Search the Web with AI
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Clelia (Astra) Bertelli PRO
as-cle-bert
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Biology + Artificial Intelligence = โค๏ธ | AI for sustainable development, sustainable development for AI | Researching on Machine Learning Enhancement | I love automation for everyday things | Blogger | Open Source
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about 17 hours ago
Hi HuggingFace community!๐ค
I recently released PrAIvateSearch v2.0-beta.0 (https://github.com/AstraBert/PrAIvateSearch), my privacy-first, AI-powered, user-centered and data-safe application aimed at providing a local and open-source alternative to big AI search engines such as SearchGPT or Perplexity AI.
We have several key changes:
- New chat UI built with NextJS
- DuckDuckGo API used for web search instead of Google
- https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct as a language model served on API (by FastAPI)
- Crawl4AI crawler used for web scraping
- Optimizations in the data workflow inside the application
Read more in my blog post ๐ https://huggingface.co/blog/as-cle-bert/search-the-web-with-ai
Have fun and feel free to leave feedback about how to improve the application!โจ
posted
an
update
1 day ago
Hi HuggingFace community!๐ค
I recently released PrAIvateSearch v2.0-beta.0 (https://github.com/AstraBert/PrAIvateSearch), my privacy-first, AI-powered, user-centered and data-safe application aimed at providing a local and open-source alternative to big AI search engines such as SearchGPT or Perplexity AI.
We have several key changes:
- New chat UI built with NextJS
- DuckDuckGo API used for web search instead of Google
- https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct as a language model served on API (by FastAPI)
- Crawl4AI crawler used for web scraping
- Optimizations in the data workflow inside the application
Read more in my blog post ๐ https://huggingface.co/blog/as-cle-bert/search-the-web-with-ai
Have fun and feel free to leave feedback about how to improve the application!โจ
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as-cle-bert's activity
replied to
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about 17 hours ago
Thank you so much for letting me know! This is indeed a very interesting role :)
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an
update
1 day ago
Post
716
Hi HuggingFace community!๐ค
I recently released PrAIvateSearch v2.0-beta.0 (https://github.com/AstraBert/PrAIvateSearch), my privacy-first, AI-powered, user-centered and data-safe application aimed at providing a local and open-source alternative to big AI search engines such as SearchGPT or Perplexity AI.
We have several key changes:
- New chat UI built with NextJS
- DuckDuckGo API used for web search instead of Google
- Qwen/Qwen2.5-1.5B-Instruct as a language model served on API (by FastAPI)
- Crawl4AI crawler used for web scraping
- Optimizations in the data workflow inside the application
Read more in my blog post ๐ https://huggingface.co/blog/as-cle-bert/search-the-web-with-ai
Have fun and feel free to leave feedback about how to improve the application!โจ
I recently released PrAIvateSearch v2.0-beta.0 (https://github.com/AstraBert/PrAIvateSearch), my privacy-first, AI-powered, user-centered and data-safe application aimed at providing a local and open-source alternative to big AI search engines such as SearchGPT or Perplexity AI.
We have several key changes:
- New chat UI built with NextJS
- DuckDuckGo API used for web search instead of Google
- Qwen/Qwen2.5-1.5B-Instruct as a language model served on API (by FastAPI)
- Crawl4AI crawler used for web scraping
- Optimizations in the data workflow inside the application
Read more in my blog post ๐ https://huggingface.co/blog/as-cle-bert/search-the-web-with-ai
Have fun and feel free to leave feedback about how to improve the application!โจ
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7 days ago
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534
Are you using Obsidian to write your notes?
