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Nicolay Rusnachenko

nicolay-r
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https://nicolayr.com/

AI & ML interests

Information RetrievalใƒปMedical Multimodal NLP (๐Ÿ–ผ+๐Ÿ“) Research Fellow @BU_Researchใƒปsoftware developer http://arekit.ioใƒปPhD in NLP

Recent Activity

reacted to julien-c's post with ๐Ÿ”ฅ 1 day ago
BOOOOM: Today I'm dropping TINY AGENTS the 50 lines of code Agent in Javascript ๐Ÿ”ฅ I spent the last few weeks working on this, so I hope you will like it. I've been diving into MCP (Model Context Protocol) to understand what the hype was all about. It is fairly simple, but still quite powerful: MCP is a standard API to expose sets of Tools that can be hooked to LLMs. But while doing that, came my second realization: Once you have a MCP Client, an Agent is literally just a while loop on top of it. ๐Ÿคฏ โžก๏ธ read it exclusively on the official HF blog: https://huggingface.co/blog/tiny-agents
reacted to as-cle-bert's post with ๐Ÿ”ฅ 1 day ago
Ever dreamt of ingesting into a vector DB that pile of CSVs, Word documents and presentations laying in some remote folders on your PC?๐Ÿ—‚๏ธ What if I told you that you can do it within three to six lines of code?๐Ÿคฏ Well, with my latest open-source project, ๐ข๐ง๐ ๐ž๐ฌ๐ญ-๐š๐ง๐ฒ๐ญ๐ก๐ข๐ง๐  (https://github.com/AstraBert/ingest-anything), you can take all your non-PDF files, convert them to PDF, extract their text, chunk, embed and load them into a vector database, all in one go!๐Ÿš€ How? It's pretty simple! ๐Ÿ“ The input files are converted into PDF by PdfItDown (https://github.com/AstraBert/PdfItDown) ๐Ÿ“‘ The PDF text is extracted using LlamaIndex readers ๐Ÿฆ› The text is chunked exploiting Chonkie ๐Ÿงฎ The chunks are embedded thanks to Sentence Transformers models ๐Ÿ—„๏ธ The embeddings are loaded into a Qdrant vector database And you're done!โœ… Curious of trying it? Install it by running: ๐˜ฑ๐˜ช๐˜ฑ ๐˜ช๐˜ฏ๐˜ด๐˜ต๐˜ข๐˜ญ๐˜ญ ๐˜ช๐˜ฏ๐˜จ๐˜ฆ๐˜ด๐˜ต-๐˜ข๐˜ฏ๐˜บ๐˜ต๐˜ฉ๐˜ช๐˜ฏ๐˜จ And you can start using it in your python scripts!๐Ÿ Don't forget to star it on GitHub and let me know if you have any feedback! โžก๏ธ https://github.com/AstraBert/ingest-anything
posted an update 2 days ago
๐Ÿš€ Delighted to share a major milestone in adapting reasoning techniques for data collections augmentation! Introducing bulk-chain 1.0.0 -- the first major release of a no-string API for adapting your LLM for Chain-of-Thought alike reasoning over records with large amount of parameters across large datasets. โญ Check it out: https://github.com/nicolay-r/bulk-chain Whatโ€™s new and why it matters: ๐Ÿ“ฆ Fully no-string API for easy client deployment ๐Ÿ”ฅ Demos are now standalone projects: Demos: ๐Ÿ“บ bash / shell (dispatched): https://github.com/nicolay-r/bulk-chain-shell ๐Ÿ“บ tksheet: https://github.com/nicolay-r/bulk-chain-tksheet-client Using nlp-thirdgate to host the supported providers: ๐ŸŒŒ LLM providers: https://github.com/nicolay-r/nlp-thirdgate
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reacted to julien-c's post with ๐Ÿ”ฅ 1 day ago
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3431
BOOOOM: Today I'm dropping TINY AGENTS

the 50 lines of code Agent in Javascript ๐Ÿ”ฅ

I spent the last few weeks working on this, so I hope you will like it.

I've been diving into MCP (Model Context Protocol) to understand what the hype was all about.

It is fairly simple, but still quite powerful: MCP is a standard API to expose sets of Tools that can be hooked to LLMs.

But while doing that, came my second realization:

Once you have a MCP Client, an Agent is literally just a while loop on top of it. ๐Ÿคฏ

โžก๏ธ read it exclusively on the official HF blog: https://huggingface.co/blog/tiny-agents
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reacted to as-cle-bert's post with ๐Ÿ”ฅ 1 day ago
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2713
Ever dreamt of ingesting into a vector DB that pile of CSVs, Word documents and presentations laying in some remote folders on your PC?๐Ÿ—‚๏ธ
What if I told you that you can do it within three to six lines of code?๐Ÿคฏ
Well, with my latest open-source project, ๐ข๐ง๐ ๐ž๐ฌ๐ญ-๐š๐ง๐ฒ๐ญ๐ก๐ข๐ง๐  (https://github.com/AstraBert/ingest-anything), you can take all your non-PDF files, convert them to PDF, extract their text, chunk, embed and load them into a vector database, all in one go!๐Ÿš€
How? It's pretty simple!
๐Ÿ“ The input files are converted into PDF by PdfItDown (https://github.com/AstraBert/PdfItDown)
๐Ÿ“‘ The PDF text is extracted using LlamaIndex readers
๐Ÿฆ› The text is chunked exploiting Chonkie
๐Ÿงฎ The chunks are embedded thanks to Sentence Transformers models
๐Ÿ—„๏ธ The embeddings are loaded into a Qdrant vector database

And you're done!โœ…
Curious of trying it? Install it by running:

