So you’ve got too many study materials and not enough brain RAM? Throw your notes at this cat. It reads all your crap and answers like it’s been secretly doing 10x engineering while napping.
Built with Streamlit because React is too much work. Powered by Groq LLMs 'cause they’re turbo fast.
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Upload Your Mess:
- PDFs
- Word Docs (.docx)
- PowerPoints (.pptx)
- Image files (.png, .jpg, etc.)
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Reads Literally Anything:
- Text? Easy.
- Images inside slides or scanned PDFs? OCR handles it like a champ.
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RAG Magic:
- Smart embeddings via sentence-transformers
- FAISS = fancy text search engine on roids
- Groq-powered LLMs reply like it knows everything (almost)
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Chat Like It’s 2025:
- Streamlit chat UI, no weird CSS
- Dropdown to choose your LLM weapon (Llama, Mixtral, Gemma, etc.)
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Frontend: Streamlit (no React, we’re chill)
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Backend: Python 3.10+
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LLMs: Groq API (Llama 3, Mixtral, Gemma 2, and more)
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Embeddings: sentence-transformers
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Vector Store: FAISS
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File Reading:
- PyMuPDF, python-docx, python-pptx
- Tesseract OCR (for image-based suffering)
- Python 3.10+ (yes, it matters)
- Git
- Tesseract-OCR (seriously, install it)
git clone https://github.com/givenby/askthecat
cd askthecatpython3 -m venv venv
source venv/bin/activate # or .\venv\Scripts\activate on Windowspip install -r requirements.txtCreate .streamlit/secrets.toml with:
GROQ_API_KEY="gsk_yourSuperSecretGroqKey"streamlit run ui/app.pyThen open http://localhost:8501 in your browser. It just works™.
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Add
packages.txt:tesseract-ocr poppler-utils -
Push code to GitHub
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Add your Groq API key in Streamlit secrets
- Docker is ready to go. Use this from root:
docker build -t askthecat . && docker run -p 7860:7860 askthecat- Citations so you can pretend it's research
- See the chunks it retrieved (for nerds)
- Save your vector DB like save game files
- Semantic chunking (because fixed-size is dumb)
- Docker that actually works
MIT – Basically, do what you want, just don’t blame the cat.