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Tooling and frameworks to support building tools that utilize LLM agents

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awesome-llm-utilities

Tooling and frameworks to support building tools that utilize LLM agents

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Agent orchestration, multi-step planning

Coding agents, Implicitly defined tools, Tools for Developers

Prompt Construction, Generation Validation and Guidance

IDE extensions, frontends, browser plugins

Annotation, Conversational Information Retrieval, misc

  • https://github.com/explosion/prodigy-openai-recipes - This repository contains example code on how to combine zero- and few-shot learning with a small annotation effort to obtain a high-quality dataset with maximum efficiency. Specifically, we use large language models available from OpenAI to provide us with an initial set of predictions, then spin up a Prodigy instance on our local machine to go through these predictions and curate them. This allows us to obtain a gold-standard dataset pretty quickly, and train a smaller, supervised model that fits our exact needs and use-case.
  • https://github.com/hwchase17/chat-langchain - This repo is an implementation of a locally hosted chatbot specifically focused on question answering over the LangChain documentation.
  • https://github.com/whitead/paper-qa - LLM Chain for answering questions from documents with citations
  • https://github.com/jagilley/fact-checker - Fact-checking LLM outputs with langchain
  • https://github.com/argilla-io/argilla - ✨ Argilla: Open-source platform empowering teams to build better language models through human feedback. docs.argilla.io
  • https://github.com/deepset-ai/haystack - 🔍 Haystack is an open source NLP framework to interact with your data using Transformer models and LLMs (GPT-4, ChatGPT and alike). Haystack offers production-ready tools to quickly build complex decision making, question answering, semantic search, text generation applications, and more. haystack.deepset.ai
  • https://github.com/hwchase17/notion-qa

Verctor stores

Generation SDKs

  • https://github.com/hyperonym/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.
  • https://github.com/NVIDIA/NeMo - NVIDIA NeMo is a conversational AI toolkit built for researchers working on automatic speech recognition (ASR), text-to-speech synthesis (TTS), large language models (LLMs), and natural language processing (NLP). The primary objective of NeMo is to help researchers from industry and academia to reuse prior work (code and pretrained models) and make it easier to create new conversational AI models.
  • https://github.com/togethercomputer/OpenChatKit - OpenChatKit provides a powerful, open-source base to create both specialized and general purpose chatbots for various applications. The kit includes an instruction-tuned language models, a moderation model, and an extensible retrieval system for including up-to-date responses from custom repositories. OpenChatKit models were trained on the OIG-43M training dataset, which was a collaboration between Together, LAION, and Ontocord.ai.
  • https://github.com/neuml/txtai - 💡 Semantic search and workflows powered by language models. neuml.github.io/txtai
  • https://github.com/RasaHQ/rasa - Rasa is an open source machine learning framework to automate text and voice-based conversations. With Rasa, you can build contextual assistants on: . Rasa helps you build contextual assistants capable of having layered conversations with lots of back-and-forth. In order for a human to have a meaningful exchange with a contextual assistant, the assistant needs to be able to use context to build on things that were previously discussed – Rasa enables you to build assistants that can do this in a scalable way.

Autonomy Experiments

Misc Research

LLM Red Teaming and Prompt Bypass

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