We are excited to welcome Abdel Sghiouar, Cloud Developer Advocate at @GoogleCloudTech, as a speaker at the WeAreDevelopers World Congress 2024 🚀
He will lead an interesting discussion on:
🌐 Gemini in Java with Vertex AI and LangChain4j
Don't miss this talk!
We are excited to welcome Asrar Khan, Developer Marketing Lead at @GoogleCloudTech, as a speaker at the WeAreDevelopers World Congress 2024 🚀
He will lead an interesting discussion on:
🌐 Gemini in Java with Vertex AI and LangChain4j
Don't miss this talk!
📣 @AlexGallice
has shared a nice post about using @ApacheCamel, @ollama and @langchain4j to process unstructured data.
If you ever wondered how you could transform a blob of text into a Java object, this is how you could start.
#ai#ApacheCamel#LLM
https://t.co/LzTz6MQqmB
Nothing better to start the day than submitting a PR on @langchain4j : Adding a sample about securing your Azure OpenAI model invocation https://t.co/roY0EXtCew
Explore a variety of AI capabilities at @WeAreDevs 2024.
In this session, we'll start with the #Quarkus DevUI, where you can try out AI models even before writing any code, and then we’ll get our hands dirty with code and explore LangChain4j features.
https://t.co/pJ0q3om0U3
Lastly I use an Embedding Models approach to calculate vector embeddings of labeled samples, to compare them with the text to classify, thanks to @langchain4j's EmbeddingModelTextClassifier class.
I used #VertexAI's latest embedding model to compute vectors.
Another useful use-case for #LLM's. Text classification for Sentiment analysis, request triaging, document labeling...etc.
Check this article by @glaforge where he explored using @langchain4j and @GoogleCloudTech#Gemini to classify text 🔽
The first implementation of MixtureOfAgents (MoA) 🤖in @java is here 🥳
Explore and use collaborativeness of OSS LLMs capabilities to provide better responses than ChatGPT-4o using @langchain4j and LC4J-workflow 🦜🔀
Code 💻 https://t.co/UjKNtIFi3u
https://t.co/3SPDvIQ7WA
One of most approachable use cases for generative AI is text summarization. Most folks have chunky content that we could use help digesting.
@ddobrin has a post about 3 patterns for summarizing with @langchain4j and Gemini: https://t.co/vzhS0aWe38
#LLMs are useful beyond just #chatbots and #RAG
They are great at text classification:
Sentiment analysis, request triaging, document labeling...
In this article, I explore using @langchain4j with #Gemini to classify text.
https://t.co/7aBfQRJbvL
Version 0.16 of the @quarkusio@langchain4j extension is out, with improved tracing, OpenWebUI integration, generic authentication flow, parallelized ingestion, and more! https://t.co/HSK13U3hh5