#Ollama

Chatd provides a secure and private solution for document interaction using local AI, ensuring all data remains on your computer. The application uses the Mistral-7B language model, simplifying setup with no extra installations required. Additionally, Chatd integrates with the Ollama LLM server for cross-platform compatibility. It manages the local LLM runner automatically for efficient document chat.

This Node.js CLI tool utilizes AI models like Llava, Gemma, and Llama for intelligent file renaming by content. Compatible with providers such as Ollama, LM Studio, and OpenAI, it offers flexible model choices and configurations. Easy installation and ffmpeg integration enable efficient video renaming. Ideal for managing images, videos, and other files, users can tailor naming conventions and languages to specific requirements.

Page Assist is an open-source Chrome extension providing a Sidebar and Web UI for engaging with Local AI models on webpages. Supporting Chromium-based browsers like Chrome, Brave, and Firefox, it offers real-time chat capabilities with webpage content. Featuring straightforward installation, it supports various features including OpenAI API endpoints. Designed with privacy in mind, this tool collects no personal data and is continuously developed for more customization and improved UI/UX, making AI model interaction straightforward and efficient.

The june project offers a local voice chatbot utilizing Ollama, Hugging Face Transformers, and Coqui TTS Toolkit. This solution ensures privacy by processing interactions locally without sending data externally. Features include various interaction modes, comprehensive installation documentation, and a FAQ section, making it suitable for secure and private local voice-assisted applications.

Ollama provides an easy-to-use framework for deploying and customizing large language models across macOS, Windows, and Linux. With a library featuring models like Llama and Phi, Ollama supports local execution and Docker deployment. Import models from GGUF, PyTorch, or Safetensors, and enjoy simple integration with prompt adjustments and model file configurations. The project also offers community-driven integrations and comprehensive documentation for APIs and command-line usage, making it perfect for developers who want to seamlessly harness the power of language models.

Oterm is a terminal client designed for managing multiple persistent chat sessions with customizable prompts and parameters. Users can integrate external tools to enhance model capabilities, using models from Ollama or their own. With multiple installation support and intuitive keyboard navigation, it offers a streamlined interface for chat management and session export.

This project provides an API that simulates Llama.cpp, facilitating the integration of Code Llama with the Continue Visual Studio Code extension. It uniquely allows local implementation of Code Llama across platforms like Windows and Linux without API keys or registration. The setup includes downloading the necessary models, installing relevant extensions, and following guided configuration steps, making it straightforward for developers using Meta's codellama.

The Ollama Python Library facilitates easy integration of chat functionalities into Python 3.8+ projects via Ollama REST API. By using function calls like chat and generate, developers can interact with models such as 'llama3.1'. The library also supports real-time streaming, custom clients, and asynchronous operations for improved application performance. Easily installable with pip, it provides efficient tools to manage, modify, and control chat models.

This open-source app supports secure interaction with privately hosted AI models such as Llama 2 and Mistral on macOS, iOS, and visionOS. Compatible with Ollama for a seamless and private conversation experience, the app features text-to-speech, markdown support, and locally stored conversation histories. Voice prompts and image attachments enable a customizable interface. Enchanted's offline capabilities ensure privacy and efficiency across iOS devices, including Vision Pro.

Transcription Stream is a self-hosted service providing offline audio transcription and speaker diarization, featuring SSH-based file handling and a user-friendly web interface. It integrates with Ollama and Mistral for advanced summarization, while Meilisearch offers quick full-text searching. Designed for integration into existing workflows, it includes an HTML5 player for file review and download, making it ideal for privacy-focused environments requiring offline operation.

This guide provides instructions to construct a Python-based voice assistant with offline capabilities. Utilizing technologies such as Whisper for speech recognition, Bark for text-to-speech synthesis, and Ollama for managing LLMs, it details the setup of essential libraries like Rich and langchain. Additionally, the guide discusses performance optimization strategies and suggests improvements like customizable prompts and multimodal capabilities for enhanced functionality.

Explore a refined language model crafted for Chinese-English use, featuring enhancements in roleplay, function calling, and math. With significantly larger datasets, it enhances performance and minimizes language mixing. Offered in multiple formats such as GGUF and BF16 for broad compatibility. Find detailed guidance for reproducing and integrating the model on Hugging Face and Ollama. Stay informed about the latest updates and enhancements in Llama3 releases.

Lumos is a Chrome extension powered by local LLMs, designed to summarize discussions, articles, and answer questions from documents using local server support. It features content parsing, multimodal capabilities, and customizable settings to streamline web interactions. Set up a local Ollama server to leverage Lumos's advanced tools and shortcuts for enhanced browsing.

The project facilitates a quick setup for local and offline use of Large Language Models, featuring a user-friendly interface inspired by ChatGPT. It supports mobile and desktop operations and includes functionalities like chat saving, model management, and code syntax highlighting. With minimal setup requirements, the tool offers deployment options on Vercel and Netlify, supports light and dark modes, and ensures efficient model switching and chat history management without needing a database.

Heat provides an intuitive interface for iOS and macOS users to interact with top LLM services. It consolidates functionality across platforms like OpenAI and Mistral, and supports local model execution with Ollama, eliminating the need for external servers. Features include image generation using models like Stable Diffusion and Dall-e, a Spotlight-style launcher, and enhanced web search. Users can easily customize model settings and services for a tailored experience. Heat continues to evolve with plans for improved on-device model execution, offering a versatile gateway to the dynamic realm of open-source LLMs.

Explore a virtual pet initiative that blends cutting-edge AI with Tamagotchi nostalgia. The project employs local LLM to animate virtual pets with interactive emotions and minds. Engage with these AI creations through ascii animations and manage the game state leveraging technologies such as Ollama and Inngest. For deployment, options include Supabase and Fly.io, allowing adaptive scaling and management. Tailored for developers exploring AI applications, this project supports diverse orchestration and deployment methods, ensuring optimal performance. Participate in an active community for collaboration and assistance.