README.md

---
license: mit
tags:
- transformers.js
- transformers
- semanticsearch
- SemanticFinder
---
<p align="center">
  <a href="https://do-me.github.io/SemanticFinder/">
    <img src="https://github.com/do-me/SemanticFinder/assets/47481567/4522ab9d-08f4-4f4c-92db-dbf14ccb2b70" width="320" alt="SemanticFinder">
  </a>    
<h1 align="center">Frontend-only live semantic search with transformers.js</h1>
</p>

- **App: [SemanticFinder](https://do-me.github.io/SemanticFinder/)**

- **GitHub: [do-me/SemanticFinder](https://github.com/do-me/SemanticFinder)**

This is the HF data repo for indexed texts, ready-to-import in SemanticFinder. The files contain the original text, text chunks and their embeddings. 

### Catalogue

| filesize | textTitle | textAuthor | textYear | textLanguage | URL | modelName | quantized | splitParam | splitType | characters | chunks | wordsToAvoidAll | wordsToCheckAll | wordsToAvoidAny | wordsToCheckAny | exportDecimals | lines | textNotes | textSourceURL | filename |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 4.78 | Das Kapital | Karl Marx | 1867 | de | https://do-me.github.io/SemanticFinder/?hf=Das_Kapital_c1a84fba | Xenova/multilingual-e5-small | True | 80 | Words | 2003807 | 3164 |  |  |  |  | 5 | 28673 |  | https://ia601605.us.archive.org/13/items/KarlMarxDasKapitalpdf/KAPITAL1.pdf | Das_Kapital_c1a84fba.json.gz |
| 2.58 | Divina Commedia | Dante | 1321 | it | https://do-me.github.io/SemanticFinder/?hf=Divina_Commedia_d5a0fa67 | Xenova/multilingual-e5-base | True | 50 | Words | 383782 | 1179 |  |  |  |  | 5 | 6225 |  | http://www.letteratura-italiana.com/pdf/divina%20commedia/08%20Inferno%20in%20versione%20italiana.pdf | Divina_Commedia_d5a0fa67.json.gz |
| 11.92 | Don Quijote | Miguel de Cervantes | 1605 | es | https://do-me.github.io/SemanticFinder/?hf=Don_Quijote_14a0b44 | Xenova/multilingual-e5-base | True | 25 | Words | 1047150 | 7186 |  |  |  |  | 4 | 12005 |  | https://parnaseo.uv.es/lemir/revista/revista19/textos/quijote_1.pdf | Don_Quijote_14a0b44.json.gz |
| 0.06 | Hansel and Gretel | Brothers Grimm | 1812 | en | https://do-me.github.io/SemanticFinder/?hf=Hansel_and_Gretel_4de079eb | TaylorAI/gte-tiny | True | 100 | Chars | 5304 | 55 |  |  |  |  | 5 | 9 |  | https://www.grimmstories.com/en/grimm_fairy-tales/hansel_and_gretel | Hansel_and_Gretel_4de079eb.json.gz |
| 13.52 | Iliad | Homer | -750 | gr | https://do-me.github.io/SemanticFinder/?hf=Iliad_8de5d1ea | Xenova/multilingual-e5-small | True | 20 | Words | 1597139 | 11848 |  |  |  |  | 5 | 32659 | Including modern interpretation | https://www.stipsi.gr/homer/iliada.pdf | Iliad_8de5d1ea.json.gz |
| 1.74 | IPCC Report 2023 | IPCC | 2023 | en | https://do-me.github.io/SemanticFinder/?hf=IPCC_Report_2023_2b260928 | Supabase/bge-small-en | True | 200 | Chars | 307811 | 1566 |  |  |  |  | 5 | 3230 | state of knowledge of climate change | https://report.ipcc.ch/ar6syr/pdf/IPCC_AR6_SYR_LongerReport.pdf | IPCC_Report_2023_2b260928.json.gz |
| 25.56 | King James Bible |  | None | en | https://do-me.github.io/SemanticFinder/?hf=King_James_Bible_24f6dc4c | TaylorAI/gte-tiny | True | 200 | Chars | 4556163 | 23056 |  |  |  |  | 5 | 80496 |  | https://www.holybooks.com/wp-content/uploads/2010/05/The-Holy-Bible-King-James-Version.pdf | King_James_Bible_24f6dc4c.json.gz |
| 11.45 | King James Bible |  | None | en | https://do-me.github.io/SemanticFinder/?hf=King_James_Bible_6434a78d | TaylorAI/gte-tiny | True | 200 | Chars | 4556163 | 23056 |  |  |  |  | 2 | 80496 |  | https://www.holybooks.com/wp-content/uploads/2010/05/The-Holy-Bible-King-James-Version.pdf | King_James_Bible_6434a78d.json.gz |
| 39.32 | Les Misérables | Victor Hugo | 1862 | fr | https://do-me.github.io/SemanticFinder/?hf=Les_Misérables_2239df51 | Xenova/multilingual-e5-base | True | 25 | Words | 3236941 | 19463 |  |  |  |  | 5 | 74491 | All five acts included | https://beq.ebooksgratuits.com/vents/Hugo-miserables-1.pdf | Les_Misérables_2239df51.json.gz |
| 0.46 | REGULATION (EU) 2023/138 | European Commission | 2022 | en | https://do-me.github.io/SemanticFinder/?hf=REGULATION_(EU)_2023_138_c00e7ff6 | Supabase/bge-small-en | True | 25 | Words | 76809 | 424 |  |  |  |  | 5 | 1323 |  | https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32023R0138&qid=1704492501351 | REGULATION_(EU)_2023_138_c00e7ff6.json.gz |
| 0.07 | Universal Declaration of Human Rights | United Nations | 1948 | en | https://do-me.github.io/SemanticFinder/?hf=Universal_Declaration_of_Human_Rights_0a7da79a | TaylorAI/gte-tiny | True | \nArticle  | Regex | 8623 | 63 |  |  |  |  | 5 | 109 | 30 articles | https://www.un.org/en/about-us/universal-declaration-of-human-rights | Universal_Declaration_of_Human_Rights_0a7da79a.json.gz |

### Example
Once loaded in SemanticFinder it takes around 2 seconds to search through the whole bible! Try it out. 

1. Click on one of the example URLs of your choice.
2. Once the index loaded, simply enter something you want to search for and hit "Find". The results will appear almost instantly.

### Create SemanticFinder files 

1. Just use SemanticFinder as usual and run at least one search so that the index is created. This might take a while if your input is large. E.g. indexing the bible with 200 chars results in ~23k embeddings and takes 15-30 mins with a quantized gte-tiny model.
2. Add the metadata (so other people can find your index) and export the file. Note that you have the freedom to reduce decimals to reduce file size; usually 3 is more than enough depending on the model. Less than 3 will also do in most cases but if you need highest accuracy go with 5 or more.
3. Create a PR here if you want to see it added in the official collection! Just make sure to run `create_meta_data_csv_md.py` once to update the csv/md file. For now, the `readme.md` table here needs to be updated with the meta_data.md manually.

### Privacy
- This repo is public and shares documents of public interest or documents in the public domain.
- If you have sensitive documents you can still create the index with SemanticFinder and use it only locally.
  Either you can load the index from disk each time or you host it in your local network and add the URL in SemanticFinder.