🔍 AI-Enhanced TV Series Analysis & Character Interaction
SeriesLens is an AI-powered framework designed to analyze TV series using NLP, LLMs, and character interactions. It enables users to chat with their favorite TV series characters, classify themes, extract character networks, and analyze series transcripts. The scope of this project is to built a character Chatbot to chat with your favorite TV series characters, analyze a series with NLP and LLMs, scrape our own dataset, use zero shot classifiers, build our own LLM text classifier, use NER to build a character network and build a character chatbot to chat..
🗣️ Character Chatbot – Chat with TV series characters using LLM-powered conversational AI.
📊 Theme Classification – Identify and categorize themes in series scripts using zero-shot classifiers.
🕵️ Named Entity Recognition (NER) – Extract character names and interactions to build a character network.
🤖 Custom LLM Text Classifier – Train a personalized text classification model for deeper series analysis.
📡 Data Scraping – Collect and process custom dataset for improved model training.
A[Data Collection & Scraping] --> B[Preprocessing & Cleaning];
B --> C[NER & Character Network];
C --> D[Theme Classification];
D --> E[Text Classification];
E --> F[Character Chatbot];
F --> G[Insights & Analysis];
Frameworks: Gradio, Hugging Face Transformers, Scrapy, BeautifulSoup
Models: Llama-3, Zero-shot Classifiers, Named Entity Recognition (NER)
Languages: Python
Visualization: Graph Networks, Bar Charts
Clone the repository and install dependencies:
git clone https://github.com/yash-raj202134/SeriesLens.git
cd SeriesLens
pip install -r requirements.txt
Run the application:
python app.py
Expand support for more TV series.
Enhance chatbot personality and response generation.
Improve character network analysis with advanced NLP techniques.
This project is licensed under the MIT License.
For any suggestions or contributions, feel free to reach out!