left: 1.45rem;
margin-right: 1.45rem;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
}
form {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
}
noscript {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
}
iframe {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
}
hr {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: calc(1.45rem - 1px);
background: hsla(0, 0%, 0%, 0.2);
border: none;
height: 1px;
}
address {
margin-left: 0;
margin-right: 0;
margin-top: 0;
padding-bottom: 0;
padding-left: 0;
padding-right: 0;
padding-top: 0;
margin-bottom: 1.45rem;
}
b {
font-weight: bold;
}
strong {
font-weight: bold;
}
dt {
font-weight: bold;
}
th {
font-weight: bold;
}
li {
margin-bottom: calc(1.45rem / 2);
}
ol li {
padding-left: 0;
}
ul li {
padding-left: 0;
}
li > ol {
margin-left: 1.45rem;
margin-bottom: calc(1.45rem / 2);
margin-top: calc(1.45rem / 2);
}
li > ul {
margin-left: 1.45rem;
margin-bottom: calc(1.45rem / 2);
margin-top: calc(1.45rem / 2);
}
blockquote *:last-child {
margin-bottom: 0;
}
li *:last-child {
margin-bottom: 0;
}
p *:last-child {
margin-bottom: 0;
}
li > p {
margin-bottom: calc(1.45rem / 2);
}
code {
font-size: 0.85rem;
line-height: 1.45rem;
}
kbd {
font-size: 0.85rem;
line-height: 1.45rem;
}
samp {
font-size: 0.85rem;
line-height: 1.45rem;
}
abbr {
border-bottom: 1px dotted hsla(0, 0%, 0%, 0.5);
cursor: help;
}
acronym {
border-bottom: 1px dotted hsla(0, 0%, 0%, 0.5);
cursor: help;
}
abbr[title] {
border-bottom: 1px dotted hsla(0, 0%, 0%, 0.5);
cursor: help;
text-decoration: none;
}
thead {
text-align: left;
}
td,
th {
text-align: left;
border-bottom: 1px solid hsla(0, 0%, 0%, 0.12);
font-feature-settings: "tnum";
-moz-font-feature-settings: "tnum";
-ms-font-feature-settings: "tnum";
-webkit-font-feature-settings: "tnum";
padding-left: 0.96667rem;
padding-right: 0.96667rem;
padding-top: 0.725rem;
padding-bottom: calc(0.725rem - 1px);
}
th:first-child,
td:first-child {
padding-left: 0;
}
th:last-child,
td:last-child {
padding-right: 0;
}
tt,
code {
background-color: hsla(0, 0%, 0%, 0.04);
border-radius: 3px;
font-family: "SFMono-Regular", Consolas, "Roboto Mono", "Droid Sans Mono",
"Liberation Mono", Menlo, Courier, monospace;
padding: 0;
padding-top: 0.2em;
padding-bottom: 0.2em;
}
pre code {
background: none;
line-height: 1.42;
}
code:before,
code:after,
tt:before,
tt:after {
letter-spacing: -0.2em;
content: " ";
}
pre code:before,
pre code:after,
pre tt:before,
pre tt:after {
content: "";
}
@media only screen and (max-width: 480px) {
html {
font-size: 100%;
}
}
src/components/layout.js deleted 100644 → 0
View file @ 60c3df39
/**
* Layout component that queries for data
* with Gatsby's useStaticQuery component
*
* See: https://www.gatsbyjs.org/docs/use-static-query/
*/
import React from "react"
import PropTypes from "prop-types"
import { useStaticQuery, graphql } from "gatsby"
import Header from "./header"
import "./layout.css"
const Layout = ({ children }) => {
const data = useStaticQuery(graphql`
query SiteTitleQuery {
site {
siteMetadata {
title
}
}
}
`)
return (
<>
<Header siteTitle={data.site.siteMetadata.title} />
<div
style={{
margin: `0 auto`,
maxWidth: 960,
padding: `0px 1.0875rem 1.45rem`,
paddingTop: 0,
}}
>
<main>{children}</main>
<footer>
© {new Date().getFullYear()}, Built with
{` `}
<a href="https://www.gatsbyjs.org">Gatsby</a>
</footer>
</div>
</>
)
}
Layout.propTypes = {
children: PropTypes.node.isRequired,
}
export default Layout
src/components/seo.js deleted 100644 → 0
View file @ 60c3df39
/**
* SEO component that queries for data with
* Gatsby's useStaticQuery React hook
*
* See: https://www.gatsbyjs.org/docs/use-static-query/
*/
import React from "react"
import PropTypes from "prop-types"
import Helmet from "react-helmet"
import { useStaticQuery, graphql } from "gatsby"
function SEO({ description, lang, meta, title }) {
const { site } = useStaticQuery(
graphql`
query {
site {
siteMetadata {
title
description
author
}
}
}
`
)
const metaDescription = description || site.siteMetadata.description
