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Introduction to using Voiceflow with Mistral AI or Open Sourced AI Model
️ Setting up Voiceflow's Knowledge Base and Data Sources
Using Voiceflow Knowledge Base API and Custom Large Language Models
Leveraging Functions for Advanced API Calls
Integrating Mistral AI with Voiceflow for Custom Responses
Testing the Integrated System and Final Thoughts
Introduction to the tutorial
️ Demonstrating core functionality of the Assistants API
Explaining how Voiceflow can replicate Assistants API functionality
Comparing pros and cons of using Assistants API and Voiceflow
Creating a conversation flow in Voiceflow using memory and AI steps
Utilizing memory and AI prompts in Voiceflow for dynamic conversations
Understanding intents and entities in Voiceflow
Integrating API calls within Voiceflow for enhanced functionality
Building a conversation flow with intents, entities, and prompts
Overview of creating a voice assistant with Voiceflow
Matching intents and user input
Embedding Google Maps and using Google APIs
Using the Places API for information retrieval
Leveraging memory for conversation context
Comparison between Voiceflow and OpenAI's API
️ Improvements and future developments
Structuring Data for AI Accuracy
Formatting Documents for AI Understanding
Quality Over Quantity in Data Sources
Injecting FAQs for Enhanced Responses
️ Modifying Knowledge Base Settings for Optimization
Optimizing Chunk Limit for AI Accuracy
Utilizing System Prompts for AI Instruction
Testing Improved Voiceflow Assistant
Introduction to Twilio SMS Integration
Setting up the Development Environment
Running the Integration Locally and Enro Setup
Twilio Webhook Configuration
Handling SMS Messages
️ *Handling Images with OpenAI Vision API
Code explanation for SMS integration
️ *Using an image in the conversation
Handling user requests for image generation
Debugging and testing the integration
Wrapping up and running the integration