convostack
NeMo-Guardrails
| convostack | NeMo-Guardrails | |
|---|---|---|
| 5 | 13 | |
| 194 | 3,463 | |
| 3.1% | 7.1% | |
| 8.7 | 9.9 | |
| 11 months ago | 2 days ago | |
| TypeScript | Python | |
| MIT License | GNU General Public License v3.0 or later |
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convostack
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Run and create custom ChatGPT-like bots with OpenChat
https://github.com/ConvoStack/convostack
- Show HN: ConvoStack – Open-source chat framework for langchain
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Does anyone know the best way to put a nice UI/GUI on a LangChain app and in your opinion what is the best online VectorDB to use that's simple and flexible like ChromaDB?
I've found Pinecone very easy to work with and their free tier (if you can get on it) is solid. For the GUI, I suggest checking out https://github.com/ConvoStack/convostack. It also has a ready to go playground for chat QA using Pinecone (with a web crawler for loading your documents).
- Open-source chat widget for Langchain apps
- GitHub - ConvoStack/convostack: Open-source alternative to Intercom’s AI chatbot
NeMo-Guardrails
- NeMO Guardrails from Nvidia
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Run and create custom ChatGPT-like bots with OpenChat
- https://github.com/NVIDIA/NeMo-Guardrails/
- LangChain: The Missing Manual
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The Dual LLM pattern for building AI assistants that can resist prompt injection
Here's "jailbreak detection", in the NeMo-Guardrails project from Nvidia:
https://github.com/NVIDIA/NeMo-Guardrails/blob/327da8a42d5f8...
I.e. they ask the llm if the prompt will break the llm. (I believe that more data /some evaluation on how well this performs is intended to be released. Probably fair to call this stuff "not battle tested".)
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How To Setup a Model With Guardrails?
I have been playing around with some models locally and creating a discord bot as a fun side project, and I wanted to setup some guardrails on inputs / outputs of the bot to make sure that it isn't violating any ethical boundaries. I was going to use Nvidia's Nemo guardrails, but they only support openai currently. Are there any other good ways to control inputs?
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RasaGPT: First headless LLM chatbot built on top of Rasa, Langchain and FastAPI
Thanks, I hadn't seen those. I did find https://github.com/NVIDIA/NeMo-Guardrails earlier but haven't looked into it yet.
I'm not sure it solves the problem of restricting the information it uses though. For example, as a proof of concept for a customer, I tried providing information from a vector database as context, but GPT would still answer questions that were not provided in that context. It would base its answers on information that was already crawled from the customer website and in the model. That is concerning because the website might get updated but you can't update the model yourself (among other reasons).
- How do we prevent prompt injection in a GPT API app?
- Nvidia NeMo Guardrails – open-source guardrails to conversational systems
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Should LangChain be used in Prod?
you can use guard rails with langchain - https://github.com/NVIDIA/NeMo-Guardrails
What are some alternatives?
OpenChat - LLMs custom-chatbots console ⚡
guidance - A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance]
llama-api-server - A OpenAI API compatible REST server for llama.
langchainrb - Build LLM-powered applications in Ruby
Solara - A Pure Python, React-style Framework for Scaling Your Jupyter and Web Apps
guidance - A guidance language for controlling large language models.
magma-chat - Ruby on Rails 7-based ChatGPT Bot Platform
lmql - A language for constraint-guided and efficient LLM programming.
gpt-jargon - Jargon is a natural language programming language specified and executed by LLMs like GPT-4.
basaran - Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models.
awesome-ml - Curated list of useful LLM / Analytics / Datascience resources
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.