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TypeScript SDK for interacting with the Plato API to create and manage AI-powered medical training simulations.","maintainers":[{"name":"manuelctchealth","email":"manuel.martin.marquez@ctchealth.ch"},{"name":"torben-guijarro-heeb-ctchealth","email":"torben.guijarro.heeb@ctchealth.ch"},{"name":"tech_ctchealth","email":"tech@ctchealth.ch"},{"name":"omardraz","email":"omar.draz@ctchealth.ch"},{"name":"ali-shaaban-ctchealth","email":"ali.shaaban@ctchealth.ch"},{"name":"mohamed-battawy-ctchealth","email":"mohamed.battawy@ctchealth.ch"},{"name":"muayad-mahmoud-ctchealth","email":"muayad.mahmoud@ctchealth.ch"}],"readme":"# Plato SDK\n\nA TypeScript SDK for interacting with the Plato API to create and manage AI-powered medical training simulations.\n\n## Overview\n\nThe Plato SDK provides a simple and type-safe way to integrate with the Plato platform, allowing you to create medical training simulations with AI personas and manage voice-based interactions.\n\n## Authentication\n\nAll API requests require authentication via a client token. Pass a pre-signed JWT token as `jwtToken` when initializing the client. This is sent as the `x-client-token` header on every request.\n\n## Features\n\n- Create AI personas with customizable professional profiles and personalities\n- Real-time voice interactions with AI assistants\n- Comprehensive event system for call management\n- Type-safe API with full TypeScript support\n- Medical training simulation configuration\n- Simulation persistence across page reloads\n\n## Installation\n\n```bash\nnpm install plato-sdk\n```\n\n## Quick Start\n\n```typescript\nimport { PlatoApiClient, AvatarLanguage } from 'plato-sdk';\n\n// Initialize the client\nconst client = new PlatoApiClient({\n baseUrl: 'https://your-plato-api.com',\n jwtToken: 'your-jwt-token',\n publicKey: 'your-public-key',\n});\n\n// Get available assistant images\nconst images = await client.getAssistantImages();\n\n// Create a simulation\nconst simulation = await client.createSimulation({\n persona: {\n professionalProfile: {\n location: 'City Hospital, New York',\n practiceSettings: 'Outpatient Clinic',\n yearOfExperience: 12,\n specialityAndDepartment: 'Cardiology',\n },\n segment: SegmentType.CostConsciousPrescriber,\n assistantGender: AssistantVoiceGender.Male,\n name: 'Dr Vegapunk',\n personalityAndBehaviour: {\n riskTolerance: 40,\n researchOrientation: 70,\n recognitionNeed: 60,\n brandLoyalty: 55,\n patientEmpathy: 80,\n },\n context: {\n subSpecialityOrTherapyFocus: 'Hypertension management',\n typicalPatientMix: 'Elderly with comorbidities',\n keyClinicalDrivers: 'Reducing cardiovascular risk',\n },\n },\n product: {\n name: 'Ibuprofen 1000mg',\n description:\n 'A nonsteroidal anti-inflammatory drug used to reduce pain, inflammation, and fever',\n },\n pdfSlideId: 'pdf-slide-id', // optional, ID from uploadPdfSlides()\n scenario: 'Discussing treatment options for an elderly patient with chronic arthritis',\n objectives:\n 'Demonstrate efficacy of Ibuprofen in pain management Highlight safety profile and contraindications Encourage patient adherence',\n anticipatedObjections:\n 'Concerns about gastrointestinal side effects Preference for lower-cost generic alternatives Potential interactions with other medications',\n imageId: images[0]._id,\n avatarLanguage: AvatarLanguage.English,\n});\n\n// Check the simulation status - If simulation creation phase is equals to FINISHED, the simulation is ready to use\n// If the simulation creation phase is ERROR the simulation creation failed and you need to retry creating a new one\n// tip: you can also check the simulation status periodically using a polling mechanism\nconst status = await client.getSimulationStatus(simulation.simulationId);\n\n// Start a voice call\nconst call = await client.startCall(simulation.simulationId);\n\n// Listen to call events\ncall.on('call-start', () => {\n console.log('Call started');\n});\n\ncall.on('message', message => {\n console.log('Message received:', message.transcript);\n});\n\ncall.on('call-end', () => {\n console.log('Call ended - processing feedback...');\n});\n\n// Automatically receive post-call feedback when ready\ncall.on('call-details-ready', callDetails => {\n console.log('Call Summary:', callDetails.summary);\n console.log('Score:', callDetails.score);\n console.log('Strengths:', callDetails.strengths);\n console.log('Areas to improve:', callDetails.weaknesses);\n});\n\n// Stop the call when done\ncall.stopCall();\n```\n\n## API Reference\n\n### PlatoApiClient\n\nThe main class for interacting with the Plato API.\n\n#### Constructor\n\n```typescript\nnew PlatoApiClient(config: ApiClientConfig)\n```\n\n**Parameters:**\n\n- `config.baseUrl` (string, required): The base URL of the Plato API\n- `config.jwtToken` (string, required): A pre-signed JWT token sent as the `x-client-token` header on every request\n- `config.publicKey` (string, required): Your public key for voice call functionality\n\n**Example:**\n\n```typescript\nconst client = new PlatoApiClient({\n baseUrl: 'https://your-plato-api.com',\n jwtToken: 'eyJhbGciOiJSUzI1NiIs...',\n publicKey: 'your-public-key',\n});\n```\n\n#### Methods\n\n##### setJwtToken(jwtToken: string)\n\nUpdates the JWT token for all subsequent requests. Use this when the token is refreshed or when switching user context.