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lmstudio

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ComfyUI-IF_AI_tools is a set of custom nodes for ComfyUI that allows you to generate prompts using a local Large Language Model (LLM) via Ollama. This tool enables you to enhance your image generation workflow by leveraging the power of language models.

  • Updated Sep 15, 2025
  • Python
RAGLight

RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.

  • Updated Sep 2, 2026
  • Python

MESH-API — Off-Grid AI & API Router & with MCP server & over 30 API extensions for Meshtastic & MeshCore - Seamlessly connect LM Studio, Ollama, AI Providers , 3rd-party APIs, Agents & Home Assistant to your LoRa mesh. Supports custom commands, Twilio SMS, Discord channel routing, & GPS emergency alerts via SMS, email, or Discord + SO MUCH MORE

  • Updated Jul 28, 2026
  • Python

DocMind AI is a powerful, open-source Streamlit application leveraging LlamaIndex, LangGraph, and local Large Language Models (LLMs) via Ollama, LMStudio, llama.cpp, or vLLM for advanced document analysis. Analyze, summarize, and extract insights from a wide array of file formats, securely and privately, all offline.

  • Updated Aug 19, 2026
  • Python

RetroChat is a powerful command-line interface for interacting with various AI language models. It provides a seamless experience for engaging with different chat providers while offering robust features for managing and customizing your conversations. The code in this repo is 100% AI generated. Nothing has been written by a human.

  • Updated Jul 13, 2025
  • Python

PolyCouncil is an open-source multi-model deliberation engine for LM Studio. It runs multiple LLMs in parallel, gathers their answers, scores each response using a shared rubric, and produces a final, consensus-driven result. Designed for testing, comparing, and orchestrating local models with ease.

  • Updated Mar 24, 2026
  • Python

An open-source, model-agnostic agent harness for local LLMs. Define agents in YAML (tools, memory, deny-first permissions) and run them against any OpenAI-compatible endpoint: vLLM, Ollama, LM Studio, or llama.cpp.

  • Updated Sep 21, 2026
  • Python

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