return (
<Helmet
htmlAttributes={{
lang,
}}
title={title}
titleTemplate={`%s | ${site.siteMetadata.title}`}
meta={[
{
name: `description`,
content: metaDescription,
},
{
property: `og:title`,
content: title,
},
{
property: `og:description`,
content: metaDescription,
},
{
property: `og:type`,
content: `website`,
},
{
name: `twitter:card`,
content: `summary`,
},
{
name: `twitter:creator`,
content: site.siteMetadata.author,
},
{
name: `twitter:title`,
content: title,
},
{
name: `twitter:description`,
content: metaDescription,
},
].concat(meta)}
/>
)
}
SEO.defaultProps = {
lang: `en`,
meta: [],
description: ``,
}
SEO.propTypes = {
description: PropTypes.string,
lang: PropTypes.string,
meta: PropTypes.arrayOf(PropTypes.object),
title: PropTypes.string.isRequired,
}
export default SEO
src/pages/404.js deleted 100644 → 0
View file @ 60c3df39
import React from "react"
import Layout from "../components/layout"
import SEO from "../components/seo"
const NotFoundPage = () => (
<Layout>
<SEO title="404: Not found" />
<h1>NOT FOUND</h1>
<p>You just hit a route that doesn&#39;t exist... the sadness.</p>
</Layout>
)
export default NotFoundPage
src/pages/index.js deleted 100644 → 0
View file @ 60c3df39
import React from "react"
import { Link } from "gatsby"
import Layout from "../components/layout"
import Image from "../components/image"
import SEO from "../components/seo"
const IndexPage = () => (
<Layout>
<SEO title="Home" />
<h1>Hi people</h1>
<p>Welcome to your new Gatsby site.</p>
<p>Now go build something great.</p>
<div style={{ maxWidth: `300px`, marginBottom: `1.45rem` }}>
<Image />
</div>
<Link to="/page-2/">Go to page 2</Link>
</Layout>
)
export default IndexPage
src/pages/page-2.js deleted 100644 → 0
View file @ 60c3df39
import React from "react"
import { Link } from "gatsby"
import Layout from "../components/layout"
import SEO from "../components/seo"
const SecondPage = () => (
<Layout>
<SEO title="Page two" />
<h1>Hi from the second page</h1>
<p>Welcome to page 2</p>
<Link to="/">Go back to the homepage</Link>
</Layout>
)
export default SecondPage
temp.json 0 → 100644
View file @ 18d71758
This diff is collapsed.
test.py 0 → 100644
View file @ 18d71758
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("/data", trust_remote_code=True)
model = AutoModel.from_pretrained("/data/", trust_remote_code=True).half().cuda()
image_path = "/data/000000546717.jpg"
response, history = model.chat(tokenizer, image_path, "描述这张图片。", history=[])
print(response)
response, history = model.chat(tokenizer, image_path, "这张图片可能是在什么场所拍摄的？", history=history)
print(response)
web_demo.py 0 → 100644
View file @ 18d71758
#!/usr/bin/env python
import gradio as gr
from PIL import Image
import os
import json
from model import is_chinese, get_infer_setting, generate_input, chat
import torch
def generate_text_with_image(input_text, image, history=[], request_data=dict(), is_zh=True):
input_para = {
"max_length": 2048,
"min_length": 50,
"temperature": 0.8,
"top_p": 0.4,
"top_k": 100,
"repetition_penalty": 1.2
}
input_para.update(request_data)
input_data = generate_input(input_text, image, history, input_para, image_is_encoded=False)
input_image, gen_kwargs = input_data['input_image'], input_data['gen_kwargs']
with torch.no_grad():
answer, history, _ = chat(None, model, tokenizer, input_text, history=history, image=input_image, \
max_length=gen_kwargs['max_length'], top_p=gen_kwargs['top_p'], \
top_k = gen_kwargs['top_k'], temperature=gen_kwargs['temperature'], english=not is_zh)
return answer
def request_model(input_text, temperature, top_p, image_prompt, result_previous):
result_text = [(ele[0], ele[1]) for ele in result_previous]
for i in range(len(result_text)-1, -1, -1):
if result_text[i][0] == "" or result_text[i][1] == "":
del result_text[i]
print(f"history {result_text}")
is_zh = is_chinese(input_text)
if image_prompt is None:
if is_zh:
result_text.append((input_text, '图片为空！请上传图片并重试。'))
else:
result_text.append((input_text, 'Image empty! Please upload a image and retry.'))
