Add model selection to OpenAI payloads
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8 changed files with 134 additions and 9 deletions
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@ -34,6 +34,7 @@ There are currently no automated tests for this project. If you add tests in the
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## Endpoint Notes
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Sortana targets the `/v1/completions` API. The endpoint value stored in settings is a base URL; the full request URL is constructed by appending `/v1/completions` (adding a slash when needed) and defaulting to `https://` if no scheme is provided.
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The options page can query `/v1/models` from the same base URL to populate the Model dropdown; selecting **None** omits the `model` field from the request payload.
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Responses are expected to include a JSON object with `match` (or `matched`) plus a short `reason` string; the parser extracts the last JSON object in the response text and ignores any surrounding commentary.
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## Documentation
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@ -14,6 +14,7 @@ expecting a `match` (or `matched`) boolean plus a `reason` string.
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## Features
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- **Configurable endpoint** – set the classification service base URL on the options page.
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- **Model selection** – load available models from the endpoint and choose one (or omit the model field).
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- **Prompt templates** – choose between OpenAI/ChatML, Qwen, Mistral, Harmony (gpt-oss), or provide your own custom template.
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- **Custom system prompts** – tailor the instructions sent to the model for more precise results.
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- **Persistent result caching** – classification results and reasoning are saved to disk so messages aren't re-evaluated across restarts.
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@ -79,7 +80,8 @@ Sortana is implemented entirely with standard WebExtension scripts—no custom e
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## Usage
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1. Open the add-on's options and set the base URL of your classification service
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(Sortana will append `/v1/completions`).
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(Sortana will append `/v1/completions`). Use the Model dropdown to load
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`/v1/models` and select a model or choose **None** to omit the `model` field.
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2. Use the **Classification Rules** section to add a criterion and optional
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actions such as tagging, moving, copying, forwarding, replying,
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deleting or archiving a message when it matches. Drag rules to
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@ -484,7 +484,7 @@ async function clearCacheForMessages(idsInput) {
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}
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try {
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const store = await storage.local.get(["endpoint", "templateName", "customTemplate", "customSystemPrompt", "aiParams", "debugLogging", "htmlToMarkdown", "stripUrlParams", "altTextImages", "collapseWhitespace", "tokenReduction", "aiRules", "theme", "showDebugTab"]);
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const store = await storage.local.get(["endpoint", "model", "templateName", "customTemplate", "customSystemPrompt", "aiParams", "debugLogging", "htmlToMarkdown", "stripUrlParams", "altTextImages", "collapseWhitespace", "tokenReduction", "aiRules", "theme", "showDebugTab"]);
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logger.setDebug(store.debugLogging);
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await AiClassifier.setConfig(store);
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userTheme = store.theme || 'auto';
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@ -514,9 +514,10 @@ async function clearCacheForMessages(idsInput) {
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aiRules = normalizeRules(newRules);
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logger.aiLog("aiRules updated from storage change", { debug: true }, aiRules);
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}
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if (changes.endpoint || changes.templateName || changes.customTemplate || changes.customSystemPrompt || changes.aiParams || changes.debugLogging) {
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if (changes.endpoint || changes.model || changes.templateName || changes.customTemplate || changes.customSystemPrompt || changes.aiParams || changes.debugLogging) {
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const config = {};
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if (changes.endpoint) config.endpoint = changes.endpoint.newValue;
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if (changes.model) config.model = changes.model.newValue;
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if (changes.templateName) config.templateName = changes.templateName.newValue;
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if (changes.customTemplate) config.customTemplate = changes.customTemplate.newValue;
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if (changes.customSystemPrompt) config.customSystemPrompt = changes.customSystemPrompt.newValue;
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@ -1,7 +1,7 @@
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{
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"manifest_version": 2,
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"name": "Sortana",
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"version": "2.2.0",
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"version": "2.4.0",
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"default_locale": "en-US",
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"applications": {
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"gecko": {
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@ -16,6 +16,7 @@ try {
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}
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const COMPLETIONS_PATH = "/v1/completions";
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const MODELS_PATH = "/v1/models";
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const SYSTEM_PREFIX = `You are an email-classification assistant.
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Read the email below and the classification criterion provided by the user.
