chainlit
llamafile
chainlit | llamafile | |
---|---|---|
7 | 36 | |
5,535 | 15,120 | |
7.8% | 29.1% | |
9.7 | 9.6 | |
3 days ago | 5 days ago | |
TypeScript | C++ | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
chainlit
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Chat with your Github Repo using llama_index and chainlit
chainlit is open source project that makes it very easy to build frontend interfaces like chatgpt and other features that are required for conversational ai app, so we can focus on the core part and don't need to worry about basic things, and it is dead simple to work with
- Show HN: I made an app to use local AI as daily driver
- Help with conversational_qa_chain - Streamlit Messages
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AI Chatbot powered by Amazon Bedrock 🚀🤖
I have created a sample chatbot application that uses Chainlit and LangChain to showcase Amazon Bedrock.
- Chainlit: Create ChatGPT-like UIs on top of Python code
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Personal movie recommendation agent with GPT4 + Neo4J
For the interface, I'm using chainlit, a new UI library for building LLM apps, with an integration with Langchain.
- Chainlit/chainlit: Build Python LLM apps in minutes ⚡️
llamafile
- FLaNK-AIM Weekly 06 May 2024
- llamafile v0.8
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Mistral AI Launches New 8x22B Moe Model
I think the llamafile[0] system works the best. Binary works on the command line or launches a mini webserver. Llamafile offers builds of Mixtral-8x7B-Instruct, so presumably they may package this one up as well (potentially a quantized format).
You would have to confirm with someone deeper in the ecosystem, but I think you should be able to run this new model as is against a llamafile?
[0] https://github.com/Mozilla-Ocho/llamafile
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Apple Explores Home Robotics as Potential 'Next Big Thing'
Thermostats: https://www.sinopetech.com/en/products/thermostat/
I haven't tried running a local text-to-speech engine backed by an LLM to control Home Assistant. Maybe someone is working on this already?
TTS: https://github.com/SYSTRAN/faster-whisper
LLM: https://github.com/Mozilla-Ocho/llamafile/releases
LLM: https://huggingface.co/TheBloke/Nous-Hermes-2-Mixtral-8x7B-D...
It would take some tweaking to get the voice commands working correctly.
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LLaMA Now Goes Faster on CPUs
While I did not succeed in making the matmul code from https://github.com/Mozilla-Ocho/llamafile/blob/main/llamafil... work in isolation, I compared eigen, openblas, and mkl: https://gist.github.com/Dobiasd/e664c681c4a7933ef5d2df7caa87...
In this (very primitive!) benchmark, MKL was a bit better than eigen (~10%) on my machine (i5-6600).
Since the article https://justine.lol/matmul/ compared the new kernels with MLK, we can (by transitivity) compare the new kernels with Eigen this way, at least very roughly for this one use-case.
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Llamafile 0.7 Brings AVX-512 Support: 10x Faster Prompt Eval Times for AMD Zen 4
Yes, they're just ZIP files that also happen to be actually portable executables.
https://github.com/Mozilla-Ocho/llamafile?tab=readme-ov-file...
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Show HN: I made an app to use local AI as daily driver
have you seen llamafile[0]?
[0] https://github.com/Mozilla-Ocho/llamafile
- FLaNK Stack 26 February 2024
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Gemma.cpp: lightweight, standalone C++ inference engine for Gemma models
llama.cpp has integrated gemma support. So you can use llamafile for this. It is a standalone executable that is portable across most popular OSes.
https://github.com/Mozilla-Ocho/llamafile/releases
So, download the executable from the releases page under assets. You want either just main or just server. Don't get the huge ones with the model inlined in the file. The executable is about 30MB in size,
https://github.com/Mozilla-Ocho/llamafile/releases/download/...
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Ollama releases OpenAI API compatibility
The improvements in ease of use for locally hosting LLMs over the last few months have been amazing. I was ranting about how easy https://github.com/Mozilla-Ocho/llamafile is just a few hours ago [1]. Now I'm torn as to which one to use :)
1: Quite literally hours ago: https://euri.ca/blog/2024-llm-self-hosting-is-easy-now/
What are some alternatives?
langchain - 🦜🔗 Build context-aware reasoning applications
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
nitro - Create apps 10x quicker, without Javascript/HTML/CSS.
ollama-webui - ChatGPT-Style WebUI for LLMs (Formerly Ollama WebUI) [Moved to: https://github.com/open-webui/open-webui]
web-llm - Bringing large-language models and chat to web browsers. Everything runs inside the browser with no server support.
dify - Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.
LLaVA - [NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
open-webui - User-friendly WebUI for LLMs (Formerly Ollama WebUI)
llama.cpp - LLM inference in C/C++
react-llm - Easy-to-use headless React Hooks to run LLMs in the browser with WebGPU. Just useLLM().
safetensors - Simple, safe way to store and distribute tensors