Alternatives
Products that do what navitusLMS does
Mobile-first LMS built for the modern, distributed workforce
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Trace LLM requests + costs with OpenTelemetry monitoring
Oct 2025
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LLMStack is a low-code platform that can be used to build LLM apps, chatbots and integrate AI experiences into existing products/workflows. It comes with everything out of the box that one needs to build LLM apps locally. It can also be used in a multi-tenant setting, making it available for everyone to use in an enterprise. Some highlights of the platform: - Chain multiple LLM models allowing for complex pipelines - Includes a vector database and necessary connectors to help enrich LLM responses with private data - App templates tailored to specific use cases to quickly build LLM apps…
2023 · github.com
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With the latest launch from Google I've added support for Gemma 3 270M, the speed for local LLM to TTS token time is incredible! This is an heavy obvious work in progress - any contributions or tips would be welcome. The idea is to have a fast moving edge model playground, and maybe have some utility (like the e reader) on the side.
2025 · github.com
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2023 · github.com
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Hi Hackernews, we're Maitreya, Prateek and Marmik. Over the past few months we've been working on building a platform to build, scale and monitor voice based LLM applications. Demo (https://www.youtube.com/watch?v=OSrOmyR7oQs) 1⃣ Open Source orchestration: We're open-sourcing our orchestration to quickly setup and create LLM based voice driven conversational applications https://github.com/bolna-ai/bolna/ 2⃣ Hosted API Platform: Exposing our managed solution via APIs to build voice driven applications…
2024 · bolna.dev
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2024 · ttsdemo.themetavoice.xyz
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Hi HN, we're Ashpreet, Eli and Yash and we're excited to share Phidata: a collection of AI Apps built with open-source tools. While helping teams build AI products, we built templates for spinning up LLM Apps quickly. Today we're open-sourcing our templates for building: - RAG LLM Apps - Autonomous LLM Apps - Multimodal LLM Apps - Data Engineering LLM Apps Templates are built with FastApi for serving, Streamlit for prototyping, PgVector for vectors and PosgreSQL for storage. Run them locally using docker and in production on AWS - with 1 command. - Github:…
2023 · github.com
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I've built an airgapped Retrieval-Augmented Generation (RAG) system for question-answering on documents, running entirely offline with local inference. Using Llama 3, Mistral, and Gemini, this setup allows secure, private NLP on your own machine. Perfect for researchers, data scientists, and developers who need to process sensitive data without cloud dependencies. Built with Llama C++, LangChain, and Streamlit, it supports quantized models and provides a sleek UI for document processing. Check it out, contribute, or suggest new features!
2024 · github.com
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2020 · github.com
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I've been building agentic apps for some large Fortune 500 companies (T-Mobile, Twilio, etc.) and developed a mental model that serves as a practical guide in building agentic apps: separate the high-level agent specific logic from low-level platform capabilities. I call it the L-MM: the Logical Mental Model for LLM applications. This mental model has not only been tremendously helpful in building agents but also helping customers think about the development process - so when I am done with a consulting engagement they can move faster across the stack and enable engineers and platform teams…
2025
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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've been using LLMs for long discovery and research chats (papers, repos, best practices), then distilling that into phased markdown (build plan + tests), then handing those phases to Codex/Claude to implement and test phase by phase. The annoying part was always the distillation and keeping docs and architecture current, so I built Unpack: a lightweight GitHub template plus docs structure and a few commands that turns conversations into phases/specs and keeps project docs up to date as the agent builds. It can also generate Mintlify-friendly end-user docs. There are other…
Feb 2026 · github.com
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2015 · github.com
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Hey everyone! we just launched Promptly apps (https://trypromptly.com/), a no-code platform to build generative AI apps and chatbots. We allow users to build web apps and chatbots by chaining LLM APIs (we call processors) from providers like OpenAI, StabilityAI, Cohere etc, without writing any code. We also let users to bring in their own data and store it in a vector database to be used for context augmentation in their apps. Users can import data from a variety of sources including urls, sitemaps, PDFs and other file types Published apps are accessible to app's users via a…
2023 · trypromptly.com
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Here is a production-first Keras-inspired LM framework, built with the advice of François Chollet (ex-Google, creator of Keras and ARC-AGI), our technical advisor. This system have already been deployed in production with our clients (which is why we have already every LLMOps practice implemented). It is also compatible with Jupyter and Marimo to integrate seamlessly in you Data Scientists workflows. You can try the code examples online on HF space and you can find more information in the documentation and FAQ. If you have any feedback for us don't hesitate to join our discord! More releases…
2025 · github.com
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Hello everyone! I am Jan, CTO and one of the creators of Pathway, the real-time data processing framework. I’m excited to share Pathway’s ready-to-use AI Pipelines, configurable with just YAML! These frameworks offer out-of-the-box solutions for AI search, RAG, and more—optimized for real-time indexing and in-memory processing. What makes it simple? YAML templates! The pipeline templates are fully customizable using YAMLs to fit your needs, from changing the data sources to the choice of the LLM model, all without touching Pathway’s Python code. Thanks to the Pathway data processing engine,…
2024 · pathway.com
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2024 · github.com
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I’ve been building LLM tooling for a small VC fund and found myself explaining the same mental model over and over to non-technical people around me: how a stateless LLM becomes a chatbot, how tool use works, what an agent is mechanically, and why context windows shape all of it. I never found a guide that covered that full chain at the level I wanted, so I wrote one. It’s nine short chapters, each building on the last. Deliberately simplified: the goal is a useful mental model, not a textbook. Feedback, corrections, and contributions welcome: github.com/ymyke/aiaiai
Apr 2026 · aiaiai.guide
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hey hn, I built an open-source Perplexity clone that can run local LLMs and cloud LLMs. It's fully self-hostable through Docker and uses ollama to support local LLMs. The demo video in the repository shows me running it locally with llama3 on my M1 Macbook Pro. I'm open to any suggestions or feedback, thanks!
2024 · github.com
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