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## π Quick Checklist
- [ ] All files created
- [ ] HF account ready
- [ ] HF Token obtained
- [ ] Space created
- [ ] Files uploaded
- [ ] App running
---
## π Project Structure
Create a folder called `paperchat` with these files:
```
paperchat/
βββ app.py # Main Streamlit application
βββ requirements.txt # Python dependencies
βββ README.md # Hugging Face Spaces config
βββ .env # Local environment variables (don't upload this!)
```
---
## π§ Step 1: Local Setup & Testing (Optional but Recommended)
### 1.1 Create virtual environment
```bash
# Create project folder
mkdir paperchat
cd paperchat
# Create virtual environment
python -m venv venv
# Activate it
# On Windows:
venv\Scripts\activate
# On Mac/Linux:
source venv/bin/activate
```
### 1.2 Install dependencies
```bash
pip install -r requirements.txt
```
### 1.3 Set up HF Token
Create a `.env` file:
```bash
# .env file content
HF_TOKEN=hf_your_token_here
```
**Get your token**: https://huggingface.co/settings/tokens
### 1.4 Test locally
```bash
streamlit run app.py
```
Open http://localhost:8501 and test with a sample PDF!
---
## π Step 2: Deploy to Hugging Face Spaces
### 2.1 Create a new Space
1. Go to https://huggingface.co/spaces
2. Click **"Create new Space"**
3. Fill in:
- **Space name**: `paperchat` (or your preferred name)
- **License**: MIT
- **Select SDK**: Streamlit
- **Hardware**: CPU (free tier is fine!)
- **Visibility**: Public
### 2.2 Upload files
**Option A: Via Web Interface**
1. Click "Files" tab in your Space
2. Click "Add file" β "Upload files"
3. Upload: `app.py`, `requirements.txt`, `README.md`
4. Commit changes
**Option B: Via Git (Recommended)**
```bash
# Clone your space
git clone https://huggingface.co/spaces/YOUR_USERNAME/paperchat
cd paperchat
# Copy your files
cp /path/to/app.py .
cp /path/to/requirements.txt .
cp /path/to/README.md .
# Commit and push
git add .
git commit -m "Initial commit"
git push
```
### 2.3 Add HF Token to Secrets
1. Go to your Space settings
2. Click "Settings" β "Repository secrets"
3. Click "Add a secret"
4. Name: `HF_TOKEN`
5. Value: Your Hugging Face token
6. Save
### 2.4 Wait for build
The Space will automatically build and deploy. Watch the logs:
- β³ Building... (1-2 minutes)
- β
Running!
---
## β
Step 3: Verify Deployment
1. Visit your Space URL: `https://huggingface.co/spaces/YOUR_USERNAME/paperchat`
2. Upload a test PDF (try a short research paper)
3. Ask a question
4. Verify you get an answer
---
## π Common Issues & Fixes
### Issue 1: "Module not found" error
**Fix**: Check `requirements.txt` has all dependencies
```txt
smolagents
streamlit
pypdf
langchain
langchain-community
sentence-transformers
python-dotenv
rank_bm25
```
### Issue 2: "HF_TOKEN not found"
**Fix**: Add token to Space secrets (Step 2.3)
### Issue 3: App crashes on PDF upload
**Fix**: Usually a memory issue. Try:
- Smaller PDF (< 10 MB)
- Reduce `chunk_size` in app.py to 300
### Issue 4: Slow response times
**Fix**: This is normal for free tier. Upgrade to better hardware in Space settings if needed.
---
## π¨ Step 4: Customization (Optional)
### Change the model
In `app.py`, modify the agent creation:
```python
agent = CodeAgent(
tools=[retriever_tool],
model=InferenceClientModel(model_id="meta-llama/Llama-3.3-70B-Instruct"),
max_steps=4,
verbosity_level=0,
)
```
### Change colors/theme
Update `README.md` header:
```yaml
colorFrom: red
colorTo: yellow
```
### Add example papers
Pre-load famous papers in the sidebar for quick demos.
---
## π Step 5: Monitor & Improve
### Track usage
- Check Space analytics in HF dashboard
- Monitor error logs
### Collect feedback
Add a feedback button:
```python
if st.button("π Helpful"):
st.success("Thanks for your feedback!")
```
### Add features
Ideas:
- Multiple paper comparison
- Export chat as PDF
- Highlight relevant sections
- Paper summarization mode
---
## π Step 6: Add to Resume/Portfolio
### Resume bullet point
```
β’ Built PaperChat, an AI-powered research paper Q&A tool using Agentic RAG,
deployed on Hugging Face Spaces with 100+ users
β’ Implemented retrieval-augmented generation with BM25 + LLM agents for
accurate question answering with source citations
```
### Portfolio description
```
PaperChat - Research Paper Q&A Assistant
An intelligent document assistant that helps researchers quickly understand
and extract information from academic papers. Built with smolagents and
deployed on Hugging Face Spaces.
Tech: Python, Streamlit, LangChain, RAG, BM25, LLM Agents
Live Demo: [your-space-url]
```
---
## π You're Done!
Your app is now:
- β
Live on the internet
- β
Accessible to anyone
- β
Resume-ready
- β
Portfolio-worthy
Share your Space URL with friends, on LinkedIn, or in your resume!
---
## π Need Help?
- **Hugging Face Docs**: https://huggingface.co/docs/hub/spaces
- **Streamlit Docs**: https://docs.streamlit.io
- **smolagents Docs**: https://github.com/huggingface/smolagents
---
**Pro Tip**: Record a 30-second demo video showing:
1. Upload a paper
2. Ask a question
3. Get an answer
Use this video in your portfolio or LinkedIn post! π¬ |