New Qdrant swag, has arrived!

If you are at the GenAI Summit in San Francisco this week, go meet our team and grab a t-shirt in a new, cool look. 🚀

Parsing different file formats is a challenging task. Llamaparse is there for rescue 🙌

Easily parse documents via LlamaParse from LlamaIndex 🦙, store the embeddings in Qdrant and use LLM’s via Groq Inc’s API

Video: youtu.be/w7Ap6gZFXl0

#llamaindex #llamaparse #groq

How to become exceptional

When Qdrant meets Mario Kart 64 ...

The most complex, convoluted and useless use case of semantic search for images

But it was soooo much fun 😍

Blog coming soon ...

Tuesday tips 💸
Qdrant Timeplus

We're excited to announce our partnership with Qdrant!

This collaboration marks a significant step forward in AI development by offering developers a comprehensive, end-to-end solution for building, evaluating, and shipping LLM products using RAG.

🌟 Big news! We are excited to roll out Qdrant Stars, our ambassador program designed to recognize and support the developers, researchers, and leaders simplifying and enriching the vector search space.

With this program, our top contributors will get exclusive benefits,

Let's begin by analyzing what is Qdrant.

Qdrant is an open-source vector similarity search engine that excels at storing and managing vector embeddings.

It provides a robust and scalable solution for handling large volumes of vector data, ideal for applications like ours.

In this tutorial, go beyond the basic RAG pipeline and build an Agentic RAG with Shuttle, Rust, and OpenAI.

This tutorial by Josh 🦀🐪 shows you how to create an agent using Rust that parses a CSV file, embeds its contents into Qdrant, and retrieves relevant embeddings

Our website has just been updated! Developing this concept was quite a ride, but we are really excited about the result. 🚀

Now, deep in the datasphere: qdrant.tech

Learn how to create a sophisticated voice assistant using OpenAI's Whisper and LLaMA3 in this tutorial by Datadrifters.

👉 buff.ly/4bQKcIe

Json >>> YAML

Sorry k8s friends.

this week's fafo
- travelled a lot
- played with chatdev, swe agent, open architect
- made rudimentary agents
- read cool papers, and codebases
- explored dspy, qdrant, brushed up system design
- a bit of ocaml

met some cool guys, hope growth is exponential henceforth

everything-ai was featured as one of the 'Projects of the week' in Qdrant's Content Highlight by Sabrina!

Make sure to check it out: github.com/AstraBert/ever…

Remember: the only thing between you and unleashing the true power of AI is a 'docker compose up'!🐋🚀

GPT-4o has an earlier knowledge cutoff compared to GPT-4-turbo.

That's not an issue, though.

Just add Qdrant to supply it with real-time knowlege! We put together a super quick tutorial that uses the new GPT-4o model.

You can build a chatbot in a few minutes if you follow

Get your Qdrant environment up and running in under 5 minutes with harpreet 🦀

Learn from the Leaders

This course instructors are from top companies: GPU.net, Lyzr AI, Qdrant, Streamlit, Snowflake, Voyage AI, Daxa, Agent Ops and goML.

📢 We've integrated Qdrant vector database into the 🐫 CAMEL-AI framework! This enhancement enables advanced vector similarity search capabilities, crucial for next-generation AI optimizations. 🚀

Kudos to Tianqi Xu for implementing this powerful feature! 🤝 Explore

Working on a UI for Qdrant filters 👀👀

Not easy