mirror of https://github.com/xtekky/gpt4free.git
Serverless webview gui
This commit is contained in:
Heiner Lohaus
parent
b7eee50930
commit
905ced06bd
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@ -1,5 +1,5 @@
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<!DOCTYPE html>
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<html lang="en">
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<html lang="en" data-framework="javascript">
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<head>
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<meta charset="UTF-8">
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@ -10,14 +10,14 @@
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<meta property="og:image" content="https://openai.com/content/images/2022/11/ChatGPT.jpg">
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<meta property="og:description" content="A conversational AI system that listens, learns, and challenges">
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<meta property="og:url" content="https://g4f.ai">
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<link rel="stylesheet" href="/assets/css/style.css">
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<link rel="apple-touch-icon" sizes="180x180" href="/assets/img/apple-touch-icon.png">
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<link rel="icon" type="image/png" sizes="32x32" href="/assets/img/favicon-32x32.png">
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<link rel="icon" type="image/png" sizes="16x16" href="/assets/img/favicon-16x16.png">
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<link rel="manifest" href="/assets/img/site.webmanifest">
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<script src="/assets/js/icons.js"></script>
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<script src="/assets/js/highlightjs-copy.min.js"></script>
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<script src="/assets/js/chat.v1.js" defer></script>
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<link rel="stylesheet" href="/static/css/style.css">
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<link rel="apple-touch-icon" sizes="180x180" href="/static/img/apple-touch-icon.png">
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<link rel="icon" type="image/png" sizes="32x32" href="/static/img/favicon-32x32.png">
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<link rel="icon" type="image/png" sizes="16x16" href="/static/img/favicon-16x16.png">
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<link rel="manifest" href="/static/img/site.webmanifest">
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<script src="/static/js/icons.js"></script>
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<script src="/static/js/highlightjs-copy.min.js"></script>
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<script src="/static/js/chat.v1.js" defer></script>
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<script src="https://cdn.jsdelivr.net/npm/markdown-it@13.0.1/dist/markdown-it.min.js"></script>
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<link rel="stylesheet"
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href="//cdn.jsdelivr.net/gh/highlightjs/cdn-release@11.7.0/build/styles/base16/dracula.min.css">
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@ -38,8 +38,8 @@
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</script>
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<script src="https://unpkg.com/gpt-tokenizer/dist/cl100k_base.js" async></script>
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<script>
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const user_image = '<img src="/assets/img/user.png" alt="your avatar">';
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const gpt_image = '<img src="/assets/img/gpt.png" alt="your avatar">';
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const user_image = '<img src="/static/img/user.png" alt="your avatar">';
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const gpt_image = '<img src="/static/img/gpt.png" alt="your avatar">';
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</script>
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<style>
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.hljs {
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@ -74,8 +74,8 @@
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background: #8b3dff;
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}
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</style>
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<script src="/assets/js/highlight.min.js"></script>
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<script>window.conversation_id = `{{chat_id}}`</script>
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<script src="/static/js/highlight.min.js"></script>
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<script>window.conversation_id = "{{chat_id}}"</script>
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<title>g4f - gui</title>
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</head>
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Before Width: | Height: | Size: 8.7 KiB After Width: | Height: | Size: 8.7 KiB |
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Before Width: | Height: | Size: 17 KiB After Width: | Height: | Size: 17 KiB |
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Before Width: | Height: | Size: 7.8 KiB After Width: | Height: | Size: 7.8 KiB |
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Before Width: | Height: | Size: 499 B After Width: | Height: | Size: 499 B |
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Before Width: | Height: | Size: 1.0 KiB After Width: | Height: | Size: 1.0 KiB |
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Before Width: | Height: | Size: 2.8 KiB After Width: | Height: | Size: 2.8 KiB |
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Before Width: | Height: | Size: 17 KiB After Width: | Height: | Size: 17 KiB |
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@ -1,5 +1,4 @@
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const colorThemes = document.querySelectorAll('[name="theme"]');
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const markdown = window.markdownit();
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const message_box = document.getElementById(`messages`);
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const messageInput = document.getElementById(`message-input`);
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const box_conversations = document.querySelector(`.top`);
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@ -22,8 +21,6 @@ let prompt_lock = false;
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const options = ["switch", "model", "model2", "jailbreak", "patch", "provider", "history"];
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hljs.addPlugin(new CopyButtonPlugin());
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messageInput.addEventListener("blur", () => {
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window.scrollTo(0, 0);
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});
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@ -39,31 +36,29 @@ appStorage = window.localStorage || {
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length: 0
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}
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const markdown = window.markdownit();
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const markdown_render = (content) => {
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return markdown.render(content
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.replaceAll(/<!--.+-->/gm, "")
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.replaceAll(/<!-- generated images start -->[\s\S]+<!-- generated images end -->/gm, "")
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.replaceAll(/<img data-prompt="[^>]+">/gm, "")
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)
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.replaceAll("<a href=", '<a target="_blank" href=')
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.replaceAll('<code>', '<code class="language-plaintext">')
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}
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hljs.addPlugin(new CopyButtonPlugin());
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let typesetPromise = Promise.resolve();
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let timeoutHighlightId;
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const highlight = (container) => {
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if (timeoutHighlightId) clearTimeout(timeoutHighlightId);
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timeoutHighlightId = setTimeout(() => {
