Vector Databases: How They Work, Use Cases & LLM Applications

Did you know you can use Voiceflow's built in Vector database to connect with 3rd Party AI models like Mistral AI?

This video explains what a vector database is, how a vector database works at a high level, and how you can use it in Voiceflow to build highly customized AI agents!

You can download the two functions used in the video here
Extract Chunks: https://developer.voiceflow.com/docs/...
Send Query to Mistral 7xB: https://developer.voiceflow.com/docs/...

Learn more about functions here:    • Functions: create reusable custom log...  

00:00 📊 Understanding Vector Databases
- Vector databases vs. traditional databases,
- Conceptual understanding of how Vector databases work,
- The role of chunking and embedding in Vector databases.
06:00 🧩 Uploading Documents and Creating Vectors
- Using Voiceflow's built-in Vector database,
- Process of uploading and chunking documents,
- How embedding turns chunks into numerical vectors.
09:00 💡 Using Voiceflow's Knowledge Base API
- Exploring the Knowledge Base API for querying chunks,
- Filtering and processing chunks based on similarity scores,
- Integration with third-party AI models like Mistral AI.
18:26 📊 Function Overview
- The presenter discusses the function setup, including loading an API key and organizing the system prompt, question, and chunks.
- Explains the process of making an API call and extracting the answer.
- Mentions additional resources for learning about functions and examples.
20:06 🛠️ Debugging Process
- Shows how debugging is helpful in identifying errors in the function.
- Corrects a mapping issue related to the API key.
- Demonstrates the successful execution of the function after debugging.
21:51 💬 Chatbot Integration
- Integrates the function into a chatbot example.
- Tests the chatbot's ability to respond to user queries.
- Highlights the customization and usage of the open-source model, Mistol.
22:22 📚 Utilizing Vector Database
- Explains how the Voiceflow Vector database can be used to send chunks to third-party models.
- Emphasizes the flexibility and cost-effectiveness of experimenting with various models.
- Offers the option to download and customize the provided functions for quicker implementation.
23:04 📋 Conclusion and Next Steps
- Wraps up the explanation of vector databases and Voiceflow usage.
- Encourages viewers to like, subscribe, and suggest topics for future videos.
- Provides a foundation for understanding vector databases and their applications in Voiceflow.

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