fix: remove console logs and gpt-5 to test

apps/webapp/app/lib/batch/providers/openai.ts

@@ -16,6 +16,8 @@ export class OpenAIBatchProvider extends BaseBatchProvider {
   providerName = "openai";
   supportedModels = [
     "gpt-4.1-2025-04-14",
+    "gpt-5-mini-2025-08-07",
+    "gpt-5-2025-08-07",
     "gpt-4.1-mini-2025-04-14",
     "gpt-4.1-nano-2025-04-14",
     "gpt-4o*",

apps/webapp/app/lib/model.server.ts

@@ -32,6 +32,8 @@ export async function makeModelCall(
   switch (model) {
     case "gpt-4.1-2025-04-14":
     case "gpt-4.1-mini-2025-04-14":
+    case "gpt-5-mini-2025-08-07":
+    case "gpt-5-2025-08-07":
     case "gpt-4.1-nano-2025-04-14":
       modelInstance = openai(model, { ...options });
       break;

apps/webapp/app/services/knowledgeGraph.server.ts

@@ -41,10 +41,7 @@ import {
 } from "./graphModels/statement";
 import { getEmbedding, makeModelCall } from "~/lib/model.server";
 import { runQuery } from "~/lib/neo4j.server";
-import {
+import { Apps, getNodeTypesString } from "~/utils/presets/nodes";
-  Apps,
-  getNodeTypesString,
-} from "~/utils/presets/nodes";
 import { normalizePrompt, normalizeDocumentPrompt } from "./prompts";
 import { type PrismaClient } from "@prisma/client";
 
@@ -312,7 +309,6 @@ export class KnowledgeGraphService {
       const expandedTime = Date.now();
       logger.log(`Processed entities in ${expandedTime - extractedTime} ms`);
 
-      console.log(extractedNodes.map((e) => e.name));
       // Step 4: Statement Extrraction - Extract statements (triples) instead of direct edges
       const extractedStatements = await this.extractStatements(
         episode,
@@ -431,7 +427,7 @@ export class KnowledgeGraphService {
     };
 
     // Get the unified entity extraction prompt
-    const extractionMode = episode.sessionId ? 'conversation' : 'document';
+    const extractionMode = episode.sessionId ? "conversation" : "document";
     const messages = extractEntities(context, extractionMode);
 
     let responseText = "";
@@ -451,7 +447,7 @@ export class KnowledgeGraphService {
       // Batch generate embeddings for entity names
       const entityNames = extractedEntities.map((entity: any) => entity.name);
       const nameEmbeddings = await Promise.all(
-        entityNames.map((name: string) => this.getEmbedding(name))
+        entityNames.map((name: string) => this.getEmbedding(name)),
       );
 
       entities = extractedEntities.map((entity: any, index: number) => ({
@@ -509,8 +505,6 @@ export class KnowledgeGraphService {
       responseText = text;
     });
 
-    console.log(responseText);
-
     const outputMatch = responseText.match(/<output>([\s\S]*?)<\/output>/);
     if (outputMatch && outputMatch[1]) {
       responseText = outputMatch[1].trim();
@@ -522,7 +516,7 @@ export class KnowledgeGraphService {
     const extractedTriples: ExtractedTripleData[] =
       JSON.parse(responseText || "{}").edges || [];
 
-    console.log(`extracted triples length: ${extractedTriples.length}`)
+    console.log(`extracted triples length: ${extractedTriples.length}`);
 
     // Create maps to deduplicate entities by name within this extraction
     const predicateMap = new Map<string, EntityNode>();
@@ -575,11 +569,11 @@ export class KnowledgeGraphService {
       (triple: ExtractedTripleData, tripleIndex: number) => {
         // Find the subject and object nodes by matching name (type-free approach)
         const subjectNode = allEntities.find(
-          (node) => node.name.toLowerCase() === triple.source.toLowerCase()
+          (node) => node.name.toLowerCase() === triple.source.toLowerCase(),
         );
 
         const objectNode = allEntities.find(
-          (node) => node.name.toLowerCase() === triple.target.toLowerCase()
+          (node) => node.name.toLowerCase() === triple.target.toLowerCase(),
         );
 
         // Get the deduplicated predicate node
@@ -633,8 +627,6 @@ export class KnowledgeGraphService {
     return triples.filter(Boolean) as Triple[];
   }
 