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container.querySelectorAll('code:not(.hljs').forEach((el) => {
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if (el.className != "hljs") {
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hljs.highlightElement(el);
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}
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});
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typesetPromise = typesetPromise.then(
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() => MathJax.typesetPromise([container])
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).catch(
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(err) => console.log('Typeset failed: ' + err.message)
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);
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}, 100);
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container.querySelectorAll('code:not(.hljs').forEach((el) => {
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if (el.className != "hljs") {
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hljs.highlightElement(el);
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}
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});
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typesetPromise = typesetPromise.then(
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() => MathJax.typesetPromise([container])
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).catch(
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(err) => console.log('Typeset failed: ' + err.message)
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);
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}
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const register_remove_message = async () => {
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@ -99,47 +94,48 @@ const handle_ask = async () => {
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window.scrollTo(0, 0);
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message = messageInput.value
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if (message.length > 0) {
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messageInput.value = "";
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prompt_lock = true;
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count_input()
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await add_conversation(window.conversation_id, message);
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if ("text" in fileInput.dataset) {
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message += '\n```' + fileInput.dataset.type + '\n';
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message += fileInput.dataset.text;
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message += '\n```'
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}
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let message_index = await add_message(window.conversation_id, "user", message);
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window.token = message_id();
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if (imageInput.dataset.src) URL.revokeObjectURL(imageInput.dataset.src);
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const input = imageInput && imageInput.files.length > 0 ? imageInput : cameraInput
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if (input.files.length > 0) imageInput.dataset.src = URL.createObjectURL(input.files[0]);
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else delete imageInput.dataset.src
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message_box.innerHTML += `
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<div class="message" data-index="${message_index}">
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<div class="user">
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${user_image}
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<i class="fa-solid fa-xmark"></i>
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<i class="fa-regular fa-phone-arrow-up-right"></i>
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</div>
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<div class="content" id="user_${token}">
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<div class="content_inner">
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${markdown_render(message)}
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${imageInput.dataset.src
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? '<img src="' + imageInput.dataset.src + '" alt="Image upload">'
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: ''
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}
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</div>
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<div class="count">${count_words_and_tokens(message, get_selected_model())}</div>
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</div>
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</div>
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`;
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await register_remove_message();
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highlight(message_box);
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await ask_gpt();
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if (message.length <= 0) {
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return;
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}
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messageInput.value = "";
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prompt_lock = true;
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count_input()
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await add_conversation(window.conversation_id, message);
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if ("text" in fileInput.dataset) {
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message += '\n```' + fileInput.dataset.type + '\n';
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message += fileInput.dataset.text;
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message += '\n```'
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}
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let message_index = await add_message(window.conversation_id, "user", message);
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window.token = message_id();
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if (imageInput.dataset.src) URL.revokeObjectURL(imageInput.dataset.src);
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const input = imageInput && imageInput.files.length > 0 ? imageInput : cameraInput
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if (input.files.length > 0) imageInput.dataset.src = URL.createObjectURL(input.files[0]);
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else delete imageInput.dataset.src
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message_box.innerHTML += `
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<div class="message" data-index="${message_index}">
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<div class="user">
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${user_image}
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<i class="fa-solid fa-xmark"></i>
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<i class="fa-regular fa-phone-arrow-up-right"></i>
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</div>
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<div class="content" id="user_${token}">
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<div class="content_inner">
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${markdown_render(message)}
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${imageInput.dataset.src
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? '<img src="' + imageInput.dataset.src + '" alt="Image upload">'
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: ''
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}
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</div>
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<div class="count">${count_words_and_tokens(message, get_selected_model())}</div>
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</div>
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</div>
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`;
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highlight(message_box);
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await ask_gpt();
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};
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const remove_cancel_button = async () => {
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@ -151,7 +147,7 @@ const remove_cancel_button = async () => {