\n\n```typescript\nclient.setJwtToken('new-jwt-token');\n```\n\n##### clearJwtToken()\n\nRemoves the JWT token from subsequent requests.\n\n```typescript\nclient.clearJwtToken();\n```\n\n##### createSimulation(params: CreateSimulationDto)\n\nCreates a new medical training simulation. It may take a few minutes for the simulation to be ready for use.\n\n**Returns:** `Promise<{ simulationId: string, phase: CreationPhase }>`\n\n**Learning mode (`isLearning`):** Pass `isLearning: true` and their calls are excluded from `getRecommendations()` and have no post call. Defaults to `false`.\n\n##### startCall(simulationId: string)\n\nStarts a voice call with the AI persona for the specified simulation.\n\n**Returns:** Object with:\n\n- `stopCall()`: Function to end the call\n- `callId`: Unique identifier for the call\n- `notifySlideChange(slideNumber: number)`: Inform the assistant which PDF slide the user is currently viewing (see [Slide-Aware Conversations](#slide-aware-conversations))\n- `on(event: K, listener: CallEventListener)`: Subscribe to call events\n- `off(event: K, listener: CallEventListener)`: Unsubscribe from call events\n\n##### getCallDetails(callId: string)\n\nRetrieves detailed information about a completed call, including transcript, summary, recording URL, ratings, and evaluation metrics.\n\n**Parameters:**\n\n- `callId` (string): The MongoDB `_id` of the call\n\n**Returns:** `Promise` — An object containing:\n\n- `_id`: MongoDB ID of the call\n- `summary`: Summary of the conversation\n- `transcript`: Full transcript of the call\n- `recordingUrl`: URL to access the call recording\n- `rating`: User-provided rating (0-5)\n- `successEvaluation`: Boolean indicating if the call was successful\n- `score`: Overall score for the call\n- `strengths`: Array of identified strengths\n- `weaknesses`: Array of identified weaknesses\n- `metric1`, `metric2`, `metric3`: Evaluation metric names\n- `metric1Value`, `metric2Value`, `metric3Value`: Values for each metric\n- `createdAt`: Timestamp when the call was created\n- `endedAt`: Timestamp when the call ended\n- `callDurationMs`: Duration of the call in milliseconds\n- And other call-related fields\n\n**Example:**\n\n```typescript\n// After a call has ended, retrieve its details\nconst callDetails = await client.getCallDetails(call._id);\nconsole.log('Call Summary:', callDetails.summary);\n```\n\n##### deleteCall(callId: string)\n\nDeletes a single call and all associated data including messages, recommendations, and the S3 recording. Only the owner of the call (the rep who made it) can delete it.\n\n**Parameters:**\n\n- `callId` (string): The MongoDB `_id` of the call to delete\n\n**Returns:** `Promise`\n\n**Example:**\n\n```typescript\nawait client.deleteCall('507f1f77bcf86cd799439011');\n```\n\n**Note:** This action is irreversible. The call, its transcript, messages, recording, and any recommendations generated from it will be permanently removed.\n\n##### getCallRecordings(queryParams: SimulationRecordingsQueryDto)\n\nRetrieves a paginated list of call recordings for the authenticated user.\n\n**Parameters:**\n\n- `queryParams` (SimulationRecordingsQueryDto): Query parameters for filtering and pagination\n - `limit` (optional): Number of recordings per page (`5`, `10`, or `25`)\n - `page` (optional): Page number for pagination\n - `sort` (optional): Sort order (`'asc'` or `'desc'`)\n\n**Returns:** `Promise` — An array of recording objects, each containing:\n\n- `_id`: MongoDB ID of the call\n- `createdAt`: Timestamp when the call was created\n- `recordingStatus`: Status of the recording (`'STARTED'`, `'PROCESSING'`, `'FINISHED'`, or `'FAILED'`)\n\n**Example:**\n\n```typescript\n// Get the 10 most recent call recordings\nconst recordings = await client.getCallRecordings({\n limit: 10,\n page: 1,\n sort: 'desc',\n});\n\nrecordings.forEach(recording => {\n console.log(`Call ${recording._id} - Status: ${recording.recordingStatus}`);\n});\n```\n\n##### getCallRecording(callId: string)\n\nRetrieves the recording URL for a specific call.\n\n**Parameters:**\n\n- `callId` (string): The MongoDB `_id` of the call\n\n**Returns:** `Promise` — The URL to access the call recording\n\n**Example:**\n\n```typescript\n// Get the recording URL for a specific call\nconst recordingUrl = await client.getCallRecording(call._id);\nconsole.log('Recording URL:', recordingUrl);\n```\n\n##### uploadPdfSlides(file: File | Blob)\n\nUploads a PDF file for slide analysis. The file will be uploaded to S3 and analyzed asynchronously.\n\n**Parameters:**\n\n- `file` (File | Blob): The PDF file to upload\n\n**Returns:** `Promise` — The MongoDB ID of the created PDF record, which can be used to track the analysis status.\n\n**Limitations:**\n\n- **Latin-only file names:** The PDF file name must contain only Latin characters. Non-latin characters in the file name are not supported.