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--- |
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license: mit |
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language: |
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- en |
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base_model: |
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- deepseek-ai/DeepSeek-R1 |
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- Qwen/Qwen2.5-VL-72B-Instruct |
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--- |
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# Model Card for Model ID |
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AI that can answer user's queries based on the user's given pdf, url links and straight direct researchers |
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It has three main functions , PDF-ChatBot, Edu-Scraper, and Edu Researcher. |
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## Installation |
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1. ```cd Edu-Ai``` |
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2. ```pip install requirements.txt``` |
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3. ```pip install streamlit``` |
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4. ```streamlit run Hellopage.py``` |
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5. Please get your own hugging face token to add in secrets.toml so that you can use the models. |
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### Model Description |
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1. ```Hellopage.py``` : The starting page where you can choose the options between PDF-ChatBot, Edu-Scraper, Edu-Researcher. |
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2. ```pdf_rag.py``` : Using RAG, user can input their queries and pdfs so that they can recieve their desired answers. |
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3. ```Edu-Scraper.py``` : Using RAG and selenium, user can input their url and their queries so that they can recieve their desired answers. |
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4. ```Edu-Researcher.py``` : Using DDGS and Stategraph, user can get straight to the point searches. |
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- **Developed by:** [UIT batch 10 Section A] |
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- **Model type:** [RAG] |
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- **Language(s) (NLP):** [English] |
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- **License:** [MIT] |
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### Model Sources |
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- **Repository:** [https://github.com/FightaHackathon/Edu-Ai] |
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- **Demo:** [https://edu-ai.streamlit.app/] |
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## Uses |
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- Able to summarize pdfs and urls given by user's queries and straight to the point researches. |
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### Important notes |
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1. Users can choose between qwen and deepseek for their preference modes(Can add more models by just modifying the codes slightly |
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2. Please get your own hugging face token from making an account in https://huggingface.co/welcome |
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