A collection of Python examples demonstrating the use of Mistral.rs, a Rust library for working with mistral models.
Fast and easy LLM serving for the mac.
LLM 0.17 release enables multi-modal input, allowing users to send images, audio, and video files to Large Language Models like GPT-4o, Llama, and Gemini, with a Python API and cost-effective pricing.
An analysis of the tradeoffs between building bespoke code-based agents and using major agent frameworks such as LangGraph and LlamaIndex Workflows for creating autonomous AI systems.
WilmerAI is a sophisticated middleware system designed to handle incoming prompts and route them to appropriate categories and workflows. It supports multiple Large Language Models (LLMs) and can handle a single incoming connection to many backend LLMs.
ASCVIT V1 aims to make data analysis easier by automating statistical calculations, visualizations, and interpretations.
Includes descriptive statistics, hypothesis tests, regression, time series analysis, clustering, and LLM-powered data interpretation.
- Accepts CSV or Excel files. Provides a data overview including summary statistics, variable types, and data points.
- Histograms, boxplots, pairplots, correlation matrices.
- t-tests, ANOVA, chi-square test.
- Linear, logistic, and multivariate regression.
- Time series analysis.
- k-means, hierarchical clustering, DBSCAN.
Integrates with an LLM (large language model) via Ollama for automated interpretation of statistical results.
Includes descriptive statistics, hypothesis tests, regression, time series analysis, clustering, and LLM-powered data interpretation.
- Accepts CSV or Excel files. Provides a data overview including summary statistics, variable types, and data points.
- Histograms, boxplots, pairplots, correlation matrices.
- t-tests, ANOVA, chi-square test.
- Linear, logistic, and multivariate regression.
- Time series analysis.
- k-means, hierarchical clustering, DBSCAN.
Integrates with an LLM (large language model) via Ollama for automated interpretation of statistical results.
MLX-VLM: A package for running Vision LLMs on Mac using MLX.
Learn about AI Agents, their benefits, and how to create a complete system from scratch using Python.
Parsera is a new tool for web scraping that leverages large language models (LLMs) to make the process more straightforward and efficient. It focuses on minimizing token usage for faster processing and lower costs.
Parsera is a simple and fast Python library for scraping websites using Large Language Models (LLMs). It's designed to be lightweight and minimize token usage for speed and cost efficiency.
