privateGPT
gpt4all
Our great sponsors
| privateGPT | gpt4all | |
|---|---|---|
| 1 | 139 | |
| 50,198 | 64,046 | |
| - | 3.6% | |
| - | 9.8 | |
| about 1 month ago | 6 days ago | |
| Python | C++ | |
| Apache License 2.0 | MIT License |
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.
privateGPT
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PrivateGPT exploring the Documentation
# install developer tools xcode-select --install # create python sandbox mkdir PrivateGTP cd privateGTP/ python3 -m venv . # actiavte local context source bin/activate # privateGTP uses poetry for python module management privateGTP> pip install poetry # sync privateGTP project privateGTP> git clone https://github.com/imartinez/privateGPT # enable MPS for model loading and processing privateGTP> CMAKE_ARGS="-DLLAMA_METAL=on" pip install --force-reinstall --no-cache-dir llama-cpp-python privateGTP> cd privateGPT # Import configure python dependencies privateGTP> poetry run python3 scripts/setup # launch web interface to confirm operational on default model privateGTP> python3 -m private_gpt # navigate safari browser to http://localhost:8001/ # To bulk import documentation needed to stop the web interface as vector database not in multi-user mode privateGTP> [control] + "C" # import some PDFs privateGTP> curl "https://docs.intersystems.com/irislatest/csp/docbook/pdfs.zip" -o /tmp/pdfs.zip privateGTP> unzip /tmp/pdfs.zip -d /tmp # took a few hours to process privateGTP> make ingest /tmp/pdfs/pdfs/ # launch web interface again for query documentation privateGTP> python3 -m private_gpt
gpt4all
- Show HN: I made an app to use local AI as daily driver
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Ollama Python and JavaScript Libraries
I don’t know if Ollama can do this but https://gpt4all.io/ can.
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Ask HN: How do I train a custom LLM/ChatGPT on my own documents in Dec 2023?
Gpt4all is a local desktop app with a Python API that can be trained on your documents: https://gpt4all.io/
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WyGPT: Minimal mature GPT model in C++
The readme page is cryptic. What does 'mature' mean in this context? What is the sample text a continuation of?
Hving a gif the thing in use would be great, similar to the gpt4all readme page. (https://github.com/nomic-ai/gpt4all)
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LibreChat
Check https://github.com/nomic-ai/gpt4all instead.
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OpenAI Negotiations to Reinstate Altman Hit Snag over Board Role
"I ran performance tests on two systems, here's the results of system 1, and heres the results of system 2. Summarize the results, and build a markdown table containing x,y,z rows."
"extract the reusable functions out of this bash script"
"write me a cfssl command to generate a intermediate CA"
"What is the regex for _____"
"Here are my accomplishments over the last 6 months, summarize them into a 1 page performance report."
etc etc etc
If you're not using GPT4 or some LLM as part of your daily flow you're working too hard.
Get GPT4All (https://gpt4all.io), log into OpenAI, drop $20 on your account, get a API key, and start using GPT4.
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Darbe uzdraude naudotis CHATGPT: ar cia normalu?
offline versija, nors ir ne tokia pažengus - https://github.com/nomic-ai/gpt4all ; https://gpt4all.io/index.html
- GPT4All: An ecosystem of open-source on-edge large language models - by Nomic AI
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Why use OpenAI's ChatGPT3.5 online service, if you can instead host your own local llama?
Take a look at https://gpt4all.io, their docs are pretty awesome
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Ask HN: Are you using a local LLM? If yes, what for?
I run one. I built an iMessage-like frontend to it using plain JS and a Python websocket backend. I mostly just use it for curiosity and playing with different prompts. I only have 16GB of RAM to dedicate to it, so I use an 8B parameter model which is enough for fun and chitchat, but I don't find it good enough to replace ChatGPT.
https://github.com/nomic-ai/gpt4all
What are some alternatives?
localGPT - Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.
llama.cpp - LLM inference in C/C++
anything-llm - The all-in-one Desktop & Docker AI application with full RAG and AI Agent capabilities.
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
h2ogpt - Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://codellama.h2o.ai/
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
langchain - 🦜🔗 Build context-aware reasoning applications
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
danswer - Gen-AI Chat for Teams - Think ChatGPT if it had access to your team's unique knowledge.
TavernAI - Atmospheric adventure chat for AI language models (KoboldAI, NovelAI, Pygmalion, OpenAI chatgpt, gpt-4)