# Service Design Specification **workforceos-aiworkforceanalytics-service** documentation **Version:** `1.0.134` ## Scope This document provides a structured architectural overview of the `aiWorkforceAnalytics` microservice, detailing its configuration, data model, authorization logic, business rules, and API design. It has been automatically generated based on the service definition within Mindbricks, ensuring that the information reflects the source of truth used during code generation and deployment. The document is intended to serve multiple audiences: * **Service architects** can use it to validate design decisions and ensure alignment with broader architectural goals. * **Developers and maintainers** will find it useful for understanding the structure and behavior of the service, facilitating easier debugging, feature extension, and integration with other systems. * **Stakeholders and reviewers** can use it to gain a clear understanding of the service's capabilities and domain logic. > **Note for Frontend Developers**: While this document is valuable for understanding business logic and data interactions, please refer to the [Service API Documentation](#) for endpoint-level specifications and integration details. > **Note for Backend Developers**: Since the code for this service is automatically generated by Mindbricks, you typically won't need to implement or modify it manually. However, this document is especially valuable when you're building other services—whether within Mindbricks or externally—that need to interact with or depend on this service. It provides a clear reference to the service's data contracts, business rules, and API structure, helping ensure compatibility and correct integration. ## `AiWorkforceAnalytics` Service Settings Microservice for computing and delivering AI-powered workforce analytics (e.g., shift optimization, absenteeism insights, staffing trends) for eligible (subscribed) companies. Handles insight calculation, storage, and secure distribution to authorized users. Publishes insight alerts/events for notifications. Strictly enforces company data isolation and subscription gating on all features. ### Service Overview This service is configured to listen for HTTP requests on port `3006`, serving both the main API interface and default administrative endpoints. The following routes are available by default: * **API Test Interface (API Face):** `/` * **Swagger Documentation:** `/swagger` * **Postman Collection Download:** `/getPostmanCollection` * **Health Checks:** `/health` and `/admin/health` * **Current Session Info:** `/currentuser` * **Favicon:** `/favicon.ico` The service uses a **PostgreSQL** database for data storage, with the database name set to `workforceos-aiworkforceanalytics-service`. This service is accessible via the following environment-specific URLs: * **Preview:** `https://workforceos.prw.mindbricks.com/aiworkforceanalytics-api` * **Staging:** `https://workforceos-stage.mindbricks.co/aiworkforceanalytics-api` * **Production:** `https://workforceos.mindbricks.co/aiworkforceanalytics-api` ### Authentication & Security - **Login Required**: Yes This service requires user authentication for access. It supports both JWT and RSA-based authentication mechanisms, ensuring secure user sessions and data integrity. If a crud route also is configured to require login, it will check a valid JWT token in the request query/header/bearer/cookie. If the token is valid, it will extract the user information from the token and make the fetched session data available in the request context. ### Service Data Objects The service uses a **PostgreSQL** database for data storage, with the database name set to `workforceos-aiworkforceanalytics-service`. Data deletion is managed using a **soft delete** strategy. Instead of removing records from the database, they are flagged as inactive by setting the `isActive` field to `false`. | Object Name | Description | Public Access | Tenant Level | |-------------|-------------|---------------| --------------| | `aiInsight` | Represents an AI-generated insight, analytic, or tip for a company (and optionally individual user) for a specific period/type. Used for staffing recommendations, absenteeism patterns, productivity, and targeted advice. Stores computed detail as JSON and current delivery/processing status. | accessPrivate | Yes | ## aiInsight Data Object ### Object Overview **Description:** Represents an AI-generated insight, analytic, or tip for a company (and optionally individual user) for a specific period/type. Used for staffing recommendations, absenteeism patterns, productivity, and targeted