Maharshi Gor
Squash merge dictify-states into main
9756440
"""Guide content for the Quizbowl platform."""
GUIDE_MARKDOWN = """
# 🎯 Quizbowl Bot Guide
"""
QUICKSTART_MARKDOWN = """
## Quick Start
1. Choose between Tossup or Bonus mode
2. Design your pipeline
3. Test on example questions
4. Submit for evaluation
## Competition Rules
### 🧠 Tossup Questions
- **Format**: Individual questions progressively revealed. Questions get easier as they are revealed.
- **Scoring**:
- Correct early buzz: +10 points
- Incorrect early buzz: -5 points
- Correct after full read: +10 points
- **Required Outputs**:
- `answer`: Your predicted answer
- `confidence`: Score between 0-1
- `buzzer`: When to attempt answering
- Configure with confidence threshold (0.0-1.0)
- Optional token probability threshold for more control
- Combine thresholds using AND/OR logic (buzz when both/either condition met)
### 🎁 Bonus Questions
- **Format**:
- Consists of a `leadin` paragraph that introduces the topic
- Followed by three related `parts` (A, B, C) that test specific knowledge
- Each part is worth 10 points
- **Scoring**: +10 points per correct part (max 30)
- **Required Outputs**:
- `answer`: Your predicted answer
- `confidence`: Score between 0-1
- `explanation`: Brief justification for human collaboration
"""
BUILDING_MARKDOWN = """
## Building Your First Pipeline
### 1. Simple Pipeline (Recommended for First Submission)
- Single model step
- Configure:
- Model selection
- Temperature (0.0-1.0)
- System prompt
- Required outputs
### 2. Using Demo Pipelines
- Load existing demo pipelines as starting points
- Modify configurations:
- Adjust model parameters
- Update system prompts
- Change confidence thresholds
- Add/remove pipeline steps
- Save modified versions as new pipelines
- Test changes incrementally
### 3. Testing Your Pipeline
1. Select an example question
2. For Tossup:
- Set buzz threshold (0.5-1.0)
- Enable early stopping
3. Run and check:
- Answer accuracy
- Confidence scores
- Performance metrics
### 4. Evaluation
- Test on multiple questions
- Monitor:
- Accuracy
- Confidence patterns
- Response times
### 5. Submission
1. Log in to Hugging Face
2. Name your model
3. Add description
4. Submit for evaluation
## Tips for Success
- Start with simple pipeline
- Test thoroughly before submission
- Use appropriate temperature (0.3-0.7 recommended)
- Monitor confidence scores
- Check example submissions
## Need Help?
- Review example submissions
- Check documentation
- Contact support
"""