Scope all DB objects to chatbot PostgreSQL schema

- drizzle/schema.ts: use pgSchema("chatbot") for all tables and enums
- drizzle.config.ts: add schemaFilter: ["chatbot"]
- server/db.ts: set search_path=chatbot,public on connection

DBA setup (run once on DB server):
  CREATE SCHEMA chatbot;
  GRANT ALL ON SCHEMA chatbot TO chatbot_user;

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

drizzle.config.ts

@@ -12,4 +12,5 @@ export default defineConfig({
   dbCredentials: {
     url: connectionString,
   },
+  schemaFilter: ["chatbot"],
 });

drizzle/schema.ts

@@ -2,258 +2,264 @@ import {
   boolean,
   integer,
   jsonb,
-  pgEnum,
-  pgTable,
+  pgSchema,
   serial,
   text,
   timestamp,
   varchar,
 } from "drizzle-orm/pg-core";
 
-// ── Enum definitions ─────────────────────────────────────────────────────────
+// ── Schema ───────────────────────────────────────────────────────────────────
+// All chatbot objects live in the "chatbot" PostgreSQL schema.
+// DBA setup (run once):
+//   CREATE SCHEMA chatbot;
+//   GRANT ALL ON SCHEMA chatbot TO chatbot_user;
+export const chatbotSchema = pgSchema("chatbot");
 
-export const roleEnum = pgEnum("role", ["user", "agent", "admin"]);
-export const conversationStatusEnum = pgEnum("conversation_status", ["active", "escalated", "resolved", "closed"]);
-export const senderEnum = pgEnum("sender", ["visitor", "bot", "agent"]);
-export const workflowNodeTypeEnum = pgEnum("workflow_node_type", [
+// ── Enums (scoped to chatbot schema) ─────────────────────────────────────────
+
+export const roleEnum               = chatbotSchema.enum("role",                ["user", "agent", "admin"]);
+export const conversationStatusEnum = chatbotSchema.enum("conversation_status", ["active", "escalated", "resolved", "closed"]);
+export const senderEnum             = chatbotSchema.enum("sender",              ["visitor", "bot", "agent"]);
+export const workflowNodeTypeEnum   = chatbotSchema.enum("workflow_node_type",  [
   "greeting", "intent", "response", "condition", "escalation",
   "action", "end", "customer_data", "sales_order", "guardrail",
 ]);
-export const inviteStatusEnum = pgEnum("invite_status", ["pending", "accepted", "expired", "revoked"]);
-export const suggestionStatusEnum = pgEnum("suggestion_status", ["pending", "approved", "declined", "waiting"]);
-export const eventTypeEnum = pgEnum("event_type", [
+export const inviteStatusEnum       = chatbotSchema.enum("invite_status",       ["pending", "accepted", "expired", "revoked"]);
+export const suggestionStatusEnum   = chatbotSchema.enum("suggestion_status",   ["pending", "approved", "declined", "waiting"]);
+export const eventTypeEnum          = chatbotSchema.enum("event_type",          [
   "session_start", "message_sent", "message_received",
   "intent_detected", "flow_triggered", "escalated",
   "resolved_by_bot", "resolved_by_agent", "abandoned",
   "button_clicked", "feedback_positive", "feedback_negative",
 ]);
-export const sourceTypeEnum = pgEnum("source_type", ["url", "file", "qa_pair", "api"]);
-export const sourceStatusEnum = pgEnum("source_status", ["active", "inactive", "syncing", "error"]);
-export const httpMethodEnum = pgEnum("http_method", ["GET", "POST", "PUT", "DELETE"]);
+export const sourceTypeEnum         = chatbotSchema.enum("source_type",         ["url", "file", "qa_pair", "api"]);
+export const sourceStatusEnum       = chatbotSchema.enum("source_status",       ["active", "inactive", "syncing", "error"]);
+export const httpMethodEnum         = chatbotSchema.enum("http_method",         ["GET", "POST", "PUT", "DELETE"]);
 
-// ── Tables ───────────────────────────────────────────────────────────────────
+// ── Tables (all inside chatbot schema) ───────────────────────────────────────
 
