Configuration Options
Credentials Setup
Before using any OpenAI functionality, you must configure your API credentials:-
OpenAI Account: Select or create OpenAI API credentials
- Requires a valid OpenAI API key
- Supports organization-specific API keys
- Credentials are securely encrypted and stored
-
Custom Provider Settings (Optional)
- Base URL: Override the default OpenAI API endpoint (
https://api.openai.com/v1) - API Version: Specify API version for Azure OpenAI or other compatible services
- Supports OpenAI-compatible providers like Azure OpenAI, LocalAI, or custom implementations
- Base URL: Override the default OpenAI API endpoint (
Task Selection
The OpenAI block supports multiple task types:- Create chat completion: Generate conversational responses using GPT models
- Ask Assistant: Interact with OpenAI Assistants with function calling capabilities
- Create speech: Convert text to speech using OpenAI’s TTS models
- Create transcription: Convert audio files to text using Whisper
- Generate variables: Extract structured data from text using AI
Features
Create Chat Completion
Generate AI-powered responses using OpenAI’s GPT models with advanced configuration options.
Model Configuration
- Model Selection: Choose from available GPT models (gpt-4o, gpt-4o-mini, gpt-4-turbo, etc.)
- Temperature: Control response randomness (0.0 to 2.0, default: 1.0)
- Settings: Fine-tune model behavior for specific use cases
Message Management
Configure conversation context with multiple message types:- System: Define AI behavior and instructions
- User: Represent user input and queries
- Assistant: Include AI responses for context
- Dialogue: Reference conversation history variables
Dialogue Integration
The Dialogue message type provides seamless conversation history management through thesystem_conversation variable:
Key Features:
- Automatically maintains conversation history without manual message creation
- No need to manually add user/assistant message pairs
- Built-in conversation context management
- Dialogue Variable: Use
system_conversation(automatically available) or select a custom variable - Starts By: Choose whether conversation begins with user or assistant message
system_conversation variable automatically stores and manages the conversation history in the correct format, eliminating the need to manually construct chat history arrays.

Response Mapping
Configure how AI responses are saved to variables:- Message content: Save the AI’s response text
- Total tokens: Save token usage for cost tracking
- Tool results: Save results from any executed functions (if applicable)
Ask Assistant
Interact with OpenAI Assistants that support advanced capabilities including file processing, code execution, and custom function calling.Assistant Configuration
- Assistant ID: Select from your OpenAI Assistants
- Thread Management: Automatic conversation threading
- Thread ID Variable: Maintain conversation context
- Auto-creation: New threads created automatically if none exists
- Message Input: Define the user’s query or instruction
Function Integration
Assistants can execute custom JavaScript functions:- Function Detection: Automatically fetch available functions from your assistant
- Code Execution: Write JavaScript code that runs server-side
- Variable Access: Functions can read and modify bot variables
- Parameter Handling: Receive structured parameters from the AI
- Return Values: Send function results back to the assistant
Create Speech
Convert text to natural-sounding speech using OpenAI’s text-to-speech models.Configuration Options
- Model Selection: Choose TTS model (tts-1, tts-1-hd for higher quality)
- Voice Selection: Pick from 6 available voices:
alloy: Neutral, balanced toneecho: Clear, professional soundfable: Warm, storytelling voiceonyx: Deep, authoritative tonenova: Bright, energetic voiceshimmer: Soft, gentle sound
- Input Text: The content to convert to speech (supports variables)
- URL Storage: Automatically save generated audio URL to a variable
Output Management
- Generated audio files are temporary (7-day expiration)
- Files stored in MP3 format for broad compatibility
- URLs can be used directly in audio bubble blocks
- Download files before expiration for permanent storage
Create Transcription
Transcribe audio files to text using OpenAI’s Whisper model.Configuration
- Audio URL: Provide URL to audio file (MP3, WAV, M4A, etc.)
