Added content to README.md

README.md

@@ -1,13 +1,90 @@
 ---
-title: SFSeeker
-emoji: 📉
-colorFrom: green
-colorTo: red
+title: Sci-Fi Seeker
+emoji: 👽
+colorFrom: purple
+colorTo: black
 sdk: streamlit
 sdk_version: 1.27.1
 app_file: app.py
-pinned: false
+pinned: true
 license: mit
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+<h1 align="center">
+  <br>
+  <img src="img/logo.jpg" alt="SFSeeker logo" width="250">
+  <br>
+  Sci-Fi Seeker
+  <br>
+</h1>
+
+<h4 align="center">An AI assistant with a semantic engine/question writing tutor in Sci-Fi Stack Exchange service<br>built on top of <a href="https://streamlit.io/" target="_blank">Streamlit</a>.</h4>
+
+<p align="center">
+  <a href="#features">Features</a> •
+  <a href="#how-to-use">How To Use</a> •
+  <a href="#contact">Contact</a> •
+  <a href="#credits">Credits</a> •
+  <a href="#license">License</a>
+</p>
+
+![screenshot](img/semantic_search.jpg)
+
+<p align="center">
+SF Seeker is an AI assistant designed for Sci-Fi Stack Exchange, utilizing an all-MiniLM-L6-v2 language model. It helps users improve their question-writing skills and find similar questions on the Sci-Fi Stack Exchange website. This tool leverages a database of 71,013 questions to locate semantically similar questions, reducing the likelihood of creating duplicate threads. Additionally, SF Seeker is in the process of developing a feature that identifies words in questions that affect the likelihood of receiving answers, assisting users in formulating more precise inquiries. This feature uses a model trained with gradient reinforcement based on TF-IDF features.
+</p>
+
+## Features
+
+*  🔎 Based on a database of 71,013 questions, it searches for the most semantically similar questions to the one entered by the user. This supports the process of fiding the same/similar questions already asked and prevents the creation of duplicate threads.
+*  👨‍⚕️ [IN PROGRESS] Indicates words in a question that have a negative and positive effect on the chance of getting an answer. It supports the process of arranging more precise questions. A model based on gradient reinforcement learned using TF-IDF features was used.
+
+## How To Use
+There are two ways to use this app:
+1. Via the website https://huggingface.co/spaces/kamil-pytlak/SFSeeker
+2. Locally by cloning the repository (using git or by downloading it directly from the website), install the dependencies from the configuration file `Pipfile` and launch the app locally using a browser.
+
+```bash
+# Clone this repository
+$ git clone https://github.com/kamilpytlak/SFSeeker
+
+# Go into the repository
+$ cd SFSeeker
+
+# Install pipenv (in case it's not installed) and, run pipenv shell and install dependencies
+$ pip install pipenv
+$ pipenv shell
+$ pipenv install
+
+# Ensure that the streamlit package was installed successfully.
+$ streamlit hello
+
+# Finally, run the app locally
+$ streamlit run ./main.py
+```
+
+## Contact
+
+If you have any problems, ideas or general feedback, please don't hesitate to contact me at [kam.pytlak@gmail.com](mailto:kam.pytlak@gmail.com). I'd really appreciate it!
+
+## Credits
+
+This software uses the following open source packages:
+
+- [Streamlit](https://streamlit.io/)
+- [pandas](https://pandas.pydata.org/)
+- [scikit-learn](https://scikit-learn.org/stable/#)
+- [scikit-learn-intelex](https://intel.github.io/scikit-learn-intelex/)
+- [xgboost](https://xgboost.readthedocs.io/en/latest/index.html)
+- [sentence-transformers](https://www.sbert.net/)
+
+## License
+MIT
+
+---
+
+> GitHub [@kamilpytlak](https://github.com/kamilpytlak) &nbsp;&middot;&nbsp;
+> LinkedIn [kamil-pytlak](https://www.linkedin.com/in/kamil-pytlak/)
+
+