mirror of
https://github.com/ParisNeo/lollms-webui.git
synced 2024-12-19 20:37:51 +00:00
206 lines
6.3 KiB
JavaScript
206 lines
6.3 KiB
JavaScript
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fetch('/settings')
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.then(response => response.text())
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.then(html => {
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document.getElementById('settings').innerHTML = html;
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modelInput = document.getElementById('model');
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personalityInput = document.getElementById('personalities');
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languageInput = document.getElementById('language');
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voiceInput = document.getElementById('voice');
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seedInput = document.getElementById('seed');
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tempInput = document.getElementById('temp');
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nPredictInput = document.getElementById('n-predict');
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topKInput = document.getElementById('top-k');
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topPInput = document.getElementById('top-p');
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repeatPenaltyInput = document.getElementById('repeat-penalty');
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repeatLastNInput = document.getElementById('repeat-last-n');
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temperatureValue = document.getElementById('temperature-value');
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n_predictValue = document.getElementById('n-predict-value');
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topkValue = document.getElementById('top-k-value');
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toppValue = document.getElementById('top-p-value');
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repeatPenaltyValue = document.getElementById('repeat-penalty-value');
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repeatLastNValue = document.getElementById('repeat-last-n');
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tempInput.addEventListener('input',() => {
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temperatureValue.textContent =`Temperature(${tempInput.value})`
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})
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nPredictInput.addEventListener('input',() => {
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n_predictValue.textContent =`N Predict(${nPredictInput.value})`
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})
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topKInput.addEventListener('input',() => {
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topkValue.textContent =`Top-K(${topKInput.value})`
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})
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topPInput.addEventListener('input',() => {
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toppValue.textContent =`Top-P(${topPInput.value})`
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})
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repeatPenaltyInput.addEventListener('input',() => {
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repeatPenaltyValue.textContent =`Repeat penalty(${repeatPenaltyInput.value})`
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})
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repeatLastNInput.addEventListener('input',() => {
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repeatLastNValue.textContent =`Repeat last N(${repeatLastNInput.value})`
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})
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fetch('/get_config')
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.then((response) => response.json())
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.then((data) => {
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console.log(data);
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modelInput.value = data["model"]
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personalityInput.value = data["personality"]
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languageInput.value = data["language"]
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voiceInput.value = data["voice"]
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seedInput.value = data["seed"]
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tempInput.value = data["temp"]
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nPredictInput.value = data["n_predict"]
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topKInput.value = data["top_k"]
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topPInput.value = data["top_p"]
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repeatPenaltyInput.textContent = data["repeat_penalty"]
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repeatLastNInput.textContent = data["repeat_last_n"]
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temperatureValue.textContent =`Temperature(${data["temp"]})`
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n_predictValue.textContent =`N Predict(${data["n_predict"]})`
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topkValue.textContent =`Top-K(${data["top_k"]})`
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toppValue.textContent =`Top-P(${data["top_p"]})`
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repeatPenaltyValue.textContent =`Repeat penalty(${data["repeat_penalty"]})`
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repeatLastNValue.textContent =`Repeat last N(${data["repeat_last_n"]})`
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})
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.catch((error) => {
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console.error('Error:', error);
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});
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const submitButton = document.getElementById('submit-model-params');
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submitButton.addEventListener('click', (event) => {
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// Prevent default form submission
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event.preventDefault();
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// Get form values and put them in an object
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const formValues = {
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seed: seedInput.value,
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model: modelInput.value,
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personality: personalityInput.value,
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language: languageInput.value,
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voice: voiceInput.value,
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temp: tempInput.value,
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nPredict: nPredictInput.value,
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topK: topKInput.value,
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topP: topPInput.value,
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repeatPenalty: repeatPenaltyInput.value,
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repeatLastN: repeatLastNInput.value
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};
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console.log(formValues);
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// Use fetch to send form values to Flask endpoint
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fetch('/update_model_params', {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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},
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body: JSON.stringify(formValues),
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})
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.then((response) => response.json())
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.then((data) => {
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console.log(data);
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alert("Configuration set successfully")
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})
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.catch((error) => {
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console.error('Error:', error);
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alert("Error setting configuration")
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});
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});
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})
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.catch(error => {
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console.error('Error loading settings page:', error);
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});
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function populate_models(){
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// Get a reference to the <select> element
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const selectElement = document.getElementById('model');
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// Fetch the list of .bin files from the models subfolder
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fetch('/list_models')
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.then(response => response.json())
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.then(data => {
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if (Array.isArray(data)) {
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// data is an array
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data.forEach(filename => {
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const optionElement = document.createElement('option');
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optionElement.value = filename;
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optionElement.textContent = filename;
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selectElement.appendChild(optionElement);
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});
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// fetch('/get_args')
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// .then(response=> response.json())
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// .then(data=>{
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// })
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} else {
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console.error('Expected an array, but received:', data);
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}
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});
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// Fetch the list of .yaml files from the models subfolder
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fetch('/list_personalities')
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.then(response => response.json())
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.then(data => {
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if (Array.isArray(data)) {
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// data is an array
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const selectElement = document.getElementById('personalities');
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data.forEach(filename => {
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const optionElement = document.createElement('option');
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optionElement.value = filename;
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optionElement.textContent = filename;
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selectElement.appendChild(optionElement);
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});
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// fetch('/get_args')
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// .then(response=> response.json())
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// .then(data=>{
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// })
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} else {
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console.error('Expected an array, but received:', data);
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}
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});
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// Fetch the list of .yaml files from the models subfolder
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fetch('/list_languages')
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.then(response => response.json())
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.then(data => {
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if (Array.isArray(data)) {
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// data is an array
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const selectElement = document.getElementById('language');
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data.forEach(row => {
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const optionElement = document.createElement('option');
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optionElement.value = row.value;
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optionElement.innerHTML = row.label;
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selectElement.appendChild(optionElement);
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});
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// fetch('/get_args')
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// .then(response=> response.json())
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// .then(data=>{
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// })
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} else {
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console.error('Expected an array, but received:', data);
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}
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});
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}
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