advice. Stores computed detail as JSON and current delivery/processing status. This object represents a core data structure within the service and acts as the blueprint for database interaction, API generation, and business logic enforcement. It is defined using the `ObjectSettings` pattern, which governs its behavior, access control, caching strategy, and integration points with other systems such as Stripe and Redis. ### Core Configuration - **Soft Delete:** Enabled — Determines whether records are marked inactive (`isActive = false`) instead of being physically deleted. - **Public Access:** accessPrivate — If enabled, anonymous users may access this object’s data depending on API-level rules. - **Tenant-Level Scope:** Yes — Enables data isolation per tenant by attaching a tenant ID field. ### Properties Schema **Display Label Property:** `insightType` — This property is the default display label for records of this data object. Relation dropdowns and record references in the frontend will show the value of this property as the human-readable label. | Property | Type | Required | Description | |----------|------|----------|-------------| | `insightType` | String | Yes | Type/classification of the insight (e.g. 'staffingPrediction', 'absenteeismPattern', 'shiftAnomaly', 'productivityTip'). | | `audienceUserId` | ID | No | If present, insight is for a specific employee; otherwise company/manager-level. | | `applicablePeriod` | Object | Yes | Date range period to which the insight applies (object: {startDate, endDate}) | | `details` | Text | Yes | JSON-stringified blob containing the AI result, message, chart data, or recommendation. | | `aiStatus` | Enum | Yes | Status of the insight; pending (to deliver), delivered (published), error (AI-failed/delivery failed). | | `deliveredTime` | Date | No | Actual delivery/publication time (set when status becomes 'delivered'); null when pending. | | `companyId` | ID | Yes | An ID value to represent the tenant id of the company | * Required properties are mandatory for creating objects and must be provided in the request body if no default value is set. * Properties marked `Type[] (array)` MUST be sent as a JSON array (e.g. `["a","b"]`), even when only one value is present (`["a"]`). Sending a bare scalar fails validation. ### Default Values Default values are automatically assigned to properties when a new object is created, if no value is provided in the request body. Since default values are applied on db level, they should be literal values, not expressions.If you want to use expressions, you can use transposed parameters in any business API to set default values dynamically. - **insightType**: 'default' - **applicablePeriod**: {} - **details**: 'text' - **aiStatus**: pending - **companyId**: 00000000-0000-0000-0000-000000000000 ### Constant Properties `companyId` Constant properties are defined to be immutable after creation, meaning they cannot be updated or changed once set. They are typically used for properties that should remain constant throughout the object's lifecycle. A property is set to be constant if the `Allow Update` option is set to `false`. ### Auto Update Properties `insightType` `audienceUserId` `applicablePeriod` `details` `aiStatus` `deliveredTime` An update crud API created with the option `Auto Params` enabled will automatically update these properties with the provided values in the request body. If you want to update any property in your own business logic not by user input, you can set the `Allow Auto Update` option to false. These properties will be added to the update API's body parameters and can be updated by the user if any value is provided in the request body. ### Enum Properties Enum properties are defined with a set of allowed values, ensuring that only valid options can be assigned to them. The enum options value will be stored as strings in the database, but when a data object is created an addtional property with the same name plus an idx suffix will be created, which will hold the index of the selected enum option. You can use the index property to sort by the enum value or when your enum options represent a sequence of values. - **aiStatus**: [pending, delivered, error] ### Elastic Search Indexing `insightType` `audienceUserId` `applicablePeriod` `details` `aiStatus` `deliveredTime` `companyId` Properties that are indexed in Elastic Search will be searchable via the Elastic Search API. While all properties are stored in the elastic search index of the data object, only those marked for Elastic Search indexing will be available for search queries. ### Database Indexing `insightType` `audienceUserId` `applicablePeriod` `aiStatus` `companyId` Properties that are indexed in the database will be optimized for query performance, allowing for faster data retrieval. Make a property indexed in the database if you want to use it frequently in query filters or sorting. ### Secondary Key Properties `companyId` Secondary key properties are used to create an additional indexed identifiers for the data object, allowing for alternative access patterns. Different than normal indexed properties, secondary keys will act as primary keys and Mindbricks will provide automatic secondary key db utility functions to access the data object by the secondary key. ### Relation Properties `audienceUserId` Mindbricks supports relations between data objects, allowing you to define how objects are linked together. You can define relations in the data object properties, which will be used to create foreign key constraints in the database. For complex joins operations, Mindbricks supportsa BFF pattern, where you can view dynamic and static views based on Elastic Search Indexes. Use db level relations for simple one-to-one or one-to-many relationships, and use BFF views for complex joins that require multiple data objects to be joined together. - **audienceUserId**: ID Relation to `user`.id The target object is a sibling object, meaning that the relation is a many-to-one or one-to-one relationship from this object to the target. On Delete: Set Null Required: No ### Filter Properties `insightType` `audienceUserId` `applicablePeriod` `aiStatus` `companyId` Filter properties are used to define parameters that can be used in query filters, allowing for dynamic data retrieval based on user input or predefined criteria. These properties are automatically mapped as API parameters in the listing API's that have "Auto Params" enabled. - **insightType**: String has a filter named `insightType` - **audienceUserId**: ID has a filter named `audienceUserId` - **applicablePeriod**: Object has a filter named `applicablePeriod` - **aiStatus**: Enum has a filter named `aiStatus` - **companyId**: ID has a filter named `companyId` ## Business Logic aiWorkforceAnalytics has got 7 Business APIs to manage its internal and crud logic. For the details of each business API refer to its chapter. * [Create Aiinsight](/businessLogic/createaiinsight) * [Update Aiinsight](/businessLogic/updateaiinsight) * [Get Aiinsight](/businessLogic/getaiinsight) * [List Aiinsights](/businessLogic/listaiinsights) * [Delete Aiinsight](/businessLogic/deleteaiinsight) * [Save Insight](/businessLogic/saveinsight) * [Save Aiinsight](/businessLogic/saveaiinsight) ## AI Agents aiWorkforceAnalytics has 1 AI Agent configured. Each agent encapsulates a model configuration, system prompt, input/output pipeline, and optional tool access. Agents support multiple execution modes (task, chat, orchestrator) and modalities (text, image, audio, video, vision). | Agent Name | Execution Mode | Modality | Provider | Auth Required | |------------|---------------|----------|----------|---------------| | `insightGenerator` | task | text | openai | Yes | For detailed documentation on each agent, refer to: * [insightGenerator](/aiAgents/insightgenerator) ## Edge Controllers ### generateInsightHandler **Configuration:** - **Function Name**: `generateInsightHandler` - **Login Required**: Yes **REST Settings:** - **Path**: `generate-insight` - **Method**: --- ### generateAiInsightStreamHandler **Configuration:** - **Function Name**: `generateAiInsightStreamHandler` - **Login Required**: No **REST Settings:** - **Path**: `/ai-insight/stream` - **Method**: --- ## Service Library ### Functions #### checkCompanyAIAccess.js ```js module.exports = function checkCompanyAIAccess(companySubscription) { if (!companySubscription) return false; if (companySubscription.status !== 'active') return false; if (companySubscription.paymentStatus && companySubscription.paymentStatus !== 'paid') return false; if (!companySubscription.subscribedFeatures || !Array.isArray(companySubscription.subscribedFeatures)) return false; if (companySubscription.expiryDate && new Date(companySubscription.expiryDate) < new Date()) return false; return companySubscription.subscribedFeatures.includes('aiInsights') || companySubscription.subscribedFeatures.includes('aiWorkforceAnalytics'); }; ``` #### generateInsightStream.js ```js const common = require("common"); const serviceCommon = require("serviceCommon"); module.exports = async (context) => { const { goal, period, inputData, insightType, applicablePeriod, details, session } = context; // Validate required fields const requiredFields = ['insightType', 