memory isolation fix

packages/memory-service/src/entities/extraction.js

@@ -64,7 +64,7 @@ async function embedEntity(entity) {
     return data.embedding;
 }
 
-async function extractAndStoreEntities(userMessage, aiResponse) {
+async function extractAndStoreEntities(userMessage, aiResponse, projectId=null) {
     console.log('[entities] Extraction triggered')
     try {
         // Fetch existing entities to guide the model toward consistent name/type pairs
@@ -109,6 +109,7 @@ async function extractAndStoreEntities(userMessage, aiResponse) {
                     name: entity.name,
                     type: entity.type,
                     notes: entity.notes,
+                    projectId: projectId ?? null,
                 }))
                 .catch(err => {
                     console.warn(`[entities] Failed to embed entity "${entity.name}":`, err.message);

packages/memory-service/src/episodic/index.js

@@ -98,7 +98,7 @@ function deleteSessionByExternalId(externalId) {
 
 // --Episodes --------------------------------------------------
 // Creates a new episode linked to a session, with user message, AI response, optional token count, and metadata
-async function createEpisode(sessionId, userMessage, aiResponse, tokenCount = null, metadata = null) {
+async function createEpisode(sessionId, userMessage, aiResponse, tokenCount = null, metadata = null, projectId=null) {
   const db = getDB();
 
   // Wrap insert + session touch in a transaction — both succeed or neither does
@@ -128,7 +128,7 @@ async function createEpisode(sessionId, userMessage, aiResponse, tokenCount = nu
     }))
     .catch(err => console.error(`Failed to embed episode ${episode.id}:`, err.message));
 
-  extractAndStoreEntities(userMessage, aiResponse)
+  extractAndStoreEntities(userMessage, aiResponse, projectId)
     .catch(err => console.error(`Failed to extract entities for episode ${episode.id}:`, err.message));
 
 

packages/memory-service/src/index.js

@@ -96,11 +96,11 @@ app.delete('/sessions/by-external/:externalId', (req, res) => {
 /************************************* */
 
 app.post('/episodes', async (req, res) => {
-  const { sessionId, userMessage, aiResponse, tokenCount, metadata } = req.body;
+  const { sessionId, userMessage, aiResponse, tokenCount, metadata, projectId } = req.body;
   if (!sessionId || !userMessage || !aiResponse) {
     return res.status(400).json({ error: 'sessionId, userMessage and aiResponse are required' });
   }
-  const episode = await episodic.createEpisode(sessionId, userMessage, aiResponse, tokenCount, metadata);
+  const episode = await episodic.createEpisode(sessionId, userMessage, aiResponse, tokenCount, metadata, projectId);
 
   console.log('[memory] create episode body:', {
     sessionId,

packages/orchestration-service/src/chat/index.js

@@ -107,10 +107,10 @@ async function getSemanticEpisodes(
   }
 }
 
-async function getRelevantEntities(userMessage) {
+async function getRelevantEntities(userMessage, projectId=null) {
   try {
     const vector = await embedding.embed(userMessage);
-    const results = await qdrant.searchEntities(vector);
+    const results = await qdrant.searchEntities(vector, { projectId });
     console.log(
       "[orchestration] Entity search results:",
       results.map((r) => ({ name: r.payload?.name, score: r.score })),
@@ -176,7 +176,7 @@ async function chat(externalId, userMessage, options = {}) {
   );
 
   // 3b. Entity Search
-  const entities = await getRelevantEntities(userMessage);
+  const entities = await getRelevantEntities(userMessage, session.project_id ?? null);
 
   // 4. Assemble prompt
   const prompt = buildPrompt(
@@ -196,6 +196,7 @@ async function chat(externalId, userMessage, options = {}) {
       userMessage,
       result.text,
       (result.evalCount || 0) + (result.promptEvalCount || 0),
+      session.project_id ?? null,
     )
     .catch((err) =>
       console.error(`[orchestration] Failed to save episode`, err.message),
@@ -262,7 +263,7 @@ async function chatStream(externalId, userMessage, onChunk, options = {}) {
       {semanticLimit, scoreThreshold }
     );
 
-    const entities = await getRelevantEntities(userMessage);
+    const entities = await getRelevantEntities(userMessage, session.project_id ?? null);
 
     const prompt = buildPrompt(
       recentEpisodes,
@@ -323,7 +324,7 @@ async function chatStream(externalId, userMessage, onChunk, options = {}) {
     console.log("[orchestration] final streamed text length:", fullText.length);
 
     if (fullText.trim()) {
-      await memory.createEpisode(session.id, userMessage, fullText, tokenCount);
+      await memory.createEpisode(session.id, userMessage, fullText, tokenCount, session.project_id ?? null);
     } else {
       console.warn(
         "[orchestration] Stream finished with no assistant text; episode not saved",

packages/orchestration-service/src/services/memory.js

@@ -29,11 +29,11 @@ async function getRecentEpisodes(sessionId, limit = EPISODIC.DEFAULT_SESSIONS_LI
     return res.json();
 }
 
-async function createEpisode(sessionId, userMessage, aiResponse, tokenCount) {
+async function createEpisode(sessionId, userMessage, aiResponse, tokenCount, projectId=null) {
     const res = await fetch(`${BASE_URL}/episodes`, {
         method: 'POST',
         headers: { 'Content-Type': 'application/json' },
-        body: JSON.stringify({ sessionId, userMessage, aiResponse, tokenCount })
+        body: JSON.stringify({ sessionId, userMessage, aiResponse, tokenCount, projectId })
     });
     if (!res.ok) throw new Error(`Failed to create episode: ${res.status} ${res.statusText}`);
     return res.json();

packages/orchestration-service/src/services/qdrant.js

@@ -33,9 +33,15 @@ async function searchEpisodes( vector, {limit = ORCHESTRATION.RECENT_EPISODE_LIM
     return data.result;
 }
 
-async function searchEntities(vector, { limit = 5, scoreThreshold = 0.6 } = {}) {
+async function searchEntities(vector, { limit = ORCHESTRATION.ENTITIES_LIMIT, scoreThreshold = ORCHESTRATION.ENTITIES_THRESHOLD, projectId = undefined } = {}) {
     const body = { vector, limit, score_threshold: scoreThreshold, with_payload: true };
 
+    if (projectId !== undefined) {
+        body.filter = {
+        must: [{ key: 'projectId', match: { value: projectId ?? null } }]
+        };
+    }
+
     const res = await fetch(
         `${BASE_URL}/collections/${COLLECTIONS.ENTITIES}/points/search`,
         {

packages/shared/src/config/constants.js

@@ -25,6 +25,8 @@ const ORCHESTRATION = {
     RECENT_EPISODE_LIMIT:   5,
     SEMANTIC_LIMIT:         5,
     SCORE_THRESHOLD:        0.75,
+    ENTITIES_LIMIT:         5,
+    ENTITIES_THRESHOLD:     0.75,
     TEMPERATURE:            0.7,
     CORS_ORIGIN:            'http://localhost:5173',
     SYSTEM_PROMPT:          `You are a helpful, context-aware AI assistant. You have access to memories of past conversations with the user. Use them to provide consistent, personalised responses.`