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}, 300);
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};
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const prepare_messages = (messages, filter_last_message = true) => {
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const prepare_messages = (messages, filter_last_message=true) => {
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// Removes none user messages at end
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if (filter_last_message) {
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let last_message;
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@ -201,17 +197,52 @@ const prepare_messages = (messages, filter_last_message = true) => {
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return new_messages;
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}
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async function add_message_chunk(message) {
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if (message.type == "provider") {
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window.provider_result = message.provider;
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window.content.querySelector('.provider').innerHTML = `
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<a href="${message.provider.url}" target="_blank">
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${message.provider.name}
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</a>
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${message.provider.model ? ' with ' + message.provider.model : ''}
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`
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} else if (message.type == "message") {
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console.error(messag.message)
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return;
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} else if (message.type == "error") {
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console.error(message.error);
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window.content_inner.innerHTML += `<p><strong>An error occured:</strong> ${message.error}</p>`;
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} else if (message.type == "content") {
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window.text += message.content;
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html = markdown_render(window.text);
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let lastElement, lastIndex = null;
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for (element of ['</p>', '</code></pre>', '</p>\n</li>\n</ol>', '</li>\n</ol>', '</li>\n</ul>']) {
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const index = html.lastIndexOf(element)
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if (index - element.length > lastIndex) {
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lastElement = element;
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lastIndex = index;
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}
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}
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if (lastIndex) {
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html = html.substring(0, lastIndex) + '<span id="cursor"></span>' + lastElement;
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}
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window.content_inner.innerHTML = html;
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window.content_count.innerText = count_words_and_tokens(text, window.provider_result?.model);
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highlight(window.content_inner);
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}
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window.scrollTo(0, 0);
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if (message_box.scrollTop >= message_box.scrollHeight - message_box.clientHeight - 100) {
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message_box.scrollTo({ top: message_box.scrollHeight, behavior: "auto" });
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}
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}
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const ask_gpt = async () => {
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regenerate.classList.add(`regenerate-hidden`);
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messages = await get_messages(window.conversation_id);
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total_messages = messages.length;
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messages = prepare_messages(messages);
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window.scrollTo(0, 0);
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window.controller = new AbortController();
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window.text = "";
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stop_generating.classList.remove(`stop_generating-hidden`);
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message_box.scrollTop = message_box.scrollHeight;
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@ -234,103 +265,31 @@ const ask_gpt = async () => {
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</div>
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</div>
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`;
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content = document.getElementById(`gpt_${window.token}`);
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content_inner = content.querySelector('.content_inner');
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content_count = content.querySelector('.count');
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window.controller = new AbortController();
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window.text = "";
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window.error = null;
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window.provider_result = null;
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window.content = document.getElementById(`gpt_${window.token}`);
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window.content_inner = content.querySelector('.content_inner');
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window.content_count = content.querySelector('.count');
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message_box.scrollTop = message_box.scrollHeight;
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window.scrollTo(0, 0);
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error = provider_result = null;
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try {
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let body = JSON.stringify({
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const input = imageInput && imageInput.files.length > 0 ? imageInput : cameraInput;
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const file = input && input.files.length > 0 ? input.files[0] : null;
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await api("conversation", {
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id: window.token,
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conversation_id: window.conversation_id,
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model: get_selected_model(),
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jailbreak: jailbreak?.options[jailbreak.selectedIndex].value,
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web_search: document.getElementById(`switch`).checked,
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web_search: document.getElementById("switch").checked,
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provider: providerSelect.options[providerSelect.selectedIndex].value,
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patch_provider: document.getElementById('patch')?.checked,
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patch_provider: document.getElementById("patch")?.checked,
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messages: messages
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});
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const headers = {
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accept: 'text/event-stream'
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}
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const input = imageInput && imageInput.files.length > 0 ? imageInput : cameraInput
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if (input && input.files.length > 0) {
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const formData = new FormData();
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formData.append('image', input.files[0]);
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formData.append('json', body);
