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The repository contains a view for semantic-search-engine. Its individual components (pages) are used to prepare data (indexing). This is a ready‑to‑use solution for handling RAG.

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Description

This repository provides a view for the semantic‑search‑engine.
Its individual components (the pages) are used to prepare data for indexing.

Streamlit application

The streamlit_ui/ directory contains the source code for the UI of the semantic search (RAG) engine and the conversational search model.
To start the application, run the run.sh script:

cd streamlit_ui
bash run.sh

Contents of run.sh

#!/bin/bash

# Run the application under the Streamlit server
export STREAMLIT_SERVER_MAX_UPLOAD_SIZE=5000   # maximum upload size per file (in MB)

# LLama2 configuration
export SHOW_LLAMA_70B_MODEL=true   # set to true to enable the 70‑billion‑parameter LLama2 model

# Launch the app
streamlit run Home.py
  • STREAMLIT_SERVER_MAX_UPLOAD_SIZE controls the maximum size of a single file that can be uploaded for indexing. It is set to 5 GB (5000 MB).
  • SHOW_LLAMA_70B_MODEL toggles the 70 B LLama2 model on or off. To disable this model, comment out (or remove) the line that exports this variable.

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The repository contains a view for semantic-search-engine. Its individual components (pages) are used to prepare data (indexing). This is a ready‑to‑use solution for handling RAG.

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