Compare commits
23 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 4230b534fc | |||
| 119f8472f2 | |||
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| be08db8e2c | |||
| 497f051c62 | |||
| 62fbe73b22 | |||
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| 89619e211e | |||
| afc6653364 | |||
| 68e72445a2 | |||
| 1aa6cdf329 | |||
| d022a5ef4d | |||
| a1d438a20a | |||
| 52a9e3aaa4 | |||
| a7aec4ee29 | |||
| dda2d4c2a3 | |||
| 58e0e488e4 | |||
| 8dfcd06752 | |||
| 14f6cdd313 | |||
| 73d6ee0f2a | |||
| bee4085666 | |||
| 3b5c71de7c |
234
package-lock.json
generated
234
package-lock.json
generated
@@ -1,12 +1,12 @@
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|||||||
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@@ -57,34 +57,38 @@
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@@ -2565,9 +2605,9 @@
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@@ -3092,9 +3132,9 @@
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@@ -3232,9 +3272,9 @@
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@@ -3252,7 +3292,7 @@
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@@ -3787,9 +3827,9 @@
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@@ -3981,16 +4021,16 @@
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@@ -1,6 +1,6 @@
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|
||||||
"description": "AI Utility library",
|
"description": "AI Utility library",
|
||||||
"author": "Zak Timson",
|
"author": "Zak Timson",
|
||||||
"license": "MIT",
|
"license": "MIT",
|
||||||
|
|||||||
@@ -1,16 +1,27 @@
|
|||||||
import {Anthropic as anthropic} from '@anthropic-ai/sdk';
|
import {Anthropic as anthropic} from '@anthropic-ai/sdk';
|
||||||
import {findByProp, objectMap, JSONSanitize, JSONAttemptParse} from '@ztimson/utils';
|
import {findByProp, objectMap, JSONSanitize, JSONAttemptParse, makeArray} from '@ztimson/utils';
|
||||||
import {AbortablePromise, Ai} from './ai.ts';
|
import {AbortablePromise, Ai} from './ai.ts';
|
||||||
import {LLMMessage, LLMRequest} from './llm.ts';
|
import {LLMMessage, LLMRequest} from './llm.ts';
|
||||||
import {LLMProvider} from './provider.ts';
|
import {LLMProvider} from './provider.ts';
|
||||||
|
import {TokenPool} from './token-pool.ts';
|
||||||
import {convertSchema} from './tools.ts';
|
import {convertSchema} from './tools.ts';
|
||||||
|
|
||||||
export class Anthropic extends LLMProvider {
|
export class Anthropic extends LLMProvider {
|
||||||
client!: anthropic;
|
private clients = new Map<string, anthropic>();
|
||||||
|
tokenPool!: TokenPool;
|
||||||
|
|
||||||
constructor(public readonly ai: Ai, public readonly apiToken: string, public model: string) {
|
constructor(public readonly ai: Ai, public readonly apiToken: string | string[], public model: string) {
|
||||||
super();
|
super();
|
||||||
this.client = new anthropic({apiKey: apiToken});
|
this.tokenPool = new TokenPool(...makeArray(apiToken).filter(Boolean));
|
||||||
|
}
|
||||||
|
|
||||||
|
private getClient(token: string): anthropic {
|
||||||
|
let client = this.clients.get(token);
|
||||||
|
if(!client) {
|
||||||
|
client = new anthropic({apiKey: token});
|
||||||
|
this.clients.set(token, client);
|
||||||
|
}
|
||||||
|
return client;
|
||||||
}
|
}
|
||||||
|
|
||||||
private toStandard(history: any[]): LLMMessage[] {
|
private toStandard(history: any[]): LLMMessage[] {
|
||||||
@@ -21,10 +32,10 @@ export class Anthropic extends LLMProvider {
|
|||||||
messages.push(<any>{timestamp, ...h});
|
messages.push(<any>{timestamp, ...h});
|
||||||
} else {
|
} else {
|
||||||
const textContent = h.content?.filter((c: any) => c.type == 'text').map((c: any) => c.text).join('\n\n');
|
const textContent = h.content?.filter((c: any) => c.type == 'text').map((c: any) => c.text).join('\n\n');
|
||||||
if(textContent) messages.push({timestamp, role: h.role, content: textContent});
|
if(textContent) messages.push({role: h.role, content: textContent, timestamp: timestamp, duration: h.duration, tps: h.tps});
|
||||||
h.content.forEach((c: any) => {
|
h.content.forEach((c: any) => {
|
||||||
if(c.type == 'tool_use') {
|
if(c.type == 'tool_use') {
|
||||||
messages.push({timestamp, role: 'tool', id: c.id, name: c.name, args: c.input, content: undefined});
|
messages.push({role: 'tool', id: c.id, name: c.name, args: c.input, timestamp: h.timestamp, content: undefined, duration: h.duration, tps: h.tps});
|
||||||
} else if(c.type == 'tool_result') {
|
} else if(c.type == 'tool_result') {
|
||||||
const m: any = messages.findLast(m => (<any>m).id == c.tool_use_id);
|
const m: any = messages.findLast(m => (<any>m).id == c.tool_use_id);
|
||||||
if(m) m[c.is_error ? 'error' : 'content'] = c.content;
|
if(m) m[c.is_error ? 'error' : 'content'] = c.content;
|
||||||
@@ -46,13 +57,16 @@ export class Anthropic extends LLMProvider {
|
|||||||
i++;
|
i++;
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
return history.map(({timestamp, ...h}) => h);
|
return history;
|
||||||
}
|
}
|
||||||
|
|
||||||
ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> {
|
ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> {
|
||||||
const controller = new AbortController();
|
const controller = new AbortController();
|
||||||
return Object.assign(new Promise<any>(async (res) => {
|
return Object.assign(new Promise<any>(async (res) => {
|
||||||
let history = this.fromStandard([...options.history || [], {role: 'user', content: message, timestamp: Date.now()}]);
|
let history = this.fromStandard([
|
||||||
|
...(options.history || []).filter(h => h.role !== 'system'),
|
||||||
|
{role: 'user', content: message, timestamp: Date.now()}
|
||||||
|
]);
|
||||||
const tools = options.tools || this.ai.options.llm?.tools || [];
|
const tools = options.tools || this.ai.options.llm?.tools || [];
|
||||||
const requestParams: any = {
|
const requestParams: any = {
|
||||||
model: options.model || this.model,
|
model: options.model || this.model,
|
||||||
@@ -83,17 +97,17 @@ export class Anthropic extends LLMProvider {
|
|||||||
};
|
};
|
||||||
}
|
}
|
||||||
|
|
||||||
let resp: any, isFirstMessage = true;
|
let resp: any, terminal = false, duration = 0, tps = 0;
|
||||||
do {
|
do {
|
||||||
resp = await this.client.messages.create(requestParams).catch(err => {
|
requestParams.messages = history.map(({timestamp, ...m}) => m);
|
||||||
|
const callStart = Date.now();
|
||||||
|
resp = await this.tokenPool.run(token => this.getClient(token).messages.create(requestParams)).catch(err => {
|
||||||
err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`;
|
err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`;
|
||||||
throw err;
|
throw err;
|
||||||
});
|
});
|
||||||
|
|
||||||
// Streaming mode
|
let usage: any;
|
||||||
if(options.stream) {
|
if(options.stream) {
|
||||||
if(!isFirstMessage) options.stream({text: '\n\n'});
|
|
||||||
else isFirstMessage = false;
|
|
||||||
resp.content = [];
|
resp.content = [];
|
||||||
for await (const chunk of resp) {
|
for await (const chunk of resp) {
|
||||||
if(controller.signal.aborted) break;
|
if(controller.signal.aborted) break;
|
||||||
@@ -113,42 +127,57 @@ export class Anthropic extends LLMProvider {
|
|||||||
}
|
}
|
||||||
} else if(chunk.type === 'content_block_stop') {
|
} else if(chunk.type === 'content_block_stop') {
|
||||||
const last = resp.content.at(-1);
|
const last = resp.content.at(-1);
|
||||||
if(last.input != null) last.input = last.input ? JSONAttemptParse(last.input, {}) : {};
|
if(last?.input != null) last.input = last.input ? JSONAttemptParse(last.input, {}) : {};
|
||||||
|
} else if(chunk.type === 'message_delta') {
|
||||||
|
if(chunk.usage) usage = chunk.usage;
|
||||||
} else if(chunk.type === 'message_stop') {
|
} else if(chunk.type === 'message_stop') {
|
||||||
break;
|
break;
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
} else {
|
||||||
|
usage = resp.usage;
|
||||||
}
|
}
|
||||||
|
duration = Date.now() - callStart;
|
||||||
|
tps = usage?.output_tokens && duration > 0 ? usage.output_tokens / (duration / 1000) : 0;
|
||||||
|
|
||||||
// Run tools
|
|
||||||
const toolCalls = resp.content.filter((c: any) => c.type === 'tool_use');
|
const toolCalls = resp.content.filter((c: any) => c.type === 'tool_use');
|
||||||
if(toolCalls.length && !controller.signal.aborted) {
|
if(toolCalls.length && !controller.signal.aborted) {
|
||||||
history.push({role: 'assistant', content: resp.content});
|
history.push({role: 'assistant', content: resp.content, timestamp: Date.now(), duration, tps});
|
||||||
const results = await Promise.all(toolCalls.map(async (toolCall: any) => {
|
const results = await Promise.all(toolCalls.map(async (toolCall: any) => {
|
||||||
const tool = tools.find(findByProp('name', toolCall.name));
|
const tool = tools.find(findByProp('name', toolCall.name));
|
||||||
if(options.stream) options.stream({tool: toolCall.name});
|
if(options.stream) options.stream({tool: toolCall.name});
|
||||||
if(!tool) return {tool_use_id: toolCall.id, is_error: true, content: 'Tool not found'};
|
if(!tool) return {tool_use_id: toolCall.id, is_error: true, content: 'Tool not found'};
|
||||||
try {
|
try {
|
||||||
const result = await tool.fn(toolCall.input, options?.stream, this.ai);
|
const toolStream = options.stream && ((chunk: any) => {
|
||||||
|
if(chunk.done) { terminal = true; return; }
|
||||||
|
options.stream!(chunk);
|
||||||
|
});
|
||||||
|
const result = await tool.fn(toolCall.input, toolStream, this.ai, toolCall.id);
|
||||||
return {type: 'tool_result', tool_use_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result};
|
return {type: 'tool_result', tool_use_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result};
|
||||||
} catch (err: any) {
|
} catch (err: any) {
|
||||||
return {type: 'tool_result', tool_use_id: toolCall.id, is_error: true, content: err?.message || err?.toString() || 'Unknown'};
|
return {type: 'tool_result', tool_use_id: toolCall.id, is_error: true, content: err?.message || err?.toString() || 'Unknown'};
|
||||||
}
|
}
|
||||||
}));
|
}));
|
||||||
history.push({role: 'user', content: results});
|
history.push({role: 'user', content: results, timestamp: Date.now()});
|
||||||
requestParams.messages = history;
|
requestParams.messages = history;
|
||||||
}
|
}
|
||||||
} while (!controller.signal.aborted && resp.content.some((c: any) => c.type === 'tool_use'));
|
} while (!terminal && !controller.signal.aborted && resp.content.some((c: any) => c.type === 'tool_use'));
|
||||||
|
|
||||||
|
if(!terminal) {
|
||||||
const textContent = resp.content.filter((c: any) => c.type == 'text').map((c: any) => c.text).join('\n\n');
|
const textContent = resp.content.filter((c: any) => c.type == 'text').map((c: any) => c.text).join('\n\n');
|
||||||
history.push({role: 'assistant', content: textContent});
|
history.push({role: 'assistant', content: textContent.trim(), timestamp: Date.now(), duration, tps});
|
||||||
|
}
|
||||||
|
|
||||||
history = this.toStandard(history);
|
history = this.toStandard(history);
|
||||||
|
|
||||||
if(options.stream) options.stream({done: true});
|
|
||||||
if(options.history) options.history.splice(0, options.history.length, ...history);
|
if(options.history) options.history.splice(0, options.history.length, ...history);
|
||||||
|
if(options.stream) options.stream({done: true});
|
||||||
|
|
||||||
|
const turnStart = history.map(h => h.role).lastIndexOf('user');
|
||||||
|
const finalContent = history.slice(turnStart + 1).reduce((str, h) => {
|
||||||
|
if(h.role === 'assistant') return str + (h.content || '');
|
||||||
|
return str;
|
||||||
|
}, '').trim();
|
||||||
|
|
||||||
// Return parsed JSON if schema provided
|
|
||||||
const finalContent = history.at(-1)?.content;
|
|
||||||
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
|
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
|
||||||
}), {abort: () => controller.abort()});
|
}), {abort: () => controller.abort()});
|
||||||
}
|
}
|
||||||
|
|||||||
@@ -5,5 +5,6 @@ export * from './llm';
|
|||||||
export * from './memory';
|
export * from './memory';
|
||||||
export * from './open-ai';
|
export * from './open-ai';
|
||||||
export * from './provider';
|
export * from './provider';
|
||||||
|
export * from './token-pool'
|
||||||
export * from './tools';
|
export * from './tools';
|
||||||
export * from './vision';
|
export * from './vision';
|
||||||
|
|||||||
221
src/llm.ts
221
src/llm.ts
@@ -1,3 +1,4 @@
|
|||||||
|
import {snakeCase} from '@ztimson/utils';
|
||||||
import {AbortablePromise, Ai} from './ai.ts';
|
import {AbortablePromise, Ai} from './ai.ts';
|
||||||
import {Anthropic} from './antrhopic.ts';
|
import {Anthropic} from './antrhopic.ts';
|
||||||
import {OpenAi} from './open-ai.ts';
|
import {OpenAi} from './open-ai.ts';
|
||||||
@@ -6,10 +7,25 @@ import {AiTool, AiToolArg} from './tools.ts';
|
|||||||
import {fileURLToPath} from 'url';
|
import {fileURLToPath} from 'url';
|
||||||
import {dirname, join} from 'path';
|
import {dirname, join} from 'path';
|
||||||
import {spawn} from 'node:child_process';
|
import {spawn} from 'node:child_process';
|
||||||
import {Memory, MemoryCache, MemoryManager} from './memory.ts';
|
import {Memory, MemoryCache, MemoryManager, MemoryOptions} from './memory.ts';
|
||||||
|
|
||||||
export type AnthropicConfig = {proto: 'anthropic', token: string};
|
const MAX_AGENT_DEPTH = 5;
|
||||||
export type OpenAiConfig = {proto: 'openai', host?: string, token: string};
|
|
||||||
|
export type AnthropicConfig = {proto: 'anthropic', token: string | string[]};
|
||||||
|
export type OpenAiConfig = {proto: 'openai', host?: string, token: string | string[]};
|
||||||
|
|
||||||
|
export type Agent = {
|
||||||
|
name: string;
|
||||||
|
description?: string;
|
||||||
|
model?: string | null;
|
||||||
|
temperature?: number;
|
||||||
|
system: string;
|
||||||
|
delegate?: boolean;
|
||||||
|
skills?: Skill[] | null;
|
||||||
|
tools?: AiTool[] | null;
|
||||||
|
mcp?: McpServer[] | null;
|
||||||
|
agents?: string[] | null;
|
||||||
|
}
|
||||||
|
|
||||||
export type LLMMessage = {
|
export type LLMMessage = {
|
||||||
/** Message originator */
|
/** Message originator */
|
||||||
@@ -33,6 +49,10 @@ export type LLMMessage = {
|
|||||||
error?: undefined | string;
|
error?: undefined | string;
|
||||||
/** Timestamp */
|
/** Timestamp */
|
||||||
timestamp?: number;
|
timestamp?: number;
|
||||||
|
/** Response duration in ms */
|
||||||
|
duration?: number;
|
||||||
|
/** Tokens per second */
|
||||||
|
tps?: number;
|
||||||
}
|
}
|
||||||
|
|
||||||
export type LLMRequest = {
|
export type LLMRequest = {
|
||||||
@@ -55,13 +75,17 @@ export type LLMRequest = {
|
|||||||
/** Compress old messages in the chat to free up context */
|
/** Compress old messages in the chat to free up context */
|
||||||
compress?: {max: number; min: number};
|
compress?: {max: number; min: number};
|
||||||
/** User's memory documents - RAG injected automatically each turn */
|
/** User's memory documents - RAG injected automatically each turn */
|
||||||
memory?: Memory[] | MemoryCache;
|
memory?: Memory[] | MemoryCache | MemoryOptions;
|
||||||
/** Model to use for memory operations */
|
/** Model to use for memory operations */
|
||||||
memoryModel?: string;
|
memoryModel?: string;
|
||||||
/** Skill documents the AI can browse and read on demand */
|
/** Skill documents the AI can browse and read on demand */
|
||||||
skills?: Skill[];
|
skills?: Skill[];
|
||||||
/** MCP servers to connect and expose as tools */
|
/** MCP servers to connect and expose as tools */
|
||||||
mcp?: McpServer[];
|
mcp?: McpServer[];
|
||||||
|
/** Subagents exposed as delegatable/wrapped tools */
|
||||||
|
agents?: Agent[];
|
||||||
|
/** @internal recursion guard for nested agent delegation */
|
||||||
|
_agentDepth?: number;
|
||||||
}
|
}
|
||||||
|
|
||||||
export type McpServer = {
|
export type McpServer = {
|
||||||
@@ -82,7 +106,6 @@ export type Skill = {
|
|||||||
content: string;
|
content: string;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|
||||||
class LLM {
|
class LLM {
|
||||||
private memoryManager!: MemoryManager;
|
private memoryManager!: MemoryManager;
|
||||||
|
|
||||||
@@ -99,6 +122,52 @@ class LLM {
|
|||||||
this.memoryManager = new MemoryManager(this);
|
this.memoryManager = new MemoryManager(this);
|
||||||
}
|
}
|
||||||
|
|
||||||
|
private setupAgent(agents: Agent[] = [], allAgents: Agent[], history: LLMMessage[], aborts: (() => void)[], depth = 0, delegateState: {resp: string | null}): AiTool[] {
|
||||||
|
return agents.map(a => {
|
||||||
|
const toolName = `${a.delegate ? '' : 'sub'}agent_${snakeCase(a.name)}`;
|
||||||
|
return {
|
||||||
|
name: toolName,
|
||||||
|
description: `${a.delegate ? 'Delegate to ' : ''}Subagent: ${a.description || a.name}`,
|
||||||
|
args: <any>(a.delegate ? {} : {
|
||||||
|
context: {type: 'string', description: 'Summary of related messages, samples, files, etc...', required: true},
|
||||||
|
instructions: {type: 'string', description: 'Detailed instructions for subagent to complete', required: true},
|
||||||
|
}),
|
||||||
|
fn: async (args: any, stream: any, ai: any, id?: string) => {
|
||||||
|
if(depth >= MAX_AGENT_DEPTH) return 'Max agent delegation depth exceeded';
|
||||||
|
|
||||||
|
// Opt-in only, self always excluded regardless of whitelist
|
||||||
|
const nested = (a.agents || [])
|
||||||
|
.map(name => allAgents.find(x => x.name === name))
|
||||||
|
.filter((x): x is Agent => !!x && x.name !== a.name);
|
||||||
|
|
||||||
|
const request = this.ask(a.delegate ? '' : `${args.instructions}${args.context ? `\n\n<context>${args.context}</context>` : ''}`, {
|
||||||
|
system: `You are a specialized subagent. ${a.delegate ? 'Your output streams directly to the user for the remainder of this turn. You are mid conversation - dispense with greetings.' : 'You are wrapped in a tool call that will be analysis by an LLM - dispense with conversation'}
|
||||||
|
As a subagent, focus on executing your task completely using available tools and returning only the final result - no commentary, questions, or dialogue.