- Model: Uses Whisper-1 for accurate speech recognition
- Result Storage: Save transcribed text to a specified variable
Supported Formats
- Multiple audio formats supported
- Automatic language detection
- High accuracy for various accents and languages
Generate Variables
Use AI to extract structured information from text and automatically populate bot variables.Configuration
- Model Selection: Choose appropriate GPT model for the task
- Extraction Prompt: Define what information to extract
- Variable Mapping: Specify which variables to populate
- Context Input: Reference user messages or other text sources
Example Usage
Prompt Configuration:Name: User’s nameEmail: Email addressPhone: Phone number (optional)Company: Company name (optional)
- Input: “My name is John Smith and my email is john@company.com”
- Result:
Name= “John Smith”,Email= “john@company.com”
Advanced Features
Function Calling and Tools
Both Chat Completion and Assistant actions support sophisticated function calling:Tool Definition
Integration Benefits
- Dynamic Data Access: Query databases, APIs, and external services
- Real-time Processing: Execute functions during conversation flow
- Context Enhancement: Enrich AI responses with live data
- Variable Management: Update bot state based on function results
Vision Support
GPT-4 Vision models can process images alongside text:Supported Models
gpt-4oand variantsgpt-4-turboseriesgpt-4-vision-preview
Image Processing
- URL Detection: Automatically identifies image URLs in messages
- Format Requirements: Images must be accessible via direct URLs
- Context Integration: Combines visual and textual information
Usage Example
Custom Provider Configuration
Azure OpenAI Integration
- Base URL:
https://your-resource.openai.azure.com/ - API Version:
2023-12-01-preview(or latest) - Authentication: Use Azure API keys
- Model Names: Use Azure deployment names
Compatible Providers
- LocalAI: Self-hosted OpenAI-compatible API
- Ollama: Local model serving with OpenAI API compatibility
- Custom Endpoints: Any OpenAI API-compatible service
Message History Management
Dialogue Variables
Thesystem_conversation variable provides automatic conversation history management:
- Automatic Management: No manual message array construction needed
- Built-in Variable:
system_conversationis automatically available in your bot - Format: Internally stored as JSON array:
[{"role": "user", "content": "Hello"}, {"role": "assistant", "content": "Hi there!"}] - Persistence: Automatically maintained between bot sessions
- Zero Configuration: Simply reference
system_conversationin the Dialogue message type
system_conversation. The system handles all message tracking automatically.
Threading (Assistants)
- Automatic Management: Thread IDs created and stored automatically
- Persistence: Conversations continue across sessions
- Cleanup: Implement thread lifecycle management as needed
Best Practices
Security Guidelines
API Key Management
- Store API keys securely in workspace credentials
- Use organization-specific keys for team access control
- Rotate keys regularly following OpenAI’s security recommendations
- Never expose API keys in client-side code or logs
Function Security
- Validate all function inputs before processing
- Implement proper error handling and logging
- Use environment variables for sensitive configuration
- Apply rate limiting to prevent abuse
Data Privacy
- Be mindful of sensitive data sent to OpenAI
- Consider data retention policies and compliance requirements
- Use Azure OpenAI for enhanced privacy and compliance needs
- Implement data anonymization where appropriate
Performance Optimization
Model Selection
- Use
gpt-4o-minifor simple tasks to reduce costs - Reserve
gpt-4ofor complex reasoning requirements - Consider model-specific capabilities (vision, function calling)
- Monitor token usage and implement cost controls
Message Optimization
- Keep system messages concise but comprehensive
- Use the
system_conversationvariable instead of manually managing chat history - Leverage the Dialogue message type for automatic conversation context
- Implement message truncation for long conversations
- Cache frequently used responses when appropriate
Streaming Configuration
- Enable streaming for better user experience
- Handle streaming gracefully in error scenarios
- Consider network conditions and user device capabilities
Testing Strategies
Development Testing
- Test with various input types and edge cases
- Validate function calling with different parameters
- Verify error handling and graceful degradation
- Test streaming behavior and interruption handling
Production Monitoring
- Monitor API response times and error rates
- Track token usage and associated costs
- Log function execution results for debugging
- Implement alerting for service availability issues
A/B Testing
- Test different model configurations
- Compare response quality across model versions
- Evaluate user satisfaction with different approaches
- Measure conversation completion rates
Cost Management
Token Optimization
- Monitor input and output token consumption
- Implement conversation length limits
- Use cheaper models for appropriate tasks
- Consider caching for repeated queries
Usage Patterns
- Set up billing alerts in OpenAI dashboard
- Implement rate limiting per user/session
- Monitor peak usage times and plan accordingly
- Consider implementing usage quotas for users