If the answer is yes, then this post might be for you!โ
I recently created ๐จ๐๐ฌ๐ข๐๐ข๐๐ง-๐๐ข๐ ๐๐ฌ๐ญ, a Google Gemini-powered application that gives you feedback on style and contents of the documents you have been working on๐ง
Repo ๐ https://github.com/AstraBert/obsidian-digest
PyPi Package ๐ https://pypi.org/project/obsidian-digest/
The app is available as:
- ๐๐จ๐ฆ๐ฆ๐๐ง๐-๐ฅ๐ข๐ง๐ ๐ญ๐จ๐จ๐ฅ: install it as a python package with ๐ฝ๐ถ๐ฝ, and execute it from terminal anytime!๐ฆ
-๐๐ข๐ฌ๐๐จ๐ซ๐ ๐๐จ๐ญ ๐๐ฎ๐ข๐ฅ๐ญ ๐๐ซ๐จ๐ฆ ๐ฌ๐จ๐ฎ๐ซ๐๐ ๐๐จ๐๐: clone the GitHub repo, install the needed dependencies through ๐ฐ๐ผ๐ป๐ฑ๐ฎ, and run the bot: you will get hourly messages with suggestions and considerations about your activity on Obsidian in the previous hour๐ค
- ๐๐ข๐ฌ๐๐จ๐ซ๐ ๐๐จ๐ญ ๐๐๐ฉ๐ฅ๐จ๐ฒ๐๐ ๐ฅ๐จ๐๐๐ฅ๐ฅ๐ฒ ๐ฐ๐ข๐ญ๐ก ๐๐จ๐๐ค๐๐ซ ๐๐จ๐ฆ๐ฉ๐จ๐ฌ๐: clone the GitHub repo and launch ๐ฑ๐ผ๐ฐ๐ธ๐ฒ๐ฟ ๐ฐ๐ผ๐บ๐ฝ๐ผ๐๐ฒ ๐๐ฝ. Docker builds an image on the fly with all the needed dependencies and scripts, and runs them. You'll have the same functionalities as the ones from source code, but with a way easier deployment process๐
Go check out the GitHub repo for more info ๐ https://github.com/AstraBert/obsidian-digest
Have fun!โจ
If the answer is yes, then this post might be for you!โ
I recently created ๐จ๐๐ฌ๐ข๐๐ข๐๐ง-๐๐ข๐ ๐๐ฌ๐ญ, a Google Gemini-powered application that gives you feedback on style and contents of the documents you have been working on๐ง
Repo ๐ https://github.com/AstraBert/obsidian-digest
PyPi Package ๐ https://pypi.org/project/obsidian-digest/
The app is available as:
- ๐๐จ๐ฆ๐ฆ๐๐ง๐-๐ฅ๐ข๐ง๐ ๐ญ๐จ๐จ๐ฅ: install it as a python package with ๐ฝ๐ถ๐ฝ, and execute it from terminal anytime!๐ฆ
-๐๐ข๐ฌ๐๐จ๐ซ๐ ๐๐จ๐ญ ๐๐ฎ๐ข๐ฅ๐ญ ๐๐ซ๐จ๐ฆ ๐ฌ๐จ๐ฎ๐ซ๐๐ ๐๐จ๐๐: clone the GitHub repo, install the needed dependencies through ๐ฐ๐ผ๐ป๐ฑ๐ฎ, and run the bot: you will get hourly messages with suggestions and considerations about your activity on Obsidian in the previous hour๐ค
- ๐๐ข๐ฌ๐๐จ๐ซ๐ ๐๐จ๐ญ ๐๐๐ฉ๐ฅ๐จ๐ฒ๐๐ ๐ฅ๐จ๐๐๐ฅ๐ฅ๐ฒ ๐ฐ๐ข๐ญ๐ก ๐๐จ๐๐ค๐๐ซ ๐๐จ๐ฆ๐ฉ๐จ๐ฌ๐: clone the GitHub repo and launch ๐ฑ๐ผ๐ฐ๐ธ๐ฒ๐ฟ ๐ฐ๐ผ๐บ๐ฝ๐ผ๐๐ฒ ๐๐ฝ. Docker builds an image on the fly with all the needed dependencies and scripts, and runs them. You'll have the same functionalities as the ones from source code, but with a way easier deployment process๐
Go check out the GitHub repo for more info ๐ https://github.com/AstraBert/obsidian-digest
Have fun!โจ
- 1 reply
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9 days ago
Hi and thanks a lot for the specification!๐ฅฐ
Just as a note from my side, in the article I specify that there is a difference between "open weights" and "open source" models, and I link this blog post: https://www.agora.software/en/llm-open-source-open-weight-or-proprietary/ for a deeper explanation of the difference. I never (and I would never) claimed that Llama is open source, let alone a free software (see the introduction in this article of mine on privacy and data "stealing" risks: https://huggingface.co/blog/as-cle-bert/build-an-ai-powered-search-engine-from-scratch).
And I would have gladly used also DeepSeek, if it had been available on HuggingChat! :)
I nevertheless highly appreciate your comment and I'll for sure be more cautious in using the word "open/open source" in the future. Thanks!โจ
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9 days ago
Both PdfItDown and SenTrEv only work with text for now: in future releases, support for image will be added :)
For text extraction, I use PyPDF + Langchain
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an
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9 days ago
Post
2053
๐๐๐๐ซ๐ฅ๐ฒ ๐๐๐ฐ ๐๐๐๐ซ ๐ซ๐๐ฅ๐๐๐ฌ๐๐ฌ๐
Hi HuggingFacers๐ค, I decided to ship early this year, and here's what I came up with:
๐๐๐๐๐ญ๐๐จ๐ฐ๐ง (https://github.com/AstraBert/PdfItDown) - If you're like me, and you have all your RAG pipeline optimized for PDFs, but not for other data formats, here is your solution! With PdfItDown, you can convert Word documents, presentations, HTML pages, markdown sheets and (why not?) CSVs and XMLs in PDF format, for seamless integration with your RAG pipelines. Built upon MarkItDown by Microsoft
GitHub Repo ๐ https://github.com/AstraBert/PdfItDown
PyPi Package ๐ https://pypi.org/project/pdfitdown/
๐๐๐ง๐๐ซ๐๐ฏ ๐ฏ๐.๐.๐ (https://github.com/AstraBert/SenTrEv/tree/v1.0.0) - If you need to evaluate the ๐ฟ๐ฒ๐๐ฟ๐ถ๐ฒ๐๐ฎ๐น performance of your ๐๐ฒ๐ ๐ ๐ฒ๐บ๐ฏ๐ฒ๐ฑ๐ฑ๐ถ๐ป๐ด models, I have good news for you๐ฅณ๐ฅณ
The new release for ๐๐๐ง๐๐ซ๐๐ฏ now supports ๐ฑ๐ฒ๐ป๐๐ฒ and ๐๐ฝ๐ฎ๐ฟ๐๐ฒ retrieval (thanks to FastEmbed by Qdrant) with ๐๐ฒ๐ ๐-๐ฏ๐ฎ๐๐ฒ๐ฑ ๐ณ๐ถ๐น๐ฒ ๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ (.docx, .pptx, .csv, .html, .xml, .md, .pdf) and new ๐ฟ๐ฒ๐น๐ฒ๐๐ฎ๐ป๐ฐ๐ฒ ๐บ๐ฒ๐๐ฟ๐ถ๐ฐ๐!