\n- **Maximum 100 pages:** PDF files cannot exceed 100 pages.\n- **No duplicate content:** Uploading a PDF with identical content that was already uploaded by your organization throws an error. Duplicates are detected based on file content, not file name, and are scoped per organization.\n\n**Example:**\n\n```typescript\nimport { PdfAlreadyExistsError } from 'plato-sdk';\n\nconst fileInput = document.querySelector('input[type=\"file\"]') as HTMLInputElement;\nconst file = fileInput.files?.[0];\n\nif (file) {\n try {\n const pdfId = await client.uploadPdfSlides(file);\n console.log('PDF uploaded, ID:', pdfId);\n // Poll status until analysis completes\n } catch (error) {\n if (error instanceof PdfAlreadyExistsError) {\n // Inform the user this PDF already exists in their organization\n console.error(\n 'This PDF has already been uploaded by your organization. PDF ID:',\n error.pdfId\n );\n } else {\n console.error('Upload failed:', error.message);\n }\n }\n}\n```\n\n##### getSlidesAnalysis(queryParams: PdfSlidesAnalysisQueryDto)\n\nRetrieves a paginated and sorted list of PDF slide analysis records.\n\n**Parameters:**\n\n- `queryParams` (PdfSlidesAnalysisQueryDto):\n - `limit` (optional): Number of records per page\n - `page` (optional): Page number\n - `sort` (optional): Sort order (`'asc'` or `'desc'`)\n - `sortBy` (optional): Field to sort by (`'createdAt'`, `'originalFilename'`, or `'totalSlides'`)\n\n**Returns:** `Promise`\n\n**Example:**\n\n```typescript\nconst analysisList = await client.getSlidesAnalysis({\n limit: 10,\n page: 0,\n sort: 'desc',\n sortBy: 'createdAt',\n});\n```\n\n##### getSlideAnalysis(id: string)\n\nRetrieves the detailed analysis data for a specific PDF slide record, including the overview and individual slide analysis.\n\n**Parameters:**\n\n- `id` (string): The unique ID of the PDF slide record\n\n**Returns:** `Promise`\n\n**Example:**\n\n```typescript\nconst details = await client.getSlideAnalysis('pdf-slide-id');\nconsole.log('Lesson Overview:', details.lessonOverview);\n```\n\n##### deleteSlideAnalysis(id: string)\n\nDeletes a PDF slide analysis record from the database and removes the corresponding file from S3 storage.\n\n**Parameters:**\n\n- `id` (string): The unique ID of the PDF slide record to delete\n\n**Returns:** `Promise`\n\n**Example:**\n\n```typescript\nawait client.deleteSlideAnalysis('pdf-slide-id');\nconsole.log('Analysis deleted successfully');\n```\n\n##### checkPdfStatus(id: string)\n\nChecks the current processing status of a PDF slide analysis. Use this to monitor the progress of PDF analysis workflows.\n\n**Parameters:**\n\n- `id` (string): The unique ID of the PDF slide record\n\n**Returns:** `Promise<{ status: PdfSlidesStatus }>` — An object containing the current status\n\n**Available Status Values:**\n\n- `started` - PDF uploaded and record created\n- `processing` - Receiving batches of analyzed slides\n- `overview` - All slides analyzed, generating lesson overview\n- `completed` - Analysis complete and ready to view\n- `failed` - Analysis failed (currently not implemented)\n\n**Example:**\n\n```typescript\n// Check PDF analysis status\nconst { status } = await client.checkPdfStatus('pdf-slide-id');\n\nconsole.log('Current status:', status);\n```\n\n**Typical Workflow:**\n\n```typescript\n// 1. Upload PDF and get the ID immediately\nconst pdfId = await client.uploadPdfSlides(file);\nconsole.log('PDF uploaded with ID:', pdfId);\n\n// 2. Poll status until complete\nconst checkStatus = async () => {\n const { status } = await client.checkPdfStatus(pdfId);\n\n switch (status) {\n case 'pending':\n console.log('Waiting for upload confirmation...');\n break;\n case 'started':\n console.log('Upload confirmed, starting analysis...');\n break;\n case 'processing':\n console.log('Analyzing slides...');\n break;\n case 'overview':\n console.log('Generating lesson overview...');\n break;\n case 'completed':\n console.log('Analysis complete!');\n // Now fetch the full analysis\n const analysis = await client.getSlideAnalysis(pdfId);\n console.log('Lesson overview:', analysis.lessonOverview);\n return; // Stop polling\n case 'failed':\n console.log('Analysis failed');\n return; // Stop polling\n }\n\n // Check again in 3 seconds\n setTimeout(checkStatus, 3000);\n};\n\ncheckStatus();\n```\n\n##### getAssistantImages()\n\nRetrieves all available assistant images that can be used when creating a simulation.\n\n**Returns:** `Promise` — An array of assistant image objects, each containing:\n\n- `_id`: Unique identifier for the image\n- `imageUrl`: URL of the assistant image\n\n**Example:**\n\n```typescript\n// Get all available assistant images\nconst images = await client.getAssistantImages();\n```\n\n##### deleteSimulation(simulationId: string)\n\nDeletes a simulation and all associated data. This permanently removes the simulation, all its call records, and excludes it from future recommendations analysis.