hallucination-leaderboard
dify
hallucination-leaderboard | dify | |
---|---|---|
14 | 14 | |
1,080 | 32,343 | |
4.6% | 20.7% | |
8.7 | 9.9 | |
23 days ago | 4 days ago | |
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.
hallucination-leaderboard
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How to Detect AI Hallucinations
To checkout the Hallucination leaderboard click here
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Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
Nice to see yet another open source approach to LLM/RAG. For those who do not want to meddle with the complexity of do-it-youself, Vectara (https://vectara.com) provides a RAG-as-a-service approach - pretty helpful if you want to stay away from having to worry about all the details, scalability, security, etc - and just focus on building your RAG application.
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Went down the rabbit hole of 100% local RAG, it works but are there better options?
Check this leaderboard, it is specific for RAG use case: https://github.com/vectara/hallucination-leaderboard
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Which LLM framework(s) do you use in production and why?
You should also check us out (https://vectara.com) - we provide RAG as a service so you don't have to do all the heavy lifting and putting together the pieces yourself.
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Ask HN: Best Alternatives to OpenAI ChatGPT?
Llama 2 (and variants). Has the lowest hallucination rate (https://github.com/vectara/hallucination-leaderboard), and its open source and so we know what went into it, and the community can improve it
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Inflection-2: the next step up
This is just typical of so much work in the field. They pick and choose which models to compare against and on which benchmarks. If this model was truly great, they would be comparing against Claude 2 and GPT4 across a bunch of different benchmarks. Instead they compare against Palm 2, which in a lot of tests is a weak model (https://venturebeat.com/ai/google-bard-fails-to-deliver-on-i....) and prone to hallucination (https://github.com/vectara/hallucination-leaderboard).
- LLMs by Hallucination Rate
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?
Woodpecker - ✨✨Woodpecker: Hallucination Correction for Multimodal Large Language Models. The first work to correct hallucinations in MLLMs.
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
SuperAGI - <⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.
litellm - Call all LLM APIs using the OpenAI format. Use Bedrock, Azure, OpenAI, Cohere, Anthropic, Ollama, Sagemaker, HuggingFace, Replicate (100+ LLMs)
nohide - editors that don't really delete
chainlit - Build Conversational AI in minutes ⚡️
h2ogpt - Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://codellama.h2o.ai/
duet-gpt - A conversational semi-autonomous developer assistant. AI pair programming without the copypasta.
autogen - A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap
IncognitoPilot - An AI code interpreter for sensitive data, powered by GPT-4 or Code Llama / Llama 2.
YiVal - Your Automatic Prompt Engineering Assistant for GenAI Applications
jdbc-connector-for-apache-kafka - Aiven's JDBC Sink and Source Connectors for Apache Kafka®