new baseline
This commit is contained in:
91
src/main.ts
91
src/main.ts
@ -6,10 +6,8 @@ import {
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OllamaChatResponse,
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PostAncestorsForModel,
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} from "../types.js";
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// import striptags from "striptags";
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import { PrismaClient } from "../generated/prisma/client.js";
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import {
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// getInstanceEmojis,
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deleteNotification,
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getNotifications,
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getStatusContext,
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@ -19,8 +17,6 @@ import {
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isFromWhitelistedDomain,
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alreadyRespondedTo,
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recordPendingResponse,
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// trimInputData,
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// selectRandomEmoji,
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shouldContinue,
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} from "./util.js";
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@ -34,7 +30,7 @@ export const envConfig = {
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? process.env.WHITELISTED_DOMAINS.split(",")
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: [process.env.PLEROMA_INSTANCE_DOMAIN],
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ollamaUrl: process.env.OLLAMA_URL || "",
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ollamaSystemPrompt: process.env.OLLAMA_SYSTEM_PROMPT,
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ollamaSystemPrompt: process.env.OLLAMA_SYSTEM_PROMPT || "",
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ollamaModel: process.env.OLLAMA_MODEL || "",
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fetchInterval: process.env.FETCH_INTERVAL
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? parseInt(process.env.FETCH_INTERVAL)
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@ -48,11 +44,12 @@ export const envConfig = {
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};
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const ollamaConfig: OllamaConfigOptions = {
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temperature: 0.9,
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top_p: 0.85,
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top_k: 60,
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num_ctx: 16384, // maximum context window for Llama 3.1
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repeat_penalty: 1.1,
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temperature: 0.85, // Increased from 0.6 - more creative and varied
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top_p: 0.9, // Slightly increased for more diverse responses
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top_k: 40,
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num_ctx: 16384,
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repeat_penalty: 1.1, // Reduced from 1.15 - less mechanical
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// stop: ['<|im_end|>', '\n\n']
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};
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// this could be helpful
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@ -82,47 +79,42 @@ const generateOllamaRequest = async (
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let conversationHistory: PostAncestorsForModel[] = [];
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if (replyWithContext) {
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const contextPosts = await getStatusContext(notification.status.id);
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if (!contextPosts?.ancestors || !contextPosts) {
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if (!contextPosts?.ancestors) {
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throw new Error(`Unable to obtain post context ancestors.`);
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}
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conversationHistory = contextPosts.ancestors.map((ancestor) => {
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const mentions = ancestor.mentions.map((mention) => mention.acct);
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return {
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account_fqn: ancestor.account.fqn,
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mentions,
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plaintext_content: ancestor.pleroma.content["text/plain"],
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};
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});
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// console.log(conversationHistory);
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conversationHistory = contextPosts.ancestors.map((ancestor) => ({
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account_fqn: ancestor.account.fqn,
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mentions: ancestor.mentions.map((mention) => mention.acct),
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plaintext_content: ancestor.pleroma.content["text/plain"],
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}));
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}
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// Simplified user message (remove [/INST] as it's not needed for Llama 3)
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const userMessage = `${notification.status.account.fqn} says to you: \"${notification.status.pleroma.content["text/plain"]}\".`;
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const userMessage = notification.status.pleroma.content["text/plain"];
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let systemContent = ollamaSystemPrompt;
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if (replyWithContext) {
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// Simplified context instructions (avoid heavy JSON; summarize for clarity)
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systemContent = `${ollamaSystemPrompt}\n\nPrevious conversation context:\n${conversationHistory
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.map(
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(post) =>
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`${post.account_fqn} (said to ${post.mentions.join(", ")}): ${
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post.plaintext_content
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}`
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)
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.join(
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"\n"
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)}\nReply to the user who addressed you (you are Lexi, also known as nice-ai or nice-ai@nicecrew.digital). Examine the context of the entire conversation and make references to topics or information where appropriate. Prefix usernames with '@' when addressing them. Assume if there is no domain in the username, the domain is @nicecrew.digital (for example @matty would be @matty@nicecrew.digital)`;
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systemContent = `${ollamaSystemPrompt}
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Previous conversation (JSON format):
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${JSON.stringify(conversationHistory, null, 2)}
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Instructions:
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- Each entry shows: account_fqn (who posted), mentions (tagged users), and plaintext_content (message)
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- The first mention is the direct recipient
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- Address users with @ before their names
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- Use markdown formatting and emojis sparingly`;
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}
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// Switch to chat request format (messages array auto-handles Llama 3 template)
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const ollamaRequestBody: OllamaChatRequest = {
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model: ollamaModel,
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messages: [
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{ role: "system", content: systemContent as string },
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{ role: "system", content: systemContent },
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{ role: "user", content: userMessage },
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],
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stream: false,
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options: ollamaConfig,
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options: {
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...ollamaConfig,
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stop: ["<|im_end|>", "\n\n"],
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},
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};
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// Change endpoint to /api/chat
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@ -145,16 +137,12 @@ const postReplyToStatus = async (
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ollamaResponseBody: OllamaChatResponse
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) => {
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const { pleromaInstanceUrl, bearerToken } = envConfig;
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// const emojiList = await getInstanceEmojis();
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// let randomEmoji;
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// if (emojiList) {
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// randomEmoji = selectRandomEmoji(emojiList);
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// }
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try {
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let mentions: string[];
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const statusBody: NewStatusBody = {
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content_type: "text/markdown",
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status: `${ollamaResponseBody.message.content}`,
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status: ollamaResponseBody.message.content,
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in_reply_to_id: notification.status.id,
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};
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if (
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@ -198,10 +186,17 @@ const createTimelinePost = async () => {
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model: ollamaModel,
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messages: [
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{ role: "system", content: ollamaSystemPrompt as string },
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{ role: "user", content: "Say something random." },
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{
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role: "user",
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content:
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"Make a post about something. Keep your tone authentic, as if you are a real person making a post about a topic that interests you on a microblogging platform. This can be about anything like politics, gardening, homesteading, your favorite animal, a fun fact, what happened during your day, seeking companionship, baking, cooking, et cetera. Do not format the post with a title or quotes, nor sign the post with your name. It will be posted to your timeline so everyone will know you said it.",
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},
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],
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stream: false,
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options: ollamaConfig,
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options: {
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...ollamaConfig,
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stop: ["<|start_header_id|>", "<|end_header_id|>", "<|eot_id|>"],
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},
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};
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try {
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const response = await fetch(`${ollamaUrl}/api/chat`, {
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@ -277,6 +272,11 @@ console.log(
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envConfig.fetchInterval / 1000
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} seconds.`
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);
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console.log(
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`Making ad-hoc post to ${envConfig.pleromaInstanceDomain}, every ${
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envConfig.adHocPostInterval / 1000 / 60
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} minutes.`
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);
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console.log(
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`Accepting prompts from: ${envConfig.whitelistedDomains.join(", ")}`
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);
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@ -288,7 +288,4 @@ console.log(
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console.log(`System prompt: ${envConfig.ollamaSystemPrompt}`);
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await beginFetchCycle();
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// setInterval(async () => {
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// createTimelinePost();
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// }, 10000);
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await beginStatusPostInterval();
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