\n\n**Parameters:**\n\n- `simulationId` (string): The MongoDB `_id` of the simulation to delete\n\n**Returns:** `Promise`\n\n**Example:**\n\n```typescript\nawait client.deleteSimulation('507f1f77bcf86cd799439011');\n```\n\n**Note:** This action is irreversible. All calls and recordings linked to the simulation will also be deleted.\n\n##### getRecommendations()\n\nRetrieves recommendations based on the user's recent call performance. Analyzes the 5 most recent calls using a sliding window of 3 calls to identify patterns and provide actionable insights. Calls shorter than 2 minutes are excluded from analysis, as are calls made against learning-mode simulations (`isLearning: true`). No new recommendations are generated if fewer than 3 eligible calls are available.\n\n**Returns:** `Promise` — An object containing:\n\n- `recommendations`: Array of recommendation objects, each with:\n - `title`: Brief title of the recommendation\n - `description`: Detailed, actionable description\n - `priority`: Priority level (`'high'`, `'medium'`, or `'low'`)\n- `strengths`: Array of identified strengths, each with:\n - `strength`: Description of the strength\n - `frequency`: Number of calls where this strength appeared\n- `improvementAreas`: Array of areas needing improvement, each with:\n - `area`: Description of the improvement area\n - `frequency`: Number of calls where this weakness appeared\n- `summary`: A 2-3 sentence overall summary of performance trends\n- `callsAnalyzed`: Number of calls that were analyzed\n- `generatedAt`: Timestamp when the recommendations were generated\n\n**Example:**\n\n```typescript\n// Get personalized recommendations based on call history\nconst recommendations = await client.getRecommendations();\n\nconsole.log(`Analyzed ${recommendations.callsAnalyzed} calls`);\nconsole.log('Summary:', recommendations.summary);\n\n// Display high-priority recommendations\nrecommendations.recommendations\n .filter(rec => rec.priority === 'high')\n .forEach(rec => {\n console.log(`[HIGH] ${rec.title}: ${rec.description}`);\n });\n\n// Show recurring strengths\nrecommendations.strengths.forEach(s => {\n console.log(`Strength (${s.frequency} calls): ${s.strength}`);\n});\n\n// Show areas for improvement\nrecommendations.improvementAreas.forEach(area => {\n console.log(`Needs work (${area.frequency} calls): ${area.area}`);\n});\n```\n\n**Note:** This method requires the user to have at least one completed call. If no calls are found, a `BadRequestException` will be thrown.\n\n## Checking Simulation Status\n\nYou can check the current phase/status of a simulation using the `checkSimulationStatus` method. This is useful for polling the simulation creation process until it is ready or has failed.\n\n```typescript\nconst status = await client.checkSimulationStatus(simulation.simulationId);\nconsole.log('Current phase:', status.phase); // e.g., 'FINISHED', 'ERROR', etc.\n```\n\n- **Returns:** `{ phase: CreationPhase }` — The current phase of the simulation creation process.\n- **Typical usage:** Poll this method until the phase is `FINISHED` or `ERROR` before starting a call.\n\n## Simulation Persistence\n\nSimulations are persisted server-side and can be recovered after page reloads. Store the simulation ID client-side (e.g., localStorage) for quick recovery.\n\n### getSimulationDetails(simulationId: string)\n\nRetrieves detailed information about a simulation, including its original configuration.\n\n**Returns:** `Promise` containing:\n\n- `simulationId`: MongoDB ID\n- `phase`: Current creation phase\n- `assistantId`: The assistant ID (available after creation)\n- `configuration`: Original `CreateSimulationDto`\n- `simulationBriefing`: Optional `SimulationBriefingDto` with persona description, scenario context, and training objectives (available after creation phase reaches `FINISHED`)\n- `createdAt`, `updatedAt`: Timestamps\n\n**Example:**\n\n```typescript\n// Store simulation ID after creation\nconst simulation = await client.createSimulation(config);\nlocalStorage.setItem('plato_simulation_id', simulation.simulationId);\n\n// Recover simulation on page reload\nconst simulationId = localStorage.getItem('plato_simulation_id');\nif (simulationId) {\n const details = await client.getSimulationDetails(simulationId);\n\n if (details.phase !== CreationPhase.ERROR) {\n // Resume polling if still in progress\n if (details.phase !== CreationPhase.FINISHED) {\n startPolling(details.simulationId);\n }\n\n // Access simulation briefing when available\n if (details.simulationBriefing) {\n console.log('Objective:', details.simulationBriefing.objectiveTag);\n console.log('Persona:', details.simulationBriefing.personaDescription.summary);\n console.log('Scenario:', details.simulationBriefing.scenarioContext.summary);\n console.log('Training Goals:', details.simulationBriefing.trainingObjective.keyObjectives);\n }\n } else {\n localStorage.removeItem('plato_simulation_id');\n }\n}\n```\n\n### getUserSimulations()\n\nRetrieves all simulations for the authenticated user. Useful when the simulation ID is not stored locally.\n\n**Returns:** `Promise>`\n\n**Example:**\n\n```typescript\nconst simulations = await client.getUserSimulations();\nconst inProgress = simulations.find(\n sim => sim.phase !