The primary function of Kel is to enable users to interact with LLMs such as OpenAI's GPT models, Anthropic's Claude, and others through a simple command-line interface. Users can input queries directly into the terminal, and Kel will process these requests using the chosen LLM. This setup is especially beneficial for those who prefer working in a CLI environment, as it eliminates the need to switch between applications or browsers to obtain information. For example, users can ask technical questions related to coding or system commands and receive immediate assistance without disrupting their workflow.
One of the standout features of Kel is its flexibility in supporting multiple LLMs. Users have the option to bring their own API keys for various models, allowing them to choose which AI they want to interact with based on their specific needs. This adaptability means that users can switch between LLMs for different types of queries, whether they require general knowledge or specialized expertise in areas such as software engineering or data analysis.
Kel also emphasizes customization and user control. The tool allows users to configure settings through a TOML file, enabling them to adjust parameters such as default prompts, output styles, and even the specific LLM being used for queries. This level of customization ensures that users can tailor their experience to fit their personal preferences and work requirements. Additionally, Kel provides statistics related to each query, including response times and token usage, which can help users understand the efficiency of their interactions with the AI.
Another significant aspect of Kel is its ability to facilitate conversations with documents. Users can upload files and engage in dialogue about the content within those documents. This feature is particularly useful for data scientists or professionals who need quick access to information contained in lengthy reports or datasets. By querying specific sections of a document through Kel, users can extract relevant insights without manually searching through pages of text.
As for pricing, Kel is free and open-source, allowing anyone to download and use it without any associated costs. Users simply need to provide their own API keys from supported LLM providers like OpenAI or Anthropic to start using the tool. This model makes Kel an accessible resource for individuals and organizations looking to enhance their productivity without incurring additional expenses.
Key Features:
- Command-Line Interface: Provides a straightforward way for users to interact with LLMs directly from the terminal.
- Multiple LLM Support: Allows users to connect with various language models by bringing their own API keys.
- Customizable Settings: Enables adjustments through a configuration file for tailored user experiences.
- Document Interaction: Facilitates conversations about uploaded documents for efficient information retrieval.
- Performance Statistics: Displays metrics such as response time and token usage for each query.
- Free and Open Source: Available at no cost, promoting accessibility for all users.
Overall, Kel serves as a powerful tool that enhances productivity by integrating AI capabilities into the command-line environment. By providing easy access to large language models and offering customizable features, it empowers users to streamline their workflows and improve their efficiency in handling various tasks related to software development and data analysis.