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body = formData;
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} else {
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headers['content-type'] = 'application/json';
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}
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const response = await fetch(`/backend-api/v2/conversation`, {
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method: 'POST',
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signal: window.controller.signal,
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headers: headers,
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body: body
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});
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const reader = response.body.pipeThrough(new TextDecoderStream()).getReader();
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let buffer = ""
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while (true) {
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const { value, done } = await reader.read();
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if (done) break;
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for (const line of value.split("\n")) {
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if (!line) {
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continue;
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}
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let message;
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try {
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message = JSON.parse(buffer + line);
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buffer = "";
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} catch {
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buffer += line
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continue;
|
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}
|
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if (message.type == "content") {
|
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text += message.content;
|
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} else if (message.type == "provider") {
|
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provider_result = message.provider
|
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content.querySelector('.provider').innerHTML = `
|
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<a href="${provider_result.url}" target="_blank">
|
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${provider_result.name}
|
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</a>
|
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${provider_result.model ? ' with ' + provider_result.model : ''}
|
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`
|
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} else if (message.type == "error") {
|
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error = message.error;
|
||||
} else if (messag.type == "message") {
|
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console.error(messag.message)
|
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}
|
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}
|
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if (error) {
|
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console.error(error);
|
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content_inner.innerHTML += `<p><strong>An error occured:</strong> ${error}</p>`;
|
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} else {
|
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html = markdown_render(text);
|
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let lastElement, lastIndex = null;
|
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for (element of ['</p>', '</code></pre>', '</p>\n</li>\n</ol>', '</li>\n</ol>', '</li>\n</ul>']) {
|
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const index = html.lastIndexOf(element)
|
||||
if (index - element.length > lastIndex) {
|
||||
lastElement = element;
|
||||
lastIndex = index;
|
||||
}
|
||||
}
|
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if (lastIndex) {
|
||||
html = html.substring(0, lastIndex) + '<span id="cursor"></span>' + lastElement;
|
||||
}
|
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content_inner.innerHTML = html;
|
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content_count.innerText = count_words_and_tokens(text, provider_result?.model);
|
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highlight(content_inner);
|
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}
|
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|
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window.scrollTo(0, 0);
|
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if (message_box.scrollTop >= message_box.scrollHeight - message_box.clientHeight - 100) {
|
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message_box.scrollTo({ top: message_box.scrollHeight, behavior: "auto" });
|
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}
|
||||
}
|
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}, file);
|
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if (!error) {
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html = markdown_render(text);
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content_inner.innerHTML = html;
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|
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@ -355,7 +314,7 @@ const ask_gpt = async () => {
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await add_message(window.conversation_id, "assistant", text, provider_result);
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await load_conversation(window.conversation_id);
|
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} else {
|
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let cursorDiv = document.getElementById(`cursor`);
|
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let cursorDiv = document.getElementById("cursor");
|
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if (cursorDiv) cursorDiv.parentNode.removeChild(cursorDiv);
|
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}
|
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window.scrollTo(0, 0);
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|
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@ -444,7 +403,7 @@ const new_conversation = async () => {
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say_hello();
|
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};
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|
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const load_conversation = async (conversation_id, scroll = true) => {
|
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const load_conversation = async (conversation_id, scroll=true) => {
|
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let conversation = await get_conversation(conversation_id);
|
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let messages = conversation?.items || [];
|
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|
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|
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@ -459,7 +418,6 @@ const load_conversation = async (conversation_id, scroll = true) => {
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last_model = item.provider?.model;
|
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let next_i = parseInt(i) + 1;
|
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let next_provider = item.provider ? item.provider : (messages.length > next_i ? messages[next_i].provider : null);
|
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|
||||
let provider_link = item.provider?.name ? `<a href="${item.provider.url}" target="_blank">${item.provider.name}</a>` : "";
|
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let provider = provider_link ? `
|
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<div class="provider">
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|
|
@ -496,7 +454,6 @@ const load_conversation = async (conversation_id, scroll = true) => {
|
|||
}
|
||||
|
||||
message_box.innerHTML = elements;
|
||||
|
||||
register_remove_message();
|
||||
highlight(message_box);
|
||||
|
||||
|
|
@ -548,7 +505,9 @@ async function add_conversation(conversation_id, content) {
|
|||
}
|
||||
|
||||
async function save_system_message() {
|
||||
if (!window.conversation_id) return;
|
||||
if (!window.conversation_id) {
|
||||
return;
|
||||
}
|
||||
const conversation = await get_conversation(window.conversation_id);
|
||||
conversation.system = systemPrompt?.value;
|
||||
await save_conversation(window.conversation_id, conversation);
|
||||
|
|