== CreationPhase.FINISHED && sim.phase !== CreationPhase.ERROR\n);\n```\n\n\n\n## Slide-Aware Conversations\n\nWhen a simulation is linked to a PDF (`pdfSlideId`), the user navigates through slides while talking to the assistant. `notifySlideChange` lets you push the current slide number to the assistant so it always has up-to-date context — without requiring the user to say \"I'm on slide 3\" out loud.\n\n### How It Works\n\nThe method sends a silent system message to the voice session. The assistant reads it as background context and never reads it aloud or reacts to it directly.\n\n```typescript\ncall.notifySlideChange(3); // tell the assistant the user is now on slide 3\n```\n\n### Recommended Pattern: Defer Until the User Speaks\n\nSending `notifySlideChange` the moment the user clicks \"Next\" works, but can cause the assistant to receive mid-conversation context updates while it is already responding. A better approach is to **hold the slide number in a pending state and flush it only when the user next starts talking**. This way the assistant always receives the update at a natural boundary, and multiple rapid navigations collapse into a single notification (the last pending slide wins).\n\n```typescript\nlet pendingSlideNumber: number | undefined;\n\nconst call = await client.startCall(simulationId);\n\n// Load and sort slides\nconst slideData = await client.getSlideAnalysis(pdfSlideId);\nconst slides = slideData.slideAnalysis?.sort((a, b) => a.slideNumber - b.slideNumber) ?? [];\nlet currentSlideIndex = 0;\n\n// Flush the pending slide the moment the user starts speaking\ncall.on('message', event => {\n if (event.type === 'transcript' && event.role === 'user' && pendingSlideNumber !== undefined) {\n call.notifySlideChange(pendingSlideNumber);\n pendingSlideNumber = undefined;\n }\n});\n\n// When the user navigates, store the slide number — don't send it yet\nfunction goToSlide(index: number): void {\n currentSlideIndex = index;\n pendingSlideNumber = slides[currentSlideIndex].slideNumber;\n}\n```\n\n## Event System\n\nThe SDK provides a comprehensive event system for managing voice calls:\n\n### Available Events\n\n- `call-start`: Triggered when a call begins\n- `call-end`: Triggered when a call ends\n- `speech-start`: Triggered when speech detection starts\n- `speech-end`: Triggered when speech detection ends\n- `message`: Triggered when a message is received (contains transcript and metadata)\n- `volume-level`: Triggered with volume level updates (number)\n- `error`: Triggered when an error occurs\n- `call-ended-reason`: Triggered just before `call-end` with the reason the call was terminated (e.g. silence timeout). Use this to show the user a contextual message immediately\n- `call-details-ready`: Triggered when post-call processing completes and call details are available (includes full `CallDTO` with transcript, summary, ratings, and evaluation)\n\n### Event Usage\n\n```typescript\n// Subscribe to events\ncall.on('message', message => {\n console.log('Transcript:', message.transcript);\n console.log('Type:', message.transcriptType); // 'final' or 'partial'\n});\n\ncall.on('volume-level', level => {\n console.log('Volume level:', level);\n});\n\ncall.on('error', error => {\n console.error('Call error:', error);\n});\n\n// Listen for call details after post-call processing\ncall.on('call-details-ready', callDetails => {\n console.log('Post-call feedback ready:', callDetails);\n});\n```\n\n## Detecting Why a Call Ended\n\nThe `call-ended-reason` event fires **just before** `call-end`, giving you the reason the call was terminated in time to update the UI before any post-call processing begins.\n\n### Usage\n\n```typescript\ncall.on('call-ended-reason', ({ reason, isInactivity }) => {\n // reason — raw string from the platform, e.g. \"silence-timed-out\"\n // isInactivity — true when reason contains \"silence\" or \"inactivity\"\n});\n```\n\n### Known Reason Values\n\n| `reason` | `isInactivity` | When it occurs |\n| --------------------- | -------------- | ------------------------------------------------------- |\n| `silence-timed-out` | `true` | No speech detected within the configured silence window |\n| `customer-ended-call` | `false` | The user clicked \"End Call\" |\n| `pipeline-error` | `false` | An internal platform error terminated the call |\n\n> **Note:** The `reason` field reflects the raw value from the underlying voice platform. New values may be introduced over time. Always handle unknown reasons gracefully by falling back to a generic message.\n\n## Automatic Post-Call Feedback\n\nThe SDK automatically fetches detailed call information after each call ends and completes post-call processing. This includes comprehensive feedback such as transcript, summary, evaluation metrics, strengths, weaknesses, and ratings.\n\n### How It Works\n\nWhen a call ends, the SDK automatically:\n\n1. Triggers the `call-end` event\n2. Processes the call on the backend (post-call analysis)\n3. Fetches complete call details\n4. Emits the `call-details-ready` event with full `CallDTO` data\n\nThis happens automatically—you don't need to manually call `getCallDetails()` after each call.