|
||||||
|
|
||||||
|
${a.system}`,
|
||||||
|
model: a.model || undefined,
|
||||||
|
temperature: a.temperature,
|
||||||
|
stream: a.delegate ? stream : undefined,
|
||||||
|
history: a.delegate ? history : [],
|
||||||
|
mcp: a.mcp || undefined,
|
||||||
|
skills: a.skills || undefined,
|
||||||
|
tools: a.tools || undefined,
|
||||||
|
agents: nested,
|
||||||
|
_agentDepth: depth + 1,
|
||||||
|
} as any);
|
||||||
|
aborts.push(request.abort);
|
||||||
|
const resp = await request;
|
||||||
|
|
||||||
|
if(a.delegate) {
|
||||||
|
delegateState.resp = resp;
|
||||||
|
return '';
|
||||||
|
}
|
||||||
|
return resp;
|
||||||
|
}
|
||||||
|
};
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
private async setupMcp(servers: McpServer[] = []): Promise<{prompt: string, tools: AiTool[]}> {
|
private async setupMcp(servers: McpServer[] = []): Promise<{prompt: string, tools: AiTool[]}> {
|
||||||
if(!servers?.length) return {prompt: '', tools: []};
|
if(!servers?.length) return {prompt: '', tools: []};
|
||||||
const allTools: AiTool[] = [];
|
const allTools: AiTool[] = [];
|
||||||
@@ -143,7 +212,7 @@ class LLM {
|
|||||||
return {
|
return {
|
||||||
prompt: `You have access to the following skill documents, use \`read_skill\` to access them:\n${list}`,
|
prompt: `You have access to the following skill documents, use \`read_skill\` to access them:\n${list}`,
|
||||||
tools: [{
|
tools: [{
|
||||||
name: 'read_skill',
|
name: 'skill_read',
|
||||||
description: 'Read the full content of a skill/knowledge document',
|
description: 'Read the full content of a skill/knowledge document',
|
||||||
args: {
|
args: {
|
||||||
name: {type: 'string', description: 'Exact skill name', required: true}
|
name: {type: 'string', description: 'Exact skill name', required: true}
|
||||||
@@ -157,6 +226,20 @@ class LLM {
|
|||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
private wrapToolTiming(tools: AiTool[], timings: Map<string, {duration: number, tps: number}>): AiTool[] {
|
||||||
|
return tools.map(t => ({
|
||||||
|
...t,
|
||||||
|
fn: async (args: any, stream: any, ai: any, id?: string) => {
|
||||||
|
const start = Date.now();
|
||||||
|
const result = await t.fn(args, stream, ai, id);
|
||||||
|
const duration = Date.now() - start;
|
||||||
|
const tps = duration > 0 ? this.estimateTokens(result) / (duration / 1000) : 0;
|
||||||
|
if(id) timings.set(id, {duration, tps});
|
||||||
|
return result;
|
||||||
|
}
|
||||||
|
}));
|
||||||
|
}
|
||||||
|
|
||||||
ask(message: string, options: LLMRequest = {}): AbortablePromise<string> {
|
ask(message: string, options: LLMRequest = {}): AbortablePromise<string> {
|
||||||
options = <any>{
|
options = <any>{
|
||||||
system: '',
|
system: '',
|
||||||
@@ -167,8 +250,19 @@ class LLM {
|
|||||||
}
|
}
|
||||||
const m = options.model || this.defaultModel;
|
const m = options.model || this.defaultModel;
|
||||||
if(!this.models[m]) throw new Error(`Model does not exist: ${m}`);
|
if(!this.models[m]) throw new Error(`Model does not exist: ${m}`);
|
||||||
let abort = () => {};
|
let request: AbortablePromise<string> | null = null;
|
||||||
return Object.assign(new Promise<string>(async res => {
|
let aborted = false;
|
||||||
|
const nestedAborts: (() => void)[] = [];
|
||||||
|
const abort = () => {
|
||||||
|
aborted = true;
|
||||||
|
request?.abort?.();
|
||||||
|
nestedAborts.forEach(a => a());
|
||||||
|
};
|
||||||
|
|
||||||
|
let promise: any;
|
||||||
|
const requestStart = Date.now();
|
||||||
|
|
||||||
|
promise = (async () => {
|
||||||
let tools: AiTool[] = options.tools || this.ai.options.llm?.tools || [];
|
let tools: AiTool[] = options.tools || this.ai.options.llm?.tools || [];
|
||||||
const prompts: string[] = [];
|
const prompts: string[] = [];
|
||||||
let history = options.history || [];
|
let history = options.history || [];
|
||||||
@@ -189,48 +283,93 @@ class LLM {
|
|||||||
tools.push(...s.tools);
|
tools.push(...s.tools);
|
||||||
}
|
}
|
||||||
|
|
||||||
|
// Agents
|
||||||
|
const agents = options.agents || this.ai.options?.llm?.agents;
|
||||||
|
const delegateState: {resp: string | null} = {resp: null};
|
||||||
|
if(agents?.length) tools.push(...this.setupAgent(agents, agents, history, nestedAborts, options._agentDepth || 0, delegateState));
|
||||||
|
|
||||||
// Memory
|
// Memory
|
||||||
if (options.memory) {
|
const mem = MemoryManager.normalize(options.memory);
|
||||||
const mems = options.memory instanceof MemoryCache ? options.memory.memories : options.memory;
|
if(mem) {
|
||||||
const relevant = await this.memoryManager.recollect(message, options.memory, 5);
|
const mems = mem.memory instanceof MemoryCache ? mem.memory.memories : mem.memory;
|
||||||
|
if(mems.length) {
|
||||||
|
if(mem.inject) {
|
||||||
|
const pool = 15; // candidates considered, cheap since only refs are listed
|
||||||
|
const budget = mem.maxTokens ?? 2000; // actual content injected
|
||||||
|
const relevant = await this.memoryManager.recollect(message, mem.memory, pool);
|
||||||
|
|
||||||
|
let used = 0;
|
||||||
|
const preloaded: typeof relevant = [];
|
||||||
|
const listed: typeof relevant = [];
|
||||||
|
for(const r of relevant) {
|
||||||
|
const t = this.estimateTokens(r.content);
|
||||||
|
if(used + t <= budget || preloaded.length === 0) {
|
||||||
|
preloaded.push(r);
|
||||||
|
used += t;
|
||||||
|
} else listed.push(r);
|
||||||
|
}
|
||||||
|
|
||||||
prompts.unshift(`You have access to the following memory files:
|
prompts.unshift(`You have access to the following memory files:
|
||||||
${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')}
|
${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')}
|
||||||
${relevant.length ? `
|
${preloaded.length ? `
|
||||||
Relevant memories have been preloaded:
|
Relevant memories have been preloaded:
|
||||||
${relevant.map(r => `
|
${preloaded.map(r => `
|
||||||
**${r.name}**
|
**${r.name}**
|
||||||
${r.description}
|
${r.description}
|
||||||
${r.content}
|
${r.content}
|
||||||
`).join('\n---\n')}
|
`).join('\n---\n')}
|
||||||
|
` : ''}${listed.length ? `
|
||||||
|
Also relevant but not preloaded (use \`memory_recall\`): ${listed.map(r => r.name).join(', ')}
|
||||||
` : ''}`.trim());
|
` : ''}`.trim());
|
||||||
tools.push(this.memoryManager.tools.read(options.memory));
|
|
||||||
}
|
}
|
||||||
|
if(mem.tool) tools.push(this.memoryManager.tools.read(mem.memory));
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
if(aborted) throw Object.assign(new Error('Aborted'), {name: 'AbortError'});
|
||||||
|
|
||||||
|
const toolTimings = new Map<string, {duration: number, tps: number}>();
|
||||||
|
tools = this.wrapToolTiming(tools, toolTimings);
|
||||||
|
|
||||||
|
if(aborted) throw Object.assign(new Error('Aborted'), {name: 'AbortError'});
|
||||||
|
|
||||||
prompts.unshift(options.system || this.ai.options.llm?.system || '');
|
prompts.unshift(options.system || this.ai.options.llm?.system || '');
|
||||||
const resp = await this.models[m].ask(message, {...options, tools, system: prompts.filter(Boolean).join('\n\n')});
|
request = this.models[m].ask(message, {...options, tools, system: prompts.filter(Boolean).join('\n\n')});
|
||||||
|
let resp = await request;
|
||||||
|
|
||||||
// Trim memory injections from history
|
// Capture meta (duration / tps)
|
||||||
if(options.memory) {
|
for(const h of history) {
|
||||||
history.splice(0, history.length, ...history.filter(h => h.role !== 'tool' || h.name !== 'recall'));
|
if(h.role === 'tool' && toolTimings.has(h.id)) Object.assign(h, toolTimings.get(h.id));
|
||||||
}
|
}
|
||||||
|
|
||||||
// Auto-memorize before compressing
|
if(typeof resp === 'string' && !resp.trim() && delegateState.resp !== null) resp = delegateState.resp;
|
||||||
|
|
||||||
|
if(mem?.tool) history.splice(0, history.length, ...history.filter(h => h.role !== 'tool' || h.name !== 'memory_recall'));
|
||||||
if(options.compress && this.estimateTokens(history) >= options.compress.max) {
|
if(options.compress && this.estimateTokens(history) >= options.compress.max) {
|
||||||
if(options.memory) await this.memoryManager.memorize(history, options.memory, {model: options.memoryModel || this.defaultModel, ...options});
|
if(mem?.update) await this.memoryManager.memorize(history, mem.memory, {model: options.memoryModel || this.defaultModel, ...options});
|
||||||
const compressed = await this.compressHistory(history, options.compress.max, options.compress.min, options);
|
const compressed = await this.compressHistory(history, options.compress.max, options.compress.min, options);
|
||||||
if(options.history) options.history.splice(0, options.history.length, ...compressed);
|
if(options.history) options.history.splice(0, options.history.length, ...compressed);
|
||||||
}
|
}
|
||||||
|
|
||||||
return res(resp);
|
const requestDuration = Date.now() - requestStart;
|
||||||
}), {abort});
|
const totalTokens = history
|
||||||
|
.filter((h: any) => h.role === 'assistant' && h.duration && h.tps)
|
||||||
|
.reduce((sum: number, h: any) => sum + h.tps * (h.duration / 1000), 0);
|
||||||
|
const requestTps = requestDuration > 0 ? totalTokens / (requestDuration / 1000) : 0;
|
||||||
|
Object.assign(promise, {duration: requestDuration, tps: requestTps});
|
||||||
|
|
||||||
|
return resp;
|
||||||
|
})();
|
||||||
|
|
||||||
|
return Object.assign(promise, {abort});
|
||||||
}
|
}
|
||||||
|
|
||||||
/**
|
/**
|
||||||
* Digest full conversation history into memory documents.
|
* Digest full conversation history into memory documents.
|
||||||
* Call on session end to persist the conversation.
|
* Call on session end to persist the conversation.
|
||||||
*/
|
*/
|
||||||
async updateMemory(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<void> {
|
async updateMemory(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<Memory[]> {
|
||||||
await this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options});
|
return this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options});
|
||||||
}
|
}
|
||||||
|
|
||||||
/**
|
/**
|
||||||
@@ -383,15 +522,33 @@ ${r.content}
|
|||||||
* @param {string} searchTerms Multiple search terms to check against target
|
* @param {string} searchTerms Multiple search terms to check against target
|
||||||
* @returns {{avg: number, max: number, similarities: number[]}} Similarity values 0-1: 0 = unique, 1 = identical
|
* @returns {{avg: number, max: number, similarities: number[]}} Similarity values 0-1: 0 = unique, 1 = identical
|
||||||
*/
|
*/
|
||||||
fuzzyMatch(target: string, ...searchTerms: string[]) {
|
fuzzyMatch(target, ...searchTerms) {
|
||||||
if(searchTerms.length < 2) throw new Error('Requires at least 2 strings to compare');
|
if (searchTerms.length < 2) throw new Error('Requires at least 2 strings to compare');
|
||||||
const vector = (text: string, dimensions: number = 10): number[] => {
|
const levenshtein = (a, b) => {
|
||||||
return text.toLowerCase().split('').map((char, index) =>
|
const m = a.length, n = b.length;
|
||||||
(char.charCodeAt(0) * (index + 1)) % dimensions / dimensions).slice(0, dimensions);
|
if (!m) return n;
|
||||||
|
if (!n) return m;
|
||||||
|
const dp = Array.from({length: m + 1}, (_, i) => [i, ...Array(n).fill(0)]);
|
||||||
|
for (let j = 0; j <= n; j++) dp[0][j] = j;
|
||||||
|
for (let i = 1; i <= m; i++) {
|
||||||
|
for (let j = 1; j <= n; j++) {
|
||||||
|
dp[i][j] = a[i - 1] === b[j - 1]
|
||||||
|
? dp[i - 1][j - 1]
|
||||||
|
: 1 + Math.min(dp[i - 1][j - 1], dp[i - 1][j], dp[i][j - 1]);
|
||||||
}
|
}
|
||||||
const v = vector(target);
|
}
|
||||||
const similarities = searchTerms.map(t => vector(t)).map(refVector => this.cosineSimilarity(v, refVector));
|
return dp[m][n];
|
||||||
return {avg: similarities.reduce((acc, s) => acc + s, 0) / similarities.length, max: Math.max(...similarities), similarities};
|
};
|
||||||
|
const similarity = (a, b) => {
|
||||||
|
a = a.toLowerCase(); b = b.toLowerCase();
|
||||||
|
return 1 - levenshtein(a, b) / Math.max(a.length, b.length, 1);
|
||||||
|
};
|
||||||
|
const similarities = searchTerms.map(t => similarity(target, t));
|
||||||
|
return {
|
||||||
|
avg: similarities.reduce((acc, s) => acc + s, 0) / similarities.length,
|
||||||
|
max: Math.max(...similarities),
|
||||||
|
similarities
|
||||||
|
};
|
||||||
}
|
}
|
||||||
|
|
||||||
/**
|
/**
|
||||||
|
|||||||
697
src/memory.ts
697
src/memory.ts
@@ -1,92 +1,23 @@
|
|||||||
import {LLMRequest, LLMMessage} from './llm.ts';
|
import {LLMRequest, LLMMessage} from './llm.ts';
|
||||||
import {AiTool} from './tools.ts';
|
import {AiTool} from './tools.ts';
|
||||||
import {KDTree, KDPoint} from './kd-tree.ts';
|
import {KDPoint, KDTree} from './kd-tree.ts';
|
||||||
|
|
||||||
export type Memory = {
|
const FACTS_HEADING = '## Facts';
|
||||||
name: string;
|
|
||||||
description: string;
|
|
||||||
content: string;
|
|
||||||
embedding: number[];
|
|
||||||
links: string[];
|
|
||||||
backlinks: string[];
|
|
||||||
}
|
|
||||||
|
|
||||||
type MemoryRef = {
|
const GENERIC_TEMPLATE = `# {{Title}}
|
||||||
name: string;
|
|
||||||
description: string;
|
|
||||||
}
|
|
||||||
|
|
||||||
type FactBucket = {
|
## Summary
|
||||||
subject: string;
|
|
||||||
facts: string[];
|
|
||||||
}
|
|
||||||
|
|
||||||
export type MemoryNode = {
|
## Details
|
||||||
name: string;
|
|
||||||
missing: boolean;
|
|
||||||
links: string[];
|
|
||||||
backlinks: string[];
|
|
||||||
}
|
|
||||||
|
|
||||||
export function buildMemoryGraph(memories: Memory[] | MemoryCache): MemoryNode[] {
|
## Related`;
|
||||||
const mems = memories instanceof MemoryCache ? memories.memories : memories;
|
|
||||||
const nameSet = new Set(mems.map(m => m.name));
|
|
||||||
const ghosts = new Set<string>();
|
|
||||||
|
|
||||||
for (const m of mems) {
|
|
||||||
for (const link of m.links) {
|
|
||||||
if (!nameSet.has(link)) ghosts.add(link);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
return [
|
|
||||||
...mems.map(m => ({
|
|
||||||
name: m.name,
|
|
||||||
missing: false,
|
|
||||||
links: m.links,
|
|
||||||
backlinks: m.backlinks,
|
|
||||||
})),
|
|
||||||
...[...ghosts].map(name => ({
|
|
||||||
name,
|
|
||||||
missing: true,
|
|
||||||
links: [],
|
|
||||||
backlinks: mems
|
|
||||||
.filter(m => m.links.includes(name))
|
|
||||||
.map(m => m.name),
|
|
||||||
}))
|
|
||||||
];
|
|
||||||
}
|
|
||||||
|
|
||||||
function extractLinks(content: string): string[] {
|
|
||||||
const matches = content.matchAll(/\[\[([^\]]+)\]\]/g);
|
|
||||||
return [...new Set([...matches].map(m => m[1].trim()))];
|
|
||||||
}
|
|
||||||
|
|
||||||
function rebuildBacklinks(memories: Memory[]): void {
|
|
||||||
for (const m of memories) m.backlinks = [];
|
|
||||||
for (const m of memories) {
|
|
||||||
for (const link of m.links) {
|
|
||||||
const target = memories.find(t => t.name === link);
|
|
||||||
if (target) target.backlinks.push(m.name);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
function cosineDistance(a: number[], b: number[]): number {
|
|
||||||
let dot = 0, normA = 0, normB = 0;
|
|
||||||
for (let i = 0; i < a.length; i++) {
|
|
||||||
dot += a[i] * b[i];
|
|
||||||
normA += a[i] * a[i];
|
|
||||||
normB += b[i] * b[i];
|
|
||||||
}
|
|
||||||
const denom = Math.sqrt(normA) * Math.sqrt(normB);
|
|
||||||
return denom === 0 ? 1 : 1 - dot / denom;
|
|
||||||
}
|
|
||||||
|
|
||||||
export class MemoryCache {
|
export class MemoryCache {
|
||||||
private tree: KDTree<MemoryRef>;
|
private tree: KDTree<MemoryRef>;
|
||||||
public memories: Memory[];
|
public memories: Memory[];
|
||||||
|
|
||||||
|
get length() { return this.memories.length; }
|
||||||
|
|
||||||
constructor(memories: Memory[]) {
|
constructor(memories: Memory[]) {
|
||||||
this.memories = memories;
|
this.memories = memories;
|
||||||
this.tree = this.buildTree();
|
this.tree = this.buildTree();
|
||||||
@@ -94,7 +25,7 @@ export class MemoryCache {
|
|||||||
|
|
||||||
private buildTree(): KDTree<MemoryRef> {
|
private buildTree(): KDTree<MemoryRef> {
|
||||||
const embedded = this.memories.filter(m => m.embedding?.length);
|
const embedded = this.memories.filter(m => m.embedding?.length);
|
||||||
if(!embedded.length) return new KDTree<MemoryRef>(0);
|
if (!embedded.length) return new KDTree<MemoryRef>(0);
|
||||||
|
|
||||||
const dims = embedded[0].embedding.length;
|
const dims = embedded[0].embedding.length;
|
||||||
const points: KDPoint<MemoryRef>[] = embedded.map(m => ({
|
const points: KDPoint<MemoryRef>[] = embedded.map(m => ({
|
||||||
@@ -125,102 +56,250 @@ export class MemoryCache {
|
|||||||
this.rebuild();
|
this.rebuild();
|
||||||
}
|
}
|
||||||
|
|
||||||
|
remove(name: string): void {
|
||||||
|
const idx = this.memories.findIndex(m => m.name === name);
|
||||||
|
if (idx !== -1) {
|
||||||
|
this.memories.splice(idx, 1);
|
||||||
|
this.rebuild();
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
rebuild(): void {
|
rebuild(): void {
|
||||||
this.tree = this.buildTree();
|
this.tree = this.buildTree();
|
||||||
}
|
}
|
||||||
|
}
|
||||||
|
|
||||||
rebuildLinks(): void {
|
export type MemoryOptions = {
|
||||||
rebuildBacklinks(this.memories);
|
/** Memory object */
|
||||||
|
memory: Memory[] | MemoryCache;
|
||||||
|
