AI Communication via WebSockets

ProductFlo provides powerful AI capabilities through its WebSocket API, enabling real-time interaction with the Haitch AI assistant and various AI-powered generation features. This page details how to integrate with these AI capabilities.

Overview

The WebSocket API supports several AI-powered features:

Haitch AI Assistant

Intelligent assistant for product development, engineering, and documentation

Idea Generation

AI-powered brainstorming and product ideation

Document Generation

Create technical documentation, specifications, and reports

Engineering AI

CAD generation, DFM analysis, and engineering assistance

Message Structure

AI communication uses the standard WebSocket message structure with specific code types:

{
  "code": "ai_code_type",     // e.g., "haitch_chat", "idea", "documentation", "engineering"
  "user_id": "user-123",
  "room_id": "product-456",
  "data": {
    // AI-specific message data
  }
}

Haitch AI Assistant

The Haitch AI assistant provides intelligent assistance for product development questions and tasks.

Sending a Haitch Chat Message

socket.send(JSON.stringify({
  "code": "haitch_chat",
  "user_id": "user-123",
  "room_id": "product-456",
  "data": {
    "query": "What materials would work best for a waterproof enclosure?",
    "doc_type": "consultation",  // Optional: Specifies type of response needed
    "source_urls": ["https://example.com/materials-guide.pdf"]  // Optional: Reference URLs
  }
}));

Receiving a Haitch Response

{
  "status": "success",
  "code": "chat_response",
  "user_id": "user-123",
  "room_id": "product-456",
  "timestamp": "2024-05-19T10:30:45Z",
  "data": {
    "message": "For a waterproof enclosure, I recommend considering these materials:\n\n1. ABS plastic with IP67 rating\n2. Polycarbonate with silicone gaskets\n3. Aluminum with O-ring seals\n\nThe choice depends on your specific requirements for impact resistance, temperature range, and manufacturing methods. Would you like me to elaborate on any of these options?",
    "sender": "haitch",
    "message_id": "msg-789",
    "sources": ["https://example.com/materials-guide.pdf"],
    "metadata": {
      "confidence": 0.92,
      "processing_time": 1.25,
      "doc_type": "consultation" 
    }
  }
}

Streaming Responses

For longer AI responses, you’ll receive the response in chunks as they’re generated (streaming is enabled by default):

socket.send(JSON.stringify({
  "code": "haitch_chat",
  "user_id": "user-123",
  "room_id": "product-456",
  "data": {
    "query": "Generate a comprehensive analysis of our thermostat design",
    "doc_type": "analysis",
    "request_id": "req-123"  // Optional: Track this specific request
  }
}));

You’ll receive multiple stream chunks with pending status:

{
  "status": "pending",
  "code": "chat_response",
  "user_id": "user-123",
  "room_id": "product-456",
  "timestamp": "2024-05-19T10:30:45Z",
  "data": {
    "message": "Here's my analysis of the thermostat design:",
    "is_complete": false,
    "sender": "haitch",
    "message_id": "stream-chunk-1"
  }
}

And when complete, you’ll receive a final message with success status:

{
  "status": "success",
  "code": "chat_response",
  "user_id": "user-123",
  "room_id": "product-456",
  "timestamp": "2024-05-19T10:30:47Z",
  "data": {
    "message": "Here's my analysis of the thermostat design: [complete response]",
    "sender": "haitch",
    "message_id": "msg-790",
    "is_complete": true,
    "sources": [],
    "metadata": {
      "processing_time": 2.5,
      "doc_type": "analysis"
    }
  }
}

Client Implementation for Streaming

let fullResponse = '';
let messageMap = new Map(); // Store chunks by message ID

socket.onmessage = (event) => {
  const data = JSON.parse(event.data);
  
  // Only process chat_response messages
  if (data.code === "chat_response") {
    // For pending status (streaming chunks)
    if (data.status === "pending") {
      // Accumulate the response text
      fullResponse += data.data.message || '';
      
      // Update UI to show progress
      updateProgressiveUI(fullResponse);
    }
    
    // For success status (final message)
    if (data.status === "success" && data.data.is_complete) {
      // Final message contains the complete response
      finalResponse = data.data.message;
      
      // Update UI with complete response
      finalizeUI(finalResponse);
      
      // Reset for next conversation
      fullResponse = '';
    }
  }
};

Document Generation

Generate professional documentation from product data and requirements.

