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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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+ # Recommendation system project
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+ # Find my book
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+ ![](https://sun9-46.userapi.com/impg/HvvkmK5Z3-HWHh2eT7Knv-E-ibwK04HI25ASUg/aBMfuCXNiR0.jpg?size=1920x1285&quality=95&sign=48abf3e3dc9344005305f55f18ddee5d&type=album)
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+ ### Additional subtask:
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+ # Find a dish for me
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+ ![](https://i.imgur.com/LqccfIw.jpg)
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+ # Elbrus Bootcamp | Phase-2 | Team Project
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+
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+ ## Team
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+ * [Daniil Lvov](https://huggingface.co/Norgan97)
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+ * [Dmitry Budazhapov](https://huggingface.co/DmitryDorzhievich)
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+ * [Larisa Khlapushina](https://huggingface.co/Larrisa)
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+ ___
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+ ## Tasks
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+ In this project, our team has developed a book search system based on user requests.
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+ The service takes a user's description of the book as input and returns a specified number of suitable options.
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+ In addition to book search, we can offer a system that will find the desired dish and a link to its recipe.
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+ In this case, the user only needs to enter an approximate description of the characteristics and ingredients.
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+ We have implemented a mechanism for analyzing and comparing textual descriptions of dishes,
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+ which allows for effectively finding alternatives and variations of desired dishes.
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+ The work represents an innovative approach to searching for culinary recipes and can be useful for both professional chefs and culinary enthusiasts.
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+ ___
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+ ## Contents
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+ 1. Parsing information from websites.
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+ 2. Vectorization using a model *rubert-tiny2*
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+ 3. Finding similar vectors using *faiss*.
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+ ___
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+ ## Deployment
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+ The service is implemented on [Streamlit](https://huggingface.co/spaces/ds-meteors/find_my_book)
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+ _
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+ ## How to run locally?
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+ ## To run the provided applications on your computer, follow these steps:
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+ 1. Clone this repository to your local machine.
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+ 2. Install the required libraries by running the command *pip install -r requirements.txt* in your terminal or command prompt.
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+ 3. Once the libraries are installed, navigate to the repository's directory in your terminal.
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+ 4. Run the command *streamlit run main.py* in your terminal to start the application.
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+ This will launch the Streamlit server, and you can access the applications by opening a browser window and navigating to the specified URL.