I Forked Karpathy's LLM Council project... The Result is INSANE! 🚀
Introduction to User Experience Project
Overview of the Project
- Jacob introduces a project focused on user experience, inspired by Andre Kapathy's concept of "vibe coding."
- The project utilizes a tool called LLM Council, which allows users to query multiple language models (LLMs) and receive peer-reviewed answers.
Functionality of LLM Council
- The original tool requires installation and configuration, making it less user-friendly for casual experimentation.
- Jacob demonstrates the user interface where multiple models provide their answers to a question, followed by peer ranking.
Enhancements Made: Search Capability and More
Initial Limitations Observed
- Jacob notes that responses from the models were limited due to their training data cutoffs, particularly regarding current events like the AI bubble.
Upgrades Implemented
- He aimed to enhance the tool with search capabilities but ended up adding more features through what he calls "vibe product management" or VIPMing.
Introducing LLM Council Plus
New Features Added
- Jacob presents his fork of the original tool named "LLM Council Plus," which includes additional functionalities beyond the original version.
Visual Enhancements
- A visual representation shows participants in the council, including a designated chairman for decision-making.
User-Friendly Configuration Options
API Key Management
- A settings page has been added for easier management of LLM API keys without needing complex configurations.
Local Model Support
- Users can now utilize local models alongside paid APIs, allowing for side-by-side comparisons during testing.
Advanced Customization Features
System Prompt Control
- The application allows customization of system prompts sent to models, enabling varied response styles based on user-defined parameters.
Creativity Controls
- Users can adjust creativity levels (temperature settings), influencing how conservative or creative model responses are.
User Control and Search Features in AI Models
Overview of User Control
- The interface allows users to have full control over various stages, including a reset option to revert settings to default.
- Multiple search engines can be integrated, such as DuckDuckGo (limited free access), Tavi (requires API keys), Brave Search, and Gina AI for article retrieval.
Challenges with Information Retrieval
- Some websites block certain services, leading to truncated responses; however, many sites still provide well-formatted AI responses.
- Users can create unique councils with pre-selected models that can be exported or imported for future use.
Configuration and Model Selection
- Users can select specific providers like OpenRouter and filter for free models while being warned about potential rate limits when using multiple free models from one provider.
- There is a batching feature for adding multiple council members but caution is advised due to possible errors.
Interactive Features in the New Chat Interface
Enhanced Interaction Capabilities
- A new feature allows users to enable or disable search functionality during chats, providing flexibility in interaction.
- Users can ask questions across multiple models without ratings initially, allowing for unbiased comparisons of responses.
Peer Ranking System
- After receiving answers, there is a peer ranking stage where each model's response is evaluated against others.
- A visual leaderboard displays the rankings of different models based on their performance in answering queries.
Future Enhancements and Ideas
- The speaker expresses interest in developing a local arena for ongoing queries but acknowledges time constraints limiting further development.