 /**
  * Core user table backing auth flow.
  */
-export const users = pgTable("users", {
-  id: serial("id").primaryKey(),
-  openId: varchar("openId", { length: 64 }).notNull().unique(),
-  name: text("name"),
-  email: varchar("email", { length: 320 }),
-  loginMethod: varchar("loginMethod", { length: 64 }),
-  role: roleEnum("role").default("user").notNull(),
-  createdAt: timestamp("createdAt").defaultNow().notNull(),
-  updatedAt: timestamp("updatedAt").defaultNow().notNull(),
+export const users = chatbotSchema.table("users", {
+  id:           serial("id").primaryKey(),
+  openId:       varchar("openId",       { length: 64  }).notNull().unique(),
+  name:         text("name"),
+  email:        varchar("email",        { length: 320 }),
+  loginMethod:  varchar("loginMethod",  { length: 64  }),
+  role:         roleEnum("role").default("user").notNull(),
+  createdAt:    timestamp("createdAt").defaultNow().notNull(),
+  updatedAt:    timestamp("updatedAt").defaultNow().notNull(),
   lastSignedIn: timestamp("lastSignedIn").defaultNow().notNull(),
   passwordHash: varchar("passwordHash", { length: 255 }),
 });
 
-export type User = typeof users.$inferSelect;
+export type User       = typeof users.$inferSelect;
 export type InsertUser = typeof users.$inferInsert;
 
 /**
  * Password reset tokens — for forgot password flow.
  */
-export const passwordResetTokens = pgTable("password_reset_tokens", {
-  id: serial("id").primaryKey(),
-  userId: integer("userId").notNull(),
-  token: varchar("token", { length: 64 }).notNull().unique(),
+export const passwordResetTokens = chatbotSchema.table("password_reset_tokens", {
+  id:        serial("id").primaryKey(),
+  userId:    integer("userId").notNull(),
+  token:     varchar("token", { length: 64 }).notNull().unique(),
   expiresAt: timestamp("expiresAt").notNull(),
-  usedAt: timestamp("usedAt"),
+  usedAt:    timestamp("usedAt"),
   createdAt: timestamp("createdAt").defaultNow().notNull(),
 });
 
-export type PasswordResetToken = typeof passwordResetTokens.$inferSelect;
+export type PasswordResetToken       = typeof passwordResetTokens.$inferSelect;
 export type InsertPasswordResetToken = typeof passwordResetTokens.$inferInsert;
 
 /**
  * Chat conversations — each visitor session creates one conversation.
  */
-export const conversations = pgTable("conversations", {
-  id: serial("id").primaryKey(),
-  sessionId: varchar("sessionId", { length: 64 }).notNull().unique(),
-  visitorName: varchar("visitorName", { length: 255 }),
-  visitorEmail: varchar("visitorEmail", { length: 320 }),
-  customerId: varchar("customerId", { length: 64 }),
-  salesRep: varchar("salesRep", { length: 255 }),
-  status: conversationStatusEnum("status").default("active").notNull(),
+export const conversations = chatbotSchema.table("conversations", {
+  id:              serial("id").primaryKey(),
+  sessionId:       varchar("sessionId",    { length: 64  }).notNull().unique(),
+  visitorName:     varchar("visitorName",  { length: 255 }),
+  visitorEmail:    varchar("visitorEmail", { length: 320 }),
+  customerId:      varchar("customerId",   { length: 64  }),
+  salesRep:        varchar("salesRep",     { length: 255 }),
+  status:          conversationStatusEnum("status").default("active").notNull(),
   assignedAgentId: integer("assignedAgentId"),
-  metadata: jsonb("metadata"),
-  createdAt: timestamp("createdAt").defaultNow().notNull(),
-  updatedAt: timestamp("updatedAt").defaultNow().notNull(),
+  metadata:        jsonb("metadata"),
+  createdAt:       timestamp("createdAt").defaultNow().notNull(),
+  updatedAt:       timestamp("updatedAt").defaultNow().notNull(),
 });
 
-export type Conversation = typeof conversations.$inferSelect;
+export type Conversation       = typeof conversations.$inferSelect;
 export type InsertConversation = typeof conversations.$inferInsert;
 
 /**
  * Chat messages — each message belongs to a conversation.
  */
-export const messages = pgTable("messages", {
-  id: serial("id").primaryKey(),
+export const messages = chatbotSchema.table("messages", {
+  id:             serial("id").primaryKey(),
   conversationId: integer("conversationId").notNull(),
-  sender: senderEnum("sender").notNull(),
-  content: text("content").notNull(),
-  metadata: jsonb("metadata"),
-  createdAt: timestamp("createdAt").defaultNow().notNull(),
+  sender:         senderEnum("sender").notNull(),
+  content:        text("content").notNull(),
+  metadata:       jsonb("metadata"),
+  createdAt:      timestamp("createdAt").defaultNow().notNull(),
 });
 
-export type Message = typeof messages.$inferSelect;
+export type Message       = typeof messages.$inferSelect;
 export type InsertMessage = typeof messages.$inferInsert;
 