'applicablePeriod', 'details']; const missingFields = requiredFields.filter(field => { const value = context[field]; return value === undefined || value === null || value === ''; }); if (missingFields.length > 0) { const error = new Error(`Missing required fields: ${missingFields.join(', ')}`); error.statusCode = 400; error.code = 'VALIDATION_ERROR'; throw error; } // Validate applicablePeriod has startDate and endDate if (!applicablePeriod || !applicablePeriod.startDate || !applicablePeriod.endDate) { const error = new Error('applicablePeriod must contain startDate and endDate'); error.statusCode = 400; error.code = 'VALIDATION_ERROR'; throw error; } // Build the prompt for AI agent const prompt = JSON.stringify({ goal: goal || 'Generate workforce insight', period: period || '', inputData: inputData || {}, insightType: insightType, applicablePeriod: applicablePeriod }); // Call AI Agent via AgentHub try { const agentHub = serviceCommon.getAgentHubClient(); const agentResult = await agentHub.callAgent('insightGenerator', { message: prompt, session: session }); // Return the AI insight result for SSE streaming return { success: true, insightType: insightType, applicablePeriod: applicablePeriod, details: agentResult.response || details, aiStatus: 'delivered', generatedContent: agentResult.response || '' }; } catch (agentError) { console.error('AI Agent call failed:', agentError); throw new Error(`AI insight generation failed: ${agentError.message}`); } }; ``` #### fetchCompanyWorkforceData.js ```js const axios = require("axios"); const common = require("common"); module.exports = async (context) => { const { companyId, period } = context; if (!companyId) throw new Error("companyId is required"); const authUrl = process.env.AUTH_SERVICE_URL || "http://auth-api:3011"; const employeeUrl = process.env.EMPLOYEEPROFILE_API_URL || "http://employeeprofile-api:3011"; const scheduleUrl = process.env.SCHEDULEMANAGEMENT_API_URL || "http://schedulemanagement-api:3011"; const attendanceUrl = process.env.ATTENDANCEMANAGEMENT_API_URL || "http://attendancemanagement-api:3011"; const taskUrl = process.env.TASKMANAGEMENT_API_URL || "http://taskmanagement-api:3011"; const leaveUrl = process.env.LEAVEMANAGEMENT_API_URL || "http://leavemanagement-api:3011"; const jwtToken = await common.crypto.createInternalServiceJWT(); const headers = { Authorization: `Bearer ${jwtToken}` }; try { // Build query params with companyId filter const companyQuery = `companyId=${companyId}&pageRowCount=0`; const [ departmentsRes, usersRes, employeeProfilesRes, shiftsRes, attendanceRes, tasksRes, leaveRes, ] = await Promise.allSettled([ axios.get(`${authUrl}/v1/usergroups?${companyQuery}`, { headers }) .catch(() => ({ data: { userGroups: [] } })), axios.get(`${authUrl}/v1/users?${companyQuery}`, { headers }) .catch(() => ({ data: { items: [] } })), axios.get(`${employeeUrl}/v1/employeeprofiles?${companyQuery}`, { headers }) .catch(() => ({ data: { employeeProfiles: [] } })), axios.get(`${scheduleUrl}/v1/shifts?${companyQuery}`, { headers }) .catch(() => ({ data: { shifts: [] } })), axios.get(`${attendanceUrl}/v1/attendancerecords?${companyQuery}`, { headers }) .catch(() => ({ data: { attendanceRecords: [] } })), axios.get(`${taskUrl}/v1/taskassignments?${companyQuery}`, { headers }) .catch(() => ({ data: { taskAssignments: [] } })), axios.get(`${leaveUrl}/v1/leaverequests?${companyQuery}`, { headers }) .catch(() => ({ data: { leaveRequests: [] } })), ]); const departments = departmentsRes.status === "fulfilled" ? departmentsRes.value.data?.userGroups || [] : []; const users = usersRes.status === "fulfilled" ? usersRes.value.data?.items || [] : []; const employeeProfiles = employeeProfilesRes.status === "fulfilled" ? employeeProfilesRes.value.data?.employeeProfiles || employeeProfilesRes.value.data?.items || [] : []; const shifts = shiftsRes.status === "fulfilled" ? shiftsRes.value.data?.shifts || [] : []; const attendance = attendanceRes.status === "fulfilled" ? attendanceRes.value.data?.attendanceRecords || attendanceRes.value.data?.items || [] : []; const tasks = tasksRes.status === "fulfilled" ? tasksRes.value.data?.taskAssignments || tasksRes.value.data?.items || [] : []; const leaveRequests = leaveRes.status === "fulfilled" ? leaveRes.value.data?.leaveRequests || [] : []; const stats = { totalEmployees: employeeProfiles.length || users.length, totalDepartments: departments.length, totalShifts: shifts.length, totalAttendanceRecords: attendance.length, totalTasks: tasks.length, pendingLeaveRequests: leaveRequests.filter((l) => l.status === "pending").length, approvedLeaveRequests: leaveRequests.filter((l) => l.status === "approved").length, rejectedLeaveRequests: leaveRequests.filter((l) => l.status === "rejected").length, lateCheckIns: attendance.filter((a) => a.status === "late").length, earlyDepartures: attendance.filter((a) => a.status === "earlyLeave").length, absences: attendance.filter((a) => a.status === "absent").length, completedTasks: tasks.filter((t) => t.status === "completed").length, pendingTasks: tasks.filter((t) => t.status === "pending" || t.status === "active").length, }; return { stats, departments: departments.map((d) => ({ id: d.id, groupName: d.groupName })), employees: employeeProfiles.map((p) => { const user = users.find((u) => u.id === p.userId); const dept = departments.find((d) => d.id === p.departmentId); return { id: p.id, userId: p.userId, fullname: user?.fullname || "Unknown", email: user?.email || "N/A", department: dept?.groupName || "Unassigned", position: p.position || "N/A", contractType: p.contractType || "N/A", }; }), attendanceSummary: attendance.slice(0, 50), recentTasks: tasks.slice(0, 20), recentLeaveRequests: leaveRequests.slice(0, 20), }; } catch (error) { console.error("fetchCompanyWorkforceData error:", error.message); return { error: error.message, stats: {}, departments: [], employees: [] }; } }; ``` #### fetchCompanyData.js ```js const axios = require('axios'); module.exports = async (context) => { const { token, baseUrl, userId, companyCodename, companyId } = context; if (!token || !baseUrl) { throw new Error('Token and baseUrl are required'); } const headers = { 'Authorization': `Bearer ${token}`, 'Content-Type': 'application/json' }; if (companyCodename) { headers['mbx-company-codename'] = companyCodename; } try { // Get current user info const userResponse = await axios.get(`${baseUrl}/auth-api/currentuser`, { headers }); const currentUser = userResponse.data; const userCompanyId = companyId || currentUser?.company?.companyId; // Get employee profiles for the company (use companyId filter if API supports it) let employeeCount = 0; try { const employeeResponse = await axios.get(`${baseUrl}/employeeprofile-api/v1/employeeprofiles?pageNumber=0`, { headers }); // Filter by company if the API returns all - items should already be filtered by session const items = employeeResponse.data?.data || employeeResponse.data?.items || []; employeeCount = employeeResponse.data.rowCount || items.length; } catch (e) { console.log('Employee API error:', e.message); } // Get departments (userGroups) let departmentCount = 0; try { const deptResponse = await axios.get(`${baseUrl}/auth-api/v1/usergroups?pageNumber=0`, { headers }); const items = deptResponse.data?.data || deptResponse.data?.userGroups || []; departmentCount = deptResponse.data.rowCount || items.length; } catch (e) { console.log('Department API error:', e.message); } // Get today's shifts let todayShifts = 0; try { const today = new Date().toISOString().split('T')[0]; const shiftsResponse = await axios.get(`${baseUrl}/schedulemanagement-api/v1/shifts?shiftDate=${today}&pageNumber=0`, { headers }); const items = shiftsResponse.data?.data || shiftsResponse.data?.shifts || []; todayShifts = shiftsResponse.data.rowCount || items.length; } catch (e) { console.log('Today shifts API error:', e.message); } // Get all shifts let totalShifts = 0; try { const allShiftsResponse = await axios.get(`${baseUrl}/schedulemanagement-api/v1/shifts?pageNumber=0`, { headers }); const items = allShiftsResponse.data?.data || allShiftsResponse.data?.shifts || []; totalShifts = allShiftsResponse.data.rowCount || items.length; } catch (e) { console.log('All shifts API error:', e.message); } // Get task assignments - THIS WAS THE BUG - using wrong endpoint let taskCount = 0; try { const tasksResponse = await axios.get(`${baseUrl}/taskmanagement-api/v1/taskassignments?pageNumber=0`, { headers }); const items = tasksResponse.data?.data || tasksResponse.data?.items || []; taskCount = tasksResponse.data.rowCount || items.length; } catch (e) { console.log('Tasks API error:', e.message); } // Get individual tasks for this user let myTaskCount = 0; try { const myTasksResponse = await axios.get(`${baseUrl}/taskmanagement-api/v1/myindividualtasks?pageNumber=0`, { headers }); const items = myTasksResponse.data?.data || myTasksResponse.data?.items || []; myTaskCount = myTasksResponse.data.rowCount || items.length; } catch (e) { console.log('My tasks API error:', e.message); } // Get attendance records let attendanceCount = 0; try { const attendanceResponse = await axios.get(`${baseUrl}/attendancemanagement-api/v1/attendancerecords?pageNumber=0`, { headers }); const items = attendanceResponse.data?.data || attendanceResponse.data?.items || []; attendanceCount = attendanceResponse.data.rowCount || items.length; } catch (e) { console.log('Attendance API error:', e.message); } // Get leave requests let leaveCount = 0; try { const leaveResponse = await axios.get(`${baseUrl}/leavemanagement-api/v1/leaverequests?pageNumber=0`, { headers }); const items = leaveResponse.data?.data || leaveResponse.data?.leaveRequests || []; leaveCount = leaveResponse.data.rowCount || items.length; } catch (e) { console.log('Leave API error:', e.message); } return { user: currentUser, employeeCount, departmentCount, todayShifts, totalShifts, taskCount, myTaskCount, attendanceCount, leaveCount, today: new Date().toISOString().split('T')[0], companyCodename: companyCodename || currentUser?.company?.codename || 'unknown', userCompanyId: userCompanyId }; } catch (error) { console.error('Error fetching company data:', error.message); if (error.response) { console.error('Response status:', error.response.status); console.error('Response data:', error.response.data); } throw new Error(`Failed to fetch company data: ${error.message}`); } }; ``` ### Edge Functions #### generateAiInsightStreamHandler.js ```js const axios = require("axios"); module.exports = async (req) => { const baseUrl = "https://workforceos.prw.mindbricks.com"; const authHeader = req.headers?.authorization; const token = authHeader?.substring(7); const companyCodename = req.headers["mbx-company-codename"]; if (!token) return { status: 401, headers: { "Content-Type": "text/event-stream" }, content: `event: error\ndata: {"error":"Authentication required"}\n\n`, }; const goal = req.body?.goal || req.body?.query; if (!goal) return { status: 400, headers: { "Content-Type": "text/event-stream" }, content: `event: error\ndata: {"error":"Goal or query is required"}\n\n`, }; const headers = { Authorization: `Bearer ${token}`, "Content-Type": "application/json", }; if (companyCodename) headers["mbx-company-codename"] = companyCodename; try { // Call the workforceAssistant AI agent in agentHub const agentUrl = `${baseUrl}/agenthub-api/agents/workforceAssistant`; const agentRes = await axios.post( agentUrl, { message: goal }, { headers } ); const aiResponse = agentRes.data; // Stream the response const sse = `event: start\ndata: {}\n\n` + `event: chunk\ndata: {"chunk": "Workforce AI Analysis", "type": "title"}\n\n` + `event: chunk\ndata: {"chunk": ${JSON.stringify(aiResponse)}, "type": "summary"}\n\n` + `event: complete\ndata: {"status": "completed", "insightType": "companySpecific"}\n\n`; return { status: 200, headers: { "Content-Type": "text/event-stream" }, content: sse, }; } catch (agentError) { console.error("AI Agent call failed:", agentError.message); // Fallback response if AI agent fails const sse = `event: start\ndata: {}\n\n` + `event: chunk\ndata: {"chunk": "Workforce AI", "type": "title"}\n\n` + `event: chunk\ndata: {"chunk": "I'm having trouble accessing the AI service right now. Please try again in a moment.", "type": "summary"}\n\n` + `event: complete\ndata: {"status": "completed", "insightType": "general"}\n\n`; return { status: 200, headers: { "Content-Type": "text/event-stream" }, content: sse, }; } }; ``` #### streamAiInsight.js ```js // Wrapper for generateAiInsightStreamHandler with login enforcement const handler = require('./generateAiInsightStreamHandler'); module.exports = async (request) => { return handler(request); }; ``` #### testFunction.js ```js module.exports = async (req) => { return { status: 200, content: 'test' }; }; ``` #### generateInsightHandler.js ```js const axios = require('axios'); module.exports = async (req, res) => { try { // Get token from request const authHeader = req.headers['authorization'] || req.headers['Authorization']; const token = authHeader ? authHeader.replace('Bearer ', '') : null; if (!token) { return res.status(401).json({ status: 'ERR', message: 'Authorization token required' }); } // Get company codename from header const companyCodename = req.headers['mbx-company-codename'] || req.headers['mbx-Company-Codename']; // Build base URL from request const protocol = req.headers['x-forwarded-proto'] || 'https'; const host = req.headers['host']; const baseUrl = `${protocol}://${host}`; const headers = { 'Authorization': `Bearer ${token}`, 'Content-Type': 'application/json' }; if (companyCodename) { headers['mbx-company-codename'] = companyCodename; } // Get current user info const userResponse = await axios.get(`${baseUrl}/auth-api/currentuser`, { headers }); const currentUser = userResponse.data; if (!currentUser || !currentUser.userId) { return res.status(401).json({ status: 'ERR', message: 'Invalid token or user