GitHub repo ๐ https://github.com/AstraBert/SenTrEv
Release Notes ๐ https://github.com/AstraBert/SenTrEv/releases/tag/v1.0.0
PyPi Package ๐ https://pypi.org/project/sentrev/
Happy New Year and have fun!๐ฅ
Hi HuggingFacers๐ค, I decided to ship early this year, and here's what I came up with:
๐๐๐๐๐ญ๐๐จ๐ฐ๐ง (https://github.com/AstraBert/PdfItDown) - If you're like me, and you have all your RAG pipeline optimized for PDFs, but not for other data formats, here is your solution! With PdfItDown, you can convert Word documents, presentations, HTML pages, markdown sheets and (why not?) CSVs and XMLs in PDF format, for seamless integration with your RAG pipelines. Built upon MarkItDown by Microsoft
GitHub Repo ๐ https://github.com/AstraBert/PdfItDown
PyPi Package ๐ https://pypi.org/project/pdfitdown/
๐๐๐ง๐๐ซ๐๐ฏ ๐ฏ๐.๐.๐ (https://github.com/AstraBert/SenTrEv/tree/v1.0.0) - If you need to evaluate the ๐ฟ๐ฒ๐๐ฟ๐ถ๐ฒ๐๐ฎ๐น performance of your ๐๐ฒ๐ ๐ ๐ฒ๐บ๐ฏ๐ฒ๐ฑ๐ฑ๐ถ๐ป๐ด models, I have good news for you๐ฅณ๐ฅณ
The new release for ๐๐๐ง๐๐ซ๐๐ฏ now supports ๐ฑ๐ฒ๐ป๐๐ฒ and ๐๐ฝ๐ฎ๐ฟ๐๐ฒ retrieval (thanks to FastEmbed by Qdrant) with ๐๐ฒ๐ ๐-๐ฏ๐ฎ๐๐ฒ๐ฑ ๐ณ๐ถ๐น๐ฒ ๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ (.docx, .pptx, .csv, .html, .xml, .md, .pdf) and new ๐ฟ๐ฒ๐น๐ฒ๐๐ฎ๐ป๐ฐ๐ฒ ๐บ๐ฒ๐๐ฟ๐ถ๐ฐ๐!
GitHub repo ๐ https://github.com/AstraBert/SenTrEv
Release Notes ๐ https://github.com/AstraBert/SenTrEv/releases/tag/v1.0.0
PyPi Package ๐ https://pypi.org/project/sentrev/
Happy New Year and have fun!๐ฅ
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10 days ago
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hey nvidia, can you send me a gpu?
comment or react if you want ~~me~~ to get one too. ๐๐
comment or react if you want ~~me~~ to get one too. ๐๐
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12 days ago
Post
544
Hi HF Community!๐ค
As my last 2024 contribution, I decided to write an article about a Competitive Debate Championship simulation I ran with 5 LLMs as competitors and 2 as judges:
https://huggingface.co/blog/as-cle-bert/debate-championship-for-llms
The article covers code, analyses and results, and you can find everything to reproduce this tournament in the GitHub repo ๐ https://github.com/AstraBert/DebateLLM-Championship
I also released a dataset related to the data (motions, arguments, topics, winners...) collected during the tournament ๐ as-cle-bert/DebateLLMs
Happy reading and happy new yeAIr!๐
As my last 2024 contribution, I decided to write an article about a Competitive Debate Championship simulation I ran with 5 LLMs as competitors and 2 as judges:
https://huggingface.co/blog/as-cle-bert/debate-championship-for-llms
The article covers code, analyses and results, and you can find everything to reproduce this tournament in the GitHub repo ๐ https://github.com/AstraBert/DebateLLM-Championship
I also released a dataset related to the data (motions, arguments, topics, winners...) collected during the tournament ๐ as-cle-bert/DebateLLMs
Happy reading and happy new yeAIr!๐
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