#python

This GitHub repo runs a 6-month experiment where ChatGPT manages a real $100 micro-cap stock portfolio daily, using trading data, strict 10% stop-losses, and weekly research to pick trades—outperforming the S&P 500 by 25% (+29% vs. +4%) in the first two months. It offers Python scripts, prompts, CSVs, performance charts, and a starter guide to run your own. You benefit by testing AI stock picking transparently with low risk, learning from logs to boost your trading skills or generate real returns.

https://github.com/LuckyOne7777/ChatGPT-Micro-Cap-Experiment

#python #agent #agent_framework #browsecomp #deep_research #futurex #gaia #hle #research_agent #search_agent #xbench

MiroThinker v1.5 is the top open-source AI search agent with a 256K context window and up to 400 tool calls per task for deep web research, code execution, and multi-step reasoning. It leads benchmarks like HLE-Text (39.2%), BrowseComp (69.8%), and GAIA (80.8%), beating other free agents at low cost. You benefit by getting accurate, real-world research help—like finding arXiv papers or solving complex queries—faster and cheaper than paid tools, with full open-source access on GitHub and Hugging Face.

https://github.com/MiroMindAI/MiroThinker

#python #large_language_models #llms #long_video_understanding #multi_modal_llms #rag #retrieval_augmented_generation

Vimo is a desktop app that lets me chat with any video, from short clips to hundreds of hours, in simple natural language. I can drag and drop videos, ask questions, find exact moments, compare multiple videos, and export useful insights, all on macOS, Windows, or Linux. Powering this is the VideoRAG algorithm, which deeply understands visual, audio, and contextual information, giving accurate answers even for very long videos. This helps me save time, understand complex content faster, and turn large video libraries into searchable, usable knowledge.

https://github.com/HKUDS/VideoRAG

#python #agent #agentic_ai #agentic_framework #agentic_workflow #ai #ai_agents #ai_companion #ai_roleplay #benchmark #framework #llm #mcp #memory #open_source #python #sandbox

MemU lets AI systems take in conversations, documents, and media, turn them into structured memories, and store them in a clear three-layer file system. It offers both fast embedding search and deeper LLM-based retrieval, works with many data types, and supports cloud or self-hosted setups with simple APIs. This helps you build AI agents that truly remember past interactions, retrieve the right context when needed, and improve over time, making your applications more accurate, personal, and efficient.

https://github.com/NevaMind-AI/memU

#python

AlpaSim is an open-source simulator that lets me test full autonomous driving systems in realistic, closed-loop virtual environments. It gives me high-quality camera and sensor data, realistic vehicle physics, and complex traffic scenarios, all configurable for my experiments. Because it is modular, Python-based, and built on microservices, I can easily plug in my own algorithms, scale across machines, and debug tricky behaviors. Built-in support for advanced driving policies, rich documentation, and sample datasets helps me quickly validate, compare, and improve my models while reducing the cost and risk of real-world testing.

https://github.com/NVlabs/alpasim

#python #n8n #n8n_workflow #workflows

n8n offers ready-made templates for creating AI agents that automate content creation and business tasks. These templates cover everything from generating social media posts and videos to researching topics and managing leads—all without requiring coding skills. By using these pre-built workflows, you can quickly launch automation projects for marketing, content production, and lead generation, saving time and reducing manual work while scaling your business operations efficiently.

https://github.com/gyoridavid/ai_agents_az

#python

ChatDev 2.0 (DevAll) is a free, zero-code platform to build and run teams of AI agents for any task—like software coding, data charts, 3D models, games, or deep research—using simple drag-and-drop workflows, no programming needed. Install with Python/uv and Node.js, then launch via web console or Python SDK for quick results. This saves you hours of manual work, cuts costs, and lets you create complex projects fast and easily, even without tech skills.

https://github.com/OpenBMB/ChatDev

#python #agent #ai #aippt #editable_pptx #langgraph #paper2slides #ppt_generator

Paper2Any turns paper PDFs, images, or text into editable diagrams, technical roadmaps, experiment plots, PPT slides, and more with one click. Key tools include Paper2Figure for scientific visuals, Paper2PPT for custom decks with table extraction, PDF2PPT for layout-perfect conversions, and AI beautification. Install via GitHub on Python 3.11+, Linux preferred; try online demo or scripts. You save hours recreating figures or slides for research, talks, or reports, getting pro-quality, customizable outputs fast.

https://github.com/OpenDCAI/Paper2Any

#python #audio #deeplearning #minicpm #python #pytorch #speech #speech_synthesis #text_to_speech #tts #tts_model #voice_cloning

VoxCPM is a free, open-source TTS tool that turns text into realistic speech without tokens, creating expressive audio that matches context and clones voices perfectly from just 3-10 seconds of sample. Download VoxCPM1.5 (800M params) from Hugging Face, install via pip, and use simple Python or CLI commands for fast synthesis (RTF 0.15 on RTX 4090) or fine-tuning your own voices. You benefit by easily making natural audiobooks, podcasts, clones, or apps with pro-quality sound—saving time and costs on voice work.

https://github.com/OpenBMB/VoxCPM

#python

Grok-1 is a powerful open-source AI model with 314 billion parameters that you can download and run on your own computer. To use it, download the model weights, install required software packages, and run a simple Python script to test it. The model uses a Mixture of Experts architecture with 64 layers and can process up to 8,192 tokens of text at once. The main benefit is that you get access to a large, capable language model under an open Apache 2.0 license, allowing you to experiment with advanced AI technology locally. However, you'll need a powerful GPU with substantial memory to run it effectively.

https://github.com/xai-org/grok-1

#python

The Compound Marketplace provides a Claude Code plugin that transforms your development workflow through a cycle of planning, working, reviewing, and documenting learnings. By spending 80% of effort on thorough planning and code review while only 20% on execution, you build knowledge that makes each subsequent task easier. Commands like `/workflowswork` executes them with task tracking, `/workflowscompound` documents patterns for reuse. This approach prevents technical debt accumulation, keeping your codebase maintainable and future changes straightforward.

https://github.com/EveryInc/compound-engineering-plugin