dify
haystack
| dify | haystack | |
|---|---|---|
| 12 | 55 | |
| 25,645 | 13,633 | |
| 29.1% | 2.5% | |
| 9.9 | 9.9 | |
| 2 days ago | 6 days ago | |
| TypeScript | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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.
dify
- 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
- langgenius/dify: One API for plugins and datasets, one interface for prompt engineering and visual operation, all for creating powerful AI applications.
haystack
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Haystack DB – 10x faster than FAISS with binary embeddings by default
I was confused for a bit but there is no relation to https://haystack.deepset.ai/
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Release Radar • March 2024 Edition
View on GitHub
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First 15 Open Source Advent projects
4. Haystack by Deepset | Github | tutorial
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Generative AI Frameworks and Tools Every Developer Should Know!
Haystack can be classified as an end-to-end framework for building applications powered by various NLP technologies, including but not limited to generative AI. While it doesn't directly focus on building generative models from scratch, it provides a robust platform for:
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Best way to programmatically extract data from a set of .pdf files?
But if you want an API that you can use to develop your own flow, Haystack from Deepset could be worth a look.
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Which LLM framework(s) do you use in production and why?
Haystack for production. We cannot afford breaking changes in our production apps. Its stable, documentation is excellent and did I mention its' STABLE!??
- Overview: AI Assembly Architectures
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Llama2 and Haystack on Colab
I recently conducted some experiments with Llama2 and Haystack (https://github.com/deepset-ai/haystack), the NLP/LLM framework.
The notebook can be helpful for those trying to load Llama2 on Colab.
1) Installed Transformers from the main branch (and other libraries)
- Build with LLMs for production with Haystack – has 10k stars on GitHub
- Show HN: Haystack – Production-Ready LLM Framework
What are some alternatives?
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
langchain - 🦜🔗 Build context-aware reasoning applications
litellm - Call all LLM APIs using the OpenAI format. Use Bedrock, Azure, OpenAI, Cohere, Anthropic, Ollama, Sagemaker, HuggingFace, Replicate (100+ LLMs)
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
chainlit - Build Conversational AI in minutes ⚡️
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
duet-gpt - A conversational semi-autonomous developer assistant. AI pair programming without the copypasta.
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
IncognitoPilot - An AI code interpreter for sensitive data, powered by GPT-4 or Code Llama / Llama 2.
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
jdbc-connector-for-apache-kafka - Aiven's JDBC Sink and Source Connectors for Apache Kafka®
jina - ☁️ Build multimodal AI applications with cloud-native stack