/** Inject N memories into the system prompt */
|
||||||
|
inject?: boolean;
|
||||||
|
/** expose recall tool to LLM */
|
||||||
|
tool?: boolean;
|
||||||
|
/** Update memory on compression */
|
||||||
|
update?: boolean;
|
||||||
|
/** Max context size of memories to inject to each call (removed immediately after use) */
|
||||||
|
maxTokens?: number;
|
||||||
|
}
|
||||||
|
|
||||||
|
export type Memory = {
|
||||||
|
name: string;
|
||||||
|
description: string;
|
||||||
|
content: string;
|
||||||
|
embedding: number[];
|
||||||
|
links: string[];
|
||||||
|
backlinks: string[];
|
||||||
|
}
|
||||||
|
|
||||||
|
type MemoryRef = {
|
||||||
|
name: string;
|
||||||
|
description: string;
|
||||||
|
}
|
||||||
|
|
||||||
|
type FactBucket = {
|
||||||
|
subject: string;
|
||||||
|
facts: string[];
|
||||||
|
}
|
||||||
|
|
||||||
|
function extractLinks(content: string): string[] {
|
||||||
|
if (!content) return [];
|
||||||
|
const matches = content.matchAll(/\[\[([^\]]+)\]\]/g);
|
||||||
|
return [...new Set([...matches].map(m => m[1].trim()))];
|
||||||
|
}
|
||||||
|
|
||||||
|
export function rebuildGraph(memories: Memory[]): void {
|
||||||
|
for (const m of memories) m.links = extractLinks(m.content).filter(l => l !== m.name);
|
||||||
|
for (const m of memories) m.backlinks = [];
|
||||||
|
for (const m of memories) {
|
||||||
|
for (const link of m.links) {
|
||||||
|
const target = memories.find(t => t.name === link);
|
||||||
|
if (target) target.backlinks.push(m.name);
|
||||||
|
}
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
function dedupeFacts(facts: string[]): string[] {
|
||||||
|
const seen = new Map<string, string>();
|
||||||
|
for (const f of facts) {
|
||||||
|
const clean = f.trim();
|
||||||
|
if (clean) seen.set(clean.toLowerCase(), clean);
|
||||||
|
}
|
||||||
|
return [...seen.values()];
|
||||||
|
}
|
||||||
|
|
||||||
|
function cosineDistance(a: number[], b: number[]): number {
|
||||||
|
let dot = 0, normA = 0, normB = 0;
|
||||||
|
for (let i = 0; i < a.length; i++) {
|
||||||
|
dot += a[i] * b[i];
|
||||||
|
normA += a[i] * a[i];
|
||||||
|
normB += b[i] * b[i];
|
||||||
|
}
|
||||||
|
const denom = Math.sqrt(normA) * Math.sqrt(normB);
|
||||||
|
return denom === 0 ? 1 : 1 - dot / denom;
|
||||||
|
}
|
||||||
|
|
||||||
|
function getWeekMonday(date: Date = new Date()): string {
|
||||||
|
const d = new Date(Date.UTC(date.getFullYear(), date.getMonth(), date.getDate()));
|
||||||
|
const day = d.getUTCDay();
|
||||||
|
const diff = day === 0 ? -6 : 1 - day;
|
||||||
|
d.setUTCDate(d.getUTCDate() + diff);
|
||||||
|
return d.toISOString().slice(0, 10);
|
||||||
|
}
|
||||||
|
|
||||||
export class MemoryManager {
|
export class MemoryManager {
|
||||||
|
private recentlyTouched = new Map<string, number>();
|
||||||
|
|
||||||
|
private queues = new Map<string, {
|
||||||
|
dirty: boolean,
|
||||||
|
request: {abort?: () => void} | null,
|
||||||
|
task: Promise<void>,
|
||||||
|
}>();
|
||||||
|
|
||||||
tools = {
|
tools = {
|
||||||
read: (memories: Memory[] | MemoryCache): AiTool => ({
|
read: (memories: Memory[] | MemoryCache): AiTool => ({
|
||||||
name: 'read_memory',
|
name: 'memory_recall',
|
||||||
description: 'Read the full content of a memory document',
|
description: 'Read the full content of a memory document',
|
||||||
args: {
|
args: {
|
||||||
name: {type: 'string', description: 'Exact memory name', required: true},
|
name: {type: 'string', description: 'Exact memory name', required: true},
|
||||||
},
|
},
|
||||||
fn:(args: any) => {
|
fn: (args: any) => {
|
||||||
const mems = memories instanceof MemoryCache ? memories.memories : memories;
|
const mems = this.unwrap(memories);
|
||||||
const mem = mems.find(m => m.name === args.name);
|
const mem = mems.find(m => m.name === args.name);
|
||||||
if(!mem) return 'Document not found';
|
if (!mem) return 'Document not found';
|
||||||
return this.formatMemory(mem);
|
this.touch(mem.name);
|
||||||
}
|
return mem.content;
|
||||||
|
},
|
||||||
|
}),
|
||||||
|
|
||||||
|
forget: (memories: Memory[] | MemoryCache): AiTool => ({
|
||||||
|
name: 'memory_forget',
|
||||||
|
description: 'Permanently delete a memory document and clean up all references to it',
|
||||||
|
args: {
|
||||||
|
name: {type: 'string', description: 'Exact memory name to forget', required: true}
|
||||||
|
},
|
||||||
|
fn: (args: any) => {
|
||||||
|
const result = this.forget(args.name, memories);
|
||||||
|
return result ? `Forgotten: ${args.name}` : `Not found: ${args.name}`;
|
||||||
|
},
|
||||||
}),
|
}),
|
||||||
};
|
};
|
||||||
|
|
||||||
constructor(private llm: any) {}
|
constructor(private llm: any) {}
|
||||||
|
|
||||||
private cosineSearch(query: number[], memories: Memory[], limit: number): MemoryRef[] {
|
static normalize(m?: Memory[] | MemoryCache | MemoryOptions) {
|
||||||
const scored = memories
|
if(!m) return null;
|
||||||
.filter(m => m.embedding?.length)
|
const raw = m instanceof MemoryCache || Array.isArray(m);
|
||||||
.map(m => ({
|
return raw ? {memory: <Memory[] | MemoryCache>m, inject: true, tool: true, update: true} : {inject: true, tool: true, update: true, ...m};
|
||||||
ref: {name: m.name, description: m.description},
|
|
||||||
distance: cosineDistance(query, m.embedding)
|
|
||||||
}))
|
|
||||||
.sort((a, b) => a.distance - b.distance)
|
|
||||||
.slice(0, limit);
|
|
||||||
return scored.map(s => s.ref);
|
|
||||||
}
|
}
|
||||||
|
|
||||||
private createNode(name: string, memories: Memory[]): Memory {
|
private unwrap(memories: Memory[] | MemoryCache): Memory[] {
|
||||||
const existing = memories.find(m => m.name === name);
|
return memories instanceof MemoryCache ? memories.memories : memories;
|
||||||
if(existing) return existing;
|
|
||||||
return {
|
|
||||||
name,
|
|
||||||
description: '',
|
|
||||||
content: '',
|
|
||||||
embedding: [],
|
|
||||||
links: [],
|
|
||||||
backlinks: [],
|
|
||||||
};
|
|
||||||
}
|
}
|
||||||
|
|
||||||
private formatMemory(mem: Memory): string {
|
private sync(memories: Memory[] | MemoryCache): void {
|
||||||
return [
|
if (memories instanceof MemoryCache) memories.rebuild();
|
||||||
`# ${mem.name}`,
|
|
||||||
mem.description ? `> ${mem.description}` : '',
|
|
||||||
mem.links.length ? `**Links:** ${mem.links.map(l => `[[${l}]]`).join(', ')}` : '',
|
|
||||||
mem.backlinks.length ? `**Referenced by:** ${mem.backlinks.map(l => `[[${l}]]`).join(', ')}` : '',
|
|
||||||
'',
|
|
||||||
mem.content,
|
|
||||||
].filter(l => l !== undefined).join('\n');
|
|
||||||
}
|
}
|
||||||
|
|
||||||
private listNodes(memories: Memory[]): MemoryRef[] {
|
private parseFrontmatter(content: string): {fm: Map<string, string>, body: string} {
|
||||||
return memories.map(m => ({name: m.name, description: m.description}));
|
const match = content.match(/^---\n([\s\S]*?)\n---\n?([\s\S]*)$/);
|
||||||
|
if (!match) return {fm: new Map(), body: content};
|
||||||
|
const fm = new Map<string, string>();
|
||||||
|
for (const line of match[1].split('\n')) {
|
||||||
|
const i = line.indexOf(':');
|
||||||
|
if (i === -1) continue;
|
||||||
|
fm.set(line.slice(0, i).trim(), line.slice(i + 1).trim());
|
||||||
|
}
|
||||||
|
return {fm, body: match[2]};
|
||||||
|
}
|
||||||
|
|
||||||
|
private writeFrontmatter(fm: Map<string, string>, body: string): string {
|
||||||
|
const lines = [...fm.entries()].map(([k, v]) => `${k}: ${v}`);
|
||||||
|
return `---\n${lines.join('\n')}\n---\n\n${body.trimStart()}`;
|
||||||
|
}
|
||||||
|
|
||||||
|
private stripHeader(content: string): string {
|
||||||
|
return content.replace(/^---[\s\S]*?\n---\n?/, '').trimStart();
|
||||||
|
}
|
||||||
|
|
||||||
|
private touchHeader(node: Memory, body: string): string {
|
||||||
|
const {fm} = this.parseFrontmatter(node.content);
|
||||||
|
fm.set('name', node.name);
|
||||||
|
fm.set('description', node.description || '');
|
||||||
|
fm.set('modified', new Date().toISOString());
|
||||||
|
return this.writeFrontmatter(fm, body);
|
||||||
|
}
|
||||||
|
|
||||||
|
private ensureDoc(node: Memory): void {
|
||||||
|
if (node.content) return;
|
||||||
|
const title = node.name.split('/').pop() ?? node.name;
|
||||||
|
node.content = this.touchHeader(node, `# ${title}\n`);
|
||||||
|
}
|
||||||
|
|
||||||
|
private appendFacts(node: Memory, facts: string[]): void {
|
||||||
|
this.ensureDoc(node);
|
||||||
|
const body = this.stripHeader(node.content);
|
||||||
|
const bullets = facts.map(f => `- ${f}`).join('\n');
|
||||||
|
const idx = body.indexOf(FACTS_HEADING);
|
||||||
|
const newBody = idx === -1
|
||||||
|
? `${body.trimEnd()}\n\n${FACTS_HEADING}\n${bullets}\n`
|
||||||
|
: `${body.slice(0, idx + FACTS_HEADING.length)}\n${bullets}${body.slice(idx + FACTS_HEADING.length)}`;
|
||||||
|
node.content = this.touchHeader(node, newBody);
|
||||||
|
}
|
||||||
|
|
||||||
|
decay() {
|
||||||
|
for(const [name, ttl] of this.recentlyTouched) {
|
||||||
|
if(ttl <= 1) this.recentlyTouched.delete(name);
|
||||||
|
else this.recentlyTouched.set(name, ttl - 1);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
touch(name: string, ttl = 2) {
|
||||||
|
this.recentlyTouched.set(name, ttl);
|
||||||
|
}
|
||||||
|
|
||||||
|
getTouched(): string[] {
|
||||||
|
return [...this.recentlyTouched.keys()];
|
||||||
|
}
|
||||||
|
|
||||||
|
forget(name: string, memories: Memory[] | MemoryCache): boolean {
|
||||||
|
const mem = this.unwrap(memories);
|
||||||
|
const idx = mem.findIndex(m => m.name === name);
|
||||||
|
if (idx === -1) return false;
|
||||||
|
|
||||||
|
mem.splice(idx, 1);
|
||||||
|
rebuildGraph(mem);
|
||||||
|
this.sync(memories);
|
||||||
|
return true;
|
||||||
}
|
}
|
||||||
|
|
||||||
async recollect(query: string, memories: Memory[] | MemoryCache, limit = 5, graphDepth = 1): Promise<Memory[]> {
|
async recollect(query: string, memories: Memory[] | MemoryCache, limit = 5, graphDepth = 1): Promise<Memory[]> {
|
||||||
const mem: Memory[] = memories instanceof MemoryCache ? memories.memories : memories;
|
const mem = this.unwrap(memories);
|
||||||
if(!mem.length) return [];
|
if (!mem.length) return [];
|
||||||
|
|
||||||
const [e] = await this.llm.embedding(query);
|
const [e] = await this.llm.embedding(query);
|
||||||
if(!e) return [];
|
if (!e) return [];
|
||||||
|
|
||||||
let vectorResults: MemoryRef[];
|
let vectorResults: MemoryRef[];
|
||||||
if(memories instanceof MemoryCache) vectorResults = memories.search(e.embedding, limit);
|
if (memories instanceof MemoryCache) vectorResults = memories.search(e.embedding, limit);
|
||||||
else vectorResults = this.cosineSearch(e.embedding, mem, limit);
|
else vectorResults = this.cosineSearch(e.embedding, mem, limit);
|
||||||
const found = new Set<string>(vectorResults.map(r => r.name));
|
const found = new Set<string>(vectorResults.map(r => r.name));
|
||||||
|
|
||||||
if(graphDepth > 0) {
|
if (graphDepth > 0) {
|
||||||
const frontier = [...found];
|
const frontier = [...found];
|
||||||
for(let depth = 0; depth < graphDepth; depth++) {
|
for (let depth = 0; depth < graphDepth; depth++) {
|
||||||
const next: string[] = [];
|
const next: string[] = [];
|
||||||
for(const name of frontier) {
|
for (const name of frontier) {
|
||||||
const node = mem.find(m => m.name === name);
|
const node = mem.find(m => m.name === name);
|
||||||
if(!node) continue;
|
if (!node) continue;
|
||||||
for(const link of node.links) {
|
for (const link of node.links) {
|
||||||
if(!found.has(link) && mem.find(m => m.name === link)) {
|
if (!found.has(link) && mem.find(m => m.name === link)) {
|
||||||
found.add(link);
|
found.add(link);
|
||||||
next.push(link);
|
next.push(link);
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
frontier.splice(0, frontier.length, ...next);
|
frontier.splice(0, frontier.length, ...next);
|
||||||
if(!frontier.length) break;
|
if (!frontier.length) break;
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
@@ -230,272 +309,194 @@ export class MemoryManager {
|
|||||||
return ordered.map(n => mem.find(m => m.name === n)!).filter(Boolean);
|
return ordered.map(n => mem.find(m => m.name === n)!).filter(Boolean);
|
||||||
}
|
}
|
||||||
|
|
||||||
async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest): Promise<void> {
|
private cosineSearch(query: number[], memories: Memory[], limit: number): MemoryRef[] {
|
||||||
const mem = memories instanceof MemoryCache ? memories.memories : memories;
|
const scored = memories
|
||||||
|
.filter(m => m.embedding?.length)
|
||||||
|
.map(m => ({
|
||||||
|
ref: {name: m.name, description: m.description},
|
||||||
|
distance: cosineDistance(query, m.embedding),
|
||||||
|
}))
|
||||||
|
.sort((a, b) => a.distance - b.distance)
|
||||||
|
.slice(0, limit);
|
||||||
|
return scored.map(s => s.ref);
|
||||||
|
}
|
||||||
|
|
||||||
|
private listNodes(memories: Memory[]): MemoryRef[] {
|
||||||
|
return memories.map(m => ({name: m.name, description: m.description}));
|
||||||
|
}
|
||||||
|
|
||||||
|
async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest): Promise<Memory[]> {
|
||||||
const conversation = history
|
const conversation = history
|
||||||
.filter(h => h.role === 'user' || h.role === 'assistant')
|
.filter(h => h.role === 'user' || h.role === 'assistant')
|
||||||
.map(h => `[${h.role}]: ${h.content}`).join('\n\n').trim();
|
.map(h => `[${h.role}]: ${h.content}`).join('\n\n').trim();
|
||||||
|
if (!conversation) return [];
|
||||||
|
|
||||||
if(conversation) {
|
const uid = `${Date.now()}_${Math.random().toString(36).slice(2)}`;
|
||||||
const buckets = await this.factAgent(conversation, mem, options);
|
// NOTE: adjust field names below (id/tool_call_id/name) to match your LLMMessage/tool-call schema.
|
||||||
if(buckets.length) {
|
const pending = {role: 'tool', name: 'memory_process', id: uid, content: 'Processing…'} as unknown as LLMMessage;
|
||||||
await Promise.all(buckets.map(async bucket => {
|
history.push(pending);
|
||||||
const node = await this.organizingAgent(bucket, mem, options);
|
|
||||||
if(!mem.find(m => m.name === node.name)) mem.push(node);
|
const mem = this.unwrap(memories);
|
||||||
await this.docAgent(node, bucket, mem, options);
|
const buckets = await this.factAgent(conversation, mem, options, getWeekMonday());
|
||||||
}));
|
const touched: Memory[] = [];
|
||||||
|
|
||||||
|
for (const {subject, facts} of buckets) {
|
||||||
|
let node = mem.find(m => m.name === subject);
|
||||||
|
if (!node) {
|
||||||
|
node = {name: subject, description: '', content: '', embedding: [], links: [], backlinks: []};
|
||||||
|
mem.push(node);
|
||||||
}
|
}
|
||||||
|
this.appendFacts(node, facts);
|
||||||
|
const [e] = await this.llm.embedding(node.content);
|
||||||
|
if (e) node.embedding = e.embedding;
|
||||||
|
this.touch(node.name);
|
||||||
|
touched.push(node);
|
||||||
}
|
}
|
||||||
|
|
||||||
// Auto-compress old journals
|
if (touched.length) {
|
||||||
const weekAgo = Date.now() - (7 * 24 * 60 * 60 * 1000);
|
rebuildGraph(mem);
|
||||||
const oldDailies = mem.filter(m => {
|
this.sync(memories);
|
||||||
const journal = /^Journal\/(\d{4}-\d{2}-\d{2}$)/.exec(m.name);
|
(pending as any).content = `Saved to ${touched.map(n => `[[${n.name}]]`).join(', ')}`;
|
||||||
return journal && new Date(journal[1]).getTime() < weekAgo;
|
for (const node of touched) this.reconcile(node, memories, options).catch(() => {});
|
||||||
});
|
|
||||||
|
|
||||||
if(oldDailies.length) {
|
|
||||||
const byMonth = new Map<string, Memory[]>();
|
|
||||||
for(const daily of oldDailies) {
|
|
||||||
const match = daily.name.match(/^Journal\/(\d{4}-\d{2})-\d{2}$/);
|
|
||||||
if(!match) continue;
|
|
||||||
const monthKey = match[1];
|
|
||||||
if(!byMonth.has(monthKey)) byMonth.set(monthKey, []);
|
|
||||||
byMonth.get(monthKey)!.push(daily);
|
|
||||||
}
|
|
||||||
|
|
||||||
for(const [monthKey, entries] of byMonth) {
|
|
||||||
const monthlyPath = `Journal/${monthKey}`;
|
|
||||||
let monthly = mem.find(m => m.name === monthlyPath);
|
|
||||||
if(!monthly) {
|
|
||||||
monthly = this.createNode(monthlyPath, mem);
|
|
||||||
mem.push(monthly);
|
|
||||||
}
|
|
||||||
|
|
||||||
const bucket: FactBucket = {
|
|
||||||
subject: monthlyPath,
|
|
||||||
facts: entries.flatMap(e => e.content.split('\n').filter(line => line.trim())),
|
|
||||||
};
|
|
||||||
|
|
||||||
await this.docAgent(monthly, bucket, mem, options);
|
|
||||||
for(const daily of entries) {
|
|
||||||
const idx = mem.indexOf(daily);
|
|
||||||
if(idx !== -1) mem.splice(idx, 1);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
if (memories instanceof MemoryCache) {
|
|
||||||
memories.rebuildLinks();
|
|
||||||
memories.rebuild();
|
|
||||||
} else {
|
} else {
|
||||||
rebuildBacklinks(mem);
|
(pending as any).content = 'Nothing worth remembering.';
|
||||||
}
|
|
||||||
}
|
}
|
||||||
|
|
||||||
private async docAgent(node: Memory, bucket: FactBucket, memories: Memory[], options: LLMRequest): Promise<void> {
|
return touched;
|
||||||
let finalContent = node.content;
|
}
|
||||||
const isJournalCompression = node.name.match(/^Journal\/\d{4}-\d{2}$/);
|
|
||||||
const systemPrompt = isJournalCompression
|
|
||||||
? `You are a journal compressor. Condense the daily entries below into a monthly summary.
