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LLMs

Collection of sample applications and test projects for exploring LLM and Generative AI capabilities, including custom models, scanners, and integrations.

Experiment is a feature-rich chat interface for Large Language Models (LLMs) like Anthropic, OpenAI, and Mistral.

AIlin is a tool that connects AI services, such as Perplexity.ai, with your local computer.

Terminal Chat Completion client for Google's Gemini AI models written in Go

Automated Software Developer - Cyberdev - that can work on issues in the selected repository.

Repository to store all the LLM prompt officially maintained and suggested by the DX team

GNU Artanis plugin of LLM.

SlimContext is a tool to prepare code and repo files for use in Generative AI.

Use AI to automatically generate tags for your articles.

Tracing OpenAI calls with Opik for LLM evaluation purposes.

Sandbox for HuggingFace.js, testing different open source LLMs

Groq AI Transcribe is a simple Python-based project using the Groq API to transcribe audio files. The project provides a simple and efficient way to transcribe audio files using the Groq API via the command line.

The EUC RAG Agent is a Retrieval-Augmented Generation (RAG) system built to deliver accurate and relevant responses for the fictional Egyptian University in Cairo (EUC). It uses all-MiniLM-L6-v2, gemini embedding-001, or TF-IDF vectorization for precise information retrieval and employs gemini-1.5-flash, gemini-1.5-pro, or llama2:7b models for generating concise, professional answers. The agent efficiently addresses a variety of university-related inquiries.

Ce repository comprend une série d'exemple d'intégration de LLM avec Langchain en Golang.

A lightweight document security solution that protects your confidential information when using cloud-based LLMs.

The idea is to have a set of small command line utilities to easily perform tests and operations with the LLMs of the moment. Their purpose is to encapsulate models or functionalities such as Speech to Text, Text to Speech, Vision, Batch, Chat, ...

Terminal embedding client for Hugging Face's hosted embedding models written in Go

Tools for probing the reasoning ability of LLMs and logging the logprobs (log probabilties) of generated tokens to identify weak points in an LLM's response.

Make better and cleaner commits using LLM generated drafts