\n\n### Event Lifecycle\n\n```typescript\nconst call = await client.startCall(simulationId);\n\n// 1. Call begins\ncall.on('call-start', () => {\n console.log('Call started');\n});\n\n// 2. Real-time transcript messages during the call\ncall.on('message', message => {\n console.log('Real-time:', message.transcript);\n});\n\n// 3. Call ends\ncall.on('call-end', () => {\n console.log('Call ended - processing feedback...');\n});\n\n// 4. Post-call details are automatically fetched and ready\ncall.on('call-details-ready', callDetails => {\n console.log('Post-call feedback is ready!');\n\n // Access all call details\n console.log('Summary:', callDetails.summary);\n console.log('Full Transcript:', callDetails.transcript);\n console.log('Call Duration:', callDetails.callDurationMs, 'ms');\n console.log('Success:', callDetails.successEvaluation);\n console.log('Score:', callDetails.score);\n\n // Display evaluation metrics\n console.log(`${callDetails.metric1}: ${callDetails.metric1Value}`);\n console.log(`${callDetails.metric2}: ${callDetails.metric2Value}`);\n console.log(`${callDetails.metric3}: ${callDetails.metric3Value}`);\n\n // Show strengths and areas for improvement\n callDetails.strengths?.forEach(strength => {\n console.log('✓ Strength:', strength);\n });\n\n callDetails.weaknesses?.forEach(weakness => {\n console.log('⚠ Area to improve:', weakness);\n });\n\n // Access recording\n if (callDetails.recordingUrl) {\n console.log('Recording:', callDetails.recordingUrl);\n }\n});\n```\n\n### Practical Use Cases\n\n#### 1. Display Post-Call Feedback in UI\n\n```typescript\n// Angular/React example\nasync startCall() {\n const call = await this.client.startCall(this.simulationId);\n\n // Automatically update UI when feedback is ready\n call.on('call-details-ready', callDetails => {\n this.callSummary = callDetails.summary;\n this.callScore = callDetails.score;\n this.strengths = callDetails.strengths;\n this.weaknesses = callDetails.weaknesses;\n this.showFeedbackModal = true; // Display feedback to user\n });\n}\n```\n\n#### 2. Track Performance Analytics\n\n```typescript\ncall.on('call-details-ready', callDetails => {\n // Send analytics to tracking service\n analytics.track('call_completed', {\n callId: callDetails._id,\n duration: callDetails.callDurationMs,\n score: callDetails.score,\n success: callDetails.successEvaluation,\n metrics: {\n [callDetails.metric1]: callDetails.metric1Value,\n [callDetails.metric2]: callDetails.metric2Value,\n [callDetails.metric3]: callDetails.metric3Value,\n },\n });\n});\n```\n\n#### 3. Store Call History\n\n```typescript\ncall.on('call-details-ready', async callDetails => {\n // Save to local storage or database\n const callHistory = JSON.parse(localStorage.getItem('call_history') || '[]');\n callHistory.push({\n id: callDetails._id,\n date: callDetails.createdAt,\n summary: callDetails.summary,\n score: callDetails.score,\n });\n localStorage.setItem('call_history', JSON.stringify(callHistory));\n});\n```\n\n#### 4. Generate Learning Insights\n\n```typescript\ncall.on('call-details-ready', callDetails => {\n // Aggregate insights across multiple calls\n if (callDetails.successEvaluation) {\n this.successfulCalls++;\n this.successStrategies.push(...(callDetails.strengths || []));\n } else {\n this.areasToImprove.push(...(callDetails.weaknesses || []));\n }\n\n this.updateLearningDashboard();\n});\n```\n\n### Manual Fetching (Alternative Approach)\n\nWhile the SDK automatically fetches call details after each call, you can also manually retrieve them later using the call ID:\n\n```typescript\n// Get call details at any time\nconst callDetails = await client.getCallDetails(callId);\n```\n\nThis is useful when:\n\n- Viewing historical calls\n- Refreshing data after updates\n- Building a call history view\n\n### Error Handling\n\nIf fetching call details fails after a call ends, the error is logged but does not prevent the `call-end` event from completing. The call will still end gracefully.\n\n```typescript\ncall.on('call-end', () => {\n console.log('Call ended successfully');\n // This will always fire, even if call-details-ready fails\n});\n\ncall.on('call-details-ready', callDetails => {\n // This may not fire if post-call processing fails\n // In that case, you can manually fetch later using getCallDetails()\n});\n```\n\n### Best Practices\n\n1. **Always subscribe to `call-details-ready`** to capture post-call feedback automatically\n2. **Show loading state** between `call-end` and `call-details-ready` events\n3. **Handle missing data gracefully** - some fields may be `null` or `undefined` depending on call status\n4. **Store call IDs** for later retrieval using `getCallDetails()` if needed\n5. **Use the event data** to provide immediate feedback to users rather than making additional API calls\n\n### Timing Considerations\n\n- `call-ended-reason`: Fires immediately before `call-end`, with the reason the call stopped\n- `call-end`: Fires immediately when the call stops\n- `call-details-ready`: Fires after backend processing completes (typically 2-5 seconds after call ends)\n\nPlan your UX accordingly—show a contextual end message on `call-ended-reason`, then a loading/processing state until `call-details-ready` arrives.