Fixed errors in README
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# embeddingsearch
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**This is still highly work-in-progress**
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Embeddingsearch is a python library that uses Embedding Similarity Search (similiarly to [Magna](https://github.com/yousef-rafat/Magna/tree/main)) to semantically compare a given input to a database of pre-processed entries.
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When first implementing the idea, it was conceptualized to only import files into the database.
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# How to set up
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1. Install 
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1. Install [ollama](https://ollama.com/download)
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2. Pull a few models using ollama (e.g. `paraphrase-multilingual`, `bge-m3`, `mxbai-embed-large`, `nomic-embed-text`)
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3. [Install the depencencies](#installing-the-dependencies)
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4. [Set up a local mysql database](#mysql-database-setup)
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@@ -45,8 +47,7 @@ CREATE TABLE embedding (id int PRIMARY KEY auto_increment, id_datapoint int, mod
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```
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# To-do
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- Proper config file
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- Add support for other databases?
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- Implement the api server (WSGI via gunicorn / falcon)
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- Add database setup script?
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- Remove tables related to caching (It's not done on the sql server side anymore.)
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