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2 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 3121d542d4 | |||
| 51ab8f2538 |
8
main.mjs
8
main.mjs
@@ -17,5 +17,9 @@ const skills = [{
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}];
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const history = [], memory = [];
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console.log(await ai.language.ask('Can you tell me how to use momentum?', {history, skills}));
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console.log(history, memory);
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await ai.language.ask('My favorite color is red', {history, memory});
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await ai.language.updateMemory(history, memory);
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history.splice(0, history.length);
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console.log(await ai.language.ask('Whats my favorite color?', {history, memory}));
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console.log(history);
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@@ -1,6 +1,6 @@
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{
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"name": "@ztimson/ai-utils",
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"version": "1.0.2",
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"version": "1.0.4",
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"description": "AI Utility library",
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"author": "Zak Timson",
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"license": "MIT",
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37
src/llm.ts
37
src/llm.ts
@@ -171,8 +171,8 @@ class LLM {
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let abort = () => {};
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return Object.assign(new Promise<string>(async res => {
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let tools: AiTool[] = options.tools || this.ai.options.llm?.tools || [];
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const prompts: string[] = [options.system || this.ai.options.llm?.system || ''];
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if(!options.history) options.history = [];
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const prompts: string[] = [];
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let history = options.history || [];
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// MCP
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const mcp = options.mcp || this.ai.options?.llm?.mcp;
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@@ -192,30 +192,33 @@ class LLM {
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// Memory
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if(options.memory) {
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const relevant = await this.memoryManager.recollect(message, options.memory);
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if(relevant.length) {
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const context = relevant.map(m => `### ${m.name}\n${m.content}`).join('\n\n');
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options.history.push({
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id: 'auto_recall_' + Math.random().toString(), role: 'tool', name: 'recall', args: {},
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content: `Knowledge Documents:\n\n${context}`
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});
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}
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prompts.unshift('You have access to a knowledge base. Relevant documents are injected automatically before each message. Use this knowledge to inform your responses.');
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const relevant = await this.memoryManager.recollect(message, options.memory, 1);
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prompts.unshift(`You have access to the following memory files:
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${options.memory.map(m => `- ${m.name}: ${m.description}`).join('\n')}
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${relevant.length ? `
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The closest memory has been added primitively:
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\`\`\`
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Name: ${relevant[0].name}
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Description: ${relevant[0].description}
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${relevant[0].content}
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\`\`\`
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`: ''}`.trim());
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tools.push(this.memoryManager.tools.read(<Memory[]>options.memory));
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}
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prompts.unshift(options.system || this.ai.options.llm?.system || '');
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const resp = await this.models[m].ask(message, {...options, tools, system: prompts.filter(Boolean).join('\n\n')});
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// Trim memory injections from history
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if(options.memory) {
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options.history.splice(0, options.history.length, ...options.history.filter(h =>
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h.role !== 'tool' || h.name !== 'recall'));
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history.splice(0, history.length, ...history.filter(h => h.role !== 'tool' || h.name !== 'recall'));
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}
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// Auto-memorize before compressing
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if(options.compress) {
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if(options.memory) await this.memoryManager.memorize(options.history, options.memory, options);
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const compressed = await this.compressHistory(options.history, options.compress.max, options.compress.min, options);
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options.history.splice(0, options.history.length, ...compressed);
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if(options.compress && this.estimateTokens(history) >= options.compress.max) {
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if(options.memory) await this.memoryManager.memorize(history, options.memory, options);
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const compressed = await this.compressHistory(history, options.compress.max, options.compress.min, options);
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if(options.history) options.history.splice(0, options.history.length, ...compressed);
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}
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return res(resp);
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@@ -1,5 +1,6 @@
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// memory.ts
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import {LLMRequest, LLMMessage} from './llm.ts';
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import {AiTool} from './tools.ts';
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/** Background information the AI will be fed as a knowledge document */
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export type Memory = {
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@@ -25,9 +26,9 @@ export type MemoryCollection = {
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export class MemoryManager {
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tools = {
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edit: (memory: Memory) => ({
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name: 'edit',
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description: 'Edit a memory. Omit start/end to append. Pass start only to replace from that line on. Pass start+end to replace a specific range. start=0 replaces the whole document.',