Multiple OpenAI Blocks: Tips and Tricks
When using consecutive OpenAI blocks, consider these important factors:Streaming Limitations
- Text Concatenation: Streaming disabled when AI responses are prefixed/suffixed with text
- Block Sequencing: All blocks must complete before displaying combined results
- Format Preservation: Text formatting may be affected by surrounding content
Optimization Strategies
- Sequential Processing: Plan logical flow between AI blocks
- Variable Management: Use intermediate variables for complex data flows
- User Feedback: Provide loading indicators for multi-step AI processes
- Error Handling: Implement fallbacks when sequential blocks fail
Vision Integration Details
Automatic Processing: QuickBot automatically detects and processes image URLs in messages for vision-capable models. URL Requirements:- Images must be accessible via direct HTTP/HTTPS URLs
- URLs should be isolated from surrounding text
- Supported formats: PNG, JPEG, GIF, WebP
- Vision processing only works with vision-capable models
- Non-vision models treat image URLs as plain text
Troubleshooting
Configuration Errors
”OpenAI block returned error”
Causes and Solutions:- Missing Credentials: Ensure an OpenAI account is selected
- Invalid API Key: Verify API key is valid and active
- Missing Messages: Include at least one user message or dialogue reference
- Model Access: Confirm your account has access to the selected model
- Rate Limits: Check if you’ve exceeded API rate limits
”Authentication Failed”
Resolution Steps:- Verify API key format and validity
- Check organization ID if using organizational keys
- Ensure API key has sufficient permissions
- Test API key in OpenAI’s API playground
Response Issues
Empty or No Response
Common Causes:- Quota Exceeded: Add payment method to OpenAI account
- Model Overload: Try different model or retry request
- Content Filtering: Response may have been filtered
- Token Limits: Request may exceed model’s token limit
Inconsistent Responses
Troubleshooting:- Temperature Settings: Lower temperature for more consistent outputs
- System Messages: Refine system prompts for better guidance
- Context Length: Ensure sufficient context for complex tasks
- Model Selection: Consider using more capable models for complex reasoning
Function and Assistant Issues
Function Calls Not Working
Debug Steps:- Verify function names match exactly between assistant and block
- Check function code for syntax errors
- Ensure proper parameter handling in function code
- Test function logic independently
- Review assistant configuration in OpenAI dashboard
Assistant Thread Problems
Solutions:- Thread Variable: Ensure thread ID variable is properly configured
- Thread Persistence: Verify thread ID is being saved correctly
- Assistant Access: Confirm assistant ID is valid and accessible
- Function Definitions: Check that assistant has required functions defined
Audio and Transcription Issues
Speech Generation Problems
Common Fixes:- Input Length: Ensure text is within model limits
- Voice Selection: Verify voice parameter is valid
- Model Access: Confirm access to TTS models
- File Storage: Check file upload and storage permissions
Transcription Failures
Troubleshooting:- Audio Format: Ensure audio file is in supported format
- File Size: Check if audio file exceeds size limits
- URL Accessibility: Verify audio URL is publicly accessible
- Audio Quality: Poor quality audio may affect transcription accuracy
Performance and Cost Issues
Slow Response Times
Optimization:- Model Selection: Use faster models for simple tasks
- Message Length: Reduce input length when possible
- Streaming: Enable streaming for better user experience
- Regional Endpoints: Use geographically closer endpoints
High Token Usage
Cost Control:- Message Management: Implement conversation length limits
- Model Efficiency: Use appropriate models for task complexity
- Prompt Optimization: Refine prompts to be more concise
- Response Mapping: Only save necessary response components
Custom Provider Issues
Azure OpenAI Configuration
Common Problems:- Endpoint Format: Ensure base URL follows Azure format
- API Version: Use correct API version for your deployment
- Authentication: Use Azure API key, not OpenAI key
- Model Names: Use deployment names, not OpenAI model names
Compatible Provider Setup
Troubleshooting:- API Compatibility: Verify provider implements OpenAI API specification
- Authentication: Check authentication method requirements
- Model Availability: Confirm model names and availability
- Feature Support: Verify support for required features (vision, functions, etc.)
Monitoring and Debugging
Enable Detailed Logging
- Check bot execution logs for detailed error messages
- Monitor API response codes and error details
- Track token usage patterns and costs
- Set up alerting for service availability
Testing Strategies
- Isolation Testing: Test individual components separately
- Edge Case Testing: Test with various input types and sizes
- Load Testing: Verify performance under expected usage
- Error Simulation: Test error handling and recovery
Getting Help
- OpenAI Status: Check OpenAI Status Page for service issues
- API Documentation: Reference OpenAI API docs for latest information
- Community Support: Engage with QuickBot community for implementation help
- Professional Support: Contact support for enterprise-level assistance