@ -585,7 +544,6 @@ const remove_message = async (conversation_id, index) => {
|
|||
|
||||
const add_message = async (conversation_id, role, content, provider) => {
|
||||
const conversation = await get_conversation(conversation_id);
|
||||
|
||||
conversation.items.push({
|
||||
role: role,
|
||||
content: content,
|
||||
|
|
@ -667,11 +625,10 @@ sidebar_button.addEventListener("click", (event) => {
|
|||
sidebar.classList.add("shown");
|
||||
sidebar_button.classList.add("rotated");
|
||||
}
|
||||
|
||||
window.scrollTo(0, 0);
|
||||
});
|
||||
|
||||
const register_settings_localstorage = async () => {
|
||||
const register_settings_storage = async () => {
|
||||
options.forEach((id) => {
|
||||
element = document.getElementById(id);
|
||||
if (!element) {
|
||||
|
|
@ -692,10 +649,10 @@ const register_settings_localstorage = async () => {
|
|||
});
|
||||
}
|
||||
|
||||
const load_settings_localstorage = async () => {
|
||||
const load_settings_storage = async () => {
|
||||
options.forEach((id) => {
|
||||
element = document.getElementById(id);
|
||||
if (!element || !(value = appStorage.getItem(element.id))) {
|
||||
if (!element || !(value = appStorage.getItem(id))) {
|
||||
return;
|
||||
}
|
||||
if (value) {
|
||||
|
|
@ -807,9 +764,21 @@ systemPrompt.addEventListener("blur", function() {
|
|||
count_input();
|
||||
});
|
||||
|
||||
window.onload = async () => {
|
||||
setTheme();
|
||||
window.addEventListener('load', async function() {
|
||||
await on_load();
|
||||
if (window.conversation_id == "{{chat_id}}") {
|
||||
window.conversation_id = uuid();
|
||||
} else {
|
||||
await on_api();
|
||||
}
|
||||
});
|
||||
|
||||
window.addEventListener('pywebviewready', async function() {
|
||||
await on_api();
|
||||
});
|
||||
|
||||
async function on_load() {
|
||||
setTheme();
|
||||
count_input();
|
||||
|
||||
if (/\/chat\/.+/.test(window.location.href)) {
|
||||
|
|
@ -817,9 +786,10 @@ window.onload = async () => {
|
|||
} else {
|
||||
say_hello()
|
||||
}
|
||||
|
||||
load_conversations();
|
||||
}
|
||||
|
||||
async function on_api() {
|
||||
messageInput.addEventListener("keydown", async (evt) => {
|
||||
if (prompt_lock) return;
|
||||
|
||||
|
|
@ -832,48 +802,17 @@ window.onload = async () => {
|
|||
messageInput.style.height = messageInput.scrollHeight + "px";
|
||||
}
|
||||
});
|
||||
|
||||
sendButton.addEventListener(`click`, async () => {
|
||||
console.log("clicked send");
|
||||
if (prompt_lock) return;
|
||||
await handle_ask();
|
||||
});
|
||||
|
||||
messageInput.focus();
|
||||
|
||||
register_settings_localstorage();
|
||||
};
|
||||
register_settings_storage();
|
||||
|
||||
(async () => {
|
||||
response = await fetch('/backend-api/v2/models')
|
||||
models = await response.json()
|
||||
|
||||
for (model of models) {
|
||||
let option = document.createElement('option');
|
||||
option.value = option.text = model;
|
||||
modelSelect.appendChild(option);
|
||||
}
|
||||
|
||||
response = await fetch('/backend-api/v2/providers')
|
||||
providers = await response.json()
|
||||
select = document.getElementById('provider');
|
||||
|
||||
providers.forEach((provider) => {
|
||||
let option = document.createElement('option');
|
||||
option.value = option.text = provider;
|
||||
select.appendChild(option);
|
||||
})
|
||||
|
||||
await load_provider_models();
|
||||
|
||||
await load_settings_localstorage()
|
||||
})();
|
||||
|
||||
(async () => {
|
||||
response = await fetch('/backend-api/v2/version')
|
||||
versions = await response.json()
|
||||
|
||||
document.title = 'g4f - gui - ' + versions["version"];
|
||||
versions = await api('version')
|
||||
document.title = 'g4f - ' + versions["version"];
|
||||
let text = "version ~ "
|
||||
if (versions["version"] != versions["latest_version"]) {
|
||||
let release_url = 'https://github.com/xtekky/gpt4free/releases/tag/' + versions["latest_version"];
|
||||
|
|
@ -883,7 +822,24 @@ window.onload = async () => {
|
|||
text += versions["version"];
|
||||
}
|
||||
document.getElementById("version_text").innerHTML = text
|
||||
})()
|
||||
|
||||
models = await api("models");
|
||||
models.forEach((model) => {
|
||||
let option = document.createElement('option');
|
||||
option.value = option.text = model;
|
||||
modelSelect.appendChild(option);
|
||||
});
|
||||
|
||||
providers = await api('providers')
|
||||
providers.forEach((provider) => {
|
||||
let option = document.createElement('option');
|
||||
option.value = option.text = provider;
|
||||
providerSelect.appendChild(option);
|
||||
})
|
||||
|
||||
load_provider_models();
|
||||
load_settings_storage()
|
||||
}
|
||||
|
||||
for (const el of [imageInput, cameraInput]) {
|
||||
el.addEventListener('click', async () => {
|
||||
|
|
@ -899,6 +855,7 @@ fileInput.addEventListener('click', async (event) => {
|
|||
fileInput.value = '';
|
||||
delete fileInput.dataset.text;
|
||||
});
|
||||
|
||||
fileInput.addEventListener('change', async (event) => {
|
||||
if (fileInput.files.length) {
|
||||
type = fileInput.files[0].type;
|
||||
|
|
@ -947,10 +904,73 @@ function get_selected_model() {
|
|||
}
|
||||
}
|
||||
|
||||
async function api(ressource, args=null, file=null) {
|
||||
if (window?.pywebview) {
|
||||
if (args) {
|
||||
if (ressource == "models") {
|
||||
ressource = "provider_models";
|
||||
}
|
||||
return pywebview.api["get_" + ressource](args);
|
||||
}
|
||||
return pywebview.api["get_" + ressource]();
|
||||
}
|
||||
if (ressource == "models" && args) {
|
||||
ressource = `${ressource}/${args}`;
|
||||
}
|
||||
const url = `/backend-api/v2/${ressource}`;
|
||||
if (ressource == "conversation") {
|
||||
const body = JSON.stringify(args);
|
||||
const headers = {
|
||||
accept: 'text/event-stream'
|
||||
}
|
||||
if (file) {
|
||||
const formData = new FormData();
|
||||
formData.append('file', file);
|
||||
formData.append('json', body);
|
||||
body = formData;
|
||||
} else {
|
||||
headers['content-type'] = 'application/json';
|
||||
}
|
||||
response = await fetch(url, {
|
||||
method: 'POST',
|
||||
signal: window.controller.signal,
|
||||
headers: headers,
|
||||
body: body
|
||||
});
|
||||
return read_response(response);
|
||||
}
|
||||
response = await fetch(url);
|
||||
return await response.json();
|
||||
}
|
||||
|
||||
async function read_response(response) {
|
||||
const reader = response.body.pipeThrough(new TextDecoderStream()).getReader();
|
||||
let buffer = ""
|
||||
while (true) {
|
||||
const { value, done } = await reader.read();
|
||||
if (done) {
|
||||
break;
|
||||
}
|
||||
for (const line of value.split("\n")) {
|
||||
if (!line) {
|
||||
continue;
|
||||
}
|
||||
try {
|
||||
add_message_chunk(JSON.parse(buffer + line))
|
||||
buffer = "";
|
||||
} catch {
|
||||
buffer += line
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
async function load_provider_models() {
|
||||
provider = providerSelect.options[providerSelect.selectedIndex].value;
|
||||
response = await fetch('/backend-api/v2/models/' + provider);
|
||||
models = await response.json();
|
||||
const provider = providerSelect.options[providerSelect.selectedIndex].value;
|
||||
if (!provider) {
|
||||
return;
|
||||
}
|
||||
const models = await api('models', provider);
|
||||
modelProvider.innerHTML = '';
|
||||
if (models.length > 0) {
|
||||
modelSelect.classList.add("hidden");
|
||||
|
|
@ -0,0 +1,172 @@
|
|||
import logging
|
||||
import json
|
||||
from typing import Iterator
|
||||
|
||||
try:
|
||||
import webview
|
||||
except ImportError:
|
||||
...
|
||||
|
||||
from g4f import version, models
|
||||
from g4f import get_last_provider, ChatCompletion
|
||||
from g4f.errors import VersionNotFoundError
|
||||
from g4f.Provider import ProviderType, __providers__, __map__
|
||||
from g4f.providers.base_provider import ProviderModelMixin
|
||||
from g4f.Provider.bing.create_images import patch_provider
|
||||
|
||||
class Api():
|
||||
def get_models(self) -> list[str]:
|
||||
"""
|
||||
Return a list of all models.
|
||||
|
||||
Fetches and returns a list of all available models in the system.
|
||||
|
||||
Returns:
|
||||
List[str]: A list of model names.
|
||||
"""
|
||||
return models._all_models
|
||||
|
||||
def get_provider_models(self, provider: str) -> list[dict]:
|
||||
if provider in __map__:
|
||||
provider: ProviderType = __map__[provider]
|
||||
if issubclass(provider, ProviderModelMixin):
|
||||
return [{"model": model, "default": model == provider.default_model} for model in provider.get_models()]
|
||||
elif provider.supports_gpt_35_turbo or provider.supports_gpt_4:
|
||||
return [
|
||||
*([{"model": "gpt-4", "default": not provider.supports_gpt_4}] if provider.supports_gpt_4 else []),
|
||||
*([{"model": "gpt-3.5-turbo", "default": not provider.supports_gpt_4}] if provider.supports_gpt_35_turbo else [])
|
||||
]
|
||||
else:
|
||||
return [];
|
||||
|
||||
def get_providers(self) -> list[str]:
|
||||
"""
|
||||
Return a list of all working providers.
