It's definitely not just OCR - it's using vision as compression. 10x token reduction while maintaining accuracy.
It's definitely not just OCR - it's using vision as compression. 10x token reduction while maintaining accuracy.
Our own @tuana.dev is speaking at Snowflake Build to show you how to create powerful data analysis agents that can handle complex, multi-part questions:
Our own @tuana.dev is speaking at Snowflake Build to show you how to create powerful data analysis agents that can handle complex, multi-part questions:
At LlamaIndex, we've been experimenting with using coding agents like Cursor and Claude Code to speed up build agentic workflows themselves + their UIs
At LlamaIndex, we've been experimenting with using coding agents like Cursor and Claude Code to speed up build agentic workflows themselves + their UIs
Last week we released vibe-llama, a tool developed by @cle-does-things.bsky.social
Last week we released vibe-llama, a tool developed by @cle-does-things.bsky.social
Last week, me and Tomaz (from neo4j) published another demo together. The idea: you have a bunch of unstructured documents (think legal, PDFs etc) and you want to construct a knowledge graph out of them.
Last week, me and Tomaz (from neo4j) published another demo together. The idea: you have a bunch of unstructured documents (think legal, PDFs etc) and you want to construct a knowledge graph out of them.
My colleague Logan spent his morning testing gpt-oss-20b - which runs on consumer hardware, is Apache 2.0 licensed, and the reasoning quality is solid.
Also, full chain-of-thought access so you can see exactly how it's thinking.
My colleague Logan spent his morning testing gpt-oss-20b - which runs on consumer hardware, is Apache 2.0 licensed, and the reasoning quality is solid.
Also, full chain-of-thought access so you can see exactly how it's thinking.
Here's what we got:
· LlamaExtract: use extraction agents within n8n workflows
· LlamaParse: parse complex documents
· LlamaCloud: use your existing LlamaCloud indexes as knowledge bases within n8n
Here's what we got:
· LlamaExtract: use extraction agents within n8n workflows
· LlamaParse: parse complex documents
· LlamaCloud: use your existing LlamaCloud indexes as knowledge bases within n8n
🌎 Use Gemini 2.5 pro with its server side google search tool
📝 Create an agent that takes notes as it gets results from its websearch
🌎 Use Gemini 2.5 pro with its server side google search tool
📝 Create an agent that takes notes as it gets results from its websearch
- Query any index with custom parsing.
- Use LlamaExtract agents to pull structured data based on LlamaCloud's schema.
The demo features extraction agents for invoices and technical resumes.
youtu.be/IL3CEONiDF4
- Query any index with custom parsing.
- Use LlamaExtract agents to pull structured data based on LlamaCloud's schema.
The demo features extraction agents for invoices and technical resumes.
youtu.be/IL3CEONiDF4
So, co-authored a piece on Context Engineering with Logan:
Here it is:
🔗 www.llamaindex.ai/blog/contex...
So, co-authored a piece on Context Engineering with Logan:
Here it is:
🔗 www.llamaindex.ai/blog/contex...
www.llamaindex.ai/blog/announ...
www.llamaindex.ai/blog/announ...
3 servers that provide live data on:
☄️ Asteroids
🤖 the Mars Rover
🌌 Astronomy
Here's the space: huggingface.co/spaces/Agen...
3 servers that provide live data on:
☄️ Asteroids
🤖 the Mars Rover
🌌 Astronomy
Here's the space: huggingface.co/spaces/Agen...
Note: not all applications that are 'agentic' necessarily _need_ memory. And what type of memory you need also depends on the use case.
Join us at 10AM PT/7PM CET: lu.ma/t27lryii
Note: not all applications that are 'agentic' necessarily _need_ memory. And what type of memory you need also depends on the use case.
Join us at 10AM PT/7PM CET: lu.ma/t27lryii
Fill out structured forms as the user talks! Checking the completeness along the way:
✅ ArtifactEditorToolSpec to define structured artifacts
✅ ArtifactMemoryBlock to track progress
docs.llamaindex.ai/en/stable/e...
Fill out structured forms as the user talks! Checking the completeness along the way:
✅ ArtifactEditorToolSpec to define structured artifacts
✅ ArtifactMemoryBlock to track progress
docs.llamaindex.ai/en/stable/e...
So, here's a pizzeria order taking assistant using just that with the new Artifact Memory Block and Artifact Editor Tool: colab.research.google.com/drive/13ORO...
So, here's a pizzeria order taking assistant using just that with the new Artifact Memory Block and Artifact Editor Tool: colab.research.google.com/drive/13ORO...
This time, the topic of choice will be creating MCP servers with LlamaIndex, and per popular request - form filling agents:
discord.com/events/1059...
Come by to the Group By() space at 2PM to have a chat 🩵
Come by to the Group By() space at 2PM to have a chat 🩵
Structured outputs with Google Gemini to check the generated image and evaluate whether it's ready for the user or not.
The repo: github.com/run-llama/i...
Her code-along: youtu.be/RCASiu5oj6c...
Structured outputs with Google Gemini to check the generated image and evaluate whether it's ready for the user or not.
The repo: github.com/run-llama/i...
Her code-along: youtu.be/RCASiu5oj6c...