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@ -38,6 +39,7 @@ let gCustomSystemPrompt = DEFAULT_CUSTOM_SYSTEM_PROMPT;
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let gTemplateText = "";
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let gAiParams = Object.assign({}, DEFAULT_AI_PARAMS);
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let gModel = "";
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let gCache = new Map();
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let gCacheLoaded = false;
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@ -50,7 +52,7 @@ function normalizeEndpointBase(endpoint) {
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if (!base) {
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return "";
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}
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base = base.replace(/\/v1\/completions\/?$/i, "");
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base = base.replace(/\/v1\/(completions|models)\/?$/i, "");
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return base;
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}
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@ -61,7 +63,19 @@ function buildEndpointUrl(endpointBase) {
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}
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const withScheme = /^https?:\/\//i.test(base) ? base : `https://${base}`;
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const needsSlash = withScheme.endsWith("/");
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return `${withScheme}${needsSlash ? "" : "/"}v1/completions`;
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const path = COMPLETIONS_PATH.replace(/^\//, "");
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return `${withScheme}${needsSlash ? "" : "/"}${path}`;
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}
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function buildModelsUrl(endpointBase) {
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const base = normalizeEndpointBase(endpointBase);
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if (!base) {
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return "";
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}
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const withScheme = /^https?:\/\//i.test(base) ? base : `https://${base}`;
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const needsSlash = withScheme.endsWith("/");
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const path = MODELS_PATH.replace(/^\//, "");
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return `${withScheme}${needsSlash ? "" : "/"}${path}`;
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}
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function sha256HexSync(str) {
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@ -206,6 +220,9 @@ async function setConfig(config = {}) {
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}
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}
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}
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if (typeof config.model === "string") {
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gModel = config.model.trim();
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}
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if (typeof config.debugLogging === "boolean") {
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setDebug(config.debugLogging);
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}
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@ -263,6 +280,9 @@ function buildPayload(text, criterion) {
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let payloadObj = Object.assign({
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prompt: buildPrompt(text, criterion)
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}, gAiParams);
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if (gModel) {
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payloadObj.model = gModel;
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}
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return JSON.stringify(payloadObj);
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}
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@ -457,4 +477,4 @@ async function init() {
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await loadCache();
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}
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export { buildEndpointUrl, normalizeEndpointBase, classifyText, setConfig, removeCacheEntries, clearCache, getReason, getCachedResult, buildCacheKey, getCacheSize, init };
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export { buildEndpointUrl, buildModelsUrl, normalizeEndpointBase, classifyText, setConfig, removeCacheEntries, clearCache, getReason, getCachedResult, buildCacheKey, getCacheSize, init };
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@ -3,6 +3,7 @@ const storage = (globalThis.messenger ?? browser).storage;
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const KEY_GROUPS = {
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settings: [
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'endpoint',
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'model',
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'templateName',
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'customTemplate',
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'customSystemPrompt',
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@ -77,6 +77,21 @@
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<p class="help" id="endpoint-preview"></p>
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</div>
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<div class="field">
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<label class="label" for="model-select">Model</label>
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<div class="field has-addons">
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<div class="control is-expanded">
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<div class="select is-fullwidth">
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<select id="model-select"></select>
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</div>
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</div>
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<div class="control">
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<button class="button" id="refresh-models" type="button">Refresh</button>
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</div>
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</div>
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<p class="help" id="model-help"></p>
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</div>
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<div class="field">
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<label class="label" for="template">Prompt template</label>
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<div class="control">
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@ -10,6 +10,7 @@ document.addEventListener('DOMContentLoaded', async () => {
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'templateName',
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'customTemplate',
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'customSystemPrompt',
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'model',
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'aiParams',
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'debugLogging',
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'htmlToMarkdown',
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@ -100,6 +101,88 @@ document.addEventListener('DOMContentLoaded', async () => {
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endpointInput.addEventListener('input', updateEndpointPreview);
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updateEndpointPreview();
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const modelSelect = document.getElementById('model-select');
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const refreshModelsBtn = document.getElementById('refresh-models');
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const modelHelp = document.getElementById('model-help');
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const storedModel = typeof defaults.model === 'string' ? defaults.model : '';
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function setModelHelp(message = '', isError = false) {
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if (!modelHelp) return;
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modelHelp.textContent = message;
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modelHelp.classList.toggle('is-danger', isError);
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}
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function populateModelOptions(models = [], selectedModel = '') {