 /**
  * Workflow nodes — each node in the chatbot conversation flow.
  */
-export const workflowNodes = pgTable("workflow_nodes", {
-  id: serial("id").primaryKey(),
-  workflowId: varchar("workflowId", { length: 64 }).notNull(),
-  nodeId: varchar("nodeId", { length: 64 }).notNull(),
-  type: workflowNodeTypeEnum("type").notNull(),
-  label: varchar("label", { length: 255 }).notNull(),
-  config: jsonb("config"),
-  positionX: integer("positionX").default(0).notNull(),
-  positionY: integer("positionY").default(0).notNull(),
-  createdAt: timestamp("createdAt").defaultNow().notNull(),
-  updatedAt: timestamp("updatedAt").defaultNow().notNull(),
+export const workflowNodes = chatbotSchema.table("workflow_nodes", {
+  id:         serial("id").primaryKey(),
+  workflowId: varchar("workflowId", { length: 64  }).notNull(),
+  nodeId:     varchar("nodeId",     { length: 64  }).notNull(),
+  type:       workflowNodeTypeEnum("type").notNull(),
+  label:      varchar("label",      { length: 255 }).notNull(),
+  config:     jsonb("config"),
+  positionX:  integer("positionX").default(0).notNull(),
+  positionY:  integer("positionY").default(0).notNull(),
+  createdAt:  timestamp("createdAt").defaultNow().notNull(),
+  updatedAt:  timestamp("updatedAt").defaultNow().notNull(),
 });
 
-export type WorkflowNode = typeof workflowNodes.$inferSelect;
+export type WorkflowNode       = typeof workflowNodes.$inferSelect;
 export type InsertWorkflowNode = typeof workflowNodes.$inferInsert;
 
 /**
  * Workflow edges — connections between nodes.
  */
-export const workflowEdges = pgTable("workflow_edges", {
-  id: serial("id").primaryKey(),
-  workflowId: varchar("workflowId", { length: 64 }).notNull(),
-  sourceNodeId: varchar("sourceNodeId", { length: 64 }).notNull(),
-  targetNodeId: varchar("targetNodeId", { length: 64 }).notNull(),
-  label: varchar("label", { length: 255 }),
-  condition: jsonb("condition"),
-  createdAt: timestamp("createdAt").defaultNow().notNull(),
+export const workflowEdges = chatbotSchema.table("workflow_edges", {
+  id:           serial("id").primaryKey(),
+  workflowId:   varchar("workflowId",   { length: 64  }).notNull(),
+  sourceNodeId: varchar("sourceNodeId", { length: 64  }).notNull(),
+  targetNodeId: varchar("targetNodeId", { length: 64  }).notNull(),
+  label:        varchar("label",        { length: 255 }),
+  condition:    jsonb("condition"),
+  createdAt:    timestamp("createdAt").defaultNow().notNull(),
 });
 
-export type WorkflowEdge = typeof workflowEdges.$inferSelect;
+export type WorkflowEdge       = typeof workflowEdges.$inferSelect;
 export type InsertWorkflowEdge = typeof workflowEdges.$inferInsert;
 
 /**
  * Invitations — track sent invitations and their acceptance status.
  */
-export const invitations = pgTable("invitations", {
-  id: serial("id").primaryKey(),
-  email: varchar("email", { length: 320 }).notNull(),
-  role: roleEnum("role").default("agent").notNull(),
-  token: varchar("token", { length: 64 }).notNull().unique(),
-  status: inviteStatusEnum("status").default("pending").notNull(),
-  invitedById: integer("invitedById").notNull(),
-  invitedByName: varchar("invitedByName", { length: 255 }),
+export const invitations = chatbotSchema.table("invitations", {
+  id:               serial("id").primaryKey(),
+  email:            varchar("email", { length: 320 }).notNull(),
+  role:             roleEnum("role").default("agent").notNull(),
+  token:            varchar("token", { length: 64 }).notNull().unique(),
+  status:           inviteStatusEnum("status").default("pending").notNull(),
+  invitedById:      integer("invitedById").notNull(),
+  invitedByName:    varchar("invitedByName",    { length: 255 }),
   acceptedByUserId: integer("acceptedByUserId"),
-  message: text("message"),
-  expiresAt: timestamp("expiresAt").notNull(),
-  acceptedAt: timestamp("acceptedAt"),
-  createdAt: timestamp("createdAt").defaultNow().notNull(),
-  updatedAt: timestamp("updatedAt").defaultNow().notNull(),
+  message:          text("message"),
+  expiresAt:        timestamp("expiresAt").notNull(),
+  acceptedAt:       timestamp("acceptedAt"),
+  createdAt:        timestamp("createdAt").defaultNow().notNull(),
+  updatedAt:        timestamp("updatedAt").defaultNow().notNull(),
 });
 