|
|
||||||
|
|
||||||
Format:
|
/** Manual/cron entry point. scope 'touched' only reconciles docs with a pending Facts inbox. */
|
||||||
# ${node.name}
|
async reconcileVault(memories: Memory[] | MemoryCache, options: LLMRequest, scope: 'touched' | 'all' = 'touched'): Promise<void> {
|
||||||
|
const mem = this.unwrap(memories);
|
||||||
|
const targets = scope === 'all' ? mem : mem.filter(m => m.content.includes(FACTS_HEADING));
|
||||||
|
await Promise.all(targets.map(node => this.reconcile(node, memories, options)));
|
||||||
|
this.sync(memories);
|
||||||
|
}
|
||||||
|
|
||||||
## Themes
|
/**
|
||||||
(Recurring topics, moods, patterns)
|
* Coalescing queue: if a doc is already reconciling, mark it dirty and abort the in-flight
|
||||||
|
* request. The loop below always re-reads node.content fresh, so nothing is ever dropped.
|
||||||
|
*/
|
||||||
|
private reconcile(node: Memory, memories: Memory[] | MemoryCache, options: LLMRequest): Promise<void> {
|
||||||
|
const key = node.name;
|
||||||
|
const existing = this.queues.get(key);
|
||||||
|
if (existing) {
|
||||||
|
existing.dirty = true;
|
||||||
|
existing.request?.abort?.();
|
||||||
|
return existing.task;
|
||||||
|
}
|
||||||
|
|
||||||
## Key Events
|
const entry = {dirty: false, request: null, task: Promise.resolve()};
|
||||||
(Important moments, decisions, milestones)
|
this.queues.set(key, entry);
|
||||||
|
const mem = this.unwrap(memories);
|
||||||
|
entry.task = (async () => {
|
||||||
|
do {
|
||||||
|
entry.dirty = false;
|
||||||
|
await this.reconcileDoc(node, mem, options, entry);
|
||||||
|
} while (entry.dirty);
|
||||||
|
})().finally(() => {
|
||||||
|
this.queues.delete(key);
|
||||||
|
rebuildGraph(mem);
|
||||||
|
this.sync(memories);
|
||||||
|
});
|
||||||
|
return entry.task;
|
||||||
|
}
|
||||||
|
|
||||||
## Notable Conversations
|
private async reconcileDoc(node: Memory, memories: Memory[], options: LLMRequest, entry: {request: {abort?: () => void} | null}): Promise<void> {
|
||||||
(Significant discussions or revelations)
|
const currentBody = this.stripHeader(node.content);
|
||||||
|
let update;
|
||||||
|
try {
|
||||||
|
for (let i = 0; i < 2 && !update?.content; i++) {
|
||||||
|
const request = this.llm.ask(currentBody, {
|
||||||
|
model: options.model,
|
||||||
|
temperature: 0.3,
|
||||||
|
schema: {
|
||||||
|
description: {type: 'string', description: 'One-line description of what this document covers, no formatting or emojis', required: true},
|
||||||
|
content: {type: 'string', description: 'Rewritten document body in markdown, without the frontmatter block', required: true},
|
||||||
|
},
|
||||||
|
system: `You are a knowledge base editor maintaining one document in an Obsidian-style vault.
|
||||||
|
|
||||||
Rules:
|
If the document has a "${FACTS_HEADING}" section, integrate every bullet under it into the appropriate part of the document, then remove the "${FACTS_HEADING}" section entirely. If there is no such section, just tidy the document per the rules below.
|
||||||
- Use [[WikiLinks]] to reference permanent notes using full paths like [[People/Sarah]] or [[Projects/Website]]
|
|
||||||
- Keep it concise but preserve emotional/temporal context
|
|
||||||
- Discard filler but keep things the user vented about or cared about
|
|
||||||
- If a fact belongs in a permanent note, link to it instead of duplicating
|
|
||||||
|
|
||||||
Current monthly summary:
|
Structure: follow this generic shape loosely, adapting section names/order to what the content actually needs (e.g. journal-style docs may want a timeline instead of "Details"):
|
||||||
\`\`\`markdown
|
\`\`\`markdown
|
||||||
${node.content || '(empty — first compression for this month)'}
|
${GENERIC_TEMPLATE}
|
||||||
\`\`\``
|
\`\`\`
|
||||||
: `You are a knowledge base editor. Integrate the provided facts into the document below.
|
|
||||||
|
|
||||||
Formatting rules:
|
Formatting rules:
|
||||||
- Use Obsidian-style markdown: # headings, **bold** for key terms, bullet lists for facts
|
- Use Obsidian-style markdown: # headings, **bold** for emphasis, bullet & numbered lists for grouped 1D data, tables for 2D data
|
||||||
- Link related concepts with [[WikiLink]] notation using full paths like [[People/Sarah]] or [[Projects/Website]]
|
- Link related concepts with [[WikiLink]] notation using full paths like [[People/Sarah]] or [[Projects/Website]]
|
||||||
- You may create links to nodes that don't exist yet if the concept is important
|
- Create links for specific entities (person, place, project, program) and abstract concepts, but skip generics (car, red, dog)
|
||||||
- Keep the document concise, factual, and human-readable
|
- Keep the document concise, factual, and human-readable
|
||||||
- Resolve any contradictions between old content and new facts (new facts win)
|
- Resolve contradictions: newer facts always win — delete the outdated statement entirely, never keep both
|
||||||
- Do not add filler, preamble, or AI commentary — just clean knowledge documents
|
- Do not add frontmatter blocks, filler, preamble, or AI commentary
|
||||||
|
|
||||||
All nodes:
|
Other nodes in the vault (link to these instead of duplicating their content):
|
||||||
${this.listNodes(memories).map(n => n.name).join(', ') || 'none'}
|
${this.listNodes(memories).filter(n => n.name !== node.name).map(n => n.name).join(', ') || 'none'}
|
||||||
|
|
||||||
Current document:
|
Current document:
|
||||||
\`\`\`markdown
|
\`\`\`markdown
|
||||||
${node.content || '(empty — this is a new document)'}
|
${currentBody}
|
||||||
\`\`\``;
|
\`\`\``,
|
||||||
|
});
|
||||||
await this.llm.ask(
|
entry.request = request;
|
||||||
`New facts to integrate:\n${bucket.facts.map(f => `- ${f}`).join('\n')}`,
|
update = await request;
|
||||||
{
|
|
||||||
model: options.model,
|
|
||||||
temperature: 0.3,
|
|
||||||
system: systemPrompt,
|
|
||||||
tools: [{
|
|
||||||
name: 'update_document',
|
|
||||||
description: 'Write the complete updated document content',
|
|
||||||
args: {
|
|
||||||
description: {type: 'string', description: 'One-line description of what this document covers, no formatting or emojis', required: true},
|
|
||||||
content: {type: 'string', description: 'Fully updated document in markdown', required: true},
|
|
||||||
},
|
|
||||||
fn:(args: any) => {
|
|
||||||
node.description = args.description;
|
|
||||||
finalContent = args.content;
|
|
||||||
return 'Saved';
|
|
||||||
}
|
}
|
||||||
}]
|
} catch (err: any) {
|
||||||
|
if (err?.name === 'AbortError') return;
|
||||||
|
throw err;
|
||||||
|
} finally {
|
||||||
|
entry.request = null;
|
||||||
}
|
}
|
||||||
);
|
|
||||||
|
|
||||||
node.content = finalContent;
|
if (!update?.content) return;
|
||||||
node.links = extractLinks(finalContent);
|
node.description = node.name !== 'People/User' ? update.description : 'All information about the current user';
|
||||||
const needsEmbed = !node.embedding?.length || node.description !== memories.find(m => m.name === node.name)?.description;
|
node.content = this.touchHeader(node, update.content);
|
||||||
if (needsEmbed) {
|
const [e] = await this.llm.embedding(node.content);
|
||||||
const [e] = await this.llm.embedding(node.description);
|
|
||||||
if (e) node.embedding = e.embedding;
|
if (e) node.embedding = e.embedding;
|
||||||
}
|
}
|
||||||
}
|
|
||||||
|
|
||||||
private async factAgent(conversation: string, memories: Memory[], options: LLMRequest): Promise<FactBucket[]> {
|
|
||||||
const buckets: FactBucket[] = [];
|
|
||||||
const today = new Date().toISOString().split('T')[0];
|
|
||||||
|
|
||||||
|
private async factAgent(conversation: string, memories: Memory[], options: LLMRequest, weekKey: string): Promise<FactBucket[]> {
|
||||||
|
const buckets = new Map<string, string[]>();
|
||||||
await this.llm.ask(conversation, {
|
await this.llm.ask(conversation, {
|
||||||
model: options.model,
|
model: options.model,
|
||||||
temperature: 0.2,
|
temperature: 0.2,
|
||||||
system: `You are a fact extractor. Analyze this conversation and extract facts worth remembering long-term.
|
system: `You are a fact extractor. Analyze this conversation and extract facts worth remembering long-term.
|
||||||
|
|
||||||
Rules:
|
Rules:
|
||||||
- ONLY extract facts the USER explicitly stated about themselves, their work, or their projects
|
- ONLY extract current facts the USER explicitly stated about themselves, their work, or their projects
|
||||||
- ONLY extract decisions that were MADE during this conversation
|
- ONLY extract decisions that were MADE during this conversation
|
||||||
- DO NOT extract anything the AI said, its capabilities, or meta-conversation about the AI
|
- DO NOT extract anything the AI said, its capabilities, or meta-conversation about the AI
|
||||||
- DO NOT extract greetings, pleasantries, or generic exchanges
|
- DO NOT extract greetings, pleasantries, or generic exchanges
|
||||||
|
- DO NOT extract deltas or changes in facts; ONLY the end fact
|
||||||
- If nothing worth remembering was said, do not call any tools
|
- If nothing worth remembering was said, do not call any tools
|
||||||
|
|
||||||
**Organizational patterns:**
|
When extracting facts, you MUST also decide the exact destination path:
|
||||||
- Journal entries use paths like: Journal/${today}
|
- Use an existing node name if the facts clearly belong there
|
||||||
- People use paths like: People/Name
|
- All information primarily about the user should go under "People/User"
|
||||||
- Projects use paths like: Projects/Name
|
- When required, create a new path following collection/subject format (e.g., People/Sarah, Projects/Oxide) — you are not limited to any fixed list of collections, use whatever fits
|
||||||
- Personal info uses paths like: Personal/Goals, Personal/Tasks, etc.
|
- For journal entries, use "Journal"
|
||||||
- General knowledge uses paths like: Biology/Topic, History/Topic, etc.
|
|
||||||
|
|
||||||
Learn from existing nodes and follow the same pattern when extracting.
|
|
||||||
|
|
||||||
Group facts by subject. For each group call \`extract_facts\` once with the FULL PATH.
|
|
||||||
|
|
||||||
Known nodes (name: description):
|
|
||||||
${this.listNodes(memories).map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None yet.'}`,
|
|
||||||
tools: [{
|
|
||||||
name: 'extract_facts',
|
|
||||||
description: 'Submit a group of related facts for a specific subject',
|
|
||||||
args: {
|
|
||||||
subject: {type: 'string', description: 'Full path for the subject (e.g., "Journal/2025-01-27", "People/Sarah", "Projects/Website")', required: true},
|
|
||||||
facts: {type: 'string', description: 'Comma-separated list of extracted facts', required: true},
|
|
||||||
},
|
|
||||||
fn: (args: any) => {
|
|
||||||
buckets.push({
|
|
||||||
subject: args.subject,
|
|
||||||
facts: args.facts.split(',').map((f: string) => f.trim()).filter(Boolean),
|
|
||||||
});
|
|
||||||
return 'Recorded';
|
|
||||||
}
|
|
||||||
}]
|
|
||||||
});
|
|
||||||
|
|
||||||
return buckets;
|
|
||||||
}
|
|
||||||
|
|
||||||
private async organizingAgent(bucket: FactBucket, memories: Memory[], options: LLMRequest): Promise<Memory> {
|
|
||||||
let candidates = this.listNodes(memories);
|
|
||||||
let attempts = 0;
|
|
||||||
const maxAttempts = 3;
|
|
||||||
|
|
||||||
while (attempts++ < maxAttempts) {
|
|
||||||
let home = '', mode: string | null = null;
|
|
||||||
|
|
||||||
const resp = await this.llm.ask(`Subject: ${bucket.subject}\n\nFacts:\n${bucket.facts.map(f => `- ${f}`).join('\n')}`, {
|
|
||||||
model: options.model,
|
|
||||||
temperature: 0.1,
|
|
||||||
system: `You are a knowledge organizer. Your job is to find the correct home for the supplied facts.
|
|
||||||
|
|
||||||
1. Review the facts and the node list below. Pick the most likely match or decide if a new node is needed.
|
|
||||||
2. If you picked an existing node, use \`read\` to verify it's the right place.
|
|
||||||
- After reading, call either \`confirm\` (correct node) or \`mismatched\` (wrong node).
|
|
||||||
3. If none of the nodes match, call \`create\` to make a new node.
|
|
||||||
|
|
||||||
**Organizational patterns:**
|
|
||||||
- Journal entries: Journal/YYYY-MM-DD
|
|
||||||
- People: People/Name
|
|
||||||
- Projects: Projects/Name
|
|
||||||
- Personal: Personal/Goals, Personal/Tasks, etc.
|
|
||||||
- Knowledge: Biology/Topic, History/Topic, etc.
|
|
||||||
|
|
||||||
Available nodes:
|
Available nodes:
|
||||||
${candidates.map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None — create a new node.'}`,
|
- Journal
|
||||||
|
${this.listNodes(memories).filter(n => !n.name.includes('Journal')).map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None yet.'}`,
|
||||||
tools: [{
|
tools: [{
|
||||||
name: 'read',
|
name: 'facts_extract',
|
||||||
description: 'Read a node file to verify it is the right home for these facts',
|
description: 'Submit facts with their destination',
|
||||||
args: {name: {type: 'string', description: 'Exact node name (full path)', required: true}},
|
|
||||||
fn: ({name}) => {
|
|
||||||
const mem = memories.find(m => m.name === name);
|
|
||||||
if (!mem) return 'Node not found';
|
|
||||||
home = name;
|
|
||||||
return this.formatMemory(mem);
|
|
||||||
}
|
|
||||||
}, {
|
|
||||||
name: 'confirm',
|
|
||||||
description: 'Confirm this is the correct node for the facts',
|
|
||||||
args: {},
|
|
||||||
fn: () => {
|
|
||||||
mode = 'success';
|
|
||||||
resp.abort();
|
|
||||||
}
|
|
||||||
}, {
|
|
||||||
name: 'mismatched',
|
|
||||||
description: 'This is not the node you are looking for',
|
|
||||||
args: {},
|
|
||||||
fn: () => {
|
|
||||||
mode = 'failed';
|
|
||||||
resp.abort();
|
|
||||||
}
|
|
||||||
}, {
|
|
||||||
name: 'create',
|
|
||||||
description: 'No existing node fits — create a new one',
|
|
||||||
args: {
|
args: {
|
||||||
name: {type: 'string', description: 'Full path for the new node (e.g., "People/Sarah", "Journal/2025-01-27")', required: true}
|
destination: {type: 'string', description: 'Exact existing node name OR new path (e.g. "People/Sarah", "Projects/Oxide")', required: true},
|
||||||
|
facts: {type: 'string', description: 'Comma-separated facts', required: true},
|
||||||
},
|
},
|
||||||
fn: ({name}) => {
|
fn: (args: any) => {
|
||||||
home = name;
|
const subject = args.destination.trim().toLowerCase() === 'journal'
|
||||||
mode = 'create';
|
? `Journal/${weekKey}` : args.destination.trim();
|
||||||
resp.abort();
|
const facts = buckets.get(subject) ?? [];
|
||||||
}
|
facts.push(...dedupeFacts(String(args.facts).split(',')));
|
||||||
}]
|
buckets.set(subject, facts);
|
||||||
|
return 'Recorded';
|
||||||
|
},
|
||||||
|
}],
|
||||||
});
|
});
|
||||||
|
return buckets.entries().toArray().map(([subject, facts]) => ({subject, facts}));
|
||||||
if(mode === 'create') {
|
|
||||||
return this.createNode(home, memories);
|
|
||||||
} else if (mode === 'failed') {
|
|
||||||
candidates = candidates.filter(c => c.name !== home);
|
|
||||||
if(!candidates.length) return this.createNode(bucket.subject, memories);
|
|
||||||
} else if (mode === 'success') {
|
|
||||||
const existing = memories.find(m => m.name === home);
|
|
||||||
return existing || this.createNode(home, memories);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
return this.createNode(bucket.subject, memories);
|
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|||||||
119
src/open-ai.ts
119
src/open-ai.ts
@@ -1,39 +1,52 @@
|
|||||||
import {OpenAI as openAI} from 'openai';
|
import {OpenAI as openAI} from 'openai';
|
||||||
import {findByProp, objectMap, JSONSanitize, JSONAttemptParse, clean} from '@ztimson/utils';
|
import {findByProp, objectMap, JSONSanitize, JSONAttemptParse, clean, makeArray} from '@ztimson/utils';
|
||||||
import {AbortablePromise, Ai} from './ai.ts';
|
import {AbortablePromise, Ai} from './ai.ts';
|
||||||
import {LLMMessage, LLMRequest} from './llm.ts';
|
import {LLMMessage, LLMRequest} from './llm.ts';
|
||||||
import {LLMProvider} from './provider.ts';
|
import {LLMProvider} from './provider.ts';
|
||||||
|
import {TokenPool} from './token-pool.ts';
|
||||||
import {convertSchema} from './tools.ts';
|
import {convertSchema} from './tools.ts';
|
||||||
|
|
||||||
export class OpenAi extends LLMProvider {
|
export class OpenAi extends LLMProvider {
|
||||||
client!: openAI;
|
tokenPool!: TokenPool;
|
||||||
|
private clients = new Map<string, openAI>();
|
||||||
|
|
||||||
constructor(public readonly ai: Ai, public readonly host: string | null, public readonly token: string, public model: string) {
|
constructor(public readonly ai: Ai, public readonly host: string | null, public readonly token: string | string[], public model: string) {
|
||||||
super();
|
super();
|
||||||
this.client = new openAI(clean({
|
const tokens = makeArray(token).filter(Boolean);
|
||||||
baseURL: host,
|
this.tokenPool = new TokenPool(...(tokens.length ? tokens : [host ? 'ignored' : '']));
|
||||||
apiKey: token || (host ? 'ignored' : undefined)
|
}
|
||||||
}));
|
|
||||||
|
private getClient(token: string): openAI {
|
||||||
|
let client = this.clients.get(token);
|