|
||||
"""
|
||||
return [provider.__name__ for provider in __providers__ if provider.working]
|
||||
|
||||
def get_version(self):
|
||||
"""
|
||||
Returns the current and latest version of the application.
|
||||
|
||||
Returns:
|
||||
dict: A dictionary containing the current and latest version.
|
||||
"""
|
||||
try:
|
||||
current_version = version.utils.current_version
|
||||
except VersionNotFoundError:
|
||||
current_version = None
|
||||
return {
|
||||
"version": current_version,
|
||||
"latest_version": version.utils.latest_version,
|
||||
}
|
||||
|
||||
def generate_title(self):
|
||||
"""
|
||||
Generates and returns a title based on the request data.
|
||||
|
||||
Returns:
|
||||
dict: A dictionary with the generated title.
|
||||
"""
|
||||
return {'title': ''}
|
||||
|
||||
def get_conversation(self, options: dict, **kwargs) -> Iterator:
|
||||
window = webview.active_window()
|
||||
for message in self._create_response_stream(
|
||||
self._prepare_conversation_kwargs(options, kwargs)
|
||||
):
|
||||
window.evaluate_js(f"this.add_message_chunk({json.dumps(message)})")
|
||||
|
||||
def _prepare_conversation_kwargs(self, json_data: dict, kwargs: dict):
|
||||
"""
|
||||
Prepares arguments for chat completion based on the request data.
|
||||
|
||||
Reads the request and prepares the necessary arguments for handling
|
||||
a chat completion request.
|
||||
|
||||
Returns:
|
||||
dict: Arguments prepared for chat completion.
|
||||
"""
|
||||
provider = json_data.get('provider', None)
|
||||
if "image" in kwargs and provider is None:
|
||||
provider = "Bing"
|
||||
if provider == 'OpenaiChat':
|
||||
kwargs['auto_continue'] = True
|
||||
|
||||
messages = json_data['messages']
|
||||
if json_data.get('web_search'):
|
||||
if provider == "Bing":
|
||||
kwargs['web_search'] = True
|
||||
else:
|
||||
from .internet import get_search_message
|
||||
messages[-1]["content"] = get_search_message(messages[-1]["content"])
|
||||
|
||||
model = json_data.get('model')
|
||||
model = model if model else models.default
|
||||
patch = patch_provider if json_data.get('patch_provider') else None
|
||||
|
||||
return {
|
||||
"model": model,
|
||||
"provider": provider,
|
||||
"messages": messages,
|
||||
"stream": True,
|
||||
"ignore_stream": True,
|
||||
"patch_provider": patch,
|
||||
**kwargs
|
||||
}
|
||||
|
||||
def _create_response_stream(self, kwargs) -> Iterator:
|
||||
"""
|
||||
Creates and returns a streaming response for the conversation.
|
||||
|
||||
Args:
|
||||
kwargs (dict): Arguments for creating the chat completion.
|
||||
|
||||
Yields:
|
||||
str: JSON formatted response chunks for the stream.
|
||||
|
||||
Raises:
|
||||
Exception: If an error occurs during the streaming process.
|
||||
"""
|
||||
try:
|
||||
first = True
|
||||
for chunk in ChatCompletion.create(**kwargs):
|
||||
if first:
|
||||
first = False
|
||||
yield self._format_json('provider', get_last_provider(True))
|
||||
if isinstance(chunk, Exception):
|
||||
logging.exception(chunk)
|
||||
yield self._format_json('message', get_error_message(chunk))
|
||||
else:
|
||||
yield self._format_json('content', chunk)
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
yield self._format_json('error', get_error_message(e))
|
||||
|
||||
def _format_json(self, response_type: str, content):
|
||||
"""
|
||||
Formats and returns a JSON response.
|
||||
|
||||
Args:
|
||||
response_type (str): The type of the response.
|
||||
content: The content to be included in the response.
|
||||
|
||||
Returns:
|
||||
str: A JSON formatted string.
|
||||
"""
|
||||
return {
|
||||
'type': response_type,
|
||||
response_type: content
|
||||
}
|
||||
|
||||
def get_error_message(exception: Exception) -> str:
|
||||
"""
|
||||
Generates a formatted error message from an exception.
|
||||
|
||||
Args:
|
||||
exception (Exception): The exception to format.
|
||||
|
||||
Returns:
|
||||
str: A formatted error message string.
|
||||
"""
|
||||
return f"{get_last_provider().__name__}: {type(exception).__name__}: {exception}"
|
||||
|
|
@ -2,8 +2,8 @@ import sys, os
|
|||
from flask import Flask
|
||||
|
||||
if getattr(sys, 'frozen', False):
|
||||
template_folder = os.path.join(sys._MEIPASS, "client/html")
|
||||
template_folder = os.path.join(sys._MEIPASS, "client")
|
||||
else:
|
||||
template_folder = "./../client/html"
|
||||
template_folder = "../client"
|
||||
|
||||
app = Flask(__name__, template_folder=template_folder)
|
||||
app = Flask(__name__, template_folder=template_folder, static_folder=f"{template_folder}/static")
|
||||
|
|
@ -1,16 +1,9 @@
|
|||
import logging
|
||||
import json
|
||||
from flask import request, Flask
|
||||
from typing import Generator
|
||||
from g4f import version, models
|
||||
from g4f import get_last_provider, ChatCompletion
|
||||
from g4f.image import is_allowed_extension, to_image
|
||||
from g4f.errors import VersionNotFoundError
|
||||
from g4f.Provider import ProviderType, __providers__, __map__
|
||||
from g4f.providers.base_provider import ProviderModelMixin
|
||||
from g4f.Provider.bing.create_images import patch_provider
|
||||
from .api import Api
|
||||
|
||||
class Backend_Api:
|
||||
class Backend_Api(Api):
|
||||
"""
|
||||
Handles various endpoints in a Flask application for backend operations.