\n\n### Call Duration and Data Availability\n\nThe quality of data returned in `call-details-ready` depends on the duration of the call:\n\n| Call duration | Behaviour |\n| ----------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| **< ~15 seconds** | `call-details-ready` fires immediately after `call-end` with whatever the database currently holds. Fields like `transcript`, `summary`, `score`, `strengths`, and `weaknesses` will typically be empty or zero — the call was too short to generate a meaningful analysis. |\n| **≥ ~15 seconds** | The SDK polls the backend until Vapi's post-call analysis is ready (transcript present), then emits `call-details-ready` with the fully populated `CallDTO`. |\n\n> **Note:** The ~15 second threshold accounts for the Vapi connection handshake (typically 1–5 seconds) plus a minimum amount of conversation time required for analysis to be generated. Always handle empty fields gracefully regardless of call length.\n\n## Data Types\n\n### CallDTO\n\nComplete call details returned by `call-details-ready` event and `getCallDetails()` method:\n\n```typescript\ninterface CallDTO {\n _id: string; // MongoDB ID of the call\n callId: string; // Vapi call ID\n assistantId: string; // ID of the AI assistant used\n summary?: string; // AI-generated summary of the conversation\n transcript?: string; // Full transcript of the call\n recordingUrl?: string; // URL to the call recording\n rating?: number; // User-provided rating (0-5)\n successEvaluation?: boolean; // Whether the call was successful\n score?: number; // Overall score for the call\n strengths?: string[]; // Array of identified strengths\n weaknesses?: string[]; // Array of areas for improvement\n metric1?: string; // Name of evaluation metric 1\n metric1Value?: number; // Value for metric 1\n metric2?: string; // Name of evaluation metric 2\n metric2Value?: number; // Value for metric 2\n metric3?: string; // Name of evaluation metric 3\n metric3Value?: number; // Value for metric 3\n createdAt: Date; // When the call was created\n endedAt?: Date; // When the call ended\n callDurationMs?: number; // Duration in milliseconds\n // Additional fields may be present depending on call status\n}\n```\n\n### CreateSimulationDto\n\nConfiguration for creating a simulation:\n\n```typescript\ninterface CreateSimulationDto {\n persona: CharacterCreateDto;\n product: ProductConfig;\n scenario: string;\n objectives?: string;\n anticipatedObjections?: string;\n imageId: string;\n avatarLanguage: AvatarLanguage;\n pdfSlideId?: string;\n isLearning?: boolean;\n}\n```\n\n### CharacterCreateDto\n\nAI persona configuration:\n\n```typescript\ninterface CharacterCreateDto {\n name: string;\n professionalProfile: ProfessionalProfileDto;\n segment: SegmentType;\n personalityAndBehaviour: PersonalityAndBehaviourDto;\n context: ContextDto;\n assistantGender?: AssistantVoiceGender;\n}\n```\n\n### SimulationDetailsDto\n\nDetailed simulation information returned by `getSimulationDetails()`:\n\n```typescript\ninterface SimulationDetailsDto {\n simulationId: string;\n phase: CreationPhase;\n assistantId: string;\n configuration?: CreateSimulationDto;\n simulationBriefing?: SimulationBriefingDto;\n createdAt: Date;\n updatedAt: Date;\n}\n```\n\n### SimulationBriefingDto\n\nStructured briefing data generated by the multi-agent system. This data provides context about the simulation's objectives, persona, and scenario:\n\n```typescript\ninterface SimulationBriefingDto {\n objectiveTag: string;\n personaDescription: PersonaDescriptionDto;\n scenarioContext: ScenarioContextDto;\n trainingObjective: TrainingObjectiveDto;\n}\n\ninterface PersonaDescriptionDto {\n summary: string;\n details: string[];\n}\n\ninterface ScenarioContextDto {\n summary: string;\n steps: string[];\n}\n\ninterface TrainingObjectiveDto {\n summary: string;\n keyObjectives: string[];\n}\n```\n\n**Example:**\n\n```typescript\nconst details = await client.getSimulationDetails(simulationId);\n\nif (details.simulationBriefing) {\n console.log('Objective:', details.simulationBriefing.objectiveTag);\n console.log('Persona:', details.simulationBriefing.personaDescription.summary);\n console.log('Scenario:', details.simulationBriefing.scenarioContext.summary);\n console.log('Training Goals:', details.simulationBriefing.trainingObjective.keyObjectives);\n}\n```\n\n**Note:** The `simulationBriefing` field is optional and will only be present for simulations created after the briefing feature was implemented.