Learn how to use the Mistral AI to build intelligent apps, all the way from simple chat completions to advanced use-cases like RAG and function calling. Created in collaboration between Mistral AI and Scrimba.
Overview
COURSE DIFFICULTY
Skills Learned
After completing this online training course, students will be able to:
Understand Mistral’s platform and tools
Utilize Mistral’s Chat Completion API
Understand Mistral’s models
Create and manage embeddings
Utilize vector databases for data retrieval and storage
Generate and improve completions through Retrieval-Augmented Generation (RAG)
Implement and manage function calls
Handle multiple functions and arguments
Create efficient loops for repeated operations
Set up and run Mistral on a local machine
Organize and query data within vector databases
01. Welcome
- Welcome to the Course
02. Introduction
- Intro to Mistral by Sophia Yang
- Sign Up for La Plateforme
03. Mistral's Chat Completion API
- Mistral’s Chat Completion API
- Mistral’s Chat Completion API Part 2
04. Mistral's Models
- Mistral’s Models
05. Retrieval-Augmented Generation (RAG)
- What is RAG?
- What are Embeddings?
- RAG: Chunking Text with LangChain
- RAG: Completing the SplitDocument Function
- RAG: Creating Our Very First Embedding
- RAG Challenge: Embedding All Chunks and Preparing It for the Vector DB
- Set Up Your Vector Database
- Vector Databases
- RAG: Uploading Data to the Vector DB
- RAG: Query and Create Completion
- RAG: Improve the Retrieval and Complete the Generation
06. Function Calling
- Function Calling
- Function Calling: Adding a Second Function
- Function Calling: Unpacking the Function and Arguments
- Function Calling: Making the Call
- Function Calling: Updating the Messages Array
- Function Calling: Creating the Loop
07. Running Mistral Locally
- Running Mistral Locally
08. Conclusion
- Outro: Recap Mistral AI
SKILLS LEARNED
Skills Learned
After completing this online training course, students will be able to:
Understand Mistral’s platform and tools
Utilize Mistral’s Chat Completion API
Understand Mistral’s models
Create and manage embeddings
Utilize vector databases for data retrieval and storage
Generate and improve completions through Retrieval-Augmented Generation (RAG)
Implement and manage function calls
Handle multiple functions and arguments
Create efficient loops for repeated operations
Set up and run Mistral on a local machine
Organize and query data within vector databases
COURSE OUTLINE
01. Welcome
- Welcome to the Course
02. Introduction
- Intro to Mistral by Sophia Yang
- Sign Up for La Plateforme
03. Mistral's Chat Completion API
- Mistral’s Chat Completion API
- Mistral’s Chat Completion API Part 2
04. Mistral's Models
- Mistral’s Models
05. Retrieval-Augmented Generation (RAG)
- What is RAG?
- What are Embeddings?
- RAG: Chunking Text with LangChain
- RAG: Completing the SplitDocument Function
- RAG: Creating Our Very First Embedding
- RAG Challenge: Embedding All Chunks and Preparing It for the Vector DB
- Set Up Your Vector Database
- Vector Databases
- RAG: Uploading Data to the Vector DB
- RAG: Query and Create Completion
- RAG: Improve the Retrieval and Complete the Generation
06. Function Calling
- Function Calling
- Function Calling: Adding a Second Function
- Function Calling: Unpacking the Function and Arguments
- Function Calling: Making the Call
- Function Calling: Updating the Messages Array
- Function Calling: Creating the Loop
07. Running Mistral Locally
- Running Mistral Locally
08. Conclusion
- Outro: Recap Mistral AI
