A user-friendly desktop application that allows you to engage directly with the contents of PDF files. Upload your PDF and ask questions to receive instant, contextually accurate responses.
Find any information inside your PDFs quickly without scrolling through pages.
Ask questions and receive accurate answers based on the content of your PDF.
All processing happens locally on your machine, ensuring data privacy.
Simply upload a PDF and start chatting with its content immediately.
Flan-T5 is a powerful language model capable of performing a wide range of question answering.
| Component | Description | Benefit |
|---|---|---|
| Tokenizer | Converts input text into token IDs | Enables numerical processing of text |
| Embedding Layer | Maps token IDs to dense vector representations | Captures semantic meaning of words |
| Positional Encoding | Adds position-dependent information to embeddings | Helps model understand word order |
| Self-Attention (Encoder & Decoder) | Captures contextual relationships between tokens | Improves long-range dependencies |
| Cross-Attention (Decoder) | Uses encoder output to refine generation | Ensures context-aware text generation |
| Feed-Forward Layer | Applies transformations to enhance feature extraction | Improves model’s representational power |
| Layer Normalization | Stabilizes activations during training | Prevents gradient explosion or vanishing |
| Dropout | Randomly drops connections during training | Reduces overfitting and improves generalization |
| Linear Layer | Transforms decoder output to vocabulary size | Prepares data for probability computation |
| Softmax Layer | Converts logits into probability distribution | Enables text generation with confidence scores |