-export type Invitation = typeof invitations.$inferSelect;
+export type Invitation       = typeof invitations.$inferSelect;
 export type InsertInvitation = typeof invitations.$inferInsert;
 
 /**
  * Audit logs — track important user management actions.
  */
-export const auditLogs = pgTable("audit_logs", {
-  id: serial("id").primaryKey(),
-  action: varchar("action", { length: 64 }).notNull(),
-  actorId: integer("actorId").notNull(),
-  actorName: varchar("actorName", { length: 255 }),
-  targetId: integer("targetId"),
+export const auditLogs = chatbotSchema.table("audit_logs", {
+  id:         serial("id").primaryKey(),
+  action:     varchar("action",     { length: 64  }).notNull(),
+  actorId:    integer("actorId").notNull(),
+  actorName:  varchar("actorName",  { length: 255 }),
+  targetId:   integer("targetId"),
   targetName: varchar("targetName", { length: 255 }),
-  details: jsonb("details"),
-  createdAt: timestamp("createdAt").defaultNow().notNull(),
+  details:    jsonb("details"),
+  createdAt:  timestamp("createdAt").defaultNow().notNull(),
 });
 
-export type AuditLog = typeof auditLogs.$inferSelect;
+export type AuditLog       = typeof auditLogs.$inferSelect;
 export type InsertAuditLog = typeof auditLogs.$inferInsert;
 
 /**
  * AI workflow suggestions — AI-recommended nodes based on FAQ analysis.
  */
-export const workflowSuggestions = pgTable("workflow_suggestions", {
-  id: serial("id").primaryKey(),
-  workflowId: varchar("workflowId", { length: 64 }).notNull(),
-  suggestedNodeType: varchar("suggestedNodeType", { length: 64 }).notNull(),
-  label: varchar("label", { length: 255 }).notNull(),
-  description: text("description"),
-  config: jsonb("config"),
-  faqQuestion: text("faqQuestion"),
-  frequency: integer("frequency").default(0).notNull(),
-  status: suggestionStatusEnum("status").default("pending").notNull(),
-  reviewedById: integer("reviewedById"),
-  reviewedAt: timestamp("reviewedAt"),
-  createdAt: timestamp("createdAt").defaultNow().notNull(),
-  updatedAt: timestamp("updatedAt").defaultNow().notNull(),
+export const workflowSuggestions = chatbotSchema.table("workflow_suggestions", {
+  id:                serial("id").primaryKey(),
+  workflowId:        varchar("workflowId",        { length: 64  }).notNull(),
+  suggestedNodeType: varchar("suggestedNodeType",  { length: 64  }).notNull(),
+  label:             varchar("label",              { length: 255 }).notNull(),
+  description:       text("description"),
+  config:            jsonb("config"),
+  faqQuestion:       text("faqQuestion"),
+  frequency:         integer("frequency").default(0).notNull(),
+  status:            suggestionStatusEnum("status").default("pending").notNull(),
+  reviewedById:      integer("reviewedById"),
+  reviewedAt:        timestamp("reviewedAt"),
+  createdAt:         timestamp("createdAt").defaultNow().notNull(),
+  updatedAt:         timestamp("updatedAt").defaultNow().notNull(),
 });
 
-export type WorkflowSuggestion = typeof workflowSuggestions.$inferSelect;
+export type WorkflowSuggestion       = typeof workflowSuggestions.$inferSelect;
 export type InsertWorkflowSuggestion = typeof workflowSuggestions.$inferInsert;
 
 /**
  * Analytics events — track chatbot interactions for resolution rate and metrics.
  */
-export const analyticsEvents = pgTable("analytics_events", {
-  id: serial("id").primaryKey(),
+export const analyticsEvents = chatbotSchema.table("analytics_events", {
+  id:             serial("id").primaryKey(),
   conversationId: integer("conversationId"),
-  sessionId: varchar("sessionId", { length: 64 }),
-  eventType: eventTypeEnum("eventType").notNull(),
-  category: varchar("category", { length: 64 }),
-  metadata: jsonb("metadata"),
-  createdAt: timestamp("createdAt").defaultNow().notNull(),
+  sessionId:      varchar("sessionId", { length: 64 }),
+  eventType:      eventTypeEnum("eventType").notNull(),
+  category:       varchar("category",  { length: 64 }),
+  metadata:       jsonb("metadata"),
+  createdAt:      timestamp("createdAt").defaultNow().notNull(),
 });
 
