llm_optimize
dify
llm_optimize | dify | |
---|---|---|
3 | 13 | |
43 | 28,957 | |
- | 32.8% | |
5.8 | 9.9 | |
about 1 year ago | about 14 hours ago | |
Python | TypeScript | |
MIT License | GNU General Public License v3.0 or later |
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llm_optimize
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Using Large Language Models for Hyperparameter Optimization, Zhang et al. 2023 [GPT-4 is quite good at finding the optimal hyperparameters for machine learning tasks]
Wrote this library as a way of doing this pretty plug and play: https://github.com/sshh12/llm_optimize
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Large Language Models as Optimizers
For anyone interested I've been working a very similar idea of LLMs for blackbox optimization: https://github.com/sshh12/llm_optimize
- Show HN: LLM Optimize, blackbox string optimization and AutoML with GPT-4
dify
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Ask HN: LLM workflows to avoid copying and pasting from the web interfaces?
This visual IDE for LLM pipelines was posted recently: https://github.com/langgenius/dify
See if it helps.
- FLaNK AI Weekly for 29 April 2024
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Dify, a visual workflow to build/test LLM applications
> https://github.com/langgenius/dify/blob/main/LICENSE
everyone is apparently a license pioneer
- Dify, an end-to-end, visualized workflow to build/test LLM applications
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GreptimeAI + Xinference - Efficient Deployment and Monitoring of Your LLM Applications
Xorbits Inference (Xinference) is an open-source platform to streamline the operation and integration of a wide array of AI models. With Xinference, you’re empowered to run inference using any open-source LLMs, embedding models, and multimodal models either in the cloud or on your own premises, and create robust AI-driven applications. It provides a RESTful API compatible with OpenAI API, Python SDK, CLI, and WebUI. Furthermore, it integrates third-party developer tools like LangChain, LlamaIndex, and Dify, facilitating model integration and development.
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Which LLM framework(s) do you use in production and why?
If you are looking to develop QnA or chat based apps then check out https://dify.ai. Do a quick check and see if it fit your requirements. You can integrate it with your app using the apis it provides
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New Discoveries in No-Code AI App Building with ChatGPT
As an AI newbie, I used to find coding apps from scratch an absolute nightmare! The learning curve was steep as a ski slope, debugging took endless hours, and developing even a simple AI app nearly drove me insane! But since discovering Dify, it has totally revolutionized my life by enabling app development without any coding skills!
- FLaNK Stack Weekly for 14 Aug 2023
- Interesting LLMOps Tools Dify.ai
- Dify.ai – Simply create and operate AI-native apps based on GPT-4
What are some alternatives?
evalml - EvalML is an AutoML library written in python.
langchain-llm-katas - This is a an open-source project designed to help you improve your skills with AI engineering using LLMs and the langchain library
LightAutoML - LAMA - automatic model creation framework
litellm - Call all LLM APIs using the OpenAI format. Use Bedrock, Azure, OpenAI, Cohere, Anthropic, Ollama, Sagemaker, HuggingFace, Replicate (100+ LLMs)
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
chainlit - Build Conversational AI in minutes ⚡️
duet-gpt - A conversational semi-autonomous developer assistant. AI pair programming without the copypasta.
IncognitoPilot - An AI code interpreter for sensitive data, powered by GPT-4 or Code Llama / Llama 2.
jdbc-connector-for-apache-kafka - Aiven's JDBC Sink and Source Connectors for Apache Kafka®
kudu - Mirror of Apache Kudu
flatdraw - A simple canvas drawing web app with responsive UI. Made with TypeScript, React, and Next.js.
GeniA - Your Engineering Gen AI Team member 🧬🤖💻