\n\n### CreationPhase\n\nEnum representing the simulation creation phases:\n\n```typescript\nenum CreationPhase {\n STARTING = 'STARTING',\n BUILD_HEADER = 'BUILD_HEADER',\n SEGMENT_SELECTED = 'SEGMENT_SELECTED',\n BUILD_CONTEXT = 'BUILD_CONTEXT',\n BUILD_PSYCHOGRAPHICS = 'BUILD_PSYCHOGRAPHICS',\n BUILD_OBJECTIVES = 'BUILD_OBJECTIVES',\n PERSONA_ASSEMBLED = 'PERSONA_ASSEMBLED',\n CORE = 'CORE',\n BOUNDARIES = 'BOUNDARIES',\n SPEECH_AND_THOUGHT = 'SPEECH_AND_THOUGHT',\n CONVERSATION_EVOLUTION = 'CONVERSATION_EVOLUTION',\n MEMORY = 'MEMORY',\n OBJECTION_HANDLING = 'OBJECTION_HANDLING',\n PERFORMANCE_EVALUATION = 'PERFORMANCE_EVALUATION',\n BEHAVIORAL_FRAMEWORKS = 'BEHAVIORAL_FRAMEWORKS',\n FINISHED = 'FINISHED',\n ERROR = 'ERROR',\n}\n```\n\n### RecommendationsResponseDto\n\nResponse object from `getRecommendations()`:\n\n```typescript\ninterface RecommendationsResponseDto {\n recommendations: RecommendationItemDto[];\n strengths: PerformancePatternDto[];\n improvementAreas: ImprovementAreaDto[];\n summary: string;\n callsAnalyzed: number;\n generatedAt: Date;\n}\n\ninterface RecommendationItemDto {\n title: string;\n description: string;\n priority: 'high' | 'medium' | 'low';\n}\n\ninterface PerformancePatternDto {\n strength: string;\n frequency: number;\n}\n\ninterface ImprovementAreaDto {\n area: string;\n frequency: number;\n}\n```\n\n### PdfSlidesDto\n\nSimplified data structure for PDF slide records (used in lists):\n\n```typescript\ninterface PdfSlidesDto {\n _id: string;\n status: PdfSlidesStatus;\n originalFilename: string;\n totalSlides?: number;\n lessonOverview?: string;\n createdAt: Date;\n updatedAt: Date;\n}\n```\n\n### PdfSlideDto\n\nDetailed data structure for a single PDF slide analysis:\n\n```typescript\ninterface PdfSlideDto {\n _id: string;\n status: PdfSlidesStatus;\n originalFilename: string;\n totalSlides?: number;\n lessonOverview?: string;\n slideAnalysis?: Array<{\n slideNumber: number;\n title: string;\n textExtraction: string;\n }>;\n createdAt: Date;\n updatedAt: Date;\n}\n```\n\n### PdfSlidesStatus\n\nEnum representing the PDF analysis workflow status:\n\n```typescript\nenum PdfSlidesStatus {\n STARTED = 'started',\n PROCESSING = 'processing',\n OVERVIEW = 'overview',\n COMPLETED = 'completed',\n FAILED = 'failed',\n}\n```\n\n### PdfSlidesAnalysisQueryDto\n\nQuery parameters for retrieving slide analysis records:\n\n```typescript\ninterface PdfSlidesAnalysisQueryDto {\n limit?: 5 | 10 | 25;\n page?: number;\n sort?: 'asc' | 'desc';\n sortBy?: 'createdAt' | 'originalFilename' | 'totalSlides';\n}\n```\n\n### AssistantImageDto\n\nData structure for assistant images:\n\n```typescript\ninterface AssistantImageDto {\n _id: string;\n imageUrl: string;\n}\n```\n\n### SegmentType\n\nEnum representing available doctor persona segments:\n\n```typescript\nenum SegmentType {\n Traditionalist = 'The Traditionalist',\n Innovator = 'The Innovator',\n PatientOrientedPhysician = 'The Patient-Oriented Physician',\n FinanciallyDrivenPrescriber = 'The Financially-Driven Prescriber',\n EvidencePurist = 'The Evidence-Purist',\n CostConsciousPrescriber = 'The Cost-Conscious Prescriber',\n}\n```\n\n### AvatarLanguage\n\nEnum representing available avatar languages:\n\n```typescript\nenum AvatarLanguage {\n English = 'en',\n German = 'de',\n Spanish = 'es',\n Italian = 'it',\n French = 'fr',\n Arabic = 'ar',\n Russian = 'ru',\n}\n```\n\n## Error Handling\n\nThe SDK throws errors for invalid configurations and API failures:\n\n```typescript\ntry {\n const client = new PlatoApiClient({\n baseUrl: 'https://api.plato.com',\n jwtToken: 'your-jwt-token',\n publicKey: 'your-public-key',\n });\n\n const simulation = await client.createSimulation(simulationConfig);\n const call = await client.startCall(simulation.simulationId);\n} catch (error) {\n console.error('Error:', error.message);\n}\n```\n\n### PDF Already Exists Error\n\nWhen a PDF with identical content has already been uploaded by your organization, `uploadPdfSlides()` throws a `PdfAlreadyExistsError`. The error exposes the `pdfId` of the existing record so you can use it directly without re-uploading.\n\n```typescript\nimport { PdfAlreadyExistsError } from 'plato-sdk';\n\ntry {\n const pdfId = await client.uploadPdfSlides(file);\n} catch (error) {\n if (error instanceof PdfAlreadyExistsError) {\n console.log('PDF already exists, using existing ID:', error.pdfId);\n } else {\n console.error('Upload failed:', error.message);\n }\n}\n```\n\n### Concurrency Limit Error\n\nWhen the platform has reached its maximum number of simultaneous active calls, `startCall()` throws a `CallConcurrencyLimitError`. This is a platform-wide limit, not user-specific. You should catch this specifically and show the user a clear message rather than a generic error.\n\n```typescript\nimport { CallConcurrencyLimitError } from 'plato-sdk';\n\nconst handleStartCall = async (simulationId: string) => {\n try {\n const call = await platoClient.startCall(simulationId);\n\n call.on('call-start', () => setCallActive(true));\n call.on('call-end', () => setCallActive(false));\n } catch (error) {\n if (error instanceof CallConcurrencyLimitError) {\n setErrorMessage(\n 'The platform has reached its maximum number of simultaneous calls. Please try again in a moment.'\n );\n } else {\n setErrorMessage('Failed to start call. Please try again.');\n }\n }\n};\n```\n\n## Support\n\nFor support and questions, please contact the development team.\n","readmeFilename":"README.md"}