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adding in entity extraction layer with semantic search enabled

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This commit is contained in:
Storme-bit
2026-04-17 06:18:39 -07:00
parent 902725b7f7
commit 06d7031e44
2 changed files with 45 additions and 4 deletions
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30
packages/orchestration-service/src/chat/index.js
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@@ -7,9 +7,17 @@ const { ORCHESTRATION } = require("@nexusai/shared");
const { RECENT_EPISODE_LIMIT, SEMANTIC_LIMIT, SCORE_THRESHOLD, SYSTEM_PROMPT } =
ORCHESTRATION;
function buildPrompt(recentEpisodes, semanticEpisodes, userMessage) {
function buildPrompt(recentEpisodes, semanticEpisodes, entities, userMessage) {
const parts = [SYSTEM_PROMPT];
if (entities.length > 0) {
parts.push('Here is what you know about entities relevant to this conversation:');
for (const e of entities) {
parts.push(`- ${e.name} (${e.type}): ${e.notes}`);
}
parts.push('---');
}
if (semanticEpisodes.length > 0) {
parts.push("Here are some relevant memories from earlier conversations:");
for (const ep of semanticEpisodes) {
@@ -97,6 +105,17 @@ async function getSemanticEpisodes(
}
}
async function getRelevantEntities(userMessage) {
try {
const vector = await embedding.embed(userMessage);
const results = await qdrant.searchEntities(vector);
return results.map(r => r.payload).filter(Boolean);
} catch (err) {
console.warn('[orchestration] Entity search failed, continuing without:', err.message);
return [];
}
}
async function chat(externalId, userMessage, options = {}) {
// 1. Resolve or create session
let session = await memory.getSessionByExternalId(externalId);
@@ -135,8 +154,11 @@ if (session.project_id) {
projectSessionIds
);
// 3b. Entity Search
const entities = await getRelevantEntities(userMessage)
// 4. Assemble prompt
const prompt = buildPrompt(recentEpisodes, semanticEpisodes, userMessage);
const prompt = buildPrompt(recentEpisodes, semanticEpisodes, entities, userMessage);
// 5. Run inference
const result = await inference.complete(prompt, options);
@@ -210,7 +232,9 @@ if (session.project_id) {
projectSessionIds
);
const prompt = buildPrompt(recentEpisodes, semanticEpisodes, userMessage);
const entities = await getRelevantEntities(userMessage);
const prompt = buildPrompt(recentEpisodes, semanticEpisodes, entities, userMessage);
const res = await inference.completeStream(prompt, options);
let fullText = "";