CML_AMP_Churn_Prediction_mlflow
dify
| CML_AMP_Churn_Prediction_mlflow | dify | |
|---|---|---|
| 1 | 13 | |
| 1 | 31,106 | |
| - | 41.6% | |
| 1.9 | 9.9 | |
| about 1 year ago | 4 days ago | |
| Jupyter Notebook | TypeScript | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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.
CML_AMP_Churn_Prediction_mlflow
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?
llama2.c - Inference Llama 2 in one file of pure C
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
FLaNK-Edge - An example of FLaNK Edge
litellm - Call all LLM APIs using the OpenAI format. Use Bedrock, Azure, OpenAI, Cohere, Anthropic, Ollama, Sagemaker, HuggingFace, Replicate (100+ LLMs)
awesome-data-temporality - A curated list to help you manage temporal data across many modalities 🚀.
chainlit - Build Conversational AI in minutes ⚡️
flatdraw - A simple canvas drawing web app with responsive UI. Made with TypeScript, React, and Next.js.
duet-gpt - A conversational semi-autonomous developer assistant. AI pair programming without the copypasta.
pkgx - the last thing you’ll install
IncognitoPilot - An AI code interpreter for sensitive data, powered by GPT-4 or Code Llama / Llama 2.
kudu - Mirror of Apache Kudu
jdbc-connector-for-apache-kafka - Aiven's JDBC Sink and Source Connectors for Apache Kafka®