Alternatives
Products that do what Graphine – Multimodel AI Chat with Branching Conversations (Beta) does
Hello Everyone, I'm excited to announce that I'm currently developing a multi-model AI chat system featuring Branches! It's still in beta right now, but the full version will be officially released later this week. Stay tuned for updates! Thank you for your support!
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We show the potential of modern, embedded graph databases in the browser by demonstrating a fully in-browser chatbot that can perform Graph RAG using Kuzu (the graph database we're building) and WebLLM, a popular in-browser inference engine for LLMs. The post retrieves from the graph via a Text-to-Cypher pipeline that translates a user question into a Cypher query, and the LLM uses the retrieved results to synthesize a response. As LLMs get better, and WebGPU and Wasm64 become more widely adopted, we expect to be able to do more and more in the browser in combination with LLMs, so a lot of…
2025 · blog.kuzudb.com
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I made this experimental art project/game that's an LLM chat assistant, but where you're the AI. I wanted people to get a visceral sense of what it's like to answer the kinds of things that people prompt their chatbots day in and day out. If you're interested, I wrote up some more info on how I made it, including how the "user" prompts are generated with an eye for realism: https://bethechatbot.com/about Hope you enjoy it! I'd love to hear people's takeaways.
Jul 2026 · bethechatbot.com
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Hi HN, I built ChatOne while working on a project and constantly switching between AI models like GPT-4 and newer ones like Claude 3.5. I kept wondering if I was missing out on better answers, so I created ChatOne to get responses from multiple models at once and compare them easily. -Teddy
2024 · chatone.io
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Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
Oct 2025 · github.com
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Hey HN, My workflow for any complex queries is to ask it in multiple AI chats (Gemini, Claude, o3,..) in parallel and then continue the conversation with the chat response that I found the most useful. I built a simple open source app that queries 10+ AI models at once and summarizes their answers with a selected combiner AI model. There's a GIF in the github repo that shows it in action. You can try it on your local machine: https://github.com/Nexarithm/multi_model_chat If you are interested, I also made a detailed blog post on technical details, feature of the personal…
2025 · github.com
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Hi HN! I develop Monadic Chat, an open-source framework that connects language models to a Linux environment via Docker. It allows AI agents to execute code, run Jupyter notebooks, and perform web scraping in a secure, sandboxed environment. Key features: - Sandboxed environment for AI code execution - Support for multiple language models - Easy integration with existing Docker workflows I built this because I needed a reliable way to let AI agents interact with a real computing environment while maintaining security and reproducibility. Some possible use cases include: - Helping developers…
2024 · yohasebe.github.io
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I trained the 65b model on my texts so I can talk to myself. It's pretty useless as an assistant, and will only do stuff you convince it to, but I guess it's technically uncensored? I'll leave it up for a bit if you want to chat with it. I posted this to Reddit and had several hundred people talking to it. Salient points from that discussion: LLAMA 1 65b Rank 128 5 epochs Batch size 1, 256 cutoff Trained in the Oobabooga suite using bitsandbytes 4-bit quantization for the lora Loss around 1.5 seems to give the most coherent results Trained on raw text dumps that is then parsed by a crappy…
2023 · airic.serveo.net
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Hey everyone! Many of you might have come across the Mamba paper a few days ago, which introduced an LLM based on a state space model architecture. The Mamba architecture is quite useful as its complexity scales subquadratically with input length and is therefore way more efficient than transformer models: https://github.com/state-spaces/mamba I got really excited about the paper, so I decided to fine-tune the model on a chat dataset. It turns that this actually worked quite well! The model is quite suitable for casual chatting, which honestly surprised me given that it…
2023 · github.com
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Hey everyone, I've been hacking on this idea with a friend as we've been using chatgpt and other AI tools in our day to day work and find ourselves copy/pasting to each other frequently. We often share chatgpt links with each other, but it's been frustrating that they are read-only and we can't pickup the conversation or both talk to an LLM with shared context. We built a shared chatroom to explore what it'd be like to talk with multiple LLMs and humans in the same chat, and so far it feels pretty cool, but we're curious if anyone else would find it useful as well. Right now you can: -…
2025 · chord.chat
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A new open source React / JS library that makes it super simple to create conversational AI interfaces, using ChatGPT or any other LLM
2024 · nlux.ai
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