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utilityInference layer 2

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This commit is contained in:
Storme-bit
2026-08-17 07:41:41 -07:00
parent fab8f32395
commit 2bee4b23d6
4 changed files with 58 additions and 56 deletions
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packages/inference-service/src/utility.js
+1 -1
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@@ -23,7 +23,7 @@ async function utilityComplete({
model: UTILITY_MODEL,
messages,
stream: false,
...UTILITY(json && {format: 'json' }),
...(json && {format: 'json' }),
options: {
temperature: temperature ?? UTILITY.TEMPERATURE,
num_predict: maxTokens ?? UTILITY.MAX_TOKENS,
packages/memory-service/src/entities/extraction.js
+35 -55
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@@ -1,9 +1,7 @@
const semantic = require('../semantic')
const { getEnv, SERVICES, formatEpisodeText, ENTITIES, logger } = require('@nexusai/shared');
const { getEnv, SERVICES, formatEpisodeText, ENTITIES, logger, utilityInference } = require('@nexusai/shared');
const { upsertEntity, upsertRelationship, linkEntityToEpisode } = require('./index');
const EXTRACTION_URL = getEnv('EXTRACTION_URL', 'http://localhost:11434');
const EXTRACTION_MODEL = getEnv('EXTRACTION_MODEL', 'qwen2.5:3b'); // ChatML format — see buildExtractionPrompt
const EMBEDDING_SERVICE_URL = getEnv('EMBEDDING_SERVICE_URL', SERVICES.EMBEDDING_URL);
const ENTITY_TYPES = ENTITIES.TYPES;
@@ -28,10 +26,9 @@ function mentionedIn(name, haystack) {
return norm(haystack).includes(norm(name));
}
// NOTE: This prompt uses ChatML format (<|im_start|> / <|im_end|> tags), which is
// specific to qwen-family models. If EXTRACTION_MODEL is changed to a Llama-family
// or other model, this format will need to change — most alternatives use either
// plain text or [INST] / <<SYS>> tags. Silent degradation is likely if mismatched.
// Returns { system, user } for utilityInference. The model's prompt template
// (ChatML for qwen, etc.) is applied by Ollama via the inference service's
// /utility/complete route — no template tags belong in this file.
function buildExtractionPrompt(userMessage, aiResponse, knownEntities = []) {
const knownBlock = knownEntities.length > 0
? [
@@ -41,33 +38,30 @@ function buildExtractionPrompt(userMessage, aiResponse, knownEntities = []) {
].join('\n')
: '';
return [
'<|im_start|>system',
'You are a named entity and relationship extractor. You output only valid JSON.',
'<|im_end|>',
'<|im_start|>user',
'Read the conversation below and extract all named entities and the relationships between them.',
`Entity types: ${ENTITY_TYPES.join(', ')}`,
'Use "character" for any fictional, game, or media characters (e.g. characters from anime, games, books, TV shows, movies)',
'Use "person" only for real people',
'For each entity provide:',
' "name": short proper noun only (max 4 words)',
' "type": one of the valid types',
' "notes": one specific sentence about this entity based on the conversation',
'For relationships, use snake_case verb labels (e.g. works_on, manages, uses, knows, located_in, part_of, created_by).',
'Only include relationships between entities you have listed above.',
'The known-entities list below is ONLY for consistent spelling and types. Do NOT output an entity unless it actually appears in the conversation.',
'Return this exact JSON structure:',
'{ "entities": [{"name": "...", "type": "...", "notes": "..."}], "relationships": [{"from": "...", "fromType": "...", "to": "...", "toType": "...", "label": "...", "notes": "..."}] }',
'',
knownBlock,
'--- CONVERSATION ---',
`User: ${userMessage}`,
`Assistant: ${aiResponse}`,
'--- END CONVERSATION ---',
'<|im_end|>',
'<|im_start|>assistant',
].join('\n');
return {
system: 'You are a named entity and relationship extractor. You output only valid JSON.',
user: [
'Read the conversation below and extract all named entities and the relationships between them.',
`Entity types: ${ENTITY_TYPES.join(', ')}`,
'Use "character" for any fictional, game, or media characters (e.g. characters from anime, games, books, TV shows, movies)',
'Use "person" only for real people',
'For each entity provide:',
' "name": short proper noun only (max 4 words)',
' "type": one of the valid types',
' "notes": one specific sentence about this entity based on the conversation',
'For relationships, use snake_case verb labels (e.g. works_on, manages, uses, knows, located_in, part_of, created_by).',
'Only include relationships between entities you have listed above.',
'The known-entities list below is ONLY for consistent spelling and types. Do NOT output an entity unless it actually appears in the conversation.',
'Return this exact JSON structure:',
'{ "entities": [{"name": "...", "type": "...", "notes": "..."}], "relationships": [{"from": "...", "fromType": "...", "to": "...", "toType": "...", "label": "...", "notes": "..."}] }',
'',
knownBlock,
'--- CONVERSATION ---',
`User: ${userMessage}`,
`Assistant: ${aiResponse}`,
'--- END CONVERSATION ---',
].join('\n'),
};
}
async function embedEntity(entity) {
@@ -91,30 +85,16 @@ async function extractAndStoreEntities(userMessage, aiResponse, episodeId=null,
// Fetch existing entities to guide the model toward consistent name/type pairs
const db = require('../db').getDB();
const knownEntities = db.prepare(`SELECT name, type FROM entities ORDER BY rowid DESC LIMIT 20`).all();
const prompt = buildExtractionPrompt(userMessage, aiResponse, knownEntities);
const { system, user } = buildExtractionPrompt(userMessage, aiResponse, knownEntities);
const res = await fetch(`${EXTRACTION_URL}/api/generate`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
model: EXTRACTION_MODEL,
prompt: prompt,
stream: false,
format: 'json',
options: {
temperature: ENTITIES.TEMPERATURE,
num_predict: ENTITIES.NUM_PREDICT,
},
}),
signal: AbortSignal.timeout(60_000),
const raw = await utilityInference({
system,
user,
json: true,
temperature: ENTITIES.TEMPERATURE,
maxTokens: ENTITIES.NUM_PREDICT,
});
if (!res.ok) throw new Error(`Ollama responded ${res.status}`);
const data = await res.json();
const raw = data.response?.trim() ?? '';
const jsonMatch = raw.match(/\{[\s\S]*\}/);
if (!jsonMatch) {
logger.warn('[entities] No JSON object found in response');
packages/shared/src/index.js
+2
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@@ -17,6 +17,7 @@ const {
} = require('./config/constants');
const {parseRow, formatEpisodeText, isTrivialTurn} = require('./utils')
const logger = require('./utils/logger');
const utilityInference = require('./utils/utilityInference');
module.exports = {
getEnv,
@@ -38,4 +39,5 @@ module.exports = {
logger,
RETRIEVAL,
UTILITY,
utilityInference,
};
packages/shared/src/utils/utilityInference.js
+20
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@@ -0,0 +1,20 @@
const { getEnv } = require('../config/env');
const { SERVICES } = require('../config/constants');
// Client for the inference service's /utility/complete route.
// Resolved at call time (not module load) so each service's .env applies.
async function utilityInference({ system, user, json = false, temperature, maxTokens }) {
const base = getEnv('INFERENCE_SERVICE_URL', SERVICES.INFERENCE_URL);
const res = await fetch(`${base}/utility/complete`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ system, user, json, temperature, maxTokens }),
});
if (!res.ok) throw new Error(`Utility inference error: ${res.status}`);
const data = await res.json();
return data.text;
}
module.exports = { utilityInference };