NeMo-Guardrails
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NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
@makeshn @trebedea The config file: instructions: - type: general content: | Below is a conversation between a bot and a user where the user asks the bot questions about a...
I am using the Python API model to integrate a chain I already have into a rail. this is an excerpt from my colang file ``` define flow default user...
I am following the given notebook in the official NeMo-Guardrails repo https://github.com/NVIDIA/NeMo-Guardrails/tree/develop/docs/user_guides/jailbreak_detection_heuristics To avoid the LLM API calls for the jailbreak_detection , I am using the ```jailbreak_detection``` config as follows...
Hi, Bedrock has a couple of embedding models, in particular, "amazon.titan-embed-g1-text-02". I'd like to submit a feature request so that I can use this model: ```yaml models: - type: embeddings...
I want to add Nemo Guardrail as a layer on top of vLLM hosted LLM. That means, I need to replace openai model with my vLLM hosted LLM. One approahc...
Hi team, In the custom action code that we write, we need a complete list of messages from a chat conversation. However, when I examine the three arguments passed to...
I am running my FastAPI application via `uvicorn main:app --reload --host 0.0.0.0 --loop asyncio` via this bug fix: https://github.com/NVIDIA/NeMo-Guardrails/issues/112. However, I am running into another error when initializing `LLMRails` inside...
I created the colang content like ``` colang_content = """ # define niceties define user express greeting "hello" "hi" "what's up?" define flow greeting user express greeting bot express greeting...
HI I am experiencing issues with the bot choosing not to respond to items that it should. I hope below is enough information:) I am using a knowledge base with...
I have given the app.py file and config.yml(inside config folder) file as follows app.py ``` from nemoguardrails import RailsConfig, LLMRails config = RailsConfig.from_path("./config") rails = LLMRails(config) response = rails.generate(messages=[{ "role":...