Requesting Document Generation

socket.send(JSON.stringify({
  "code": "documentation",
  "user_id": "user-123",
  "room_id": "product-456",
  "data": {
    "query": "Generate a technical specification for our thermostat",
    "doc_type": "technical_specification",  // Type of document required
    "source_urls": ["https://example.com/thermostat_requirements.pdf"]  // Optional reference URLs
  }
}));

Receiving Generated Document

{
  "status": "success",
  "code": "documentation_response",
  "user_id": "user-123",
  "room_id": "product-456",
  "timestamp": "2024-05-19T10:31:45Z",
  "data": {
    "message": "Technical specification generated successfully",
    "doc_type": "technical_specification",
    "files": [
      {
        "file_id": "file-901",
        "file_name": "thermostat_technical_specification.pdf",
        "file_url": "https://api.productflo.io/files/thermostat_technical_specification.pdf",
        "file_type": "application/pdf",
        "file_size": 245789
      }
    ],
    "content": "# Technical Specification: Smart Thermostat\n\n## Overview\n...",
    "sources": ["https://example.com/thermostat_requirements.pdf"],
    "metadata": {
      "word_count": 2450,
      "page_count": 12,
      "processing_time": 3.2,
      "sections": ["overview", "specifications", "requirements", "testing"]
    }
  }
}

Document Types

The system supports various document types:

technical_specification: Detailed product specifications
bom: Bill of Materials
dfm_analysis: Design for Manufacturing analysis
user_manual: End-user documentation
datasheet: Technical datasheet
requirements: Requirements document
test_plan: Testing procedures and criteria
engineering_drawing: Technical drawings
compliance_documentation: Regulatory compliance docs

Idea Generation

Generate product ideas, feature suggestions, and creative solutions.

Requesting Idea Generation

socket.send(JSON.stringify({
  "code": "idea",
  "user_id": "user-123",
  "room_id": "product-456",
  "data": {
    "query": "Generate innovative ideas for a smart thermostat",
    "source_urls": ["https://example.com/smart_home_trends.pdf"],
    "doc_type": "idea_generation"  // Optional: Specifies the type of ideation
  }
}));

Receiving Generated Ideas

{
  "status": "success",
  "code": "idea_response",
  "user_id": "user-123",
  "room_id": "product-456",
  "timestamp": "2024-05-19T10:32:45Z",
  "data": {
    "message": "Here are innovative smart thermostat feature ideas:",
    "content": {
      "product_name": "Smart EcoTherm",
      "product_description": "An AI-powered smart thermostat focused on energy efficiency and user comfort",
      "features": [
        {
          "title": "AI-Powered Usage Learning",
          "description": "Machine learning algorithm that adapts to user habits and optimizes heating/cooling schedules automatically",
          "benefits": ["Energy savings", "Improved comfort", "Reduced user configuration"],
          "implementation_complexity": "medium"
        },
        {
          "title": "Multi-Zone Sensing",
          "description": "Low-cost satellite temperature sensors that connect to the main thermostat for more accurate room-by-room temperature control",
          "benefits": ["Better comfort", "Increased efficiency", "Premium feature"],
          "implementation_complexity": "high"
        }
      ],
      "market_analysis": {
        "opportunity": "Strong demand for energy-efficient smart home devices",
        "competitive_landscape": "Current offerings lack advanced learning capabilities"
      }
    },
    "sources": ["https://example.com/smart_home_trends.pdf"],
    "metadata": {
      "processing_time": 2.8,
      "feature_count": 2,
      "doc_type": "idea_generation"
    }
  }
}

Engineering AI Features

Generate CAD models, perform engineering analysis, and create technical designs.

Requesting Engineering Analysis

socket.send(JSON.stringify({
  "code": "engineering",
  "user_id": "user-123",
  "room_id": "product-456",
  "data": {
    "query": "Generate a CAD model for a wall-mount bracket for our thermostat with dimensions 100x80x20mm, made of ABS plastic",
    "doc_type": "cad_generation",  // Type of engineering request
    "source_urls": ["https://example.com/thermostat_dimensions.pdf"]  // Optional reference URLs
  }
}));

Receiving Engineering Response

{
  "status": "success",
  "code": "engineering_response",
  "user_id": "user-123",
  "room_id": "product-456",
  "timestamp": "2024-05-19T10:35:45Z",
  "data": {
    "message": "CAD model generated successfully",
    "content": {
      "description": "Wall-mount bracket for thermostat",
      "specifications": {
        "dimensions": "100x80x20mm",
        "material": "ABS plastic",
        "mounting_type": "wall_mount",
        "estimated_weight": "42g"
      },
      "manufacturing_notes": "Suitable for injection molding with standard draft angles"
    },
    "files": [
      {
        "file_id": "file-902",
        "file_name": "thermostat_bracket.step",
        "file_url": "https://api.productflo.io/files/thermostat_bracket.step",
        "file_type": "application/step",
        "file_size": 1245789
      },
      {
        "file_id": "file-903",
        "file_name": "thermostat_bracket.stl",
        "file_url": "https://api.productflo.io/files/thermostat_bracket.stl",
        "file_type": "application/stl",
        "file_size": 2345678
      },
      {
        "file_id": "file-904",
        "file_name": "thermostat_bracket_preview.png",
        "file_url": "https://api.productflo.io/files/thermostat_bracket_preview.png",
        "file_type": "image/png",
        "file_size": 245789
      }
    ],
    "sources": ["https://example.com/thermostat_dimensions.pdf"],
    "metadata": {
      "processing_time": 5.2,
      "doc_type": "cad_generation",
      "file_count": 3
    }
  }
}

