Alternatives
Products that do what Open-Source Python REPL with AI Tutor for Learning and Problem-Solving does
Companion is a free, open-source web app, featuring a Python REPL environment with an AI Tutor designed to support one’s learning and problem-solving in programming. I am leveraging the Hermes 3 405B model from Nous Research, hosted on Lambda’s Inference API. It's community-driven, 100% free, and open to all. I’d love your feedback and suggestions. Here's a short video where I demo the tool: https://www.youtube.com/watch?v=4Plt_sh_cIg&ab_channel=Rahul
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2020 · github.com
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2012 · madlag.github.com
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I built Hermes, an open-source Python framework for multi-agent financial research. Most AI “equity research” demos stop at generating text. In practice, real workflows require pulling structured XBRL financials from SEC filings, extracting labeled sections like MD&A and Risk Factors, merging macro and market data, building actual Excel models with formulas, and generating investment memos in Word or PDF. Hermes is designed to handle that full pipeline end to end. It includes 35 financial data tools covering SEC EDGAR (via edgartools), FRED, Yahoo Finance market data, and RSS-based financial…
Feb 2026 · github.com
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Hi guys, I’m excited to share an update on ReproModel, an open-source toolbox designed to streamline the testing and reproduction of machine learning models. I, like many of you, have really struggled with benchmarking and comparing models, from missing code, to opaque experiment parameters slowing the process. I decided to take matters into my own hands, and created a mini-toolbox in my free time to streamline the process. The goal is to reduce the time and effort spent on replicating experiments, enabling researchers to focus on innovation rather than setup. Knowing this task is not an…
2024 · github.com
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We open-sourced catsu, a Python client for embedding APIs. The problem: every embedding provider has a different SDK with different bugs. OpenAI has undocumented token limits. VoyageAI's retry logic was broken until September. Cohere breaks downstream libraries every release. LiteLLM's embedding support is minimal. catsu provides: - One API for 11 providers (OpenAI, Voyage, Cohere, Jina, Mistral, Gemini, etc.) - Bundled database of 50+ models with pricing, dimensions, and benchmark scores - Built-in retry with exponential backoff - Automatic cost tracking per request - Full async support…
Dec 2025 · catsu.dev
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Hi, I'm working on a project that regroups all best AI (AIaaS) from different providers (GCP, AWS, Azure, DeepL, etc.) in one API (https://github.com/edenai/edenai-apis). I've got asked the question : why aren't you regrouping Open Source models (instead of proprietary APIs) into one repo? Well because it doesn't make sens to deploy and maintain large pytorch (or other framework) AI models (especially for document parsing, image and video moderation or speech recognition) in every solution that wants AI capabilities. So using APIs makes way more sens. Deployed OpenSource…
2023 · github.com
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I’ve been working on Code2Docs, an open-source CLI tool that helps developers automatically generate inline documentation (docstrings + comments) for Python code using AI. It’s built to solve a common problem I’ve faced (and seen often in teams): We code by "vibe" — fast iterations, minimal docs, and then forget what the logic was months later. Code2Docs helps bridge that gap by documenting as you go — without breaking your flow. Right now it supports function-level documentation. Planned features include: - README.md generation for projects - API endpoint docs - Database schema…
2025 · code2docs-open-source.netlify.app
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Hey Hacker News, I'm Nir, cofounder of Oboe (https://oboe.fyi), which we just launched publicly. Oboe lets anyone create a course out of a single prompt to learn about any topic. We're on a mission to democratize learning. We envision a future in which AI feeds us, making us smarter, and reignites the love of learning we all seem to have lost. Each course enables a variety of learning formats, letting you learn how you want, when you want. From deep dive articles to podcasts to games to quizzes. We want courses to feel lightweight and accessible, and to encourage following rabbit…
Sep 2025
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I have built many AI agents, and all frameworks felt so bloated, slow, and unpredictable. Therefore, I hacked together a minimal library that works with JSON/dict/kwargs definitions for each step, allowing you a simpler way to define reproducible agents. It supports concurrency for up to 1000 calls/min, giving you speed and predictability in your workflows. Install pip install flashlearn Input is a list of dictionaries Simply take user inputs, API responses, and calculations from other tools and feed them to FlashLearn. user_inputs = [{"query": "When was python launched?"}]…