||||||
|
if(!client) {
|
||||||
|
client = new openAI(clean({baseURL: this.host, apiKey: token || undefined}));
|
||||||
|
this.clients.set(token, client);
|
||||||
|
}
|
||||||
|
return client;
|
||||||
}
|
}
|
||||||
|
|
||||||
private toStandard(history: any[]): LLMMessage[] {
|
private toStandard(history: any[]): LLMMessage[] {
|
||||||
for(let i = 0; i < history.length; i++) {
|
for(let i = 0; i < history.length; i++) {
|
||||||
const h = history[i];
|
const h = history[i];
|
||||||
if(h.role === 'assistant' && h.tool_calls) {
|
if(h.role === 'assistant' && h.tool_calls) {
|
||||||
const tools = h.tool_calls.map((tc: any) => ({
|
const items: any[] = [];
|
||||||
|
if(h.content) items.push({role: 'assistant', content: h.content, timestamp: h.timestamp, duration: h.duration, tps: h.tps});
|
||||||
|
items.push(...h.tool_calls.map((tc: any) => ({
|
||||||
role: 'tool',
|
role: 'tool',
|
||||||
id: tc.id,
|
id: tc.id,
|
||||||
name: tc.function.name,
|
name: tc.function.name,
|
||||||
args: JSONAttemptParse(tc.function.arguments, {}),
|
args: JSONAttemptParse(tc.function.arguments, {}),
|
||||||
timestamp: h.timestamp
|
timestamp: h.timestamp,
|
||||||
}));
|
duration: h.duration,
|
||||||
history.splice(i, 1, ...tools);
|
tps: h.tps
|
||||||
i += tools.length - 1;
|
})));
|
||||||
} else if(h.role === 'tool' && h.content) {
|
history.splice(i, 1, ...items);
|
||||||
|
i += items.length - 1;
|
||||||
|
} else if(h.role === 'tool') {
|
||||||
const record = history.find(h2 => h.tool_call_id == h2.id);
|
const record = history.find(h2 => h.tool_call_id == h2.id);
|
||||||
if(record) {
|
if(record) {
|
||||||
if(h.content.includes('"error":')) record.error = h.content;
|
if(h.content?.includes('"error":')) record.error = h.content;
|
||||||
else record.content = h.content;
|
else record.content = h.content || '';
|
||||||
}
|
}
|
||||||
history.splice(i, 1);
|
history.splice(i, 1);
|
||||||
i--;
|
i--;
|
||||||
@@ -51,15 +64,16 @@ export class OpenAi extends LLMProvider {
|
|||||||
content: null,
|
content: null,
|
||||||
tool_calls: [{ id: h.id, type: 'function', function: { name: h.name, arguments: JSON.stringify(h.args) } }],
|
tool_calls: [{ id: h.id, type: 'function', function: { name: h.name, arguments: JSON.stringify(h.args) } }],
|
||||||
refusal: null,
|
refusal: null,
|
||||||
annotations: []
|
annotations: [],
|
||||||
|
timestamp: h.timestamp,
|
||||||
}, {
|
}, {
|
||||||
role: 'tool',
|
role: 'tool',
|
||||||
tool_call_id: h.id,
|
tool_call_id: h.id,
|
||||||
content: h.error || h.content
|
content: h.error || h.content,
|
||||||
|
timestamp: h.timestamp,
|
||||||
});
|
});
|
||||||
} else {
|
} else {
|
||||||
const {timestamp, ...rest} = h;
|
result.push(h);
|
||||||
result.push(rest);
|
|
||||||
}
|
}
|
||||||
return result;
|
return result;
|
||||||
}, [] as any[]);
|
}, [] as any[]);
|
||||||
@@ -68,11 +82,12 @@ export class OpenAi extends LLMProvider {
|
|||||||
ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> {
|
ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> {
|
||||||
const controller = new AbortController();
|
const controller = new AbortController();
|
||||||
return Object.assign(new Promise<any>(async (res, rej) => {
|
return Object.assign(new Promise<any>(async (res, rej) => {
|
||||||
if(options.system) {
|
const base = (options.history || []).filter(h => h.role !== 'system');
|
||||||
if(options.history?.[0]?.role != 'system') options.history?.splice(0, 0, {role: 'system', content: options.system, timestamp: Date.now()});
|
let history = this.fromStandard([
|
||||||
else options.history[0].content = options.system;
|
...(options.system ? [{role: <any>'system', content: options.system, timestamp: Date.now()}] : []),
|
||||||
}
|
...base,
|
||||||
let history = this.fromStandard([...options.history || [], {role: 'user', content: message, timestamp: Date.now()}]);
|
{role: 'user', content: message, timestamp: Date.now()}
|
||||||
|
]);
|
||||||
const tools = options.tools || this.ai.options.llm?.tools || [];
|
const tools = options.tools || this.ai.options.llm?.tools || [];
|
||||||
const requestParams: any = {
|
const requestParams: any = {
|
||||||
model: options.model || this.model,
|
model: options.model || this.model,
|
||||||
@@ -106,25 +121,27 @@ export class OpenAi extends LLMProvider {
|
|||||||
};
|
};
|
||||||
}
|
}
|
||||||
|
|
||||||
let resp: any, isFirstMessage = true;
|
if(options.stream) requestParams.stream_options = {include_usage: true};
|
||||||
|
let resp: any, terminal = false, duration = 0, tps = 0;
|
||||||
do {
|
do {
|
||||||
resp = await this.client.chat.completions.create(requestParams).catch(err => {
|
requestParams.messages = history.map(({timestamp, ...m}) => m);
|
||||||
|
const callStart = Date.now();
|
||||||
|
resp = await this.tokenPool.run(token => this.getClient(token).chat.completions.create(requestParams)).catch(err => {
|
||||||
err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`;
|
err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`;
|
||||||
throw err;
|
throw err;
|
||||||
});
|
});
|
||||||
|
|
||||||
|
let usage: any;
|
||||||
if(options.stream) {
|
if(options.stream) {
|
||||||
if(!isFirstMessage) options.stream({text: '\n\n'});
|
resp.choices = [{message: {role: 'assistant', content: '', tool_calls: [], timestamp: Date.now()}}];
|
||||||
else isFirstMessage = false;
|
|
||||||
resp.choices = [{message: {role: 'assistant', content: '', tool_calls: []}}];
|
|
||||||
for await (const chunk of resp) {
|
for await (const chunk of resp) {
|
||||||
if(controller.signal.aborted) break;
|
if(controller.signal.aborted) break;
|
||||||
if(chunk.choices[0].delta.content) {
|
if(chunk.usage) usage = chunk.usage;
|
||||||
|
if(chunk.choices[0]?.delta?.content) {
|
||||||
resp.choices[0].message.content += chunk.choices[0].delta.content;
|
resp.choices[0].message.content += chunk.choices[0].delta.content;
|
||||||
options.stream({text: chunk.choices[0].delta.content});
|
options.stream({text: chunk.choices[0].delta.content});
|
||||||
}
|
}
|
||||||
|
if(chunk.choices[0]?.delta?.tool_calls) {
|
||||||
if(chunk.choices[0].delta.tool_calls) {
|
|
||||||
for(const deltaTC of chunk.choices[0].delta.tool_calls) {
|
for(const deltaTC of chunk.choices[0].delta.tool_calls) {
|
||||||
const existing = resp.choices[0].message.tool_calls.find(tc => tc.index === deltaTC.index);
|
const existing = resp.choices[0].message.tool_calls.find(tc => tc.index === deltaTC.index);
|
||||||
if(existing) {
|
if(existing) {
|
||||||
@@ -149,38 +166,52 @@ export class OpenAi extends LLMProvider {
|
|||||||
}
|
}
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
} else {
|
||||||
|
usage = resp.usage;
|
||||||
}
|
}
|
||||||
|
duration = Date.now() - callStart;
|
||||||
|
tps = usage?.completion_tokens && duration > 0 ? usage.completion_tokens / (duration / 1000) : 0;
|
||||||
|
|
||||||
if(resp.error) throw new Error(resp.error);
|
if(resp.error) throw new Error(resp.error);
|
||||||
const toolCalls = resp.choices[0].message.tool_calls || [];
|
const toolCalls = resp.choices[0].message.tool_calls || [];
|
||||||
if(toolCalls.length && !controller.signal.aborted) {
|
if(toolCalls.length && !controller.signal.aborted) {
|
||||||
history.push(resp.choices[0].message);
|
history.push({...resp.choices[0].message, duration, tps});
|
||||||
const results = await Promise.all(toolCalls.map(async (toolCall: any) => {
|
const results = await Promise.all(toolCalls.map(async (toolCall: any) => {
|
||||||
const tool = tools?.find(findByProp('name', toolCall.function.name));
|
const tool = tools?.find(findByProp('name', toolCall.function.name));
|
||||||
if(options.stream) options.stream({tool: toolCall.function.name});
|
if(options.stream) options.stream({tool: toolCall.function.name});
|
||||||
if(!tool) return {role: 'tool', tool_call_id: toolCall.id, content: '{"error": "Tool not found"}'};
|
if(!tool) return {role: 'tool', tool_call_id: toolCall.id, content: '{"error": "Tool not found"}', timestamp: Date.now()};
|
||||||
try {
|
try {
|
||||||
const args = JSONAttemptParse(toolCall.function.arguments, {});
|
const args = JSONAttemptParse(toolCall.function.arguments, {});
|
||||||
const result = await tool.fn(args, options.stream, this.ai);
|
const toolStream = options.stream && ((chunk: any) => {
|
||||||
return {role: 'tool', tool_call_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result};
|
if(chunk.done) { terminal = true; return; }
|
||||||
|
options.stream!(chunk);
|
||||||
|
});
|
||||||
|
const result = await tool.fn(args, toolStream, this.ai, toolCall.id);
|
||||||
|
return {role: 'tool', tool_call_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result, timestamp: Date.now()};
|
||||||
} catch (err: any) {
|
} catch (err: any) {
|
||||||
return {role: 'tool', tool_call_id: toolCall.id, content: JSONSanitize({error: err?.message || err?.toString() || 'Unknown'})};
|
return {role: 'tool', tool_call_id: toolCall.id, content: JSONSanitize({error: err?.message || err?.toString() || 'Unknown'}), timestamp: Date.now()};
|
||||||
}
|
}
|
||||||
}));
|
}));
|
||||||
history.push(...results);
|
history.push(...results);
|
||||||
requestParams.messages = history;
|
requestParams.messages = history;
|
||||||
}
|
}
|
||||||
} while (!controller.signal.aborted && resp.choices?.[0]?.message?.tool_calls?.length);
|
} while (!terminal && !controller.signal.aborted && resp.choices?.[0]?.message?.tool_calls?.length);
|
||||||
|
|
||||||
|
if(!terminal) {
|
||||||
|
const textContent = resp.choices[0].message.content || '';
|
||||||
|
history.push({role: 'assistant', content: textContent.trim(), timestamp: Date.now(), duration, tps});
|
||||||
|
}
|
||||||
|
|
||||||
const textContent = resp.choices[0].message.content?.trim() || '';
|
|
||||||
history.push({role: 'assistant', content: textContent});
|
|
||||||
history = this.toStandard(history);
|
history = this.toStandard(history);
|
||||||
|
if(options.history) options.history.splice(0, options.history.length, ...history.filter(h => h.role !== 'system'));
|
||||||
if(options.stream) options.stream({done: true});
|
if(options.stream) options.stream({done: true});
|
||||||
if(options.history) options.history.splice(0, options.history.length, ...history);
|
|
||||||
|
|
||||||
// Return parsed JSON if schema provided
|
const turnStart = history.map(h => h.role).lastIndexOf('user');
|
||||||
const finalContent = history.at(-1)?.content;
|
const finalContent = history.slice(turnStart + 1).reduce((str, h) => {
|
||||||
|
if(h.role === 'assistant') return str + (h.content || '');
|
||||||
|
return str;
|
||||||
|
}, '').trim();
|
||||||
|
|
||||||
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
|
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
|
||||||
}), {abort: () => controller.abort()});
|
}), {abort: () => controller.abort()});
|
||||||
}
|
}
|
||||||
|
|||||||
@@ -1,5 +1,5 @@
|
|||||||
import {AbortablePromise} from './ai.ts';
|
import {AbortablePromise} from './ai.ts';
|
||||||
import {LLMMessage, LLMRequest} from './llm.ts';
|
import {LLMRequest} from './llm.ts';
|
||||||
|
|
||||||
export abstract class LLMProvider {
|
export abstract class LLMProvider {
|
||||||
abstract ask(message: string, options: LLMRequest): AbortablePromise<string>;
|
abstract ask(message: string, options: LLMRequest): AbortablePromise<string>;
|
||||||
|
|||||||
65
src/token-pool.ts
Normal file
65
src/token-pool.ts
Normal file
@@ -0,0 +1,65 @@
|
|||||||
|
const DEFAULT_COOLDOWN = 15 * 60 * 1000;
|
||||||
|
|
||||||
|
type TokenState = {
|
||||||
|
token: string;
|
||||||
|
cooldownUntil: number; // 0 = available now
|
||||||
|
lastError?: {code: number, message: string};
|
||||||
|
};
|
||||||
|
|
||||||
|
export class TokenPoolExhaustedError extends Error {
|
||||||
|
constructor(public tokens: Record<string, {code: number, message: string}>) {
|
||||||
|
super(`All tokens exhausted:\n${Object.entries(tokens).map(([t, e]) => `${t}: [${e.code}] ${e.message}`).join('\n')}`);
|
||||||
|
this.name = 'TokenPoolExhaustedError';
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
export class TokenPool {
|
||||||
|
private states: TokenState[];
|
||||||
|
|
||||||
|
constructor(...tokens: string[]) {
|
||||||
|
this.states = tokens.map(token => ({token, cooldownUntil: 0}));
|
||||||
|
}
|
||||||
|
|
||||||
|
private preview(token: string): string {
|
||||||
|
return token.length <= 8 ? '****' : `${token.slice(0, 4)}...${token.slice(-4)}`;
|
||||||
|
}
|
||||||
|
|
||||||
|
/** Anthropic & OpenAI SDKs both attach `status` to thrown errors */
|
||||||
|
private statusCode(err: any): number {
|
||||||
|
return err?.status ?? err?.response?.status ?? err?.statusCode;
|
||||||
|
}
|
||||||
|
|
||||||
|
private retryAfter(err: any): number {
|
||||||
|
const headers = err?.headers || err?.response?.headers;
|
||||||
|
const raw = headers?.get?.('retry-after') ?? headers?.['retry-after'];
|
||||||
|
if(raw) {
|
||||||
|
const seconds = Number(raw);
|
||||||
|
if(!isNaN(seconds)) return Date.now() + seconds * 1000;
|
||||||
|
const date = new Date(raw).getTime();
|
||||||
|
if(!isNaN(date)) return date;
|
||||||
|
}
|
||||||
|
return Date.now() + DEFAULT_COOLDOWN;
|
||||||
|
}
|
||||||
|
|
||||||
|
async run<T>(fn: (token: string) => Promise<T>): Promise<T> {
|
||||||
|
const now = Date.now();
|
||||||
|
for(const state of this.states) {
|
||||||
|
if(state.cooldownUntil > now) continue;
|
||||||
|
try {
|
||||||
|
const result = await fn(state.token);
|
||||||
|
state.cooldownUntil = 0;
|
||||||
|
state.lastError = undefined;
|
||||||
|
return result;
|
||||||
|
} catch(err: any) {
|
||||||
|
const code = this.statusCode(err);
|
||||||
|
if(![401, 403, 429].includes(code)) throw err;
|
||||||
|
state.cooldownUntil = code === 429 ? this.retryAfter(err) : Date.now() + DEFAULT_COOLDOWN;
|
||||||
|
state.lastError = {code, message: err?.message || 'Unknown error'};
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
const failures: Record<string, {code: number, message: string}> = {};
|
||||||
|
this.states.forEach(s => { if(s.lastError) failures[this.preview(s.token)] = s.lastError; });
|
||||||
|
throw new TokenPoolExhaustedError(failures);
|
||||||
|
}
|
||||||
|
}
|
||||||
667
src/tools.ts
667
src/tools.ts
@@ -41,7 +41,7 @@ export type AiTool = {
|
|||||||
/** Tool arguments */
|
/** Tool arguments */
|
||||||
args?: AiToolArg,
|
args?: AiToolArg,
|
||||||
/** Callback function */
|
/** Callback function */
|
||||||
fn: (args: any, stream: LLMRequest['stream'], ai: Ai) => any | Promise<any>,
|
fn: (args: any, stream: LLMRequest['stream'], ai: Ai, toolId?: string) => any | Promise<any>,
|
||||||
};
|
};
|
||||||
|
|
||||||
export function convertSchema(schema: any): any {
|
export function convertSchema(schema: any): any {
|
||||||
@@ -91,20 +91,33 @@ export function convertSchema(schema: any): any {
|
|||||||
};
|
};
|
||||||
}
|
}
|
||||||
|
|
||||||
export const CliTool: AiTool = {
|
export const ExecCliTool: AiTool = {
|
||||||
name: 'cli',
|
name: 'cli',
|
||||||
description: 'Use the command line interface, returns any output',
|
description: 'Use the command line interface, returns any output',
|
||||||
args: {command: {type: 'string', description: 'Command to run', required: true}},
|
args: {command: {type: 'string', description: 'Command to run', required: true}},
|
||||||
fn: (args: {command: string}) => $Sync`${args.command}`
|
fn: (args: {command: string}) => $Sync`${args.command}`
|
||||||
}
|
}
|
||||||
|
|
||||||
export const DateTimeTool: AiTool = {
|
export const ExecJSTool: AiTool = {
|
||||||
name: 'get_datetime',
|
name: 'exec_javascript',
|
||||||
description: 'Get local/UTC date/time',
|
description: 'Execute commonjs javascript',
|
||||||
args: {
|
args: {
|
||||||
timezone: {type: 'string', description: 'Which timezone to return, defaults to local', enum: ['local', 'utc'], default: 'local'}
|
code: {type: 'string', description: 'CommonJS javascript', required: true}
|
||||||
},
|
},
|
||||||
fn: ({timezone}) => new Date()[timezone === 'local' ? 'toString' : 'toUTCString']()
|
fn: async (args: {code: string}) => {
|
||||||
|
const c = consoleInterceptor(null);
|
||||||
|
const resp = await Fn<any>({console: c}, args.code, true).catch((err: any) => c.output.error.push(err));
|
||||||
|
return {...c.output, return: resp, stdout: undefined, stderr: undefined};
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
export const ExecPythonTool: AiTool = {
|
||||||
|
name: 'exec_python',
|
||||||
|
description: 'Execute commonjs javascript',
|
||||||
|
args: {
|
||||||
|
code: {type: 'string', description: 'CommonJS javascript', required: true}
|
||||||
|
},
|
||||||
|
fn: async (args: {code: string}) => ({result: $Sync`python -c "${args.code}"`})
|
||||||
}
|
}
|
||||||
|
|
||||||
export const ExecTool: AiTool = {
|
export const ExecTool: AiTool = {
|
||||||
@@ -118,11 +131,11 @@ export const ExecTool: AiTool = {
|
|||||||
try {
|
try {
|
||||||
switch(args.language) {
|
switch(args.language) {
|
||||||
case 'cli':
|
case 'cli':
|
||||||
return await CliTool.fn({command: args.code}, stream, ai);
|
return await ExecCliTool.fn({command: args.code}, stream, ai);
|
||||||