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edit: (memory: Memory): AiTool => ({
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name: 'edit_memory',
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description: 'Edit a memory. Omit start/end to append. Pass start only to replace from that line on (Note line 0 = first line of content / line AFTER description). Pass start+end to replace a specific range. start=0 replaces the whole document. Returns updated document',
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args: {
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content: {type: 'string', description: 'New content', required: true},
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start: {type: 'number', description: 'First line to replace (0-indexed, inclusive). Omit to append.'},
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@@ -40,15 +41,15 @@ export class MemoryManager {
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else if(args.end === undefined) lines.splice(args.start, lines.length - args.start, ...newLines);
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else lines.splice(args.start, args.end - args.start + 1, ...newLines);
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memory.content = lines.join('\n');
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return `Updated memory:\n${memory.content}`;
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return memory.content;
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}
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}),
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extract: (pools: MemoryCollection[]) => ({
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name: 'extract',
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extract: (pools: MemoryCollection[]): AiTool => ({
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name: 'extract_facts',
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description: 'Extract a list of facts to group into a single memory',
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args: {
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name: {type: 'string', description: 'Exact name of an existing memory, or a new name if none fits ([pro]nouns only)', required: true},
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description: {type: 'string', description: 'One sentence description of the memory subject, only required if new'},
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description: {type: 'string', description: 'One sentence description of the memory subject', required: true},
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facts: {type: 'string', description: 'Comma separated list of extracted facts', required: true},
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},
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fn: (args: any) => {
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@@ -59,8 +60,8 @@ export class MemoryManager {
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});
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return 'Success';
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}}),
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read: (memories: Memory[]) => ({
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name: 'read',
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read: (memories: Memory[]): AiTool => ({
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name: 'read_memory',
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description: 'Read entire memory',
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args: {
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name: {type: 'string', description: 'Exact memory name', required: true},
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@@ -94,9 +95,9 @@ Rules:
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- ONLY extract decisions that were MADE during this conversation
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- DO NOT extract anything the AI said, its name, capabilities, or how it introduced itself
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- DO NOT extract greetings, pleasantries or generic exchanges
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- If nothing worth remembering was said, call NO tools
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- If nothing worth remembering was said, dont do anything, skip calling tools
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For each fact decide whether it belongs in an existing document or needs a new one, then call the \`extract\` tool.
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For each fact decide whether it belongs in an existing document or needs a new one, then call the \`extract_facts\` tool.
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Existing documents:\n${existingDocs || 'None yet.'}`,
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tools: [this.tools.extract(pools)]
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@@ -120,18 +121,17 @@ Existing documents:\n${existingDocs || 'None yet.'}`,
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{
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model: this.model || options.model,
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temperature: 0.2,
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system: `You are a document editor. Merge the users list of facts into the following document using the \`edit\` tool; call it as many times as necessary.
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Name: ${mem.name}
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Description: ${mem.description}
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${mem.content}`,
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system: `You are a document editor. Merge the users list of facts into the following document using the \`edit_memory\` tool; call it as many times as necessary:
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\`\`\`
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${mem.content}
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\`\`\``,
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tools: [this.tools.edit(mem)]
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}
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);
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if(isNew || mem.description !== existing?.description) {
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const [e] = await this.llm.embedding(mem.description);
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mem.embedding = e.embedding;
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const e = await this.llm.embedding(mem.description);
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mem.embedding = e?.[0]?.embedding;
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}
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if(isNew) memories.push(mem);
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@@ -12,12 +12,12 @@ export class Vision {
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*/
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ocr(path: string): AbortablePromise<string | null> {
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let worker: any;
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const p = new Promise<string | null>(async res => {
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const p = (async () => {
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worker = await createWorker(this.ai.options.ocr || 'eng', 2, {cachePath: this.ai.options.path});
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const {data} = await worker.recognize(path);
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await worker.terminate();
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res(data.text.trim() || null);
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}).finally(() => worker?.terminate());
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return data.text.trim() || null;
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})().finally(() => worker?.terminate());
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return Object.assign(p, {abort: () => worker?.terminate()});
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}
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}
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