๐˜ฑ๐˜ช๐˜ฑ ๐˜ช๐˜ฏ๐˜ด๐˜ต๐˜ข๐˜ญ๐˜ญ ๐˜ช๐˜ฏ๐˜จ๐˜ฆ๐˜ด๐˜ต-๐˜ข๐˜ฏ๐˜บ๐˜ต๐˜ฉ๐˜ช๐˜ฏ๐˜จ

And you can start using it in your python scripts!๐Ÿ
Don't forget to star it on GitHub and let me know if you have any feedback! โžก๏ธ https://github.com/AstraBert/ingest-anything
  • 4 replies
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posted an update 2 days ago
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2177
๐Ÿš€ Delighted to share a major milestone in adapting reasoning techniques for data collections augmentation!
Introducing bulk-chain 1.0.0 -- the first major release of a no-string API for adapting your LLM for Chain-of-Thought alike reasoning over records with large amount of parameters across large datasets.

โญ Check it out: https://github.com/nicolay-r/bulk-chain

Whatโ€™s new and why it matters:
๐Ÿ“ฆ Fully no-string API for easy client deployment
๐Ÿ”ฅ Demos are now standalone projects:

Demos:
๐Ÿ“บ bash / shell (dispatched): https://github.com/nicolay-r/bulk-chain-shell
๐Ÿ“บ tksheet: https://github.com/nicolay-r/bulk-chain-tksheet-client

Using nlp-thirdgate to host the supported providers:
๐ŸŒŒ LLM providers: https://github.com/nicolay-r/nlp-thirdgate
reacted to fdaudens's post with ๐Ÿคฏ 17 days ago
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4086
๐ŸŽจ Designers, meet OmniSVG! This new model helps you create professional vector graphics from text/images, generate editable SVGs from icons to detailed characters, convert rasters to vectors, maintain style consistency with references, and integrate into your workflow.

@OmniSVG
  • 2 replies
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authored a paper 18 days ago
upvoted a paper 18 days ago
commented a paper 18 days ago
updated a collection 18 days ago
posted an update 19 days ago
posted an update 24 days ago
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1764
๐Ÿ“ข For those who in textual IR and experimenting with quick deployment of CoT / reasoning, the following update might be relevant. I am happy to announce new version of the bulk-chain 0.25.3. It is a no-string framework for quick application of reasoning schema adaptation over your data.

https://github.com/nicolay-r/bulk-chain/releases/tag/0.25.3

The latest release brings huge updates on:
โœ… Reforged mechanism of models inference that work in steraming mode.
- Callbacks support for streaming mode (earlier only in demo)
- Deployment of various clients (shell, tksheet; see attachment)
โœ… Support for batching (earlier in API mode only)
โœ… Optional caching of inferred data in SQlite (always enabled earlier)
- This now makes possible to faster launch small (but mighty) LLMs

๐ŸŒŸ Project: https://github.com/nicolay-r/bulk-chain
๐ŸŒŒ Proviers: https://github.com/nicolay-r/nlp-thirdgate
liked a model about 1 month ago
posted an update about 1 month ago
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1666
The Concept behind xLSTM has recently turn into the xLSTM-7B model that showcase the performance in the category of the similar-scale Gemma 7B, LLama2 7B, FlaconMamba 7B but with higher performing Inference Kernel

Model: NX-AI/xLSTM-7b
Paper: https://arxiv.org/abs/2503.13427

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liked 2 models about 1 month ago
posted an update about 1 month ago
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672
๐Ÿ“ข Several weeks ago Microsoft announced Phi-4. My most-recent list of LLM models have had only wrapper for Phi-2, so it was time to update! With this post, happy to share that Phi-4 wrapper is now available at nlp-thirdgate for adopting Chain-of-Thought reasoning:

๐Ÿค– https://github.com/nicolay-r/nlp-thirdgate/blob/master/llm/transformers_phi4.py

๐Ÿ“’ https://github.com/nicolay-r/nlp-thirdgate/blob/master/tutorials/llm_phi4.py

Findings on adaptation: I was able to reproduce only the pipeline based model launching. This version is for textual llm only. Microsoft also released multimodal Phi-4 which is out of scope of this wrapper.

๐ŸŒŒ nlp-thirdgate: https://lnkd.in/ef-wBnNn
posted an update about 1 month ago
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1132
๐Ÿ“ข Delighted to announce the updated version of the no-string framework for chain-of-thought application over JSONL/CSV data:
https://github.com/nicolay-r/bulk-chain/releases/tag/0.25.2

๐Ÿ”ง Fixes:
- Fixed issues with batching mode
- Fixed problem with parsing and passing args in shell mode

โš ๏ธ Limitation: bathing mode is still available only via API.

๐Ÿ“’ Quick Start with Gemma-3 in batching mode: https://github.com/nicolay-r/nlp-thirdgate/blob/master/tutorials/llm_gemma_3.ipynb
replied to their post about 1 month ago
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The important comment is to use the very latest version of the bulk-chain from github which fixes the bug for double-inference in batching.
posted an update about 2 months ago
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1582
๐Ÿ“ข With the recent release of Gemma-3, If you interested to play with textual chain-of-though, the notebook below is a wrapper over the the model (native transformers inference API) for passing the predefined schema of promps in batching mode.
https://github.com/nicolay-r/nlp-thirdgate/blob/master/tutorials/llm_gemma_3.ipynb

Limitation: schema supports texts only (for now), while gemma-3 is a text+image to text.

Model: google/gemma-3-1b-it
Provider: https://github.com/nicolay-r/nlp-thirdgate/blob/master/llm/transformers_gemma3.py
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liked 2 models about 2 months ago