2025 · github.com
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Hi everyone! I've been loving building with AI, and over the past few years I've been leaning more and more into Typescript (and bun). My team at inference.net is constantly trying to get more leverage out of AI and find ways to setup our codebase to be able to increase the level of correctness that our AI is able to write code at. This starter repo is a very opinionated way to lay out a repo to lean into AI heavily. It leverages Cloudflare Workers as a deployment target for the API (my goal is to never have to deploy an API on a AWS/Azure/GCP server ever again unless I get to a…
2025 · abeahmed.com
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Built this because I was tired of every AI tool shipping my data to someone else server n0x runs the full stack LLM inference via WebGPU, autonomous ReAct agents, RAG over your own docs, sandboxed Python execution via Pyodide all inside a single browser tab. No account No keys No backend Models download once, cache in IndexedDB permanently. Biggest challenge was context window budgeting for the agent loop and making the WASM vector search non-blocking. Happy to talk architecture. GitHub: https://github.com/ixchio/n0x | Live demo: https://n0x-three.vercel.app
Mar 2026 · n0xth.vercel.app
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2024 · codepal.vercel.app
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Library makes requests asynchronously across models, so you can spend a lot of $$ quickly if you want XD. But seriously I hope this enables folks to create and run evals (especially safety ones) a lot easier than before.
2024 · github.com
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Google Docs for Python basically. For the past 4 months, I’ve been working on a full-stack project I’m really proud of called PyTogether; a real-time collaborative Python IDE designed with beginners in mind (think Google Docs, but for Python). It’s meant for pair programming, tutoring, or just learning Python together. It’s completely free. No subscriptions, no ads, nothing. Just create an account, make a group, and start a project. Has proper code-linting, live drawings for note-taking or teaching, voice chat, an extremely intuitive UI, autosaving, and live cursors. There are no limitations…
Nov 2025 · pytogether.org
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We combined Stanford's ACE (agents learning from execution feedback) with the Reflective Language Model pattern. Instead of reading traces in a single pass, an LLM writes and runs Python in a sandbox to programmatically explore them - finding cross-trace patterns that single-pass analysis misses. The framework achieved 2x consistency improvement on τ2-bench.
Mar 2026 · github.com
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Blog post: https://spencerburleigh.com/blog/2026/02/13/crosscheck/ Repo: https://github.com/sburl/CrossCheck
Feb 2026 · github.com
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Hi HN, We needed a simple way to connect to the top AI models to experiment, prototype and evaluate them. Main features: - Connect to top LLMs in few lines of code (currenly OpenAI, Anthropic and AI21 are supported) - Response meta includes tokens processed, cost and latency standardized across the models - Multi-model support: Get completitions from different models at the same time - LLM benchmark: Eevaluate models on quality, speed and cost The benchmark uses predefine questions to test AI reasoning abilities across a range of "hard" queries. The outputs are then automatically evaulauted…
2023 · github.com
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Hi there, I've created this side project to make it easier to find interesting repositories using AI. There's still a lot of work to be done to improve it, so any suggestions for enhancements would be greatly appreciated. Thank you!
2024 · awesome-repositories.com
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I'm Tyler - the solo operator of Quanta Intellect based in Portland, Oregon. I recently participated in Nous Research's Hermes Agent Hackathon, which is where this project was born. I've used agents extensively in my workflows for the better part of the last year - the biggest pain point was always the browser. Every tool out there assumes a human operator with automation bolted on. I wanted to flip that - make the agent the primary driver and give the human a supervisory role. Enter: Vessel Browser - an Electron-based browser with 40+ MCP-native tools, persistent sessions that survive…
Mar 2026 · quantaintellect.com
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2025 · niquests.readthedocs.io
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