LangChain4j @langchain4j
Build LLM-powered applications in Java, Quarkus and Spring Boot. Chatbots, agents, RAG and much more! https://t.co/5nBDPenP6l linkedin.com/in/dmytro-liub… Munich, Bavaria Joined June 2023-
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#Java AI developers Very soon @langchain4j will support web search engines as part of its core functionality to fetching relevant info from the web. Will be useful for LLMs seeking info on recent or future events if they require it. How does it work? 👇 #LangChain4j #Java #AI
Prompt engineering is one of the most rapidly-evolving research topics in AI, but we can (roughly) group recent research on this topic into four categories… (1) Reasoning: Simple prompting techniques are effective for many problems, but more sophisticated strategies are…
Secondary benefits of having all these different LLMs integrated in @langchain4j, each providing kinda similar services: ✅ easy to build redundancy ✅ rate limits are gone, just switch calls to another provider. (key aspects when building a web app!) 🎇💝
Join us next Monday at 9am EST for Quarkus Insights Ep. 163 as Dimitrios Andreadis @dandreadis & Georgios Andrianakis @geoand86 join us to discuss the latest happenings with LangChain4j, including MistralAI and Easy RAG in Quarkus. buff.ly/3LZiEoV #quarkusinsights
With the release of version 0.12 of Quarkus LangChain4j we introduced advanced integration with Quarkus' new Websockets stack. This makes writing chatbots over websockets absolutely seamless. See docs.quarkiverse.io/quarkus-langch… for more information
first steps with @langchain4j ... I love the simplicity and the power. The code examples get me salivating 😁
So looking forward to the Quarkus Insights #163: Latest in @QuarkusIO @langchain4j youtube.com/live/EeR_8HMFw… via @YouTube
Microsoft announces Phi-3 A Highly Capable Language Model Locally on Your Phone We introduce phi-3-mini, a 3.8 billion parameter language model trained on 3.3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal testing,
NEW RAG benchmark including LLaMa-3 70B and 8B, CommandR, Mistral 8x22b: reddit.com/r/LocalLLaMA/s…
More exciting news today -- Gemini 1.5 Pro result is out! Gemini 1.5 Pro API-0409-preview now achieves #2 on the leaderboard, surpassing #3 GPT4-0125-preview to almost top-1! Gemini shows even stronger performance on longer prompts, in which it ranks joint #1 with the latest…
More exciting news today -- Gemini 1.5 Pro result is out! Gemini 1.5 Pro API-0409-preview now achieves #2 on the leaderboard, surpassing #3 GPT4-0125-preview to almost top-1! Gemini shows even stronger performance on longer prompts, in which it ranks joint #1 with the latest… https://t.co/IvrwwMRhkU
Exciting update -- Llama-3 full result is out, now reaching top-5 on the Arena leaderboard🔥 We've got stable enough CIs with over 12K votes. No question now Llama-3 70B is the new king of open model. Its powerful 8B variant has also surpassed many larger-size models. What an…
Great stuff! This reminds me of a flow that @IrynaLiubarska and I developed for our IntelliJ IDEA AI-assisted coding plugin a while ago. Apart from the basic features like "explain this code," "refactor this code," and "document this code," we wanted a more systematic way of…
Great stuff! This reminds me of a flow that @IrynaLiubarska and I developed for our IntelliJ IDEA AI-assisted coding plugin a while ago. Apart from the basic features like "explain this code," "refactor this code," and "document this code," we wanted a more systematic way of…
Got inspired by @ZinebBendhiba and @dandreadis’ #DevoxxGR talk “Quarkus meets AI” to try it out myself. Got a locally running LLM integrated in my Java code from scratch with Ollama, @QuarkusIO and Langchain4j in less than an hour! If I can do it, anyone can 😉
Really impressed by @QuarkusIO easy RAG extension: literally zero code, you just put the documents to be ingested in a folder, configure it in a property and you're done. Great job @geoand86! #DevoxxGR docs.quarkiverse.io/quarkus-langch…
The upcoming Llama-3-400B+ will mark the watershed moment that the community gains open-weight access to a GPT-4-class model. It will change the calculus for many research efforts and grassroot startups. I pulled the numbers on Claude 3 Opus, GPT-4-2024-04-09, and Gemini.…
🦙 All Llama3 release details & highlights 8B and 70B sizes: SOTA performance on most benchmarks for both Instruct and Pre-trained. Currently training a 400B+ parameters model which will be released alongside the full Llama3 paper later on: Created a new human evaluation set…
@sinedied in rockstar mode: last second changes for the overbooked workshop (500 bookmarks for the 50 people room) .. it’s accessible here: aka.ms/ws/openai-rag-… @juliendubois @langchain4j @quarkus @JavaAtMicrosoft retweet to get it redone at MS Paris
Hot on the heels of LangChain4j, we releases version 0.11 of the Quarkus LangChain4j extension! x.com/langchain4j/st…