|
||||
|
||||
|
|
@ -59,7 +52,7 @@ class Backend_Api:
|
|||
'methods': ['POST']
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
def handle_error(self):
|
||||
"""
|
||||
Initialize the backend API with the given Flask application.
|
||||
|
|
@ -69,63 +62,7 @@ class Backend_Api:
|
|||
"""
|
||||
print(request.json)
|
||||
return 'ok', 200
|
||||
|
||||
def get_models(self):
|
||||
"""
|
||||
Return a list of all models.
|
||||
|
||||
Fetches and returns a list of all available models in the system.
|
||||
|
||||
Returns:
|
||||
List[str]: A list of model names.
|
||||
"""
|
||||
return models._all_models
|
||||
|
||||
def get_provider_models(self, provider: str):
|
||||
if provider in __map__:
|
||||
provider: ProviderType = __map__[provider]
|
||||
if issubclass(provider, ProviderModelMixin):
|
||||
return [{"model": model, "default": model == provider.default_model} for model in provider.get_models()]
|
||||
elif provider.supports_gpt_35_turbo or provider.supports_gpt_4:
|
||||
return [
|
||||
*([{"model": "gpt-3.5-turbo", "default": not provider.supports_gpt_4}] if provider.supports_gpt_35_turbo else []),
|
||||
*([{"model": "gpt-4", "default": not provider.supports_gpt_4}] if provider.supports_gpt_4 else [])
|
||||
]
|
||||
else:
|
||||
return [];
|
||||
return 404, "Provider not found"
|
||||
|
||||
def get_providers(self):
|
||||
"""
|
||||
Return a list of all working providers.
|
||||
"""
|
||||
return [provider.__name__ for provider in __providers__ if provider.working]
|
||||
|
||||
def get_version(self):
|
||||
"""
|
||||
Returns the current and latest version of the application.
|
||||
|
||||
Returns:
|
||||
dict: A dictionary containing the current and latest version.
|
||||
"""
|
||||
try:
|
||||
current_version = version.utils.current_version
|
||||
except VersionNotFoundError:
|
||||
current_version = None
|
||||
return {
|
||||
"version": current_version,
|
||||
"latest_version": version.utils.latest_version,
|
||||
}
|
||||
|
||||
def generate_title(self):
|
||||
"""
|
||||
Generates and returns a title based on the request data.
|
||||
|
||||
Returns:
|
||||
dict: A dictionary with the generated title.
|
||||
"""
|
||||
return {'title': ''}
|
||||
|
||||
def handle_conversation(self):
|
||||
"""
|
||||
Handles conversation requests and streams responses back.
|
||||
|
|
@ -133,26 +70,10 @@ class Backend_Api:
|
|||
Returns:
|
||||
Response: A Flask response object for streaming.
|
||||
"""
|
||||
kwargs = self._prepare_conversation_kwargs()
|
||||
|
||||
return self.app.response_class(
|
||||
self._create_response_stream(kwargs),
|
||||
mimetype='text/event-stream'
|
||||
)
|
||||
|
||||
def _prepare_conversation_kwargs(self):
|
||||
"""
|
||||
Prepares arguments for chat completion based on the request data.
|
||||
|
||||
Reads the request and prepares the necessary arguments for handling
|
||||
a chat completion request.
|
||||
|
||||
Returns:
|
||||
dict: Arguments prepared for chat completion.
|
||||
"""
|
||||
|
||||
kwargs = {}
|
||||
if "image" in request.files:
|
||||
file = request.files['image']
|
||||
if "file" in request.files:
|
||||
file = request.files['file']
|
||||
if file.filename != '' and is_allowed_extension(file.filename):
|
||||
kwargs['image'] = to_image(file.stream, file.filename.endswith('.svg'))
|
||||
kwargs['image_name'] = file.filename
|
||||
|
|
@ -160,66 +81,20 @@ class Backend_Api:
|
|||
json_data = json.loads(request.form['json'])
|
||||
else:
|
||||
json_data = request.json
|
||||
|
||||
provider = json_data.get('provider', '').replace('g4f.Provider.', '')
|
||||
provider = provider if provider and provider != "Auto" else None
|
||||
|
||||
if "image" in kwargs and not provider:
|
||||
provider = "Bing"
|
||||
if provider == 'OpenaiChat':
|
||||
kwargs['auto_continue'] = True
|
||||
kwargs = self._prepare_conversation_kwargs(json_data, kwargs)
|
||||
|
||||
messages = json_data['messages']
|
||||
if json_data.get('web_search'):
|
||||
if provider == "Bing":
|
||||
kwargs['web_search'] = True
|
||||
else:
|
||||
# ResourceWarning: unclosed event loop
|
||||
from .internet import get_search_message
|
||||
messages[-1]["content"] = get_search_message(messages[-1]["content"])
|
||||
return self.app.response_class(
|
||||
self._create_response_stream(kwargs),
|
||||
mimetype='text/event-stream'
|
||||
)
|
||||
|
||||
model = json_data.get('model')
|
||||
model = model if model else models.default
|
||||
patch = patch_provider if json_data.get('patch_provider') else None
|
||||
def get_provider_models(self, provider: str):
|
||||
models = super().get_provider_models(provider)
|
||||
if models is None:
|
||||
return 404, "Provider not found"
|
||||
return models
|
||||
|
||||
return {
|
||||
"model": model,
|
||||
"provider": provider,
|
||||
"messages": messages,
|
||||
"stream": True,
|
||||
"ignore_stream": True,
|
||||
"patch_provider": patch,
|
||||
**kwargs
|
||||
}
|
||||
|
||||
def _create_response_stream(self, kwargs) -> Generator[str, None, None]:
|
||||
"""
|
||||
Creates and returns a streaming response for the conversation.
