ragdoll-studio
ollama
ragdoll-studio | ollama | |
---|---|---|
11 | 220 | |
156 | 69,806 | |
- | 10.3% | |
9.6 | 9.9 | |
16 days ago | 4 days ago | |
Python | Go | |
MIT License | MIT License |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ragdoll-studio
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Ask HN: What do you use local LLMs for?
- Basic internet search (I start ollama CLI faster than I can start a browser - https://ollama.com)
- Formatting/changing text
- Troubleshooting code, esp. new frameworks/libs
- Recipes
- Data entry
- Organizing thoughts: High-level lists, comparison, classification, synonyms, jargon & nomenclature
- Learning esp. by analogy and example
RAG for:
- Website assistants (https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...)
- Game NPCs (https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...)
- Discord/Slack/forum bots (https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...)
- Character-driven storytelling and creating art in a specific style for video game loading screens, background images, avatars, website art, etc. (https://github.com/bennyschmidt/ragdoll-studio/tree/master/r...)
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Apple Introduces M4 Chip
> I always say I want AI to work offline
I'm with you, I'm most excited about this too.
Currently building an AI creative studio (make stories, art, music, videos, etc.) that runs locally/offline (https://github.com/bennyschmidt/ragdoll-studio). There is a lot of focus on cloud with LLMs but I can't see how the cost will make much sense for involved creative apps like video creation, etc. Present day users might not have high-end machines, but I think they all will pretty soon - this will make them buy them the way MMORPGs made everyone buy more RAM. Especially the artists and creators. Remember, Photoshop was once pretty difficult to run, you needed a great machine.
I can imagine an offline music/movies apps, offline search engines, back office software, etc.
- Ask HN: Web framework for custom character sheets?
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Ask HN: Ideas for LLM-Based Games
I built a JavaScript library for creating LLM-based game NPCs, here's a video demo: https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...
You drop all their knowledge into a file, like .txt. or .html and it uses RAG to learn everything in the file, so if it's a vendor things like shop inventory, prices, or if it's a storyteller/questgiver you can give it knowledge the player must uncover, etc.
It uses the LLM for natural sounding conversations and instructions ("speak in the style of..." etc.)
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Answering Legal Questions with LLMs
> You would also need to load an enormous amount of precedential case law
Very easily done. Is that it?
> lack of common sense, false conclusions
The AI tool doesn't replace the judge/DA/etc. it's just a very useful tool for them to use. Checkout the "RAG-based learning" section of this app I built (https://github.com/bennyschmidt/ragdoll-studio) there's a video that shows how you can effectively load new knowledge into it (I use LlamaIndex for RAG). For example, past cases that set legal precedents, and other information you want to be considered. It creates a database of the files you load in, so it's not making those assumptions like an LLM without RAG would. I think a human would be more error-prone than an LLM with vector DB of specific data + querying engine.
> I don't see the utility
Then you are not paying attention or haven't used LLMs that much.
> actual work involved in practicing law
This is what it's best at, and what people are already using RAG for: Reading patient medical docs, technical documentation, etc. this is precisely what humans are bad at and will offload to technology.
> actual research is required
You have not tried RAG.
> LLMs struggle to produce useful outputs
You have not tried RAG.
> LLMs are unlikely to identify issues
You have not tried RAG.
> the LLM by definition is creative analysis
You have not tried RAG.
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LLMs and the Harry Potter Problem
I've made AI assistants that are perfectly accurate with products, pricing, etc. yet still maintain a human quality: https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...
You can accomplish this with RAG.
Your overall point is taken though, the LLM itself is not enough, fine-tuning is not always feasible, and I think no matter how good an AI persona gets at, say, teaching yoga - for some yoga students it will never replace an in-person instructor.
However for a game NPC, online agent, Discord bot, etc. not to mention research, translation, tutorials, summarizing, etc. there is a lot of present day utility for LLMs.
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Show HN: Real-time video clone trained on 100h of Sam Altman startup content
Very cool app, if anyone wants to try the FOSS alternative to this check out Ragdoll Studio - https://github.com/bennyschmidt/ragdoll-studio
Create anyone you want based on a list of documents (URLs), chat with them, have them create images in their style, tell stories, etc.
