Memory refinement

src/llm.ts

@@ -1,4 +1,4 @@
-import {snakeCase} from '@ztimson/utils';
+import {clean, snakeCase} from '@ztimson/utils';
 import {AbortablePromise, Ai} from './ai.ts';
 import {Anthropic} from './antrhopic.ts';
 import {OpenAi} from './open-ai.ts';
@@ -132,7 +132,7 @@ class LLM {
 			return {
 				name: toolName,
 				description: `${a.delegate ? 'Delegate to ' : ''}Subagent: ${a.description || a.name}`,
-				args: <any>({
+				args: clean<any>({
 					context: !a.delegate ? {type: 'string', description: 'Summary of related messages, samples, files, etc...', required: true} : undefined,
 					instructions: {type: 'string', description: 'Detailed instructions for subagent to complete', required: true},
 				}),
@@ -143,8 +143,6 @@ class LLM {
 						.map(name => allAgents.find(x => x.name === name))
 						.filter((x): x is Agent => !!x && x.name !== a.name);
 
-					// Delegate continues the SAME live conversation - no new user turn needed,
-					// `history` is always current (shared, mutated in place) by the time this runs
 					const q = a.delegate ? '' : `${args.instructions}${args.context ? `\n\n<context>${args.context}</context>` : ''}`;
 
 					const request = this.ask(q, {
@@ -218,7 +216,7 @@ ${a.system}`,
 		if(!skills?.length) return {prompt: '', tools: []};
 		const list = skills.map(s => `- ${s.name}: ${s.description}`).join('\n');
 		return {
-			prompt: `You have access to the following skill documents, use \`read_skill\` to access them:\n${list}`,
+			prompt: `You have access to the following skill documents, whenever there is overlap between a question and a skill file, use \`skill_read\` to get instructions and background knowledge:\n${list}`,
 			tools: [{
 				name: 'skill_read',
 				description: 'Read the full content of a skill/knowledge document',
@@ -318,19 +316,30 @@ ${a.system}`,
 							} else listed.push(r);
 						}
 
-						prompts.unshift(`You have access to the following memory files:
-${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')}
+						prompts.unshift(`You have a background memory process which has prefetched relevant information${mem.update ? ' and will create new memories from this conversation' : ''} for you
+Assume it is perfect and never mention this process to anyone ever
+Always use your memories to craft a personalized response, they contain links / [[wiki links]] which you use navigate between them
+${mem.tool ? `You can access memory files via the \`memory_search\` and \`memory_recall\` tools
+When you need information about the user, \`memory_recall\` \`People/User\` before asking (fetch if not included bellow)
+When you need information not provided, attempt 1-3 \`memory_search\` calls with unique queries before asking` : ''}
+
 ${preloaded.length ? `
-Relevant memories have been preloaded:
-${preloaded.map(r => `
-**${r.name}**
-${r.description}
+Prefetched Memories (Most relevant first):
+
+${preloaded.map(r => `Memory: ${r.name}
+Description: ${r.description}
+Linked: ${[r.links, ...r.backlinks].join(', ')}
+\`\`\`
 ${r.content}
-`).join('\n---\n')}
-` : ''}${listed.length ? `
-Additional relevant memories (use \`memory_recall\`):
-${listed.map(r => r.name).join(', ')}
-` : ''}`.trim());
+\`\`\``).join('\n\n')}` : ''}
+
+${mem.tool && listed.length ? listed.map(r => `Memory: ${r.name}
+Description: ${r.description}
+Linked: ${[r.links, ...r.backlinks].join(', ')}
+<!-- Truncated -->`).join('\n\n') : ''}
+
+${mem.tool ? `Full memory list:
+${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')}` : ''}`.trim())
 					}
 					if(mem.tool) tools.push(this.memoryManager.tools.read(mem.memory));
 				}
@@ -374,14 +383,6 @@ ${listed.map(r => r.name).join(', ')}
 		return Object.assign(promise, {abort});
 	}
 
-	/**
-	 * Digest full conversation history into memory documents.
-	 * Call on session end to persist the conversation.
-	 */
-	async updateMemory(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<Memory[]> {
-		return this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options});
-	}
-
 	/**
 	 * Compress chat history to reduce context size
 	 * @param {LLMMessage[]} history Chatlog that will be compressed
@@ -561,6 +562,14 @@ ${listed.map(r => r.name).join(', ')}
 		};
 	}
 
+	/**
+	 * Digest full conversation history into memory documents.
+	 * Call on session end to persist the conversation.
+	 */
+	async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<Memory[]> {
+		return this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options});
+	}
+
 	/**
 	 * Create a summary of some text
 	 * @param {string} text Text to summarize