-
-
   /**
    * Resolve extracted nodes to existing nodes or create new ones
    */

apps/webapp/app/services/search.server.ts

@@ -96,7 +96,7 @@ export class SearchService {
     this.updateRecallCount(userId, episodes, filteredResults);
 
     return {
-      episodes: episodes.map((episode) => episode.content),
+      episodes: episodes.map((episode) => episode.originalContent),
       facts: filteredResults.map((statement) => ({
         fact: statement.fact,
         validAt: statement.validAt,

apps/webapp/app/trigger/chat/stream-utils.ts

@@ -177,6 +177,8 @@ export async function* generate(
 
       case "gpt-4.1-2025-04-14":
       case "gpt-4.1-mini-2025-04-14":
+      case "gpt-5-mini-2025-08-07":
+      case "gpt-5-2025-08-07":
       case "gpt-4.1-nano-2025-04-14":
         if (!openaiKey) {
           throw new Error("No OpenAI API key found. Set OPENAI_API_KEY");

apps/webapp/app/utils/mcp/memory.ts

@@ -52,17 +52,20 @@ const IngestSchema = {
 export const memoryTools = [
   {
     name: "memory_ingest",
-    description: "AUTOMATICALLY invoke after completing interactions. Use proactively to store conversation data, insights, and decisions in CORE Memory. Essential for maintaining continuity across sessions. **Purpose**: Store information for future reference. **Required**: Provide the message content to be stored. **Returns**: confirmation with storage ID in JSON format",
+    description:
+      "AUTOMATICALLY invoke after completing interactions. Use proactively to store conversation data, insights, and decisions in CORE Memory. Essential for maintaining continuity across sessions. **Purpose**: Store information for future reference. **Required**: Provide the message content to be stored. **Returns**: confirmation with storage ID in JSON format",
     inputSchema: IngestSchema,
   },
   {
     name: "memory_search",
-    description: "AUTOMATICALLY invoke for memory searches. Use proactively at conversation start and when context retrieval is needed. Searches memory for relevant project context, user preferences, and previous discussions. **Purpose**: Retrieve previously stored information based on query terms. **Required**: Provide a search query in third person perspective. **Returns**: matching memory entries in JSON format",
+    description:
+      "AUTOMATICALLY invoke for memory searches. Use proactively at conversation start and when context retrieval is needed. Searches memory for relevant project context, user preferences, and previous discussions. **Purpose**: Retrieve previously stored information based on query terms. **Required**: Provide a search query in third person perspective. **Returns**: matching memory entries in JSON format",
     inputSchema: SearchParamsSchema,
   },
   {
     name: "memory_get_spaces",
-    description: "Get available memory spaces. **Purpose**: Retrieve list of memory organization spaces. **Required**: No required parameters. **Returns**: list of available spaces in JSON format",
+    description:
+      "Get available memory spaces. **Purpose**: Retrieve list of memory organization spaces. **Required**: No required parameters. **Returns**: list of available spaces in JSON format",
     inputSchema: {
       type: "object",
       properties: {
@@ -76,7 +79,8 @@ export const memoryTools = [
   },
   {
     name: "get_user_profile",
-    description: "Get the user's core profile and preferences for personalized interactions. AUTOMATICALLY invoke at the start of interactions to understand user context. **Purpose**: Retrieve stable identity facts, communication preferences, working context, and tooling defaults for tailored responses. **Required**: No required parameters. **Returns**: User profile data in JSON format.",
+    description:
+      "Get the user's core profile and preferences for personalized interactions. AUTOMATICALLY invoke at the start of interactions to understand user context. **Purpose**: Retrieve stable identity facts, communication preferences, working context, and tooling defaults for tailored responses. **Required**: No required parameters. **Returns**: User profile data in JSON format.",
     inputSchema: {
       type: "object",
       properties: {
@@ -87,7 +91,7 @@ export const memoryTools = [
         },
       },
     },
-  }
+  },
 ];
 
 // Function to call memory tools based on toolName
@@ -127,10 +131,8 @@ export async function callMemoryTool(
 // Handler for user_context
 async function handleUserProfile(userId: string) {
   try {
+    const space = await spaceService.getSpaceByName("Profile", userId);
 
-    const space = await spaceService.getSpaceByName("Profile", userId)
-
-    console.log(space?.summary)
     return {
       content: [
         {