case 'node':
|
case 'node':
|
||||||
return await JSTool.fn({code: args.code}, stream, ai);
|
return await ExecJSTool.fn({code: args.code}, stream, ai);
|
||||||
case 'python':
|
case 'python':
|
||||||
return await PythonTool.fn({code: args.code}, stream, ai);
|
return await ExecPythonTool.fn({code: args.code}, stream, ai);
|
||||||
default:
|
default:
|
||||||
throw new Error(`Unsupported language: ${args.language}`);
|
throw new Error(`Unsupported language: ${args.language}`);
|
||||||
}
|
}
|
||||||
@@ -132,8 +145,483 @@ export const ExecTool: AiTool = {
|
|||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
export const FetchTool: AiTool = {
|
export const FsDeleteTool = (whitelist: null | string[] = null): AiTool => {
|
||||||
name: 'fetch',
|
return {
|
||||||
|
name: 'fs_delete',
|
||||||
|
description: 'Delete a file or directory',
|
||||||
|
args: {
|
||||||
|
path: {type: 'string', description: 'Path to file or directory', required: true},
|
||||||
|
recursive: {type: 'boolean', description: 'Delete all children', required: false}
|
||||||
|
},
|
||||||
|
fn: async ({path, recursive = false}) => {
|
||||||
|
const {existsSync, rmSync} = await import('fs');
|
||||||
|
const normalizePath = p => p.replace(/\\/g, '/');
|
||||||
|
|
||||||
|
path = normalizePath(path);
|
||||||
|
if(whitelist && !whitelist.some(p => path.startsWith(p))) return {error: 'Permission denied'};
|
||||||
|
if(!existsSync(path)) return {error: 'Path does not exist'};
|
||||||
|
|
||||||
|
rmSync(path, {recursive, force: true});
|
||||||
|
return {success: true, path};
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
export const FsMoveTool = (whitelist: null | string[] = null): AiTool => {
|
||||||
|
return {
|
||||||
|
name: 'fs_move',
|
||||||
|
description: 'Move or rename a file or directory',
|
||||||
|
args: {
|
||||||
|
source: {type: 'string', description: 'Path to source file or directory', required: true},
|
||||||
|
destination: {type: 'string', description: 'Path to destination file or directory', required: true}
|
||||||
|
},
|
||||||
|
fn: async ({source, destination}) => {
|
||||||
|
const {existsSync, renameSync} = await import('fs');
|
||||||
|
const normalizePath = p => p.replace(/\\/g, '/');
|
||||||
|
|
||||||
|
source = normalizePath(source);
|
||||||
|
destination = normalizePath(destination);
|
||||||
|
if(whitelist && !whitelist.some(p => source.startsWith(p) && destination.startsWith(p))) return {error: 'Permission denied'};
|
||||||
|
|
||||||
|
if(!existsSync(source)) return {error: 'Source path does not exist'};
|
||||||
|
if(existsSync(destination)) return {error: 'Destination path already exists'};
|
||||||
|
|
||||||
|
renameSync(source, destination);
|
||||||
|
return {success: true, source, destination};
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
export const FsReadTool = (whitelist: null | string[] = null): AiTool => {
|
||||||
|
return {
|
||||||
|
name: 'fs_read',
|
||||||
|
description: 'Read the contents of a provided path. Works with files and directories',
|
||||||
|
args: {path: {type: 'string', description: 'Path to file or directory', required: true}},
|
||||||
|
fn: async ({path}) => {
|
||||||
|
const {existsSync, lstatSync, readdirSync, readFileSync} = await import('fs');
|
||||||
|
const {join} = await import('path');
|
||||||
|
const normalizePath = p => p.replace(/\\/g, '/');
|
||||||
|
|
||||||
|
path = normalizePath(path);
|
||||||
|
if(whitelist && !whitelist.some(p => path.startsWith(p))) return {error: 'Permission denied'};
|
||||||
|
|
||||||
|
if(!existsSync(path)) return {error: 'Path does not exist'};
|
||||||
|
const stats = lstatSync(path);
|
||||||
|
if(stats.isDirectory()) {
|
||||||
|
const children = readdirSync(path).map(name => {
|
||||||
|
const childPath = normalizePath(join(path, name));
|
||||||
|
const childStats = lstatSync(childPath);
|
||||||
|
return {name, type: childStats.isDirectory() ? 'directory' : 'file', size: childStats.size};
|
||||||
|
});
|
||||||
|
return {type: 'directory', children};
|
||||||
|
}
|
||||||
|
const content = readFileSync(path, 'utf-8');
|
||||||
|
return {type: 'file', content};
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
export const FsSearchTool = (whitelist: null | string[] = null): AiTool => {
|
||||||
|
return {
|
||||||
|
name: 'fs_search',
|
||||||
|
description: 'Scan a directory for matching glob patterns (e.g. "**/*.js", "src/**/*.test.ts")',
|
||||||
|
args: {
|
||||||
|
pattern: {type: 'string', description: 'Glob pattern to match against paths', required: true},
|
||||||
|
root: {type: 'string', description: 'Directory to search from', required: false, default: '.'}
|
||||||
|
},
|
||||||
|
fn: async ({pattern, root = '.'}) => {
|
||||||
|
const {existsSync, lstatSync, readdirSync} = await import('fs');
|
||||||
|
const {join, relative} = await import('path');
|
||||||
|
const normalizePath = p => p.replace(/\\/g, '/');
|
||||||
|
|
||||||
|
root = normalizePath(root);
|
||||||
|
if(!existsSync(root)) return {error: 'Root path does not exist'};
|
||||||
|
if(!lstatSync(root).isDirectory()) return {error: 'Root path is not a directory'};
|
||||||
|
|
||||||
|
if(whitelist && !whitelist.some(p => root.startsWith(p))) return {error: 'Permission denied'};
|
||||||
|
|
||||||
|
const globToRegex = (glob) => {
|
||||||
|
let re = '';
|
||||||
|
for(let i = 0; i < glob.length; i++) {
|
||||||
|
const c = glob[i];
|
||||||
|
if(c === '*') {
|
||||||
|
if(glob[i + 1] === '*') {
|
||||||
|
const isSlash = glob[i + 2] === '/';
|
||||||
|
re += '.*';
|
||||||
|
i += isSlash ? 2 : 1;
|
||||||
|
} else {
|
||||||
|
re += '[^/]*';
|
||||||
|
}
|
||||||
|
} else if(c === '?') {
|
||||||
|
re += '[^/]';
|
||||||
|
} else if('.+^$(){}|[]\\'.includes(c)) {
|
||||||
|
re += '\\' + c;
|
||||||
|
} else {
|
||||||
|
re += c;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
return new RegExp('^' + re + '$');
|
||||||
|
};
|
||||||
|
const regex = globToRegex(pattern);
|
||||||
|
|
||||||
|
const results: any = [];
|
||||||
|
const walk = (dir) => {
|
||||||
|
for(const name of readdirSync(dir)) {
|
||||||
|
const fullPath = normalizePath(join(dir, name));
|
||||||
|
const stats = lstatSync(fullPath);
|
||||||
|
const relPath = normalizePath(relative(root, fullPath));
|
||||||
|
if(regex.test(relPath)) {
|
||||||
|
results.push({path: relPath, type: stats.isDirectory() ? 'directory' : 'file', size: stats.size});
|
||||||
|
}
|
||||||
|
if(stats.isDirectory()) walk(fullPath);
|
||||||
|
}
|
||||||
|
};
|
||||||
|
walk(root);
|
||||||
|
|
||||||
|
return results;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
export const FsWriteTool = (whitelist: null | string[] = null): AiTool => {
|
||||||
|
return {
|
||||||
|
name: 'fs_write',
|
||||||
|
description: 'Create a directory, write content to a file or preform a find & replace',
|
||||||
|
args: {
|
||||||
|
path: {type: 'string', description: 'Path to file or directory', required: true},
|
||||||
|
content: {type: 'string', description: 'Content to write or replace (Omit to create a directory)'},
|
||||||
|
find: {type: 'string', description: 'Text or regex pattern to match (regex must match pattern: "/pattern/g")'}
|
||||||
|
},
|
||||||
|
fn: async ({path, content, find}) => {
|
||||||
|
const {existsSync, mkdirSync, readFileSync, writeFileSync} = await import('fs');
|
||||||
|
const {dirname} = await import('path');
|
||||||
|
const normalizePath = p => p.replace(/\\/g, '/');
|
||||||
|
|
||||||
|
path = normalizePath(path);
|
||||||
|
if(whitelist && !whitelist.some(p => path.startsWith(p))) return {error: 'Permission denied'};
|
||||||
|
|
||||||
|
if(content === undefined) {
|
||||||
|
mkdirSync(path, {recursive: true});
|
||||||
|
return {success: true, type: 'directory', path};
|
||||||
|
}
|
||||||
|
|
||||||
|
const dir = normalizePath(dirname(path));
|
||||||
|
if(!existsSync(dir)) mkdirSync(dir, {recursive: true});
|
||||||
|
|
||||||
|
if(find && existsSync(path)) {
|
||||||
|
const existing = readFileSync(path, 'utf-8');
|
||||||
|
const regexMatch = find.match(/^\/(.+)\/([gimuy]*)$/);
|
||||||
|
const pattern = regexMatch ? new RegExp(regexMatch[1], regexMatch[2]) : find;
|
||||||
|
|
||||||
|
if(!existing.match(pattern)) return {error: 'Find pattern not found in file'};
|
||||||
|
|
||||||
|
const updated = existing.replace(pattern, content);
|
||||||
|
writeFileSync(path, updated, 'utf-8');
|
||||||
|
return {success: true, type: 'file', path, replaced: true, content: updated};
|
||||||
|
}
|
||||||
|
|
||||||
|
writeFileSync(path, content, 'utf-8');
|
||||||
|
return {success: true, type: 'file', path, content};
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
export const GetPathsTool: AiTool = {
|
||||||
|
name: 'get_paths',
|
||||||
|
description: 'Get the current working directory, and paths to the users home directory',
|
||||||
|
fn: async () => {
|
||||||
|
return {
|
||||||
|
home: os.homedir(),
|
||||||
|
cwd: process.cwd()
|
||||||
|
};
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
export const GetDatetimeTool: AiTool = {
|
||||||
|
name: 'get_datetime',
|
||||||
|
description: 'Get local/UTC timestamp',
|
||||||
|
args: {
|
||||||
|
timezone: {type: 'string', description: 'Which timezone to return, defaults to local', enum: ['local', 'utc'], default: 'local'}
|
||||||
|
},
|
||||||
|
fn: ({timezone}) => new Date()[timezone === 'local' ? 'toString' : 'toUTCString']()
|
||||||
|
}
|
||||||
|
|
||||||
|
export const GetDevice: AiTool = {
|
||||||
|
name: 'get_device',
|
||||||
|
description: 'Get comprehensive system information including hostname, specs, load, storage, and network status',
|
||||||
|
args: {},
|
||||||
|
fn: async () => {
|
||||||
|
const platform = os.platform();
|
||||||
|
const hostname = os.hostname();
|
||||||
|
|
||||||
|
// CPU Info
|
||||||
|
const cpus = os.cpus();
|
||||||
|
const cpuModel = cpus[0].model;
|
||||||
|
const cpuCores = cpus.length;
|
||||||
|
|
||||||
|
// Memory Info
|
||||||
|
const totalMem: any = (os.totalmem() / 1024 / 1024 / 1024).toFixed(2);
|
||||||
|
const freeMem: any = (os.freemem() / 1024 / 1024 / 1024).toFixed(2);
|
||||||
|
const usedMem: any = (totalMem - freeMem).toFixed(2);
|
||||||
|
const memUsage: any = ((usedMem / totalMem) * 100).toFixed(1);
|
||||||
|
|
||||||
|
// Load Average (not available on Windows)
|
||||||
|
const loadAvg = platform === 'win32' ? ['N/A', 'N/A', 'N/A'] : os.loadavg().map(l => l.toFixed(2));
|
||||||
|
|
||||||
|
// Storage Usage
|
||||||
|
let storage = {};
|
||||||
|
if(platform === 'win32') {
|
||||||
|
const ps = $Sync`powershell "Get-PSDrive C | Select-Object Used,Free | ConvertTo-Json"`.trim();
|
||||||
|
const drive = JSON.parse(ps);
|
||||||
|
const used: any = (drive.Used / 1024 / 1024 / 1024).toFixed(2);
|
||||||
|
const free: any = (drive.Free / 1024 / 1024 / 1024).toFixed(2);
|
||||||
|
const total: any = (parseFloat(used) + parseFloat(free)).toFixed(2);
|
||||||
|
const usage: any = ((used / total) * 100).toFixed(1);
|
||||||
|
storage = {
|
||||||
|
filesystem: 'C:',
|
||||||
|
size: `${total} GB`,
|
||||||
|
used: `${used} GB`,
|
||||||
|
available: `${free} GB`,
|
||||||
|
usage: `${usage}%`
|
||||||
|
};
|
||||||
|
} else {
|
||||||
|
const df = $Sync`df -h / | tail -1`.trim();
|
||||||
|
const s = df.split(/\s+/);
|
||||||
|
storage = {
|
||||||
|
filesystem: s[0],
|
||||||
|
size: s[1],
|
||||||
|
used: s[2],
|
||||||
|
available: s[3],
|
||||||
|
usage: s[4]
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
|
// Network Status
|
||||||
|
const interfaces = os.networkInterfaces();
|
||||||
|
const activeIfaces = Object.entries(interfaces)
|
||||||
|
.filter(([name]) => name !== 'lo' && !name.includes('Loopback'))
|
||||||
|
.map(([name, addrs]) => {
|
||||||
|
const ipv4 = addrs?.find(a => a.family === 'IPv4');
|
||||||
|
return ipv4 ? {name, ip: ipv4.address} : null;
|
||||||
|
})
|
||||||
|
.filter(Boolean);
|
||||||
|
|
||||||
|
// Internet connectivity check
|
||||||
|
let internet = false;
|
||||||
|
try {
|
||||||
|
if(platform === 'win32') {
|
||||||
|
$Sync`powershell "Test-Connection -ComputerName 8.8.8.8 -Count 1 -Quiet"`;
|
||||||
|
} else {
|
||||||
|
$Sync`ping -c 1 -W 2 8.8.8.8 > /dev/null 2>&1`;
|
||||||
|
}
|
||||||
|
internet = true;
|
||||||
|
} catch {}
|
||||||
|
|
||||||
|
// Uptime
|
||||||
|
const uptime = os.uptime();
|
||||||
|
const days = Math.floor(uptime / 86400);
|
||||||
|
const hours = Math.floor((uptime % 86400) / 3600);
|
||||||
|
const minutes = Math.floor((uptime % 3600) / 60);
|
||||||
|
|
||||||
|
return {
|
||||||
|
hostname,
|
||||||
|
cpu: {
|
||||||
|
model: cpuModel,
|
||||||
|
cores: cpuCores
|
||||||
|
},
|
||||||
|
memory: {
|
||||||
|
total: `${totalMem} GB`,
|
||||||
|
used: `${usedMem} GB`,
|
||||||
|
free: `${freeMem} GB`,
|
||||||
|
usage: `${memUsage}%`
|
||||||
|
},
|
||||||
|
load: {
|
||||||
|
'1min': loadAvg[0],
|
||||||
|
'5min': loadAvg[1],
|
||||||
|
'15min': loadAvg[2]
|
||||||
|
},
|
||||||
|
storage,
|
||||||
|
network: {
|
||||||
|
interfaces: activeIfaces,
|
||||||
|
internet: internet ? 'connected' : 'disconnected'
|
||||||
|
},
|
||||||
|
uptime: `${days}d ${hours}h ${minutes}m`,
|
||||||
|
platform: `${os.type()} ${os.release()}`
|
||||||
|
};
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
export const GetWikipediaTool: AiTool = {
|
||||||
|
name: 'get_wikipedia',
|
||||||
|
description: 'Search Wikipedia for matching articles',
|
||||||
|
args: {
|
||||||
|
query: {type: 'string', description: 'Search term or article title', required: true},
|
||||||
|
mode: {type: 'string', description: 'search - look for articles, summary - intro of first found article (default), full - complete first found article', enum: ['search', 'summary', 'full'], default: 'summary'},
|
||||||
|
ua: {type: 'string', description: 'User Agent'},
|
||||||
|
},
|
||||||
|
fn: async ({query, mode, ua}) => {
|
||||||
|
class WikipediaClient {
|
||||||
|
useragent = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)';
|
||||||
|
|
||||||
|
constructor(useragent: string) {
|
||||||
|
this.useragent = useragent;
|
||||||
|
}
|
||||||
|
|
||||||
|
async get(url) {
|
||||||
|
const resp = await fetch(url, {headers: {'User-Agent': this.useragent}});
|
||||||
|
return resp.json();
|
||||||
|
}
|
||||||
|
|
||||||
|
api(params) {
|
||||||
|
const qs = new URLSearchParams({...params, format: 'json', utf8: '1'}).toString();
|
||||||
|
return this.get(`https://en.wikipedia.org/w/api.php?${qs}`);
|
||||||
|
}
|
||||||
|
|
||||||
|
clean(text) {
|
||||||
|
const cutoffs = ['== See also ==', '== References ==', '== Bibliography ==', '== External links =='];
|
||||||
|
for (const marker of cutoffs) {
|
||||||
|
const idx = text.indexOf(marker);
|
||||||
|
if (idx !== -1) text = text.slice(0, idx);
|
||||||
|
}
|
||||||
|
|
||||||
|
return text
|
||||||
|
.replace(/^={4}\s*(.+?)\s*={4}$/gm, '#### $1')
|
||||||
|
.replace(/^={3}\s*(.+?)\s*={3}$/gm, '### $1')
|
||||||
|
.replace(/^={2}\s*(.+?)\s*={2}$/gm, '## $1')
|
||||||
|
.replace(/\n{3,}/g, '\n\n')
|
||||||
|
.replace(/ {2,}/g, ' ')
|
||||||
|
.replace(/\[\d+]/g, '')
|
||||||
|
.trim();
|
||||||
|
}
|
||||||
|
|
||||||
|
async searchTitles(query: string, limit = 6) {
|
||||||
|
const data = await this.api({action: 'query', list: 'search', srsearch: query, srlimit: limit, srprop: 'snippet'});
|
||||||
|
return data.query?.search || [];
|
||||||
|
}
|
||||||
|
|
||||||
|
async fetchExtract(title: string, introOnly = false) {
|
||||||
|
const params: any = {action: 'query', prop: 'extracts', titles: title, explaintext: 1, redirects: 1};
|
||||||
|
if(introOnly) params.exintro = 1;
|
||||||
|
const data = await this.api(params);
|
||||||
|
const page: any = Object.values(data.query?.pages || {})[0];
|
||||||
|
return this.clean(page?.extract || '');
|
||||||
|
}
|
||||||
|
|
||||||
|
pageUrl(title: string) {
|
||||||
|
return `https://en.wikipedia.org/wiki/${encodeURIComponent(title.replace(/ /g, '_'))}`;
|
||||||
|
}
|
||||||
|
|
||||||
|
stripHtml(text: string) {
|
||||||
|
return text.replace(/<[^>]+>/g, '');
|
||||||
|
}
|
||||||
|
|
||||||
|
async lookup(query: string, detail = 'summary') {
|
||||||
|
const results = await this.searchTitles(query, 6);
|
||||||
|
if(!results.length) return `❌ No Wikipedia articles found for "${query}"`;
|
||||||
|
const title = results[0].title;
|
||||||
|
const url = this.pageUrl(title);
|
||||||
|
const introOnly = detail !== 'full';
|
||||||
|
const content = await this.fetchExtract(title, introOnly);
|
||||||
|
return `## ${title}\n🔗 ${url}\n\n${content}`;
|
||||||
|
}
|
||||||
|
|
||||||
|
async search(query: string) {
|
||||||
|
const results = await this.searchTitles(query, 8);
|
||||||
|
if(!results.length) return `❌ No results for "${query}"`;
|
||||||
|
const lines = [`### Search results for "${query}"\n`];
|
||||||
|
for(let i = 0; i < results.length; i++) {
|
||||||
|
const r = results[i];
|
||||||
|
const snippet = this.stripHtml(r.snippet || '').trim();
|
||||||
|
lines.push(`**${i + 1}. ${r.title}**\n${snippet}\n${this.pageUrl(r.title)}`);
|
||||||
|
}
|
||||||
|
return lines.join('\n\n');
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
