Sci-Fi Seeker

An AI assistant with a semantic engine/question writing tutor in Sci-Fi Stack Exchange service
built on top of Streamlit.

Features • How To Use • Contact • Credits • License

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.

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:

Via the website https://huggingface.co/spaces/kamil-pytlak/SFSeeker
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.

# 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. I'd really appreciate it!

Credits

This software uses the following open source packages:

License

MIT

GitHub @kamilpytlak · LinkedIn kamil-pytlak

kamilpytlak/SFSeeker