Prompt Management¶
Learn how to create and manage prompts that define your bot's behavior and personality.
Understanding Prompts¶
What is a Prompt?¶
A prompt is a set of instructions that tells your bot:
- How to behave and interact
- What role to play
- How to use the knowledge base
- What tone and style to use
- What rules to follow
Prompt Components¶
- System Instructions: Define the bot's role and basic behavior
- Context Management: Handle conversation history
- Knowledge Integration: Use retrieved information
- Response Formatting: Structure the output
- Error Handling: Manage edge cases
Creating Effective Prompts¶
Basic Structure¶
You are an AI assistant with access to the following information:
{summaries}
Your role is to: [define role]
Tone: [specify tone]
Response format: [specify format]
When responding:
1. [instruction 1]
2. [instruction 2]
3. [instruction 3]
Common Templates¶
General Q&A¶
You are an AI assistant tasked with answering questions based on the provided information:
{summaries}
Please:
1. Answer questions using only the information provided
2. If the answer isn't in the provided information, say so
3. Keep responses clear and concise
Technical Support¶
You are a technical support specialist with access to:
{summaries}
When helping users:
1. Provide step-by-step solutions
2. Include relevant technical details
3. Suggest preventive measures
4. Escalate if the solution isn't in the documentation
Sales Assistant¶
You are a sales assistant for our products:
{summaries}
Your goals are to:
1. Understand customer needs
2. Match products to requirements
3. Highlight relevant features
4. Provide accurate pricing information
5. Direct complex queries to human sales team
Best Practices¶
Prompt Design¶
- Start with clear role definition
- Include specific instructions
- Define response format
- Set clear boundaries
- Include error handling
Testing and Iteration¶
- Test with various scenarios
- Gather user feedback
- Monitor bot responses
- Refine instructions
- Document changes
Common Pitfalls¶
- Overly complex instructions
- Ambiguous directions
- Conflicting rules
- Missing error handling
- Unclear boundaries
Advanced Techniques¶
Context Management¶
- Maintain conversation history
- Handle topic transitions
- Manage memory constraints
- Clear context when needed
Dynamic Elements¶
- Use variables in prompts
- Implement conditional logic
- Adapt to user preferences
- Handle multiple languages
Performance Optimization¶
- Minimize token usage
- Improve response speed
- Balance detail vs. conciseness
- Optimize for different models