const wiki = new WikipediaClient(ua);
|
||||||
|
if(mode === 'search') return wiki.search(query);
|
||||||
|
return wiki.lookup(query, mode || 'summary');
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
export const GeoCodeTool: AiTool = {
|
||||||
|
name: 'geo_code',
|
||||||
|
description: 'Converts coordinates to address OR vice versa',
|
||||||
|
args: {
|
||||||
|
query: {type: 'string', description: 'Search query - coordinates (lat,lon) or address string', required: true},
|
||||||
|
},
|
||||||
|
fn: async ({query}) => {
|
||||||
|
const coordinates = /(-?\d+(?:\.\d+)?).*?,.*?(-?\d+(?:\.\d+)?)/.exec(query);
|
||||||
|
if(coordinates) { // Geolocate
|
||||||
|
const url = `https://nominatim.openstreetmap.org/reverse?format=json&lat=${encodeURIComponent(coordinates[1])}&lon=${encodeURIComponent(coordinates[2])}`;
|
||||||
|
const response = await fetch(url, {headers: {'User-Agent': 'OpenSight/1.0', 'Accept-Language': 'en'}});
|
||||||
|
const data = await response.json();
|
||||||
|
if(data.display_name) return {address: data.display_name, mode: 'geolocate'};
|
||||||
|
} else { // Geocode
|
||||||
|
const url = `https://nominatim.openstreetmap.org/search?format=json&q=${encodeURIComponent(query)}`;
|
||||||
|
const response = await fetch(url, {headers: {'User-Agent': 'OpenSight/1.0'}});
|
||||||
|
const data = await response.json();
|
||||||
|
if(data[0]) return {latitude: parseFloat(data[0].lat), longitude: parseFloat(data[0].lon), mode: 'geocode'};
|
||||||
|
}
|
||||||
|
return {error: 'Not found'};
|
||||||
|
},
|
||||||
|
}
|
||||||
|
|
||||||
|
export const GeoWeatherTool: AiTool = {
|
||||||
|
name: 'geo_weather',
|
||||||
|
description: 'Gets weather and air quality info for a location and time',
|
||||||
|
args: {
|
||||||
|
query: {type: 'string', description: 'Location - address or place name', required: true},
|
||||||
|
day: {type: 'string', description: 'Date to retrieve (YYYY-MM-DD), defaults to today'},
|
||||||
|
},
|
||||||
|
fn: async ({query, day}) => {
|
||||||
|
day = day || new Date().toISOString().slice(0, 10);
|
||||||
|
|
||||||
|
const geoUrl = `https://nominatim.openstreetmap.org/search?format=json&q=${encodeURIComponent(query)}`;
|
||||||
|
const geoResponse = await fetch(geoUrl, {headers: {'User-Agent': 'OpenSight/1.0'}});
|
||||||
|
const geoData = await geoResponse.json();
|
||||||
|
if(!geoData[0]) return {error: 'Location not found'};
|
||||||
|
|
||||||
|
const lat = parseFloat(geoData[0].lat);
|
||||||
|
const lon = parseFloat(geoData[0].lon);
|
||||||
|
|
||||||
|
const weatherUrl = `https://api.open-meteo.com/v1/forecast?latitude=${lat}&longitude=${lon}&start_date=${day}&end_date=${day}&daily=weathercode,temperature_2m_max,temperature_2m_min,apparent_temperature_max,apparent_temperature_min,precipitation_sum,precipitation_probability_max,windspeed_10m_max,winddirection_10m_dominant,uv_index_max,sunrise,sunset&timezone=auto`;
|
||||||
|
const airUrl = `https://air-quality-api.open-meteo.com/v1/air-quality?latitude=${lat}&longitude=${lon}&start_date=${day}&end_date=${day}&hourly=us_aqi,european_aqi,pm10,pm2_5&timezone=auto`;
|
||||||
|
|
||||||
|
const [weatherResponse, airResponse] = await Promise.all([fetch(weatherUrl), fetch(airUrl)]);
|
||||||
|
const weatherData = await weatherResponse.json();
|
||||||
|
const airData = await airResponse.json();
|
||||||
|
|
||||||
|
const avg = arr => (arr && arr.length) ? arr.reduce((a, b) => a + b, 0) / arr.length : null;
|
||||||
|
|
||||||
|
return {
|
||||||
|
location: geoData[0].display_name,
|
||||||
|
latitude: lat,
|
||||||
|
longitude: lon,
|
||||||
|
elevation: weatherData.elevation,
|
||||||
|
date: day,
|
||||||
|
weatherCode: weatherData.daily?.weathercode?.[0],
|
||||||
|
tempMax: weatherData.daily?.temperature_2m_max?.[0],
|
||||||
|
tempMin: weatherData.daily?.temperature_2m_min?.[0],
|
||||||
|
feelsLikeMax: weatherData.daily?.apparent_temperature_max?.[0],
|
||||||
|
feelsLikeMin: weatherData.daily?.apparent_temperature_min?.[0],
|
||||||
|
precipitation: weatherData.daily?.precipitation_sum?.[0],
|
||||||
|
precipitationChance: weatherData.daily?.precipitation_probability_max?.[0],
|
||||||
|
windSpeedMax: weatherData.daily?.windspeed_10m_max?.[0],
|
||||||
|
windDirection: weatherData.daily?.winddirection_10m_dominant?.[0],
|
||||||
|
uvIndexMax: weatherData.daily?.uv_index_max?.[0],
|
||||||
|
sunrise: weatherData.daily?.sunrise?.[0],
|
||||||
|
sunset: weatherData.daily?.sunset?.[0],
|
||||||
|
usAqi: avg(airData.hourly?.us_aqi),
|
||||||
|
europeanAqi: avg(airData.hourly?.european_aqi),
|
||||||
|
pm10: avg(airData.hourly?.pm10),
|
||||||
|
pm2_5: avg(airData.hourly?.pm2_5),
|
||||||
|
};
|
||||||
|
},
|
||||||
|
}
|
||||||
|
|
||||||
|
export const WebFetchTool: AiTool = {
|
||||||
|
name: 'web_fetch',
|
||||||
description: 'Make HTTP request to URL',
|
description: 'Make HTTP request to URL',
|
||||||
args: {
|
args: {
|
||||||
url: {type: 'string', description: 'URL to fetch', required: true},
|
url: {type: 'string', description: 'URL to fetch', required: true},
|
||||||
@@ -149,30 +637,59 @@ export const FetchTool: AiTool = {
|
|||||||
}) => new Http({url: args.url, headers: args.headers}).request({method: args.method || 'GET', body: args.body})
|
}) => new Http({url: args.url, headers: args.headers}).request({method: args.method || 'GET', body: args.body})
|
||||||
}
|
}
|
||||||
|
|
||||||
export const JSTool: AiTool = {
|
export const WebFlareSolverTool = (host: string) => {
|
||||||
name: 'exec_javascript',
|
return {
|
||||||
description: 'Execute commonjs javascript',
|
name: 'web_flaresolverr',
|
||||||
|
description: 'Use a flaresolverr proxy to bypass cloudflare bot detection',
|
||||||
args: {
|
args: {
|
||||||
code: {type: 'string', description: 'CommonJS javascript', required: true}
|
url: {type: 'string', description: 'URL to fetch', required: true},
|
||||||
|
cmd: {type: 'string', description: 'Flaresolverr cmd', enum: ['request.get', 'request.post'], default: 'request.get'},
|
||||||
|
maxTimeout: {type: 'number', description: 'Fetch time limit', default: 60_000},
|
||||||
|
postData: {type: 'object', description: 'Data to send during request.post requests'},
|
||||||
},
|
},
|
||||||
fn: async (args: {code: string}) => {
|
fn: async ({url, cmd, maxTimeout, postData}) => {
|
||||||
const c = consoleInterceptor(null);
|
function toFormUrlEncoded(obj, prefix = '') {
|
||||||
const resp = await Fn<any>({console: c}, args.code, true).catch((err: any) => c.output.error.push(err));
|
const pairs: any = [];
|
||||||
return {...c.output, return: resp, stdout: undefined, stderr: undefined};
|
for (const key in obj) {
|
||||||
|
if (!obj.hasOwnProperty(key)) continue;
|
||||||
|
|
||||||
|
const value = obj[key];
|
||||||
|
const encodedKey = prefix
|
||||||
|
? `${prefix}[${encodeURIComponent(key)}]`
|
||||||
|
: encodeURIComponent(key);
|
||||||
|
|
||||||
|
if (value === null || value === undefined) {
|
||||||
|
pairs.push(`${encodedKey}=`);
|
||||||
|
} else if (typeof value === 'object' && !Array.isArray(value)) {
|
||||||
|
pairs.push(toFormUrlEncoded(value, encodedKey));
|
||||||
|
} else if (Array.isArray(value)) {
|
||||||
|
value.forEach(item => {
|
||||||
|
pairs.push(`${encodedKey}[]=${encodeURIComponent(item)}`);
|
||||||
|
});
|
||||||
|
} else {
|
||||||
|
pairs.push(`${encodedKey}=${encodeURIComponent(value)}`);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
return pairs.join('&');
|
||||||
|
}
|
||||||
|
|
||||||
|
const res = await fetch(host + '/v1', {
|
||||||
|
method: 'POST',
|
||||||
|
headers: {'Content-Type': 'application/json'},
|
||||||
|
body: JSON.stringify({cmd, url, maxTimeout, postData: postData ? toFormUrlEncoded(postData) : undefined}),
|
||||||
|
});
|
||||||
|
|
||||||
|
if(!res.ok) throw new Error(`FlareSolverr HTTP error: ${res.status} ${res.statusText}`);
|
||||||
|
const data = await res.json();
|
||||||
|
if(data.status !== 'ok') throw new Error(`FlareSolverr error: ${data.message ?? data.status}`);
|
||||||
|
return data.solution.response;
|
||||||
|
}
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
export const PythonTool: AiTool = {
|
export const WebReadTool: AiTool = {
|
||||||
name: 'exec_python',
|
name: 'web_read',
|
||||||
description: 'Execute commonjs javascript',
|
|
||||||
args: {
|
|
||||||
code: {type: 'string', description: 'CommonJS javascript', required: true}
|
|
||||||
},
|
|
||||||
fn: async (args: {code: string}) => ({result: $Sync`python -c "${args.code}"`})
|
|
||||||
}
|
|
||||||
|
|
||||||
export const ReadWebpageTool: AiTool = {
|
|
||||||
name: 'read_webpage',
|
|
||||||
description: 'Extract clean content from webpages, or convert media/documents to accessible formats',
|
description: 'Extract clean content from webpages, or convert media/documents to accessible formats',
|
||||||
args: {
|
args: {
|
||||||
url: {type: 'string', description: 'URL to read', required: true},
|
url: {type: 'string', description: 'URL to read', required: true},
|
||||||
@@ -300,91 +817,3 @@ export const WebSearchTool: AiTool = {
|
|||||||
return results;
|
return results;
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
export const WikipediaTool: AiTool = {
|
|
||||||
name: 'wikipedia_search',
|
|
||||||
description: 'Search Wikipedia for matching articles',
|
|
||||||
args: {
|
|
||||||
query: {type: 'string', description: 'Search term or article title', required: true},
|
|
||||||
mode: {type: 'string', description: 'search - look for articles, summary - intro of first found article (default), full - complete first found article', enum: ['search', 'summary', 'full'], default: 'summary'}
|
|
||||||
},
|
|
||||||
fn: async (args: {query: string, mode: 'search' | 'summary' | 'full'}) => {
|
|
||||||
const UA = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)';
|
|
||||||
|
|
||||||
class WikipediaClient {
|
|
||||||
async get(url: string) {
|
|
||||||
const resp = await fetch(url, {headers: {'User-Agent': UA}});
|
|
||||||
return resp.json();
|
|
||||||
}
|
|
||||||
|
|
||||||
api(params: any) {
|
|
||||||
const qs = new URLSearchParams({...params, format: 'json', utf8: '1'}).toString();
|
|
||||||
return this.get(`https://en.wikipedia.org/w/api.php?${qs}`);
|
|
||||||
}
|
|
||||||
|
|
||||||
clean(text: string) {
|
|
||||||
const cutoffs = ['== See also ==', '== References ==', '== Bibliography ==', '== External links =='];
|
|
||||||
for (const marker of cutoffs) {
|
|
||||||
const idx = text.indexOf(marker);
|
|
||||||
if (idx !== -1) text = text.slice(0, idx);
|
|
||||||
}
|
|
||||||
|
|
||||||
return text
|
|
||||||
.replace(/^={4}\s*(.+?)\s*={4}$/gm, '#### $1')
|
|
||||||
.replace(/^={3}\s*(.+?)\s*={3}$/gm, '### $1')
|
|
||||||
.replace(/^={2}\s*(.+?)\s*={2}$/gm, '## $1')
|
|
||||||
.replace(/\n{3,}/g, '\n\n')
|
|
||||||
.replace(/ {2,}/g, ' ')
|
|
||||||
.replace(/\[\d+\]/g, '')
|
|
||||||
.trim();
|
|
||||||
}
|
|
||||||
|
|
||||||
async searchTitles(query: string, limit = 6) {
|
|
||||||
const data = await this.api({action: 'query', list: 'search', srsearch: query, srlimit: limit, srprop: 'snippet'});
|
|
||||||
return data.query?.search || [];
|
|
||||||
}
|
|
||||||
|
|
||||||
async fetchExtract(title: string, introOnly = false) {
|
|
||||||
const params: any = {action: 'query', prop: 'extracts', titles: title, explaintext: 1, redirects: 1};
|
|
||||||
if(introOnly) params.exintro = 1;
|
|
||||||
const data = await this.api(params);
|
|
||||||
const page: any = Object.values(data.query?.pages || {})[0];
|
|
||||||
return this.clean(page?.extract || '');
|
|
||||||
}
|
|
||||||
|
|
||||||
pageUrl(title: string) {
|
|
||||||
return `https://en.wikipedia.org/wiki/${encodeURIComponent(title.replace(/ /g, '_'))}`;
|
|
||||||
}
|
|
||||||
|
|
||||||
stripHtml(text: string) {
|
|
||||||
return text.replace(/<[^>]+>/g, '');
|
|
||||||
}
|
|
||||||
|
|
||||||
async lookup(query: string, detail = 'summary') {
|
|
||||||
const results = await this.searchTitles(query, 6);
|
|
||||||
if(!results.length) return `❌ No Wikipedia articles found for "${query}"`;
|
|
||||||
const title = results[0].title;
|
|
||||||
const url = this.pageUrl(title);
|
|
||||||
const introOnly = detail !== 'full';
|
|
||||||
const content = await this.fetchExtract(title, introOnly);
|
|
||||||
return `## ${title}\n🔗 ${url}\n\n${content}`;
|
|
||||||
}
|
|
||||||
|
|
||||||
async search(query: string) {
|
|
||||||
const results = await this.searchTitles(query, 8);
|
|
||||||
if(!results.length) return `❌ No results for "${query}"`;
|
|
||||||
const lines = [`### Search results for "${query}"\n`];
|
|
||||||
for(let i = 0; i < results.length; i++) {
|
|
||||||
const r = results[i];
|
|
||||||
const snippet = this.stripHtml(r.snippet || '').trim();
|
|
||||||
lines.push(`**${i + 1}. ${r.title}**\n${snippet}\n${this.pageUrl(r.title)}`);
|
|
||||||
}
|
|
||||||
return lines.join('\n\n');
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
const wiki = new WikipediaClient();
|
|
||||||
if(args.mode == 'search') return wiki.search(args.query);
|
|
||||||
return wiki.lookup(args.query, args.mode || 'summary');
|
|
||||||
}
|
|
||||||
};
|
|
||||||
|
|||||||
167
tests/llm.spec.ts
Normal file
167
tests/llm.spec.ts
Normal file
@@ -0,0 +1,167 @@
|
|||||||
|
|
||||||
|
import {describe, it, expect, vi, beforeEach} from 'vitest';
|
||||||
|
import LLM from '../src/llm';
|
||||||
|
|
||||||
|
const {FakeProvider, providerLog} = vi.hoisted(() => {
|
||||||
|
const providerLog: any[] = [];
|
||||||
|
class FakeProvider {
|
||||||
|
model: string;
|
||||||
|
constructor(...args: any[]) { this.model = args[args.length - 1]; }
|
||||||
|
ask(message: string, opts: any) {
|
||||||
|
let aborted = false;
|
||||||
|
const p = (async () => {
|
||||||
|
const script = (globalThis as any).__scripts?.[this.model];
|
||||||
|
const plan = script ? script(message, opts) : {text: ''};
|
||||||
|
providerLog.push({model: this.model, message, system: opts.system, tools: (opts.tools || []).map((t: any) => t.name)});
|
||||||
|
for (const c of plan.calls || []) {
|
||||||
|
if (aborted) break;
|
||||||
|
const tool = (opts.tools || []).find((t: any) => t.name === c.tool);
|
||||||
|
const id = c.id || `${c.tool}_${Math.random()}`;
|
||||||
|
const content = await tool.fn(c.args, opts.stream, null, id);
|
||||||
|
opts.history.push({role: 'tool', id, name: c.tool, args: c.args, content, timestamp: Date.now()});
|
||||||
|
}
|
||||||
|
const text = plan.text ?? '';
|
||||||
|
if (opts.stream && text) opts.stream({text, done: true});
|
||||||
|
opts.history.push({role: 'assistant', content: text, timestamp: Date.now(), duration: 10, tps: 5});
|
||||||
|
return text;
|
||||||
|
})();
|
||||||
|
return Object.assign(p, {abort: () => { aborted = true; }});
|
||||||
|
}
|
||||||
|
}
|
||||||
|
return {FakeProvider, providerLog};
|
||||||
|
});
|
||||||
|
|
||||||
|
vi.mock('../src/antrhopic.ts', () => ({Anthropic: FakeProvider}));
|
||||||
|
vi.mock('../src/open-ai.ts', () => ({OpenAi: FakeProvider}));
|
||||||
|
|
||||||
|
function makeAi(models: any) {
|
||||||
|
return {options: {llm: {models}}} as any;
|
||||||
|
}
|
||||||
|
|
||||||
|
beforeEach(() => {
|
||||||
|
providerLog.length = 0;
|
||||||
|
(globalThis as any).__scripts = {};
|
||||||
|
});
|
||||||
|
|
||||||
|
describe('LLM cross-provider interchangeability', () => {
|
||||||
|
it('runs identical tool calls the same way on an anthropic-backed model and an openai-backed model', async () => {
|
||||||
|
const ai = makeAi({
|
||||||
|
claude: {proto: 'anthropic', token: 'x'},
|
||||||
|
gpt: {proto: 'openai', token: 'y', host: 'http://local'},
|
||||||
|
});
|
||||||
|
const llm = new LLM(ai);
|
||||||
|
const calc = {
|
||||||
|
name: 'calc_add',
|
||||||
|
description: 'Add two numbers',
|
||||||
|
args: {a: {type: 'number', required: true}, b: {type: 'number', required: true}},
|
||||||
|
fn: (args: any) => String(args.a + args.b),
|
||||||
|
};
|
||||||
|
|
||||||
|
(globalThis as any).__scripts.claude = () => ({calls: [{tool: 'calc_add', args: {a: 2, b: 3}}], text: 'Result: 5'});
|
||||||
|
(globalThis as any).__scripts.gpt = () => ({calls: [{tool: 'calc_add', args: {a: 2, b: 3}}], text: 'Result: 5'});
|
||||||
|
|
||||||
|
const historyA: any[] = [], historyB: any[] = [];
|
||||||
|
const respA = await llm.ask('add 2 and 3', {model: 'claude', tools: [calc], history: historyA});
|
||||||
|
const respB = await llm.ask('add 2 and 3', {model: 'gpt', tools: [calc], history: historyB});
|
||||||
|
|
||||||
|
expect(respA).toBe('Result: 5');
|
||||||
|
expect(respB).toBe('Result: 5');
|
||||||
|
expect(providerLog.find(l => l.model === 'claude')!.tools).toContain('calc_add');
|
||||||
|
expect(providerLog.find(l => l.model === 'gpt')!.tools).toContain('calc_add');
|
||||||
|
|
||||||
|
// tool timing gets recomputed from real execution regardless of proto
|
||||||
|
for (const h of [historyA.find(h => h.name === 'calc_add'), historyB.find(h => h.name === 'calc_add')]) {
|
||||||
|
expect(h.content).toBe('5');
|
||||||
|
expect(typeof h.duration).toBe('number');
|
||||||
|
expect(typeof h.tps).toBe('number');
|
||||||
|
}
|
||||||
|
});
|
||||||
|
|
||||||
|
