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# Document Semantic Search
A simple Gradio interface for semantic search across multiple PDF documents using a combination of BM25 and vector embeddings to find relevant documents. The script builds a FAISS index on corpus of the uploaded documents, and first uses BM25 to find the top relevant results, then reranks them using cosine similarity to the search query.
## Setup
[Link to venv docs](https://docs.python.org/3/library/venv.html)
### Create environment
```shell
python3 -m venv venv
```
### To activate the environment
UNIX/MacOS:
```shell
source venv/bin/activate
```
Windows:
```shell
venv/Scripts/activate
```
### Install dependencies
If this is your first time running this or the package dependencies have changed, run this command to install all dependencies.
```shell
pip install -r requirements.txt
```
## Run
Run the app in reload mode with this command. This will let the app reload automatically when changes are made to the python script.
```shell
python main.py
```
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