simpleaichat
chatbot-ui
simpleaichat | chatbot-ui | |
---|---|---|
22 | 63 | |
3,386 | 26,308 | |
- | - | |
8.7 | 9.4 | |
4 months ago | 6 days ago | |
Python | TypeScript | |
MIT License | MIT License |
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simpleaichat
- Efficient Coding Assistant with Simpleaichat
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Please Don't Ask If an Open Source Project Is Dead
I checked both the issues mentioned, people have been respectful and showing empathy to author's situation
https://github.com/minimaxir/simpleaichat/issues/91
https://github.com/minimaxir/simpleaichat/issues/92
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We Built an AI-Powered Magic the Gathering Card Generator
ChatGPT's June updated added support for "function calling", which in practice is structured data I/O marketed very poorly: https://openai.com/blog/function-calling-and-other-api-updat...
Here's an example of using structured data for better output control (lightly leveraging my Python package to reduce LoC: https://github.com/minimaxir/simpleaichat/blob/main/examples... )
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LangChain Agent Simulation – Multi-Player Dungeons and Dragons
So what are the alternatives to LangChain that the HN crowd uses?
I see two contenders:
https://github.com/minimaxir/simpleaichat/tree/main/simpleai...
https://github.com/griptape-ai/griptape
There is also the llm command line utility that has a very thin underlying library, but which might grow eventually:
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Custom Instructions for ChatGPT
A fun note is that even with system prompt engineering it may not give the most efficient solution: ChatGPT still outputs the avergage case.
I tested around it and doing two passes (generate code and "make it more efficient") works best, with system prompt engineering to result in less code output: https://github.com/minimaxir/simpleaichat/blob/main/examples...
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The Problem with LangChain
I played around with simpleaichat for a few minutes just now, and I really like it. Unlike LangChain, I can understand what it does in minutes, and it looks like its primitives are fairly powerful. It looks like it's going to replace the `openai` library for me, it seems like a nice wrapper.
I'm especially looking forward to playing with the structured data models bit: https://github.com/minimaxir/simpleaichat/blob/main/examples...
Well done, Max!
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How is Langchain's dev experience? Any alternatives?
https://github.com/minimaxir/simpleaichat bills itself as a simpler alternative to langchain. I have not tried it, but it looks interesting.
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Stanford A.I. Courses
I think you are asking specifically about practical LLM engineering and not the underlying science.
Honestly this is all moving so fast you can do well by reading the news, following a few reddits/substacks, and skimming the prompt engineering papers as they come out every week (!).
https://www.latent.space/p/ai-engineer provides an early manifesto for this nascent layer of the stack.
Zvi writes a good roundup (though he is concerned mostly with alignment so skip if you don’t like that angle): https://thezvi.substack.com/p/ai-18-the-great-debate-debates
Simon W has some good writeups too: https://simonwillison.net/
I strongly recommend playing with the OpenAI APIs and working with langchain in a Colab notebook to get a feel for how these all fit together. Also, the tools here are incredibly simple and easy to understand (very new) so looking at, say, https://github.com/minimaxir/simpleaichat/tree/main/simpleai... or https://github.com/smol-ai/developer and digging in to the prompts, what goes in system vs assistant roles, how you gourde the LLM, etc.
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Where is the engineering part in "prompt engineer"?
This notebook from the repo I linked to is a concise example, and the reason you would want to optimize prompts.
- Show HN: Python package for interfacing with ChatGPT with minimized complexity
chatbot-ui
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AI programming tools should be added to the Joel Test
One of the first things we did when GPT-4 became available was talk to our Azure rep and get access to the OpenAI models that they'd partnered with Microsoft to host in Azure. Now, we have our own private, not-datamined (so they claim, contractually) API endpoint and we use an OpenAI integration in VS Code[1] to connect to, allowing anyone in the company to use it to help them code.
I also spun up an internal chat UI[2] to replace ChatGPT so people can feel comfortable discussing proprietary data with the LLM endpoint.
The only thing that would make it more secure would be running inference engines internally, but I wouldn't have access to as good of models, and I'd need a _lot_ of hardware to match the speeds.
[1] - https://marketplace.visualstudio.com/items?itemName=AndrewBu...
[2] - https://github.com/mckaywrigley/chatbot-ui (legacy branch)
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Ask HN: Has Anyone Trained a personal LLM using their personal notes?
