TypeChat: Integrating Language Models for Scripting and API Handling
TLDR; The VS Code Livestream introduces TypeChat, a library to work with language models and generates structured JSON output based on user input and schema. The discussion covers usage, integration with different language models, and future possibilities.
👋 Introduction and Throwback TikTok Thursday
The Livestream begins with greetings and mentions the special episode. The host introduces a segment called 'Throwback TikTok Thursday' but faces technical issues while trying to play a video.
💻 Fun Facts about JavaScript
A brief explanation about JavaScript's handling of octal values and its difference from other languages like C# and Python.
🤝 Introduction of Guest and Technical Issues
The host introduces the guest, Daniel Rosenwasser, and encounters technical issues with unmuting.
🗣️ TypeChat Introduction and Purpose
Daniel explains the purpose of TypeChat, focusing on its compatibility with TypeScript and its potential applications in working with language models and AI.
🔌 Integration with Different Language Models
A discussion about the ability of TypeChat to support various language models and the potential for expanding its compatibility to other languages.
🧩 Expanding Functionality and Scripting
The conversation shifts to the potential for TypeChat to handle scripting and the integration of multiple actions, providing examples of its usage in scenarios like a calendar app and scripting workflows.
⚙️ Scripting with Type Chat
The speaker discusses the need for scripting in order to connect steps and reuse results with type chat.
They explore the idea of constructing something to manage the flows between different steps.
An example of a calculator is used to demonstrate this concept, showcasing the ability to construct a program to perform specific tasks.
The program output is in the form of a JSON-like intermediate form, which is then type-checked and evaluated.
The gradual logical steps taken based on the input request are highlighted as a key feature.
🔄 Handling API Schemas
The discussion moves towards handling cases where the schema might exceed the context window or selectively sending portions of the schema.
The speaker mentions the investigation into subschema selection and the ability to decide which schema to pick out based on the request.
Additionally, they explore the possibility of determining which methods can be omitted when sending over the schema.
The constraints on the token window and the need for at least one round trip with an AI to handle such cases are also highlighted.
🚀 Future Developments in NLU Providers
The speaker expresses uncertainty about NLU providers but encourages reaching out to the type chat repo for future development inquiries.
They mention the open issue tracker and discussions area for filing requests and seeking clarification on NLU providers.
The audience is urged to engage with the speaker on Twitter and explore the type chat examples for practical understanding.
🎮 Use Cases with APIs
The speaker briefly mentions a music example using a Spotify API called 'chatify', allowing actions like play, print, tracks, pause, and more.
However, due to copyright concerns and potential embarrassment, the live demonstration of the music example is not feasible.
The potential of such examples to demonstrate the construction of programs is highlighted, despite the limitations.
🛠️ Tweaking API Calls
The speaker acknowledges the challenge of handling broken schemas and emphasizes the importance of thorough testing with AI inputs and outputs.
They discuss the potential for catching issues earlier on by utilizing types in actual code, and the possibility of modifying and patching endpoints in some cases.
The audience is encouraged to communicate with the team for potential feature additions that could address specific needs.
💬 Engagement and Feedback
The speaker encourages engagement with the examples provided and invites the audience to share their real-life examples and chat about how type chat can be of help.
They share their contact information and express a willingness to hear from the audience, emphasizing a collaborative and open approach to feedback and communication.
🌐 Lightning Round
The lightning round features a series of lighthearted questions, offering insights into the speaker's preferences and experiences.
Topics range from coding preferences to personal adventures, showcasing a more casual and interactive segment of the discussion.