it('lets the same shared history flow across model + proto swaps with different system prompts', async () => {
|
||||||
|
const ai = makeAi({
|
||||||
|
claude: {proto: 'anthropic', token: 'x'},
|
||||||
|
gpt: {proto: 'openai', token: 'y', host: 'http://local'},
|
||||||
|
});
|
||||||
|
const llm = new LLM(ai);
|
||||||
|
const history: any[] = [];
|
||||||
|
|
||||||
|
(globalThis as any).__scripts.claude = () => ({text: 'Hi from claude'});
|
||||||
|
(globalThis as any).__scripts.gpt = () => ({text: 'Hi from gpt'});
|
||||||
|
|
||||||
|
const r1 = await llm.ask('hello', {model: 'claude', system: 'You are terse.', history});
|
||||||
|
const r2 = await llm.ask('follow up', {model: 'gpt', system: 'You are verbose.', history});
|
||||||
|
|
||||||
|
expect(r1).toBe('Hi from claude');
|
||||||
|
expect(r2).toBe('Hi from gpt');
|
||||||
|
expect(history.filter(h => h.role === 'assistant').map(h => h.content)).toEqual(['Hi from claude', 'Hi from gpt']);
|
||||||
|
expect(providerLog[0].system).toContain('You are terse.');
|
||||||
|
expect(providerLog[1].system).toContain('You are verbose.');
|
||||||
|
});
|
||||||
|
|
||||||
|
it('exposes MCP tools the same way no matter which proto backs the model', async () => {
|
||||||
|
const ai = makeAi({claude: {proto: 'anthropic', token: 'x'}, gpt: {proto: 'openai', token: 'y', host: 'http://local'}});
|
||||||
|
const llm = new LLM(ai);
|
||||||
|
const mcp = [{name: 'weather', host: 'http://mcp.local'}];
|
||||||
|
|
||||||
|
global.fetch = vi.fn(async (url: string, opts?: any) => {
|
||||||
|
if (url.endsWith('/tools')) {
|
||||||
|
return {json: async () => ({tools: [{name: 'lookup', description: 'Look up weather', inputSchema: {properties: {city: {type: 'string'}}, required: ['city']}}]})} as any;
|
||||||
|
}
|
||||||
|
const body = JSON.parse(opts.body);
|
||||||
|
return {json: async () => ({content: [{text: `Sunny in ${body.arguments.city}`}]})} as any;
|
||||||
|
}) as any;
|
||||||
|
|
||||||
|
for (const model of ['claude', 'gpt']) {
|
||||||
|
(globalThis as any).__scripts[model] = () => ({calls: [{tool: 'weather_lookup', args: {city: 'Rome'}}], text: 'done'});
|
||||||
|
const history: any[] = [];
|
||||||
|
await llm.ask('weather?', {model, mcp, history});
|
||||||
|
expect(history.find(h => h.name === 'weather_lookup')?.content).toBe('Sunny in Rome');
|
||||||
|
}
|
||||||
|
});
|
||||||
|
|
||||||
|
it('exposes and resolves skill documents identically across protos', async () => {
|
||||||
|
const ai = makeAi({claude: {proto: 'anthropic', token: 'x'}, gpt: {proto: 'openai', token: 'y', host: 'http://local'}});
|
||||||
|
const llm = new LLM(ai);
|
||||||
|
const skills = [{name: 'Onboarding', description: 'How to onboard a user', content: 'Step 1...'}];
|
||||||
|
|
||||||
|
for (const model of ['claude', 'gpt']) {
|
||||||
|
(globalThis as any).__scripts[model] = () => ({calls: [{tool: 'skill_read', args: {name: 'Onboarding'}}], text: 'done'});
|
||||||
|
const history: any[] = [];
|
||||||
|
await llm.ask('onboard me', {model, skills, history});
|
||||||
|
expect(history.find(h => h.name === 'skill_read')?.content).toContain('Step 1...');
|
||||||
|
}
|
||||||
|
});
|
||||||
|
|
||||||
|
it('delegate agent mutates the shared history directly and backfills the orchestrator response, across protos', async () => {
|
||||||
|
const ai = makeAi({claude: {proto: 'anthropic', token: 'x'}, gpt: {proto: 'openai', token: 'y', host: 'http://local'}});
|
||||||
|
const llm = new LLM(ai);
|
||||||
|
const history: any[] = [{role: 'user', content: 'research quantum computing'}];
|
||||||
|
const researcher = {name: 'researcher', system: 'You research topics.', delegate: true, model: 'gpt'};
|
||||||
|
|
||||||
|
(globalThis as any).__scripts.claude = () => ({calls: [{tool: 'agent_researcher', args: {}}], text: ''});
|
||||||
|
(globalThis as any).__scripts.gpt = () => ({text: 'Quantum computers use qubits.'});
|
||||||
|
|
||||||
|
const resp = await llm.ask('go', {model: 'claude', agents: [researcher], history});
|
||||||
|
|
||||||
|
expect(resp).toBe('Quantum computers use qubits.');
|
||||||
|
expect(history.some(h => h.role === 'assistant' && h.content === 'Quantum computers use qubits.')).toBe(true);
|
||||||
|
expect(history.find(h => h.name === 'agent_researcher')?.content).toBe('');
|
||||||
|
});
|
||||||
|
|
||||||
|
it('regular (non-delegate) subagent keeps its own isolated history separate from the parent, across protos', async () => {
|
||||||
|
const ai = makeAi({claude: {proto: 'anthropic', token: 'x'}, gpt: {proto: 'openai', token: 'y', host: 'http://local'}});
|
||||||
|
const llm = new LLM(ai);
|
||||||
|
const history: any[] = [];
|
||||||
|
const summarizer = {name: 'summarizer', system: 'You summarize text.', model: 'gpt'};
|
||||||
|
|
||||||
|
(globalThis as any).__scripts.claude = () => ({calls: [{tool: 'subagent_summarizer', args: {context: 'a long article', instructions: 'summarize it'}}], text: 'Summary: short version'});
|
||||||
|
(globalThis as any).__scripts.gpt = () => ({text: 'short version'});
|
||||||
|
|
||||||
|
const resp = await llm.ask('summarize this', {model: 'claude', agents: [summarizer], history});
|
||||||
|
|
||||||
|
expect(resp).toBe('Summary: short version');
|
||||||
|
expect(history.find(h => h.name === 'subagent_summarizer')?.content).toBe('short version');
|
||||||
|
// isolated history - subagent's own assistant turn never leaks into the parent
|
||||||
|
expect(history.some(h => h.role === 'assistant' && h.content === 'short version')).toBe(false);
|
||||||
|
});
|
||||||
|
});
|
||||||
256
tests/memory.spec.ts
Normal file
256
tests/memory.spec.ts
Normal file
@@ -0,0 +1,256 @@
|
|||||||
|
import {describe, it, expect, vi, beforeEach} from 'vitest';
|
||||||
|
import {MemoryManager, MemoryCache, rebuildGraph, Memory} from '../src/memory';
|
||||||
|
|
||||||
|
function makeMemory(overrides: Partial<Memory> = {}): Memory {
|
||||||
|
return {
|
||||||
|
name: 'Test/Doc',
|
||||||
|
description: '',
|
||||||
|
content: '',
|
||||||
|
embedding: [],
|
||||||
|
links: [],
|
||||||
|
backlinks: [],
|
||||||
|
...overrides,
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
|
function makeLLM() {
|
||||||
|
return {
|
||||||
|
embedding: vi.fn(async (_text: string) => [{embedding: [1, 0, 0]}]),
|
||||||
|
ask: vi.fn(async () => undefined),
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
|
describe('rebuildGraph', () => {
|
||||||
|
it('extracts [[WikiLinks]] from content, excluding self-links', () => {
|
||||||
|
const a = makeMemory({name: 'A', content: '[[B]] and [[A]] and [[C]]'});
|
||||||
|
const b = makeMemory({name: 'B', content: 'no links here'});
|
||||||
|
const mem = [a, b];
|
||||||
|
|
||||||
|
rebuildGraph(mem);
|
||||||
|
|
||||||
|
expect(a.links).toEqual(['B', 'C']);
|
||||||
|
expect(b.links).toEqual([]);
|
||||||
|
});
|
||||||
|
|
||||||
|
it('computes backlinks only for links that resolve to a real node', () => {
|
||||||
|
const a = makeMemory({name: 'A', content: '[[B]] [[Missing]]'});
|
||||||
|
const b = makeMemory({name: 'B', content: ''});
|
||||||
|
const mem = [a, b];
|
||||||
|
|
||||||
|
rebuildGraph(mem);
|
||||||
|
|
||||||
|
expect(b.backlinks).toEqual(['A']);
|
||||||
|
expect(mem.find(m => m.name === 'Missing')).toBeUndefined();
|
||||||
|
});
|
||||||
|
|
||||||
|
it('resets stale backlinks on every rebuild (no leftover from a removed link)', () => {
|
||||||
|
const a = makeMemory({name: 'A', content: '[[B]]'});
|
||||||
|
const b = makeMemory({name: 'B', content: ''});
|
||||||
|
const mem = [a, b];
|
||||||
|
rebuildGraph(mem);
|
||||||
|
expect(b.backlinks).toEqual(['A']);
|
||||||
|
|
||||||
|
a.content = 'no more links';
|
||||||
|
rebuildGraph(mem);
|
||||||
|
expect(b.backlinks).toEqual([]);
|
||||||
|
});
|
||||||
|
});
|
||||||
|
|
||||||
|
describe('MemoryCache', () => {
|
||||||
|
it('finds nearest neighbor by embedding via KD-tree search', () => {
|
||||||
|
const close = makeMemory({name: 'Close', embedding: [1, 0, 0]});
|
||||||
|
const far = makeMemory({name: 'Far', embedding: [0, 0, 1]});
|
||||||
|
const cache = new MemoryCache([close, far]);
|
||||||
|
|
||||||
|
const results = cache.search([1, 0, 0], 1);
|
||||||
|
|
||||||
|
expect(results[0].name).toBe('Close');
|
||||||
|
});
|
||||||
|
|
||||||
|
it('rebuilds the tree on add/update/remove', () => {
|
||||||
|
const cache = new MemoryCache([makeMemory({name: 'A', embedding: [1, 0, 0]})]);
|
||||||
|
cache.add(makeMemory({name: 'B', embedding: [0, 1, 0]}));
|
||||||
|
expect(cache.search([0, 1, 0], 1)[0].name).toBe('B');
|
||||||
|
|
||||||
|
cache.remove('B');
|
||||||
|
expect(cache.search([0, 1, 0], 1)[0]?.name).not.toBe('B');
|
||||||
|
});
|
||||||
|
});
|
||||||
|
|
||||||
|
describe('MemoryManager.forget', () => {
|
||||||
|
it('removes the node and recomputes backlinks for the rest of the graph', () => {
|
||||||
|
const llm = makeLLM();
|
||||||
|
const mgr = new MemoryManager(llm);
|
||||||
|
const a = makeMemory({name: 'A', content: '[[B]]'});
|
||||||
|
const b = makeMemory({name: 'B', content: '[[C]]'});
|
||||||
|
const c = makeMemory({name: 'C', content: ''});
|
||||||
|
const mem = [a, b, c];
|
||||||
|
rebuildGraph(mem);
|
||||||
|
expect(c.backlinks).toEqual(['B']);
|
||||||
|
|
||||||
|
const ok = mgr.forget('B', mem);
|
||||||
|
|
||||||
|
expect(ok).toBe(true);
|
||||||
|
expect(mem.find(m => m.name === 'B')).toBeUndefined();
|
||||||
|
expect(a.links).toEqual(['B']);
|
||||||
|
expect(c.backlinks).toEqual([]);
|
||||||
|
});
|
||||||
|
|
||||||
|
it('returns false for an unknown name', () => {
|
||||||
|
const mgr = new MemoryManager(makeLLM());
|
||||||
|
expect(mgr.forget('Nope', [makeMemory({name: 'A'})])).toBe(false);
|
||||||
|
});
|
||||||
|
});
|
||||||
|
|
||||||
|
describe('MemoryManager.recollect', () => {
|
||||||
|
it('orders vector matches first, then expands one hop via links', async () => {
|
||||||
|
const llm = makeLLM();
|
||||||
|
llm.embedding.mockResolvedValue([{embedding: [1, 0, 0]}]);
|
||||||
|
const mgr = new MemoryManager(llm);
|
||||||
|
|
||||||
|
const near = makeMemory({name: 'Near', embedding: [1, 0, 0], content: '[[Linked]]'});
|
||||||
|
const linked = makeMemory({name: 'Linked', embedding: [0, 0, 1], content: ''});
|
||||||
|
const far = makeMemory({name: 'Far', embedding: [0, 1, 0], content: ''});
|
||||||
|
const mem = [near, linked, far];
|
||||||
|
rebuildGraph(mem);
|
||||||
|
|
||||||
|
const result = await mgr.recollect('query', mem, 1, 1);
|
||||||
|
|
||||||
|
expect(result.map(r => r.name)).toEqual(['Near', 'Linked']);
|
||||||
|
});
|
||||||
|
|
||||||
|
it('returns [] when there are no memories', async () => {
|
||||||
|
const mgr = new MemoryManager(makeLLM());
|
||||||
|
expect(await mgr.recollect('q', [])).toEqual([]);
|
||||||
|
});
|
||||||
|
});
|
||||||
|
|
||||||
|
describe('MemoryManager.memorize (fast path)', () => {
|
||||||
|
let llm: ReturnType<typeof makeLLM>;
|
||||||
|
let mgr: MemoryManager;
|
||||||
|
|
||||||
|
beforeEach(() => {
|
||||||
|
llm = makeLLM();
|
||||||
|
mgr = new MemoryManager(llm);
|
||||||
|
});
|
||||||
|
|
||||||
|
it('pushes a pending tool message, then resolves it to links once facts land', async () => {
|
||||||
|
llm.ask.mockImplementation(async (_prompt: string, opts: any) => {
|
||||||
|
if (opts.tools) {
|
||||||
|
opts.tools[0].fn({destination: 'Projects/Oxide', facts: 'Uses a hybrid memory system'});
|
||||||
|
return undefined;
|
||||||
|
}
|
||||||
|
return {description: 'd', content: '# doc'};
|
||||||
|
});
|
||||||
|
|
||||||
|
const history: any[] = [{role: 'user', content: 'we use a hybrid memory system'}];
|
||||||
|
const touched = await mgr.memorize(history, [], {model: 'test'} as any);
|
||||||
|
|
||||||
|
const pending = history.find(h => h.name === 'memory_process');
|
||||||
|
expect(pending).toBeDefined();
|
||||||
|
expect(pending.content).toContain('[[Projects/Oxide]]');
|
||||||
|
expect(touched.map(t => t.name)).toEqual(['Projects/Oxide']);
|
||||||
|
});
|
||||||
|
|
||||||
|
it('creates a new node and appends facts under "## Facts" without calling the doc LLM', async () => {
|
||||||
|
llm.ask.mockImplementation(async (_prompt: string, opts: any) => {
|
||||||
|
if (opts.tools) opts.tools[0].fn({destination: 'People/Sarah', facts: 'Works at Acme, Likes hiking'});
|
||||||
|
return undefined;
|
||||||
|
});
|
||||||
|
|
||||||
|
const mem: Memory[] = [];
|
||||||
|
await mgr.memorize([{role: 'user', content: 'Sarah works at Acme and likes hiking'}] as any, mem, {model: 'test'} as any);
|
||||||
|
|
||||||
|
const node = mem.find(m => m.name === 'People/Sarah')!;
|
||||||
|
expect(node).toBeDefined();
|
||||||
|
expect(node.content).toContain('## Facts');
|
||||||
|
expect(node.content).toContain('- Works at Acme');
|
||||||
|
expect(node.content).toContain('- Likes hiking');
|
||||||
|
// doc reconciler LLM (schema call) should NOT have been awaited synchronously in this fast path assertion
|
||||||
|
});
|
||||||
|
|
||||||
|
it('routes "journal" destination to Journal/{weekMonday}', async () => {
|
||||||
|
llm.ask.mockImplementation(async (_prompt: string, opts: any) => {
|
||||||
|
if (opts.tools) opts.tools[0].fn({destination: 'journal', facts: 'Shipped v1'});
|
||||||
|
return undefined;
|
||||||
|
});
|
||||||
|
|
||||||
|
const mem: Memory[] = [];
|
||||||
|
const touched = await mgr.memorize([{role: 'user', content: 'shipped v1 today'}] as any, mem, {model: 'test'} as any);
|
||||||
|
|
||||||
|
expect(touched[0].name).toMatch(/^Journal\/\d{4}-\d{2}-\d{2}$/);
|
||||||
|
});
|
||||||
|
|
||||||
|
it('reports nothing to remember when no facts are extracted', async () => {
|
||||||
|
llm.ask.mockResolvedValue(undefined); // tools present but fn never called
|
||||||
|
|
||||||
|
const history: any[] = [{role: 'user', content: 'hey'}];
|
||||||
|
const touched = await mgr.memorize(history, [], {model: 'test'} as any);
|
||||||
|
|
||||||
|
expect(touched).toEqual([]);
|
||||||
|
expect(history.find(h => h.name === 'memory_process').content).toBe('Nothing worth remembering.');
|
||||||
|
});
|
||||||
|
|
||||||
|
it('returns [] and does nothing for an empty conversation', async () => {
|
||||||
|
const touched = await mgr.memorize([], [], {model: 'test'} as any);
|
||||||
|
expect(touched).toEqual([]);
|
||||||
|
expect(llm.ask).not.toHaveBeenCalled();
|
||||||
|
});
|
||||||
|
});
|
||||||
|
|
||||||
|
describe('MemoryManager reconcileVault', () => {
|
||||||
|
it('integrates the "## Facts" section via the doc LLM and removes it', async () => {
|
||||||
|
const llm = makeLLM();
|
||||||
|
llm.ask.mockResolvedValue({description: 'Tidy summary', content: '# Doc\n\nIntegrated fact.'});
|
||||||
|
const mgr = new MemoryManager(llm);
|
||||||
|
|
||||||
|
const node = makeMemory({
|
||||||
|
name: 'Projects/Oxide',
|
||||||
|
content: '---\nname: Projects/Oxide\n---\n\n# Doc\n\n## Facts\n- some raw fact\n',
|
||||||
|
});
|
||||||
|
const mem = [node];
|
||||||
|
|
||||||
|
await mgr.reconcileVault(mem, {model: 'test'} as any, 'all');
|
||||||
|
|
||||||
|
expect(node.content).not.toContain('## Facts');
|
||||||
|
expect(node.content).toContain('Integrated fact.');
|
||||||
|
expect(node.description).toBe('Tidy summary');
|
||||||
|
});
|
||||||
|
|
||||||
|
it('only targets docs with a pending Facts inbox when scope is "touched"', async () => {
|
||||||
|
const llm = makeLLM();
|
||||||
|
llm.ask.mockResolvedValue({description: 'd', content: '# clean'});
|
||||||
|
const mgr = new MemoryManager(llm);
|
||||||
|
|
||||||
|
const dirty = makeMemory({name: 'A', content: '## Facts\n- x'});
|
||||||
|
const clean = makeMemory({name: 'B', content: '# already tidy'});
|
||||||
|
await mgr.reconcileVault([dirty, clean], {model: 'test'} as any, 'touched');
|
||||||
|
|
||||||
|
expect(dirty.content).toContain('# clean'); // rewritten (frontmatter now wraps it)
|
||||||
|
expect(clean.content).toBe('# already tidy'); // untouched, never queued
|
||||||
|
});
|
||||||
|
});
|
||||||
|
|
||||||
|
describe('MemoryManager reconcile coalescing', () => {
|
||||||
|
it('coalesces a second call while one is in-flight: marks dirty, aborts, reuses the same task promise', () => {
|
||||||
|
const llm = makeLLM();
|
||||||
|
const abort = vi.fn();
|
||||||
|
let calls = 0;
|
||||||
|
llm.ask.mockImplementation(() => {
|
||||||
|
calls++;
|
||||||
|
const pending: any = new Promise(() => {}); // never resolves in this test
|
||||||
|
pending.abort = abort;
|
||||||
|
return pending;
|
||||||
|
});
|
||||||
|
const mgr: any = new MemoryManager(llm);
|
||||||
|
const node = makeMemory({name: 'Q', content: '# Q\n\n## Facts\n- f'});
|
||||||
|
const mem = [node];
|
||||||
|
|
||||||
|
const p1 = mgr.reconcile(node, mem, {model: 'test'});
|
||||||
|
const p2 = mgr.reconcile(node, mem, {model: 'test'});
|
||||||
|
|
||||||
|
expect(p2).toBe(p1); // same in-flight task, not a new queue entry
|
||||||
|
expect(abort).toHaveBeenCalledTimes(1); // second call aborted the in-flight request
|
||||||
|
expect(calls).toBe(1); // no second ask() fired synchronously — it'll rerun via the dirty loop
|
||||||
|
});
|
||||||
|
});
|
||||||
Reference in New Issue
Block a user