-export type AnalyticsEvent = typeof analyticsEvents.$inferSelect;
+export type AnalyticsEvent       = typeof analyticsEvents.$inferSelect;
 export type InsertAnalyticsEvent = typeof analyticsEvents.$inferInsert;
 
 /**
  * Data sources — knowledge base for the AI agent.
  */
-export const dataSources = pgTable("data_sources", {
-  id: serial("id").primaryKey(),
-  name: varchar("name", { length: 255 }).notNull(),
-  type: sourceTypeEnum("type").notNull(),
-  status: sourceStatusEnum("status").default("active").notNull(),
-  config: jsonb("config"),
+export const dataSources = chatbotSchema.table("data_sources", {
+  id:           serial("id").primaryKey(),
+  name:         varchar("name", { length: 255 }).notNull(),
+  type:         sourceTypeEnum("type").notNull(),
+  status:       sourceStatusEnum("status").default("active").notNull(),
+  config:       jsonb("config"),
   lastSyncedAt: timestamp("lastSyncedAt"),
-  itemCount: integer("itemCount").default(0).notNull(),
-  createdById: integer("createdById"),
-  createdAt: timestamp("createdAt").defaultNow().notNull(),
-  updatedAt: timestamp("updatedAt").defaultNow().notNull(),
+  itemCount:    integer("itemCount").default(0).notNull(),
+  createdById:  integer("createdById"),
+  createdAt:    timestamp("createdAt").defaultNow().notNull(),
+  updatedAt:    timestamp("updatedAt").defaultNow().notNull(),
 });
 
-export type DataSource = typeof dataSources.$inferSelect;
+export type DataSource       = typeof dataSources.$inferSelect;
 export type InsertDataSource = typeof dataSources.$inferInsert;
 
 /**
  * API connections — external API endpoints for Actions.
  */
-export const apiConnections = pgTable("api_connections", {
-  id: serial("id").primaryKey(),
-  name: varchar("name", { length: 255 }).notNull(),
-  description: text("description"),
-  category: varchar("category", { length: 64 }),
-  method: httpMethodEnum("method").default("GET").notNull(),
-  endpoint: varchar("endpoint", { length: 1024 }).notNull(),
-  headers: jsonb("headers"),
-  inputVariables: jsonb("inputVariables"),
+export const apiConnections = chatbotSchema.table("api_connections", {
+  id:              serial("id").primaryKey(),
+  name:            varchar("name",     { length: 255  }).notNull(),
+  description:     text("description"),
+  category:        varchar("category", { length: 64   }),
+  method:          httpMethodEnum("method").default("GET").notNull(),
+  endpoint:        varchar("endpoint", { length: 1024 }).notNull(),
+  headers:         jsonb("headers"),
+  inputVariables:  jsonb("inputVariables"),
   outputVariables: jsonb("outputVariables"),
-  testPayload: jsonb("testPayload"),
-  isActive: boolean("isActive").default(true).notNull(),
-  executionCount: integer("executionCount").default(0).notNull(),
-  lastExecutedAt: timestamp("lastExecutedAt"),
-  createdById: integer("createdById"),
-  createdAt: timestamp("createdAt").defaultNow().notNull(),
-  updatedAt: timestamp("updatedAt").defaultNow().notNull(),
+  testPayload:     jsonb("testPayload"),
+  isActive:        boolean("isActive").default(true).notNull(),
+  executionCount:  integer("executionCount").default(0).notNull(),
+  lastExecutedAt:  timestamp("lastExecutedAt"),
+  createdById:     integer("createdById"),
+  createdAt:       timestamp("createdAt").defaultNow().notNull(),
+  updatedAt:       timestamp("updatedAt").defaultNow().notNull(),
 });
 
-export type ApiConnection = typeof apiConnections.$inferSelect;
+export type ApiConnection       = typeof apiConnections.$inferSelect;
 export type InsertApiConnection = typeof apiConnections.$inferInsert;

server/db.ts

@@ -21,7 +21,10 @@ let _db: ReturnType<typeof drizzle> | null = null;
 export async function getDb() {
   if (!_db && process.env.DATABASE_URL) {
     try {
-      _db = drizzle(process.env.DATABASE_URL);
+      // Set search_path so unqualified queries resolve to the chatbot schema
+      _db = drizzle(process.env.DATABASE_URL, {
+        connection: { options: "-c search_path=chatbot,public" },
+      });
     } catch (error) {
       console.warn("[Database] Failed to connect:", error);
       _db = null;