return input_text, result_text
elif input_text == "":
result_text.append((input_text, 'Text empty! Please enter text and retry.'))
return "", result_text
request_para = {"temperature": temperature, "top_p": top_p}
image = Image.open(image_prompt)
try:
answer = generate_text_with_image(input_text, image, result_text.copy(), request_para, is_zh)
except Exception as e:
print(f"error: {e}")
if is_zh:
result_text.append((input_text, '超时！请稍等几分钟再重试。'))
else:
result_text.append((input_text, 'Timeout! Please wait a few minutes and retry.'))
return "", result_text
result_text.append((input_text, answer))
print(result_text)
return "", result_text
DESCRIPTION = '''# <a href="https://github.com/THUDM/VisualGLM-6B">VisualGLM</a>'''
MAINTENANCE_NOTICE1 = 'Hint 1: If the app report "Something went wrong, connection error out", please turn off your proxy and retry.\nHint 2: If you upload a large size of image like 10MB, it may take some time to upload and process. Please be patient and wait.'
MAINTENANCE_NOTICE2 = '提示1: 如果应用报了“Something went wrong, connection error out”的错误，请关闭代理并重试。\n提示2: 如果你上传了很大的图片，比如10MB大小，那将需要一些时间来上传和处理，请耐心等待。'
NOTES = 'This app is adapted from <a href="https://github.com/THUDM/VisualGLM-6B">https://github.com/THUDM/VisualGLM-6B</a>. It would be recommended to check out the repo if you want to see the detail of our model and training process.'
def clear_fn(value):
return "", [("", "Hi, What do you want to know about this image?")], None
def clear_fn2(value):
return [("", "Hi, What do you want to know about this image?")]
def main(args):
gr.close_all()
global model, tokenizer
model, tokenizer = get_infer_setting(gpu_device=0, quant=args.quant)
with gr.Blocks(css='style.css') as demo:
gr.Markdown(DESCRIPTION)
with gr.Row():
with gr.Column(scale=4.5):
with gr.Group():
input_text = gr.Textbox(label='Input Text', placeholder='Please enter text prompt below and press ENTER.')
with gr.Row():
run_button = gr.Button('Generate')
clear_button = gr.Button('Clear')
image_prompt = gr.Image(type="filepath", label="Image Prompt", value=None)
with gr.Row():
temperature = gr.Slider(maximum=1, value=0.8, minimum=0, label='Temperature')
top_p = gr.Slider(maximum=1, value=0.4, minimum=0, label='Top P')
with gr.Group():
with gr.Row():
maintenance_notice = gr.Markdown(MAINTENANCE_NOTICE1)
with gr.Column(scale=5.5):
result_text = gr.components.Chatbot(label='Multi-round conversation History', value=[("", "Hi, What do you want to know about this image?")]).style(height=550)
gr.Markdown(NOTES)
print(gr.__version__)
run_button.click(fn=request_model,inputs=[input_text, temperature, top_p, image_prompt, result_text],
outputs=[input_text, result_text])
input_text.submit(fn=request_model,inputs=[input_text, temperature, top_p, image_prompt, result_text],
outputs=[input_text, result_text])
clear_button.click(fn=clear_fn, inputs=clear_button, outputs=[input_text, result_text, image_prompt])
image_prompt.upload(fn=clear_fn2, inputs=clear_button, outputs=[result_text])
image_prompt.clear(fn=clear_fn2, inputs=clear_button, outputs=[result_text])
print(gr.__version__)
demo.queue(concurrency_count=10)
demo.launch(share=args.share)
if __name__ == '__main__':
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--quant", choices=[8, 4], type=int, default=None)
parser.add_argument("--share", action="store_true")
args = parser.parse_args()
main(args)
\ No newline at end of file
web_demo_hf.py 0 → 100644
View file @ 18d71758
from transformers import AutoModel, AutoTokenizer
import gradio as gr
import mdtex2html
import torch
"""Override Chatbot.postprocess"""
def postprocess(self, y):
if y is None:
return []
for i, (message, response) in enumerate(y):
y[i] = (
None if message is None else mdtex2html.convert((message)),
None if response is None else mdtex2html.convert(response),
)
return y
gr.Chatbot.postprocess = postprocess
def parse_text(text):
"""copy from https://github.com/GaiZhenbiao/ChuanhuChatGPT/"""
lines = text.split("\n")
lines = [line for line in lines if line != ""]
count = 0
for i, line in enumerate(lines):
if "```" in line:
count += 1
items = line.split('`')
if count % 2 == 1:
lines[i] = f'<pre><code class="language-{items[-1]}">'
else:
lines[i] = f'<br></code></pre>'
else:
if i > 0:
if count % 2 == 1:
line = line.replace("`", "\`")
line = line.replace("<", "&lt;")
line = line.replace(">", "&gt;")
line = line.replace(" ", "&nbsp;")
line = line.replace("*", "&ast;")
line = line.replace("_", "&lowbar;")
line = line.replace("-", "&#45;")
line = line.replace(".", "&#46;")
line = line.replace("!", "&#33;")
line = line.replace("(", "&#40;")
line = line.replace(")", "&#41;")
line = line.replace("$", "&#36;")
lines[i] = "<br>"+line
text = "".join(lines)
return text
def predict(input, image_path, chatbot, max_length, top_p, temperature, history):
if image_path is None:
return [(input, "图片不能为空。请重新上传图片并重试。")], []
chatbot.append((parse_text(input), ""))
with torch.no_grad():
for response, history in model.stream_chat(tokenizer, image_path, input, history, max_length=max_length, top_p=top_p,
temperature=temperature):
chatbot[-1] = (parse_text(input), parse_text(response))
yield chatbot, history
def predict_new_image(image_path, chatbot, max_length, top_p, temperature):
input, history = "描述这张图片。", []
chatbot.append((parse_text(input), ""))
with torch.no_grad():
for response, history in model.stream_chat(tokenizer, image_path, input, history, max_length=max_length,
top_p=top_p,
temperature=temperature):
chatbot[-1] = (parse_text(input), parse_text(response))
yield chatbot, history
def reset_user_input():
return gr.update(value='')
def reset_state():
return None, [], []
DESCRIPTION = '''<h1 align="center"><a href="https://github.com/THUDM/VisualGLM-6B">VisualGLM</a></h1>'''
MAINTENANCE_NOTICE = 'Hint 1: If the app report "Something went wrong, connection error out", please turn off your proxy and retry.\nHint 2: If you upload a large size of image like 10MB, it may take some time to upload and process. Please be patient and wait.'
NOTES = 'This app is adapted from <a href="https://github.com/THUDM/VisualGLM-6B">https://github.com/THUDM/VisualGLM-6B</a>. It would be recommended to check out the repo if you want to see the detail of our model and training process.'
def main(args):
global model, tokenizer
tokenizer = AutoTokenizer.from_pretrained("THUDM/visualglm-6b", trust_remote_code=True)
if args.quant in [4, 8]:
model = AutoModel.from_pretrained("THUDM/visualglm-6b", trust_remote_code=True).quantize(args.quant).half().cuda()
else:
model = AutoModel.from_pretrained("THUDM/visualglm-6b", trust_remote_code=True).half().cuda()
model = model.eval()
with gr.Blocks(css='style.css') as demo:
gr.HTML(DESCRIPTION)
with gr.Row():
with gr.Column(scale=2):
image_path = gr.Image(type="filepath", label="Image Prompt", value=None).style(height=504)
with gr.Column(scale=4):
chatbot = gr.Chatbot().style(height=480)
with gr.Row():
with gr.Column(scale=2, min_width=100):
max_length = gr.Slider(0, 4096, value=2048, step=1.0, label="Maximum length", interactive=True)
top_p = gr.Slider(0, 1, value=0.4, step=0.01, label="Top P", interactive=True)
temperature = gr.Slider(0, 1, value=0.8, step=0.01, label="Temperature", interactive=True)
with gr.Column(scale=4):
with gr.Box():
with gr.Row():
with gr.Column(scale=2):
user_input = gr.Textbox(show_label=False, placeholder="Input...", lines=4).style(
container=False)
with gr.Column(scale=1, min_width=64):
submitBtn = gr.Button("Submit", variant="primary")
emptyBtn = gr.Button("Clear History")
gr.Markdown(MAINTENANCE_NOTICE + '\n' + NOTES)
history = gr.State([])
submitBtn.click(predict, [user_input, image_path, chatbot, max_length, top_p, temperature, history], [chatbot, history],
show_progress=True)
image_path.upload(predict_new_image, [image_path, chatbot, max_length, top_p, temperature], [chatbot, history],
show_progress=True)
image_path.clear(reset_state, outputs=[image_path, chatbot, history], show_progress=True)
submitBtn.click(reset_user_input, [], [user_input])
emptyBtn.click(reset_state, outputs=[image_path, chatbot, history], show_progress=True)
print(gr.__version__)
demo.queue().launch(share=args.share, inbrowser=True, server_name='0.0.0.0', server_port=8080)
if __name__ == '__main__':
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--quant", choices=[8, 4], type=int, default=None)
parser.add_argument("--share", action="store_true")
args = parser.parse_args()
main(args)
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