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if (!modelSelect) return;
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const modelIds = Array.isArray(models) ? models.filter(Boolean) : [];
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modelSelect.innerHTML = '';
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const noneOpt = document.createElement('option');
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noneOpt.value = '';
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noneOpt.textContent = 'None (omit model)';
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modelSelect.appendChild(noneOpt);
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if (selectedModel && !modelIds.includes(selectedModel)) {
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const storedOpt = document.createElement('option');
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storedOpt.value = selectedModel;
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storedOpt.textContent = `Stored: ${selectedModel}`;
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modelSelect.appendChild(storedOpt);
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}
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for (const id of modelIds) {
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const opt = document.createElement('option');
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opt.value = id;
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opt.textContent = id;
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modelSelect.appendChild(opt);
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}
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const hasSelected = [...modelSelect.options].some(opt => opt.value === selectedModel);
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modelSelect.value = hasSelected ? selectedModel : '';
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}
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async function fetchModels(preferredModel = '') {
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if (!modelSelect || !refreshModelsBtn) return;
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const modelsUrl = AiClassifier.buildModelsUrl(endpointInput.value);
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if (!modelsUrl) {
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setModelHelp('Set a valid endpoint to load models.', true);
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populateModelOptions([], preferredModel || modelSelect.value);
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return;
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}
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refreshModelsBtn.disabled = true;
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setModelHelp('Loading models...');
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try {
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const response = await fetch(modelsUrl, { method: 'GET' });
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if (!response.ok) {
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throw new Error(`HTTP ${response.status}`);
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}
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const data = await response.json();
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let models = [];
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if (Array.isArray(data?.data)) {
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models = data.data.map(model => model?.id ?? model?.name ?? model?.model ?? '').filter(Boolean);
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} else if (Array.isArray(data?.models)) {
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models = data.models.map(model => model?.id ?? model?.name ?? model?.model ?? '').filter(Boolean);
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} else if (Array.isArray(data)) {
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models = data.map(model => model?.id ?? model?.name ?? model?.model ?? model).filter(Boolean);
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}
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models = [...new Set(models)];
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populateModelOptions(models, preferredModel || modelSelect.value);
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setModelHelp(models.length ? `Loaded ${models.length} model${models.length === 1 ? '' : 's'}.` : 'No models returned.');
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} catch (e) {
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logger.aiLog('[options] failed to load models', { level: 'warn' }, e);
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setModelHelp('Failed to load models. Check the endpoint and network.', true);
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populateModelOptions([], preferredModel || modelSelect.value);
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} finally {
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refreshModelsBtn.disabled = false;
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}
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}
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populateModelOptions([], storedModel);
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refreshModelsBtn?.addEventListener('click', () => {
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fetchModels(modelSelect.value);
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});
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const templates = {
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openai: browser.i18n.getMessage('template.openai'),
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qwen: browser.i18n.getMessage('template.qwen'),
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@ -276,6 +359,7 @@ document.addEventListener('DOMContentLoaded', async () => {
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await loadErrors();
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updateDiffDisplay();
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await fetchModels(storedModel);
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[htmlToggle, stripUrlToggle, altTextToggle, collapseWhitespaceToggle, tokenReductionToggle].forEach(toggle => {
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toggle.addEventListener('change', () => {
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@ -914,6 +998,7 @@ document.addEventListener('DOMContentLoaded', async () => {
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document.getElementById('save').addEventListener('click', async () => {
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const endpoint = endpointInput.value.trim();
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const model = modelSelect?.value || '';
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const templateName = templateSelect.value;
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const customTemplateText = customTemplate.value;
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const customSystemPrompt = systemBox.value;
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@ -979,10 +1064,10 @@ document.addEventListener('DOMContentLoaded', async () => {
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const tokenReduction = tokenReductionToggle.checked;
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const showDebugTab = debugTabToggle.checked;
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const theme = themeSelect.value;
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await storage.local.set({ endpoint, templateName, customTemplate: customTemplateText, customSystemPrompt, aiParams: aiParamsSave, debugLogging, htmlToMarkdown, stripUrlParams, altTextImages, collapseWhitespace, tokenReduction, aiRules: rules, theme, showDebugTab });
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await storage.local.set({ endpoint, model, templateName, customTemplate: customTemplateText, customSystemPrompt, aiParams: aiParamsSave, debugLogging, htmlToMarkdown, stripUrlParams, altTextImages, collapseWhitespace, tokenReduction, aiRules: rules, theme, showDebugTab });
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await applyTheme(theme);
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try {
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await AiClassifier.setConfig({ endpoint, templateName, customTemplate: customTemplateText, customSystemPrompt, aiParams: aiParamsSave, debugLogging });
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await AiClassifier.setConfig({ endpoint, model, templateName, customTemplate: customTemplateText, customSystemPrompt, aiParams: aiParamsSave, debugLogging });
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logger.setDebug(debugLogging);
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} catch (e) {
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logger.aiLog('[options] failed to apply config', {level: 'error'}, e);
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