tanuki.py
LLMChat
| tanuki.py | LLMChat | |
|---|---|---|
| 10 | 1 | |
| 638 | 71 | |
| 2.5% | - | |
| 9.2 | 7.2 | |
| 3 months ago | 12 months ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tanuki.py
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[D] Alignment using tests? Will it work?
I came across this open source library a few times across Reddit + HN and something that piqued my interest was their concept around "test-driven alignment".
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I built a tool to make it easy to build cheap and fast LLM applications.
Hey guys, I've spent the last few weeks building Tanuki: https://github.com/Tanuki/tanuki.py
- Tanuki: Alignment-as-Code for LLM Applications
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I built a library for cheap, fast and predictable LLM functions in Python
Hi r/python, Jack here! I'm one of the creators of MonkeyPatch, an easy way to build LLM-powered functions and apps that get cheaper and faster the more you use them.
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Show HN: MonkeyPatch – Cheap, fast and predictable LLM functions in Python
Check out the ‘function_modeler’. Currently it’s OpenAI only, but local models are on the immediate roadmap.
https://github.com/monkeypatch/monkeypatch.py/blob/master/sr...
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MonkeyPatch – Cheap and fast LLM functions in Python
Hi HN, Jack here! I’m one of the creators of MonkeyPatch, an easy way to build LLM-powered functions and apps that get cheaper and faster the more you use them.
For example, if you need to classify PDFs, extract product feedback from tweets, or auto-generate synthetic data, you can spin up an LLM-powered Python function in < 5 minutes to power your application. Unlike existing LLM clients, these functions generate well-typed outputs with guardrails to mitigate unexpected behavior.
After about 200-300 calls, these functions will begin to get cheaper and faster. We’ve seen 8-10x reduction in cost and latency in some use-cases! This happens via progressive knowledge distillation - MonkeyPatch incrementally fine-tunes smaller, cheaper models in the background, tests them against the constraints defined by the developer, and retains the smallest model that meets accuracy requirements, which typically has significantly lower costs and latency.
As an LLM researcher, I kept getting asked by startups and friends to build specific LLM features that they could embed into their applications. I realized that most developers have to either 1) use existing low-level LLM clients (GPT4/Claude), which can be unreliable, untyped, and pricey, or 2) pore through LangChain documentation for days to build something.
We built MonkeyPatch to make it easy for developers to inject LLM-powered functions into their code and create tests to ensure they behave as intended. Our goal is to help developers easily build apps and functions without worrying about reliability, cost, and latency, while following best software engineering practices.
We’re only available in Python currently but actively working on a Typescript version. The repo has all the instructions you need to get up and running in a few minutes.
The world of LLMs is changing by the day and so we’re not 100% sure how MonkeyPatch will evolve. For now, I’m just excited to share what we’ve been working on with the HN community. Would love to know what you guys think!
Open-source repo: https://github.com/monkeypatch/monkeypatch.py
Sample use-cases: https://github.com/monkeypatch/monkeypatch.py/tree/master/ex...
Benchmarks: https://github.com/monkeypatch/monkeypatch.py#scaling-and-fi...
LLMChat
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I made a Discord bot with voice chat support that uses OpenAI and LLaMA for text generation
Hey all, as the title states I've made a discord bot that you can interact with that uses the OpenAI API or LLaMA for text generation. It supports voice chat, so you can enter a voice channel and talk to it. It's open source here: hc20k/LLMChat: A Discord chatbot that uses GPT-4 (or 3.5, or 3, or LLaMA) for text generation and ElevenLabs (or Azure TTS) for voice chat. (github.com)
What are some alternatives?
Free-AUTO-GPT-with-NO-API - Free Auto GPT with NO paids API is a repository that offers a simple version of Auto GPT, an autonomous AI agent capable of performing tasks independently. Unlike other versions, our implementation does not rely on any paid OpenAI API, making it accessible to anyone. [Moved to: https://github.com/IntelligenzaArtificiale/Free-Auto-GPT]
RasaGPT - 💬 RasaGPT is the first headless LLM chatbot platform built on top of Rasa and Langchain. Built w/ Rasa, FastAPI, Langchain, LlamaIndex, SQLModel, pgvector, ngrok, telegram
E2B - Secure cloud runtime for AI apps & AI agents. Fully open-source.
GPT3Discord - MOVED
monkey-patch.ts
elevenlabs-api - 🗣️🎤 elevenlabs-api is an open source Java wrapper around the ElevenLabs Voice Synthesis and Cloning Web API.
declarai - A Pythonic integration for LLMs.
gpt-voice-conversation-chatbot - Allows you to have an engaging and safely emotive spoken / CLI conversation with the AI ChatGPT / GPT-4 while giving you the option to let it remember things discussed.
OSGPT - OSGPT is a powerful plugin designed to dynamically load documents from specified folders and create searchable vector databases. Not only does it offer a quick way to query from your documents, but it also allows you to execute CLI commands on the host system, be it Linux/Unix or Windows.
gpt_chatbot - This chatbot lets you use your microphone to communicate with GPT-4. It uses the OpenAI text to speech to respond with a voice. It uses Pinecone to store long term information and retrieves it to create context. API keys for OpenAI and Pinecone required. Tested on Windows
llmflows - LLMFlows - Simple, Explicit and Transparent LLM Apps
Discordbot - AI-powered Discord bot that enhances your server experience with a variety of features.