Engineering Request Types

The system supports various engineering request types:

cad_generation: Generate 3D CAD models
dfm_analysis: Design for Manufacturing analysis
tolerance_analysis: Component tolerance stack-up analysis
structural_analysis: Basic structural integrity checks
thermal_analysis: Thermal performance simulation
electrical_design: Simple electrical system design
pcb_layout: PCB layout suggestions
manufacturing_process: Manufacturing process recommendations

Handling Errors

AI operations can sometimes fail due to various reasons. Error responses follow this format:

{
  "status": "error",
  "code": "system",
  "user_id": "user-123",
  "room_id": "product-456",
  "timestamp": "2024-05-19T10:35:45Z",
  "data": {
    "message": "Failed to generate CAD model",
    "details": {
      "error_code": "CAD_GENERATION_ERROR",
      "message": "Invalid specifications provided: dimensions must include all three axes"
    }
  }
}

Common AI-specific error codes:

HAITCH_CHAT_ERROR: Error in AI assistant processing
DOCUMENT_GENERATION_ERROR: Error in document generation
IDEA_GENERATION_ERROR: Error in idea generation
CAD_GENERATION_ERROR: Error in CAD model generation
ENGINEERING_ANALYSIS_ERROR: Error in engineering analysis
CONTENT_POLICY_VIOLATION: Request violates content policies
CONTEXT_LIMIT_EXCEEDED: Too much context provided

Canceling Operations

Long-running AI operations can be canceled using a cancel message:

socket.send(JSON.stringify({
  "code": "system",
  "user_id": "user-123",
  "room_id": "product-456",
  "data": {
    "message": "cancel",
    "request_id": "req-123"  // The request ID to cancel
  }
}));

You’ll receive a confirmation:

{
  "status": "success",
  "code": "system",
  "user_id": "user-123",
  "room_id": "product-456",
  "timestamp": "2024-05-19T10:36:45Z",
  "data": {
    "message": "Operation canceled",
    "request_id": "req-123"
  }
}

Providing Context with Files

To enhance AI results, you can attach files for additional context:

First, upload files using the /files REST API endpoint
Then reference the file IDs in your WebSocket message:

socket.send(JSON.stringify({
  "code": "haitch_chat",
  "user_id": "user-123",
  "room_id": "product-456",
  "data": {
    "message": "Analyze this PCB design and suggest improvements",
    "sender": "user-123",
    "attached_files": ["file-123", "file-456"],
    "metadata": {
      "priority_areas": ["power_efficiency", "thermal_management"]
    }
  }
}));

Best Practices

Use Request IDs: Always include a unique request_id for tracking AI operations, especially long-running ones
Enable Streaming: For responses that might be lengthy, enable streaming for better user experience
Provide Clear Context: Include relevant product IDs and files to improve AI accuracy
Handle Errors Gracefully: Implement proper error handling on the client side
Implement Cancellation: Allow users to cancel operations that are taking too long
Respect Rate Limits: AI operations are subject to rate limiting - implement retry logic with backoff
Validate Inputs: Ensure all required fields are properly formatted before sending

API Introduction

Authentication

Core Resources

File Management

AI Features

Integrations

WebSockets

Payments

AI Communication

AI Communication via WebSockets

Overview

Haitch AI Assistant

Idea Generation

Document Generation

Engineering AI

Message Structure

Haitch AI Assistant

Sending a Haitch Chat Message

Receiving a Haitch Response

Streaming Responses

Client Implementation for Streaming

Document Generation

Requesting Document Generation

Receiving Generated Document

Document Types

Idea Generation

Requesting Idea Generation

Receiving Generated Ideas

Engineering AI Features

Requesting Engineering Analysis

Receiving Engineering Response

Engineering Request Types

Handling Errors

Canceling Operations

Providing Context with Files

Best Practices

​AI Communication via WebSockets

​Overview

Haitch AI Assistant

Idea Generation

Document Generation

Engineering AI

​Message Structure

​Haitch AI Assistant

​Sending a Haitch Chat Message

​Receiving a Haitch Response

​Streaming Responses

​Client Implementation for Streaming

​Document Generation

​Requesting Document Generation

​Receiving Generated Document

​Document Types

​Idea Generation

​Requesting Idea Generation

​Receiving Generated Ideas

​Engineering AI Features

​Requesting Engineering Analysis

​Receiving Engineering Response

​Engineering Request Types

​Handling Errors

​Canceling Operations

​Providing Context with Files

​Best Practices

AI Communication via WebSockets

Overview

Message Structure

Haitch AI Assistant

Sending a Haitch Chat Message

Receiving a Haitch Response

Streaming Responses

Client Implementation for Streaming

Document Generation

Requesting Document Generation

Receiving Generated Document

Document Types

Idea Generation

Requesting Idea Generation

Receiving Generated Ideas

Engineering AI Features

Requesting Engineering Analysis

Receiving Engineering Response

Engineering Request Types

Handling Errors

Canceling Operations

Providing Context with Files

Best Practices