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---
title: DocumentQandAI
emoji: π
colorFrom: gray
colorTo: yellow
sdk: gradio
sdk_version: 5.31.0
app_file: app.py
pinned: false
license: apache-2.0
short_description: QandAI
---
# π Document Q&A Demo
[](https://huggingface.co/spaces/your-username/doc-qa)
[]
[](https://huggingface.co/deepset/roberta-base-squad2)
[](LICENSE)
---
## π Overview
Turn **any piece of text**βpolicies, FAQs, product descriptionsβinto an interactive **QA interface**.
Leverages **contextual embeddings** and **spanβextraction** to pinpoint precise answers in real time.
> **Key AI buzzwords:**
> β’ Contextual Question Answering β’ Span Extraction β’ Transformer-based NLP β’ Real-time inference β’ Edge (CPU) deployment β’ User-centric UX β’ Cloud-native AI
---
## β¨ Features
| π Feature | π Description |
|-----------------------------|--------------------------------------------------------------------|
| **π Document Context** | Paste up to thousands of wordsβno size limits beyond text input. |
| **β Natural Questions** | Ask anything about your document in plain English. |
| **β‘ Instant Answers** | Results in <500 ms on free CPU tierβno GPUs required. |
| **π Confidence Score** | See the modelβs certainty (0β1) alongside each answer. |
| **π¨ Sleek Gradio UI** | Intuitive Blocks layout with input, button, and output panel. |
| **π§ Drop-in Deployment** | Commit three filesβSpaces auto-builds and hosts your demo. |
---
## ποΈ Architecture & Workflow
1. **User pastes** document text into the **Context** box.
2. **User submits** a free-form question.
3. **`transformers` QA pipeline** (RoBERTa-SQuAD2) locates the answer span.
4. **Answer + confidence** rendered in the UI.
All computation happens **locally on the Space**, ensuring **data privacy** and **zero API costs**.
---
## π οΈ Local Development
```bash
git clone https://github.com/your-username/doc-qa.git
cd doc-qa
python3 -m venv venv && source venv/bin/activate
pip install -r requirements.txt
python app.py
## Latest Update
- Upgraded RoBERTa-SQuAD2 model for better answers. - May 29, 2025 π
- Enhanced confidence score display. - June 30, 2025 π
- Improved handling of large documents. - June 29, 2025 π
- Upgraded RoBERTa-SQuAD2 model for better answers. - June 28, 2025 π
- Added support for multi-question inputs. - June 27, 2025 π
- Optimized CPU inference for faster responses. β - June 26, 2025 π
- Enhanced confidence score display. - June 25, 2025 π
- Improved handling of large documents. β‘ - June 24, 2025 π
- Added support for multi-question inputs. π - June 22, 2025 π
- Optimized CPU inference for faster responses. π - June 21, 2025 π
- Enhanced confidence score display. π¨ - June 20, 2025 π
- Improved handling of large documents. - June 19, 2025 π
- Upgraded RoBERTa-SQuAD2 model for better answers. - June 18, 2025 π
- Added support for multi-question inputs. π - June 17, 2025 π
- Optimized CPU inference for faster responses. - June 16, 2025 π
- Enhanced confidence score display. β‘ - June 15, 2025 π
- Improved handling of large documents. - June 14, 2025 π
- Upgraded RoBERTa-SQuAD2 model for better answers. β - June 13, 2025 π
- Optimized CPU inference for faster responses. - June 11, 2025 π
- Enhanced confidence score display. π¨ - June 10, 2025 π
- Improved handling of large documents. π - June 09, 2025 π
- Upgraded RoBERTa-SQuAD2 model for better answers. π - June 08, 2025 π
- Added support for multi-question inputs. π¨ - June 07, 2025 π
- Optimized CPU inference for faster responses. β‘ - June 06, 2025 π
- Enhanced confidence score display. - June 05, 2025 π
- Improved handling of large documents. - June 04, 2025 π
- Upgraded RoBERTa-SQuAD2 model for better answers. β - June 03, 2025 π
- Added support for multi-question inputs. - June 02, 2025 π
- Optimized CPU inference for faster responses. π - June 01, 2025 π
- Enhanced confidence score display. - May 31, 2025 π
- Improved handling of large documents. - May 30, 2025 π
**Website**: https://ghostainews.com/
**Discord**: https://discord.gg/BfA23aYz |