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Migrate classifier to chat completions

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This commit is contained in:
Jordan Wages 2026-09-06 23:29:59 -05:00
commit 76195f9a92
15 changed files with 73 additions and 192 deletions
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55
modules/AiClassifier.js
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@ -4,7 +4,7 @@ import { DEFAULT_AI_PARAMS } from "./defaultParams.js";
const storage = (globalThis.messenger ?? globalThis.browser).storage;
const COMPLETIONS_PATH = "/v1/completions";
const CHAT_COMPLETIONS_PATH = "/v1/chat/completions";
const MODELS_PATH = "/v1/models";
const SYSTEM_PREFIX = `You are an email-classification assistant.
@ -22,10 +22,7 @@ Do not add any other keys, text, or formatting.`;
let gEndpointBase = "http://127.0.0.1:5000";
let gEndpoint = buildEndpointUrl(gEndpointBase);
let gTemplateName = "openai";
let gCustomTemplate = "";
let gCustomSystemPrompt = DEFAULT_CUSTOM_SYSTEM_PROMPT;
let gTemplateText = "";
let gAiParams = Object.assign({}, DEFAULT_AI_PARAMS);
let gModel = "";
@ -44,7 +41,7 @@ function normalizeEndpointBase(endpoint) {
if (!base) {
return "";
}
base = base.replace(/\/v1\/(completions|models)\/?$/i, "");
base = base.replace(/\/v1\/(chat\/completions|completions|models)\/?$/i, "");
return base;
}
@ -55,7 +52,7 @@ function buildEndpointUrl(endpointBase) {
}
const withScheme = /^https?:\/\//i.test(base) ? base : `https://${base}`;
const needsSlash = withScheme.endsWith("/");
const path = COMPLETIONS_PATH.replace(/^\//, "");
const path = CHAT_COMPLETIONS_PATH.replace(/^\//, "");
return `${withScheme}${needsSlash ? "" : "/"}${path}`;
}
@ -147,21 +144,6 @@ async function saveCache(updatedKey, updatedValue) {
}
async function loadTemplate(name) {
try {
const url = typeof browser !== "undefined" && browser.runtime?.getURL
? browser.runtime.getURL(`prompt_templates/${name}.txt`)
: `resource://aifilter/prompt_templates/${name}.txt`;
const res = await fetch(url);
if (res.ok) {
return await res.text();
}
} catch (e) {
aiLog(`Failed to load template '${name}':`, {level: 'error'}, e);
}
return "";
}
async function setConfig(config = {}) {
if (typeof config.endpoint === "string") {
const base = normalizeEndpointBase(config.endpoint);
@ -170,12 +152,6 @@ async function setConfig(config = {}) {
}
gEndpoint = buildEndpointUrl(gEndpointBase);
}
if (config.templateName) {
gTemplateName = config.templateName;
}
if (typeof config.customTemplate === "string") {
gCustomTemplate = config.customTemplate;
}
if (typeof config.customSystemPrompt === "string") {
gCustomSystemPrompt = config.customSystemPrompt;
}
@ -201,17 +177,11 @@ async function setConfig(config = {}) {
if (typeof config.debugLogging === "boolean") {
setDebug(config.debugLogging);
}
if (gTemplateName === "custom") {
gTemplateText = gCustomTemplate;
} else {
gTemplateText = await loadTemplate(gTemplateName);
}
if (!gEndpoint) {
gEndpoint = buildEndpointUrl(gEndpointBase);
}
aiLog(`[AiClassifier] Endpoint base set to ${gEndpointBase}`, {debug: true});
aiLog(`[AiClassifier] Endpoint set to ${gEndpoint}`, {debug: true});
aiLog(`[AiClassifier] Template set to ${gTemplateName}`, {debug: true});
}
function buildAuthHeaders() {
@ -234,13 +204,7 @@ function buildSystemPrompt() {
function buildPrompt(body, criterion) {
aiLog(`[AiClassifier] Building prompt with criterion: "${criterion}"`, {debug: true});
const data = {
system: buildSystemPrompt(),
email: body,
query: criterion,
};
let template = gTemplateText || "";
return template.replace(/{{\s*(\w+)\s*}}/g, (m, key) => data[key] || "");
return `**Email Contents**\n\`\`\`\n${body}\n\`\`\`\nClassification Criterion: ${criterion}`;
}
function getCachedResult(cacheKey) {
@ -265,7 +229,10 @@ function getReason(cacheKey) {
function buildPayload(text, criterion) {
let payloadObj = Object.assign({
prompt: buildPrompt(text, criterion)
messages: [
{ role: "system", content: buildSystemPrompt() },
{ role: "user", content: buildPrompt(text, criterion) }
]
}, gAiParams);
if (gModel) {
payloadObj.model = gModel;
@ -337,7 +304,11 @@ function extractLastJsonObject(text) {
}
function parseMatch(result) {
const rawText = result.choices?.[0]?.text || "";
const rawText = result.choices?.[0]?.message?.content;
if (typeof rawText !== "string") {
reportParseError("Chat response missing text content.", JSON.stringify(result).slice(0, 800));
return { matched: false, reason: "" };
}
const candidate = extractLastJsonObject(rawText);
if (!candidate) {
reportParseError("No JSON object found in AI response.", rawText.slice(0, 800));