|
||||
|
||||
Args:
|
||||
kwargs (dict): Arguments for creating the chat completion.
|
||||
|
||||
Yields:
|
||||
str: JSON formatted response chunks for the stream.
|
||||
|
||||
Raises:
|
||||
Exception: If an error occurs during the streaming process.
|
||||
"""
|
||||
try:
|
||||
first = True
|
||||
for chunk in ChatCompletion.create(**kwargs):
|
||||
if first:
|
||||
first = False
|
||||
yield self._format_json('provider', get_last_provider(True))
|
||||
if isinstance(chunk, Exception):
|
||||
logging.exception(chunk)
|
||||
yield self._format_json('message', get_error_message(chunk))
|
||||
else:
|
||||
yield self._format_json('content', str(chunk))
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
yield self._format_json('error', get_error_message(e))
|
||||
|
||||
def _format_json(self, response_type: str, content) -> str:
|
||||
"""
|
||||
Formats and returns a JSON response.
|
||||
|
|
@ -231,19 +106,4 @@ class Backend_Api:
|
|||
Returns:
|
||||
str: A JSON formatted string.
|
||||
"""
|
||||
return json.dumps({
|
||||
'type': response_type,
|
||||
response_type: content
|
||||
}) + "\n"
|
||||
|
||||
def get_error_message(exception: Exception) -> str:
|
||||
"""
|
||||
Generates a formatted error message from an exception.
|
||||
|
||||
Args:
|
||||
exception (Exception): The exception to format.
|
||||
|
||||
Returns:
|
||||
str: A formatted error message string.
|
||||
"""
|
||||
return f"{get_last_provider().__name__}: {type(exception).__name__}: {exception}"
|
||||
return json.dumps(super()._format_json(response_type, content)) + "\n"
|
||||
|
|
@ -1,12 +1,5 @@
|
|||
from flask import render_template, send_file, redirect
|
||||
from time import time
|
||||
from os import urandom
|
||||
import sys, os
|
||||
|
||||
if getattr(sys, 'frozen', False):
|
||||
assets_folder = os.path.join(sys._MEIPASS, "client")
|
||||
else:
|
||||
assets_folder = "./../client"
|
||||
import uuid
|
||||
from flask import render_template, redirect
|
||||
|
||||
class Website:
|
||||
def __init__(self, app) -> None:
|
||||
|
|
@ -24,23 +17,12 @@ class Website:
|
|||
'function': self._chat,
|
||||
'methods': ['GET', 'POST']
|
||||
},
|
||||
'/assets/<folder>/<file>': {
|
||||
'function': self._assets,
|
||||
'methods': ['GET', 'POST']
|
||||
}
|
||||
}
|
||||
|
||||
def _chat(self, conversation_id):
|
||||
if '-' not in conversation_id:
|
||||
return redirect('/chat')
|
||||
|
||||
return render_template('index.html', chat_id = conversation_id)
|
||||
return render_template('index.html', chat_id=conversation_id)
|
||||
|
||||
def _index(self):
|
||||
return render_template('index.html', chat_id = f'{urandom(4).hex()}-{urandom(2).hex()}-{urandom(2).hex()}-{urandom(2).hex()}-{hex(int(time() * 1000))[2:]}')
|
||||
|
||||
def _assets(self, folder: str, file: str):
|
||||
try:
|
||||
return send_file(f"{assets_folder}/{folder}/{file}", as_attachment=False)
|
||||
except:
|
||||
return "File not found", 404
|
||||
return render_template('index.html', chat_id=str(uuid.uuid4()))
|
||||
|
|
@ -1,34 +1,32 @@
|
|||
import webview
|
||||
from functools import partial
|
||||
try:
|
||||
from platformdirs import user_config_dir
|
||||
has_platformdirs = True
|
||||
except ImportError:
|
||||
has_platformdirs = False
|
||||
|
||||
from g4f.gui import run_gui
|
||||
from g4f.gui.run import gui_parser
|
||||
from g4f.gui.server.api import Api
|
||||
import g4f.version
|
||||
import g4f.debug
|
||||
|
||||
def run_webview(
|
||||
host: str = "0.0.0.0",
|
||||
port: int = 8080,
|
||||
debug: bool = False,
|
||||
storage_path: str = None
|
||||
):
|
||||
webview.create_window(
|
||||
f"g4f - {g4f.version.utils.current_version}",
|
||||
f"http://{host}:{port}/",
|
||||
text_select=True
|
||||
"client/index.html",
|
||||
text_select=True,
|
||||
js_api=Api(),
|
||||
)
|
||||
if has_platformdirs and storage_path is None:
|
||||
storage_path = user_config_dir("g4f-webview")
|
||||
webview.start(
|
||||
partial(run_gui, host, port),
|
||||
private_mode=False,
|
||||
storage_path=storage_path,
|
||||
debug=debug
|
||||
debug=debug,
|
||||
ssl=True
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
|
@ -36,4 +34,4 @@ if __name__ == "__main__":
|
|||
args = parser.parse_args()
|
||||
if args.debug:
|
||||
g4f.debug.logging = True
|
||||
run_webview(args.host, args.port, args.debug)
|
||||
run_webview(args.debug)
|
||||
Loading…
Reference in New Issue