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Contents

GitHub
AI Agent·2025
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AutoAgent

Jiabin Tang, Tianyu Fan +2

Lets you build, generate, and run multi-agent LLM workflows from natural-language prompts with no coding. Automatically profiles agents, creates tools/workflows, and supports multiple LLM providers plus CLI/Docker deployment.

#ai-agent#llm#ai-workflow#agent-skills#github+5
Large Language Model Tutorials·2025

Deep Dive into LLMs like ChatGPT

Andrej Karpathy·Eureka Labs

Explains how modern LLMs are trained, tokenized, post-trained, and used, from internet-scale pretraining to RLHF and tool use. The value is a coherent mental model, not a quick product tutorial.

#LLM#video#ChatGPT#tutorial
GitHub
AI Audio·2025
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IndexTTS

Yunpei Li, Xun Zhou +12·Bilibili, IndexTeam

Zero-shot, single‑reference voice cloning TTS with multilingual support (ZH/EN/JA/ES/AR), fine-grained emotion and duration control, and pronunciation hooks (Pinyin/CMU/Kana); ships model weights, Web UI and production deployment recipes for local or server use.

#tts#voice#audio#multilingual#speech+4
GitHub
AI Audio·2025
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OpenSuperWhisper

Starmel

Provides real-time, local audio recording and transcription on macOS using Whisper and Parakeet engines, with global hotkeys and hold-to-record behavior. Includes model download, microphone selection, drag-and-drop file transcription, multilingual auto-detection and Asian-language autocorrect; Apple Silicon only.

#stt#speech#audio#voice#github+3
GitHub
AI Coding·2025
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Archon

coleam00

Structures AI-assisted development as deterministic YAML workflows—planning, implementation, validation, review, and PR creation—so agent runs are repeatable and isolated. Mixes deterministic nodes with AI nodes and runs from CLI, Web UI, or chat integrations.

#ai-coding#ai-workflow#cli#gitHub#claude-code+5
GitHub
MCP Server·2025
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Vexa

Vexa-ai

Runs a self-hosted meeting bot and transcription API that joins Google Meet, Teams and Zoom and streams speaker-attributed transcripts in real time. Compiles meetings into a git-backed Markdown workspace and runs sandboxed agents on your infrastructure; Apache-2.0 and air-gap capable.

#stt#mcp-server#ai-agent#ai-api#chatbot+8
GitHub
AI Client·2025
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Local Deep Research

LearningCircuit

Performs automated, citation-backed deep research across web, arXiv, PubMed and your private documents using configurable local or cloud LLMs. Runs locally with per-user SQLCipher encryption, Docker/pip installs, LangChain integrations, and an MCP server for assistant integration.

#ollama#mcp-server#privacy#docker#embeddings+5
Hugging Face
AI Dataset·2025
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The AI CUDA Engineer Archive

Sakana AI

A curated dataset of ~30,000 CUDA kernels generated by an agentic pipeline, including reference PyTorch implementations, runtime metrics, NCU/Torch/Clang-Tidy profiles, error messages and correctness labels — released under CC-BY-4.0 for model fine-tuning and offline RL/optimization research.

#code#pytorch#pandas#huggingface#nvidia+2
GitHub
AI Client·2025
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prompt-optimizer

linshenkx

Optimizes and tests AI prompts in the browser, comparing original and rewritten versions side by side against any connected model. Runs fully client-side—keys go straight to the provider—and ships as web app, Chrome extension, and desktop builds.

#github#ai-tools#LLM#ai-image#mcp-client+1
GitHub
AI Image·2025
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PDF Craft

oomol-lab·OOMOL Lab

Converts scanned book PDFs into Markdown or EPUB using DeepSeek OCR, preserving structure, tables, formulas, footnotes, images, and generated tables of contents locally.

#github#ai-tools#ai-library
GitHub
AI Infra·2025
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DeepGEMM

Chenggang Zhao, Zhean Xu +7

High-performance CUDA tensor-core GEMM kernel library for LLM workloads: supports FP8/FP4/BF16, fused Mega MoE and MQA scoring, and runtime JIT-compiled kernels. Targets NVIDIA SM90/SM100 and PyTorch—for teams working on low-level GPU kernel optimization.

#deepseek#pytorch#nvidia#gitHub#ai-library+2
GitHub
MCP Server·2025
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Framelink MCP for Figma

GLips (Framelink)·Framelink

Feeds simplified Figma layout and style metadata to AI coding agents like Cursor and Claude Code to implement designs in one shot. Sends descriptive JSON (1px border, 16px padding) rather than code, leaving framework choices to the model.

#mcp#mcp-server#cursor#ai-coding#nodejs+2
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