Hot on the heels of LangChain4j, we releases version 0.11 of the Quarkus LangChain4j extension! x.com/langchain4j/st…
What a productive train ride to #DevoxxFR 🤩 Added all available (and more) @langchain4j cloud based LLM's to the #DevoxxGenie (v0.0.6) plugin : @Anthropic @groq @OpenAI @mistral @DeepInfra As a result you can do some heavy lifting dev work in @intellijidea online and offline…
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4K Followers 421 Following Excited about the future of intelligent software development. CEO & co-founder @CodiumAI#Java AI developers Very soon @langchain4j will support web search engines as part of its core functionality to fetching relevant info from the web. Will be useful for LLMs seeking info on recent or future events if they require it. How does it work? 👇 #LangChain4j #Java #AI
Today I updated my app to the latest @QuarkusIO and @langchain4j versions ! It still works 😅 But then, since I'm using @ollama a lot I had this idea : What if each bot could have a different LLM 🤯? Really easy to test and it works , I have Bob using llama3 discussing with…
🤩I'm so so excited ! I got a first version running of my Virtual World ! Basically, for now I have 2 bots (each is a separate @QuarkusIO app) engaging a discussion (using Redis pubsub under the hood). The initial context/seed for each bot is that they live on a small cosy…
Prompt engineering is one of the most rapidly-evolving research topics in AI, but we can (roughly) group recent research on this topic into four categories… (1) Reasoning: Simple prompting techniques are effective for many problems, but more sophisticated strategies are…
Attention Portland friends! Next week, I'll be visiting the @pjug for some fun live code learning. We'll build a custom AI chatbot using Spring Boot, LangChain4j and Hilla. Hope to see you there! meetup.com/pdxjug/events/…
Secondary benefits of having all these different LLMs integrated in @langchain4j, each providing kinda similar services: ✅ easy to build redundancy ✅ rate limits are gone, just switch calls to another provider. (key aspects when building a web app!) 🎇💝
Join us next Monday at 9am EST for Quarkus Insights Ep. 163 as Dimitrios Andreadis @dandreadis & Georgios Andrianakis @geoand86 join us to discuss the latest happenings with LangChain4j, including MistralAI and Easy RAG in Quarkus. buff.ly/3LZiEoV #quarkusinsights
Thank you @marcushellberg for the great talk and demo on building a chat it with @langchain4j at the Toronto JUG!
Full house at #DortmundJUG with @edburns talking about #Azure #OpenAI @langchain4j
If you are interested in #AI I highly recommend this interview of @ylecun by @lexfridman. It emphasizes the importance of open-source collaboration, the safety and ethical considerations of AI. It also explores the societal impact of AI. youtube.com/watch?v=5t1vTL…
Want to know more about ou new AI Endpoints product and how to use it with @QuarkusIO and @langchain4j? Take a look at this blog post: blog.ovhcloud.com/llms-streaming…
With the release of version 0.12 of Quarkus LangChain4j we introduced advanced integration with Quarkus' new Websockets stack. This makes writing chatbots over websockets absolutely seamless. See docs.quarkiverse.io/quarkus-langch… for more information
Meta researchers developed RA-DIT, a fine-tuning method that enhances the performance of large language models (LLMs) using retrieval augmented generation (RAG). Read our summary of the paper in #TheBatch: hubs.la/Q02tRXVK0
Java devs & Generative AI: No more Python! @glaforge shows how to use powerful AI models in Java with tools like LangChain4J. Generate text, translate languages & more - all without Python! #jaxcon #Java #GenerativeAI #GoogleAI
My Java AI assistant demo now has Spring AI and LangChain4j in separate branches to make it easier to add support for additional LLMs as well. Do I know anyone from the Semantic Kernel team that wants to help me add a SK branch? github.com/marcushellberg…
My talks at Montreal and Toronto JUG are fully booked, but there are still a couple of seats available for tonight's meetup at @ottawajug - see you there? meetup.com/ottawa-java-us…
Thanks everyone for attending my session at @jugpaderborn about AI for Java developers featuring Copilots and LangChain4J. Next up @deepu105 speaking about passwordless from @oktadev
Is there a better way to test generative AI apps in Java? Ignasi at @Docker has a good post about using @springboot, @testcontainers, and @langchain4j to build a "validator agent" to check LLM responses in the app. docker.com/blog/testing-g…
I saw my friend (σύντεκνος!) @heinzkabutz presenting on using OpenAI to translate a Cretan book, and it would be interesting to use @QuarkusIO w. @langchain4j instead - clearer/less code and the ability to try different LLMs by just swapping extensions - github.com/quarkiverse/qu…
Thank you @montrealjug! What an engaged crowd and good discussions. Next up: @ottawajug tomorrow 🚂