Feature/streamlit tfidf config

[Prateek2007-cmd]

Description

exposing TF-IDF Vectorizer configuration controls directly within the Streamlit UI's sidebar. This allows users to dynamically tune text processing parameters based on their custom dataset sizes before building the Content-Based recommendation model.
Closes #1637
Changes included:

• Dynamic Configuration: Added Streamlit sidebar controls for N-gram Range (slider for unigrams, bigrams, etc.), Max Features (number input), and Stop Words (dropdown for English, None, or Custom lists).
• Custom Stop Words Support: Added a conditional text input field to allow users to provide their own comma-separated stop words.
• Model Builder Integration: Passed the dynamic configuration variables directly into the ContentRecommender initialization step.
• Feedback Display: Added an st.info banner that displays the exact number of vocabulary features extracted (e.g., TF-IDF Vectorizer built with 10,000 features) after the model finishes building.

Related Issues

• Resolves #1598

Type of Change

• New Feature (Streamlit UI Controls)

Testing

• Verified selecting different max features correctly updates the total resulting features in the UI.
• Verified selecting the "Custom" stop words option correctly processes the comma-separated strings and successfully initializes the sklearn vectorizer.

[github-actions]

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Labels added: gssoc:approved | mentor:leonagoel | status:review-needed

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