not found' }); } // Fetch all company data using the APIs const today = new Date().toISOString().split('T')[0]; // Get employee profiles for the company let employeeCount = 0; try { const employeeResponse = await axios.get(`${baseUrl}/employeeprofile-api/v1/employeeprofiles?pageNumber=0`, { headers }); employeeCount = employeeResponse.data.rowCount || 0; } catch (e) { console.log('Employee API error:', e.message); } // Get departments (userGroups) let departmentCount = 0; try { const deptResponse = await axios.get(`${baseUrl}/auth-api/v1/usergroups?pageNumber=0`, { headers }); departmentCount = deptResponse.data.rowCount || 0; } catch (e) { console.log('Department API error:', e.message); } // Get today's shifts let todayShifts = 0; try { const shiftsResponse = await axios.get(`${baseUrl}/schedulemanagement-api/v1/shifts?shiftDate=${today}&pageNumber=0`, { headers }); todayShifts = shiftsResponse.data.rowCount || 0; } catch (e) { console.log('Today shifts API error:', e.message); } // Get all shifts let totalShifts = 0; try { const allShiftsResponse = await axios.get(`${baseUrl}/schedulemanagement-api/v1/shifts?pageNumber=0`, { headers }); totalShifts = allShiftsResponse.data.rowCount || 0; } catch (e) { console.log('All shifts API error:', e.message); } // Get task assignments let taskCount = 0; try { const tasksResponse = await axios.get(`${baseUrl}/taskmanagement-api/v1/taskassignments?pageNumber=0`, { headers }); taskCount = tasksResponse.data.rowCount || 0; } catch (e) { console.log('Tasks API error:', e.message); } // Get individual tasks for this user let myTaskCount = 0; try { const myTasksResponse = await axios.get(`${baseUrl}/taskmanagement-api/v1/myindividualtasks?pageNumber=0`, { headers }); myTaskCount = myTasksResponse.data.rowCount || 0; } catch (e) { console.log('My tasks API error:', e.message); } // Get attendance records let attendanceCount = 0; try { const attendanceResponse = await axios.get(`${baseUrl}/attendancemanagement-api/v1/attendancerecords?pageNumber=0`, { headers }); attendanceCount = attendanceResponse.data.rowCount || 0; } catch (e) { console.log('Attendance API error:', e.message); } // Get leave requests let leaveCount = 0; try { const leaveResponse = await axios.get(`${baseUrl}/leavemanagement-api/v1/leaverequests?pageNumber=0`, { headers }); leaveCount = leaveResponse.data.rowCount || 0; } catch (e) { console.log('Leave API error:', e.message); } // Build company data summary const companyData = { employeeCount, departmentCount, todayShifts, totalShifts, taskCount, myTaskCount, attendanceCount, leaveCount, today, companyCodename: companyCodename || currentUser?.company?.codename || 'unknown', userCompanyId: currentUser?.company?.companyId || currentUser?.companyId }; // Get user prompt from request const userPrompt = req.body?.prompt || 'Provide a workforce overview'; // Build enriched prompt with company data const enrichedPrompt = `ACTUAL COMPANY DATA (from database): - Employee Count: ${companyData.employeeCount} - Department Count: ${companyData.departmentCount} - Shifts Today (${today}): ${companyData.todayShifts} - Total Shifts: ${companyData.totalShifts} - Task Assignments: ${companyData.taskCount} - My Tasks: ${companyData.myTaskCount} - Attendance Records: ${companyData.attendanceCount} - Leave Requests: ${companyData.leaveCount} - Company Codename: ${companyData.companyCodename} USER QUESTION: ${userPrompt} IMPORTANT: Use ONLY the numbers above. Do not make up or hallucinate any data. If a count is 0, report it as 0. Provide your response as a JSON object with this exact structure: { "title": "Brief insight title", "insightType": "companySpecific", "summary": "2-3 sentence answer using the actual numbers above", "data": { "keyMetrics": [{"metric": "Name", "value": number}], "findings": ["Finding 1"], "recommendations": [] }, "audienceType": "company", "suggestion": "Optional suggestion" }`; // Call the AI agent const aiResponse = await axios.post( `${baseUrl}/aiworkforceanalytics-api/v1/aiinsight`, { prompt: enrichedPrompt }, { headers } ); // Return the insight res.json({ status: 'OK', insight: aiResponse.data.insight }); } catch (error) { console.error('Edge controller error:', error.message); if (error.response) { console.error('Response status:', error.response.status); console.error('Response data:', error.response.data); } if (!res.headersSent) { res.status(500).json({ status: 'ERR', message: error.message || 'Internal server error', error: error.response?.data || error.message }); } } }; ``` --- *This document was generated from the service architecture definition and should be kept in sync with implementation changes.*