function selectOptionByText(selectElement, optionText) { for (let i = 0; i < selectElement.options.length; i++) { if (selectElement.options[i].text === optionText) { selectElement.selectedIndex = i; break; } } } fetch('/settings') .then(response => response.text()) .then(html => { document.getElementById('settings').innerHTML = html; backendInput = document.getElementById('backend'); modelInput = document.getElementById('model'); personalityLanguageInput = document.getElementById('personalities_language'); personalityCategoryInput = document.getElementById('personalities_category'); personalityInput = document.getElementById('personalities'); languageInput = document.getElementById('language'); voiceInput = document.getElementById('voice'); seedInput = document.getElementById('seed'); tempInput = document.getElementById('temperature'); nPredictInput = document.getElementById('n-predict'); topKInput = document.getElementById('top-k'); topPInput = document.getElementById('top-p'); repeatPenaltyInput = document.getElementById('repeat-penalty'); repeatLastNInput = document.getElementById('repeat-last-n'); temperatureValue = document.getElementById('temperature-value'); n_predictValue = document.getElementById('n-predict-value'); topkValue = document.getElementById('top-k-value'); toppValue = document.getElementById('top-p-value'); repeatPenaltyValue = document.getElementById('repeat-penalty-value'); repeatLastNValue = document.getElementById('repeat-last-n'); function update_config(){ fetch('/get_config') .then((response) => response.json()) .then((data) => { console.log("Received config") console.log(data); selectOptionByText(backendInput, data["backend"]) selectOptionByText(modelInput, data["model"]) selectOptionByText(personalityLanguageInput, data["personality_language"]) selectOptionByText(personalityCategoryInput, data["personality_category"]) selectOptionByText(personalityInput, data["personality"]) languageInput.value = data["language"] voiceInput.value = data["voice"] seedInput.value = data["seed"] tempInput.value = data["temperature"] nPredictInput.value = data["n_predict"] topKInput.value = data["top_k"] topPInput.value = data["top_p"] repeatPenaltyInput.textContent = data["repeat_penalty"] repeatLastNInput.textContent = data["repeat_last_n"] temperatureValue.textContent =`Temperature(${data["temperature"]})` n_predictValue.textContent =`N Predict(${data["n_predict"]})` topkValue.textContent =`Top-K(${data["top_k"]})` toppValue.textContent =`Top-P(${data["top_p"]})` repeatPenaltyValue.textContent =`Repeat penalty(${data["repeat_penalty"]})` repeatLastNValue.textContent =`Repeat last N(${data["repeat_last_n"]})` }) .catch((error) => { console.error('Error:', error); }); } backendInput.addEventListener('input',() => { console.log(`Backend (${backendInput.value})`) // Use fetch to send form values to Flask endpoint fetch('/set_backend', { method: 'POST', headers: { 'Content-Type': 'application/json', }, body: JSON.stringify({"backend":backendInput.value}), }) .then((response) => response.json()) .then((data) => { console.log(data); if(data["status"]==="no_models_found"){ alert("No models found for this backend. Make sure you select a backend that you have models for or download models from links in our repository") } else{ populate_settings(); alert("Backend set successfully") } }) .catch((error) => { console.error('Error:', error); alert("Error setting configuration") }); }) modelInput.addEventListener('input',() => { console.log(`Model (${modelInput.value})`) // Use fetch to send form values to Flask endpoint fetch('/set_model', { method: 'POST', headers: { 'Content-Type': 'application/json', }, body: JSON.stringify({"model":modelInput.value}), }) .then((response) => response.json()) .then((data) => { console.log(data); populate_settings(); alert("Backend set successfully") }) .catch((error) => { console.error('Error:', error); alert("Error setting configuration") }); }) tempInput.addEventListener('input',() => { temperatureValue.textContent =`Temperature(${tempInput.value})` }) nPredictInput.addEventListener('input',() => { n_predictValue.textContent =`N Predict(${nPredictInput.value})` }) topKInput.addEventListener('input',() => { topkValue.textContent =`Top-K(${topKInput.value})` }) topPInput.addEventListener('input',() => { toppValue.textContent =`Top-P(${topPInput.value})` }) repeatPenaltyInput.addEventListener('input',() => { repeatPenaltyValue.textContent =`Repeat penalty(${repeatPenaltyInput.value})` }) repeatLastNInput.addEventListener('input',() => { repeatLastNValue.textContent =`Repeat last N(${repeatLastNInput.value})` }) const submitButton = document.getElementById('submit-model-params'); submitButton.addEventListener('click', (event) => { // Prevent default form submission event.preventDefault(); // Get form values and put them in an object const formValues = { seed: seedInput.value, backend: backendInput.value, model: modelInput.value, personality_language:personalityLanguageInput.value, personality_category:personalityCategoryInput.value, personality: personalityInput.value, language: languageInput.value, voice: voiceInput.value, temperature: tempInput.value, nPredict: nPredictInput.value, topK: topKInput.value, topP: topPInput.value, repeatPenalty: repeatPenaltyInput.value, repeatLastN: repeatLastNInput.value }; console.log(formValues); // Use fetch to send form values to Flask endpoint fetch('/update_model_params', { method: 'POST', headers: { 'Content-Type': 'application/json', }, body: JSON.stringify(formValues), }) .then((response) => response.json()) .then((data) => { console.log(data); alert("Configuration set successfully") }) .catch((error) => { console.error('Error:', error); alert("Error setting configuration") }); }); populate_settings(); function populate_settings(){ // Get a reference to the