RegEx-DoS
guardrails
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| RegEx-DoS | guardrails | |
|---|---|---|
| - | 13 | |
| 163 | 3,284 | |
| -0.6% | 9.8% | |
| 0.0 | 9.9 | |
| over 6 years ago | 4 days ago | |
| JavaScript | Python | |
| MIT License | Apache License 2.0 |
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RegEx-DoS
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guardrails
- Guardrails AI
- Does anyone have an example of a langchain based customer facing agent like a cashier/waitress?
- Is there a UI that can limit LLM tokens to a preset list?
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A minimal design pattern for LLM-powered microservices with FastAPI & LangChain
You're absolutely correct, and I agree that there's potentially a risk of quality loss. But likewise, since these are all intrinsically linked, it may be possible to leverage strength by combining these tasks. I'm unaware of a paper reviewing the reliability and/or performance of LLMs in this specific scenario. If you find any, do share :) With regards to generating JSON responses - there are simple ways to nudge the model and even validate it, using libraries such as https://github.com/promptslab/Promptify, https://github.com/eyurtsev/kor and https://github.com/ShreyaR/guardrails
- Ask HN: People who were laid off or quit recently, how are you doing?
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Ask HN: AI to study my DSL and then output it?
There are a couple different approaches:
- Use multi-shot prompting with something like guardrails to try prompting a commercial model until it works. [1]
- Use a local model with something with a final layer that steers token selection towards syntactically valid tokens [2]
[1] https://github.com/ShreyaR/guardrails
[2] "Structural Alignment: Modifying Transformers (like GPT) to Follow a JSON Schema" @ https://github.com/newhouseb/clownfish.
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Introducing :🤖 Megabots - State-of-the-art, production ready full-stack LLM apps made mega-easy with LangChain and FastAPI
👍 validate and correct the outputs of LLMs using guardrails
- For consistent output from vicuna 13b
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[D] Is all the talk about what GPT can do on Twitter and Reddit exaggerated or fairly accurate?
not vouching for it, but I know this is at least a thing that exists and I like the general idea: https://github.com/shreyar/guardrails
- Introducing Agents in Haystack: Make LLMs resolve complex tasks
What are some alternatives?
openzeppelin-solidity - OpenZeppelin Contracts is a library for secure smart contract development. [Moved to: https://github.com/OpenZeppelin/openzeppelin-contracts]
lmql - A language for constraint-guided and efficient LLM programming.
Themis - Easy to use cryptographic framework for data protection: secure messaging with forward secrecy and secure data storage. Has unified APIs across 14 platforms.
GPTCache - Semantic cache for LLMs. Fully integrated with LangChain and llama_index.
snyk - Snyk CLI scans and monitors your projects for security vulnerabilities. [Moved to: https://github.com/snyk/cli]
JARVIS - JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf
nsp
dynamic-gpt-ui - Dynamic UI generation with GPT-3 (OpenAI)
unix-permissions - Swiss Army knife for Unix permissions
truss - Assertions micro-library for Clojure/Script
rate-limiter-flexible - Atomic counters and rate limiting tools. Limit resource access at any scale.
ghostwheel - Hassle-free inline clojure.spec with semi-automatic generative testing and side effect detection