Hello, future LLM enthusiasts! Welcome to the LLM-Utility-Cookbook, a place where we'll explore, understand, and play with a myriad of tools and techniques related to Large Language Models (LLMs). This repository serves as an extension of our lectures, bridging theory and practice in the most interactive way possible.
Here's what we'll be exploring together:
- Voice to Text: We'll unravel the magic behind turning spoken words into written text.
- Text to Voice: A dive into how we can transform static text into expressive audible speech.
- Document Scan to Text: Learn how to breathe digital life into your physical documents.
- Prompts: Together, we'll optimize and manage prompts to extract the most from our LLMs.
- Memory: Get hands-on with persisting states between calls in a chain or agent.
- Indexes: We'll tinker with loading, querying, and updating external data.
- Chains: Discover the art of crafting structured sequences of calls to LLMs or other utilities.
- Agents: Learn to create agents that decide, act, and learn until a task is complete.
- Callbacks: Dive into the world of debugging and introspection with callbacks.*
To join the learning journey, clone this repository or use the google colab links and roll up your sleeves for some coding action.
Learning is a two-way street, and your inputs are highly valued!
This educational content is shared under the MIT License.