Open-Source Event-Driven Developer Platform for Building and Running LLM AI Apps. Powered by K8s and Kafka.
https://t.co/RLBU6NauOjgithub.com/LangStream/lan…Joined August 2023
Check out this great blog post by @DierufDavid detailing all the great new features of LangStream 0.4, including:
* Stateful agents
* Apache Camel as a source
* "Service" components
* "Service" gateways
langstream.ai/2023/11/22/lan…
You can now develop with LangStream using open-source models like Llama2 on your laptop using @Ollama_ai.
Check out this new blog post from @eolivelli explaining how to do it.
langstream.ai/2023/11/21/oll…
Streamline your data with LangStream's latest guide by @eolivelli on scalable vectorization pipelines! 🚀
From S3 buckets to vector databases, master the flow of information with ease. Dive into the full pipeline process here!
#LLM#GenAI#Vectorizationlangstream.ai/2023/11/08/sca…
Yesterday we've had another @langstream_ai meetup in Bologna with the local Java User Group and other folks!
That was fun, and we had great discussions about #GenerativeAI !
@eolivelli
Want a step-by-step tutorial on how to build a web crawler chatbot using LangStream?
Check out this great new video by @DierufDavid from the Thinking Machine YouTube channel.
youtu.be/GiS_90raubE
In the LangStream project, we are always trying to make it easier for you to develop cool LLM applications. We recently added a UI for testing and debugging your LangStream apps. Check out the video for a quick demo:
youtube.com/watch?v=laPiua…
1/8 🧵 Building a chatbot that can answer questions about private data? Let's talk about using Retrieval Augmented Generation (RAG) pattern. This pattern helps large language models (LLMs) provide fresh answers about topics they weren't trained on. Here's a detailed breakdown.👇
#RAG: going from the theory to real production-ready applications is not easy, but if you use @langstream_ai that’s another story
New blog post that explains step by step how to do it langstream.ai/2023/10/13/rag…
🔔 We just released LangStream 0.2.0 with new cool features:
* Support for FLARE pattern: FLARE is an emerging pattern, similar to RAG, that iteratively uses a prediction of the upcoming sentence to anticipate future content, which is then utilized as a query to retrieve relevant documents to regenerate the sentence if it contains low-confidence tokens. Read more in the paper (lnkd.in/g9Qfw39x).
* New agent ‘dispatch’: you can implement message routing easily by defining conditions on the record.
* New agent ‘http-request’: run HTTP requests to enrich your data model from any public service or call webhooks when an event happens on the pipeline.
* New agent ‘azure-blob-storage-source’: read and process files from Azure Blob Storage containers.
* New UI for apps monitoring and testing: you can now spin up a local UI web server to monitor and test your application in a friendly way.
* CLI support for Windows: CLI is now installable on Windows.
* Export your application as Mermaid graph: run langstream apps get myapp -o mermaid to generate a MermaidJS (mermaid.js.org) graph that shows you the entire application workflow.
Checkout the full release notes: lnkd.in/gxXcZyGU
Please add your ⭐ to spread the project!
@mohinishbasha@Meetup Hi Mohinish. We'd love to compare notes on your demo chat bot application and what we are doing in the LangStream project. We might
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