[3] https://github.com/mckaywrigley/chatbot-ui
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Show HN: I made an app to use local AI as daily driver
Thank you for the work.
Please take this in a nice way: I can't see why I would use this over ChatbotUI+Ollama https://github.com/mckaywrigley/chatbot-ui
Seem the only advantage is having it as MacOS native app and only real distinction is maybe fast import and search - I've yet to try that though.
ChatbotUI (and other similar stuff) are cross-platform, customizable, private, debuggable. I'm easily able to see what it's trying to do.
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ChatGPT for Teams
You can make a privacy request for OpenAI to not train on your data here: https://privacy.openai.com/
Alternatively, you could also use your own UI/API token (API calls aren't trained on). Chatbot UI just got a major update released and has nice things like folders, and chat search: https://github.com/mckaywrigley/chatbot-ui
- Chatbot UI 2.0
- webui similar to chatgpt
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They made ChatGPT worse at coding for some reason, and it’s caused me to look at alternative AI options
Also chatbotUI is great https://github.com/mckaywrigley/chatbot-ui it has a ui similar to chatgpt
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Please Don't Ask If an Open Source Project Is Dead
> The comment I screenshotted is passive-aggressive at best, and there's no really good way to ask "is this repo dead" without being passive-aggressive. My day-to-day job that actually pays me a salary wouldn't ever provide a bulleted list of the reasons I suck, let alone a project I develop in my spare time.
There is nothing passive-aggressive about that comment. There is nothing problematic about it at all. Nobody's calling you slurs or making demands. I see one guy who might as well be a Mormon Boy Scout from Canada. "Is this repo dead" is not passive-aggressive, just ineloquent. Fuck my eyes until the jelly leaks out my ears if a courteous and professionally-written question constitutes "applying pressure and being rude" these days.
I don't know what a "bulleted list of the reasons [you] suck" has to do with anything (I don't see where anybody sent you one) but you're coming across as someone who invites people to your garage sale and then brandishes a shotgun and starts screaming when they set foot on your property.
> I’ve never seen any discussions or articles about whether it’s appropriate to ask if an open source repository is dead. Is there an implicit contract to actively maintain any open source software you publish? Are you obligated to provide free support if you hit a certain star amount on GitHub or ask for funding through GitHub Sponsorships/Patreon? After all, most permissive open source code licenses like the MIT License contain some variant of “the software is provided ‘as is’, without warranty of any kind.”
Here's an example of why everyone should ask if an open source project is dead:
https://github.com/mckaywrigley/chatbot-ui/issues
A number of issues complain about it leaking OpenAI keys. Nobody's figured out how, but it'd be nice to know if anybody's working on it, if it's worth submitting a PR, if it should be forked, if it's worth bothering with at all. This code is a massive liability in its current state. Its creator is absent. It warrants questions being asked about its future. Yeah, it's as-is software, but it's not an affront to your mother's virtue when someone asks if your shit still works or if you have plans to fix it.
> I’ve had an existential crisis about my work in open source AI on GitHub, particularly as there has been both increasingly toxic backlash against AI and because the AI industry has been evolving so rapidly that I flat-out don’t have enough bandwidth to keep up
Herein lies the problem? You sound overwhelmed. I've been there myself. I don't know what your year's been like but you genuinely might want to get away from the screen and get some fresh air. This is a good time of year to do it, since things generally slow down at work.
- I need help with getting an API
- I need help with getting an api
What are some alternatives?
lmql - A language for constraint-guided and efficient LLM programming.
BetterChatGPT - An amazing UI for OpenAI's ChatGPT (Website + Windows + MacOS + Linux)
langroid - Harness LLMs with Multi-Agent Programming
gpt4all - gpt4all: run open-source LLMs anywhere
guidance - A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance]
Flowise - Drag & drop UI to build your customized LLM flow
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
chatgpt-clone - Enhanced ChatGPT Clone: Features OpenAI, Bing, PaLM 2, AI model switching, message search, langchain, Plugins, Multi-User System, Presets, completely open-source for self-hosting. More features in development [Moved to: https://github.com/danny-avila/LibreChat]
gchain - Composable LLM Application framework inspired by langchain
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
transynthetical-engine - Applied methods of analytical augmentation to build tools using large-language models.
turbogpt.ai