(runs open models with Ollama, Stable Diffusion, etc. not OpenAI)
I would be curious what Sam Altmans people make, you can share characters here: https://ragdoll-studio.vercel.app
- Show HN: Perfect art and photography in Ragdoll Studio (FOSS AI software)
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Show HN: Ragdoll Studio (fka Arthas.AI) is the FOSS alternative to character.ai
It's a FOSS alternative because instead of using their online platform to make an account in order to interact with their characters, you instead download and run this source code without needing an account to interact with yours, and those in the community - even offline if you want.
There's more to it than just chatting with AI models - these "ragdolls" are based on RAG so they are able to have distinct personalities and scoped knowledge. They can't leak info they don't know about, can't be censored from talking about things they do know about, and can be exported and shared with others on the community site. The model itself is more like the underlying engine, where the ragdoll is a specific persona that you can deploy to a variety of tasks (starting with just chat).
I want to go beyond what character.ai is even dreaming of doing by making this into a creative suite for all things AI: Chat, storytelling, art & visual design, cinematography, CGI, music & sound effects, and so-on. It would be great to have an open-source character-focused tool for making stories, cinematics, films, music, etc. Here's an example that uses a ragdoll as an NPC in a game that has specific knowledge that the player can uncover in order to advance in the game: https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...
Thanks for the question, I will add a section on how these are fundamentally different from just chatting with ChatGPT.
ollama
- Ollama v0.1.34 Is Out
-
Ask HN: What do you use local LLMs for?
- Basic internet search (I start ollama CLI faster than I can start a browser - https://ollama.com)
- Formatting/changing text
- Troubleshooting code, esp. new frameworks/libs
- Recipes
- Data entry
- Organizing thoughts: High-level lists, comparison, classification, synonyms, jargon & nomenclature
- Learning esp. by analogy and example
RAG for:
- Website assistants (https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...)
- Game NPCs (https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...)
- Discord/Slack/forum bots (https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...)
- Character-driven storytelling and creating art in a specific style for video game loading screens, background images, avatars, website art, etc. (https://github.com/bennyschmidt/ragdoll-studio/tree/master/r...)
- FLaNK-AIM Weekly 06 May 2024
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Introducing Jan
Jan goes a step further by integrating with other local engines like LM Studio and ollama.
- Ollama v0.1.33
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Hindi-Language AI Chatbot for Enterprises Using Qdrant, MLFlow, and LangChain
# install the Ollama curl -fsSL https://ollama.com/install.sh | sh # get the llama3 model ollama pull llama2 # install the MLFlow pip install mlflow
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Create an AI prototyping environment using Jupyter Lab IDE with Typescript, LangChain.js and Ollama for rapid AI prototyping
Ollama for running LLMs locally
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Setup Llama 3 using Ollama and Open-WebUI
curl -fsSL https://ollama.com/install.sh | sh
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Ollama v0.1.33 with Llama 3, Phi 3, and Qwen 110B
Streaming is not a problem (it's just a simple flag: https://github.com/wiktor-k/llama-chat/blob/main/index.ts#L2...) but I've never used voice input.
The examples show image input though: https://github.com/ollama/ollama/blob/main/docs/api.md#reque...
Maybe you can file an issue here: https://github.com/ollama/ollama/issues
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I Said Goodbye to ChatGPT and Hello to Llama 3 on Open WebUI - You Should Too
I’m a huge fan of open source models, especially the newly release Llama 3. Because of the performance of both the large 70B Llama 3 model as well as the smaller and self-host-able 8B Llama 3, I’ve actually cancelled my ChatGPT subscription in favor of Open WebUI, a self-hostable ChatGPT-like UI that allows you to use Ollama and other AI providers while keeping your chat history, prompts, and other data locally on any computer you control.
What are some alternatives?
llama.cpp - LLM inference in C/C++
gpt4all - gpt4all: run open-source LLMs anywhere
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
llama - Inference code for Llama models
LocalAI - :robot: The free, Open Source OpenAI alternative. Self-hosted, community-driven and local-first. Drop-in replacement for OpenAI running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. It allows to generate Text, Audio, Video, Images. Also with voice cloning capabilities.
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
exllama - A more memory-efficient rewrite of the HF transformers implementation of Llama for use with quantized weights.
text-generation-inference - Large Language Model Text Generation Inference
litellm - Call all LLM APIs using the OpenAI format. Use Bedrock, Azure, OpenAI, Cohere, Anthropic, Ollama, Sagemaker, HuggingFace, Replicate (100+ LLMs)
llama-cpp-python - Python bindings for llama.cpp
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.