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| title: Find My Book | |
| emoji: 🌍 | |
| colorFrom: red | |
| colorTo: purple | |
| sdk: streamlit | |
| sdk_version: 1.28.1 | |
| app_file: app.py | |
| pinned: false | |
| license: apache-2.0 | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
| # Recommendation system project | |
| # Find my book | |
|  | |
| ### Additional subtask: | |
| # Find a dish for me | |
|  | |
| # Elbrus Bootcamp | Phase-2 | Team Project | |
| ## Team | |
| * [Daniil Lvov](https://huggingface.co/Norgan97) | |
| * [Dmitry Budazhapov](https://huggingface.co/DmitryDorzhievich) | |
| * [Larisa Khlapushina](https://huggingface.co/Larrisa) | |
| ___ | |
| ## Tasks | |
| In this project, our team has developed a book search system based on user requests. | |
| The service takes a user's description of the book as input and returns a specified number of suitable options. | |
| In addition to book search, we can offer a system that will find the desired dish and a link to its recipe. | |
| In this case, the user only needs to enter an approximate description of the characteristics and ingredients. | |
| We have implemented a mechanism for analyzing and comparing textual descriptions of dishes, | |
| which allows for effectively finding alternatives and variations of desired dishes. | |
| The work represents an innovative approach to searching for culinary recipes and can be useful for both professional chefs and culinary enthusiasts. | |
| ___ | |
| ## Contents | |
| 1. Parsing information from websites. | |
| 2. Vectorization using a model *rubert-tiny2* | |
| 3. Finding similar vectors using *faiss*. | |
| ___ | |
| ## Deployment | |
| The service is implemented on [Streamlit](https://huggingface.co/spaces/ds-meteors/find_my_book) | |
| _ | |
| ## How to run locally? | |
| ## To run the provided applications on your computer, follow these steps: | |
| 1. Clone this repository to your local machine. | |
| 2. Install the required libraries by running the command *pip install -r requirements.txt* in your terminal or command prompt. | |
| 3. Once the libraries are installed, navigate to the repository's directory in your terminal. | |
| 4. Run the command *streamlit run main.py* in your terminal to start the application. | |
| This will launch the Streamlit server, and you can access the applications by opening a browser window and navigating to the specified URL. | |