166 lines
3.5 KiB
Markdown
166 lines
3.5 KiB
Markdown
# LLM Prompting Reference
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## Prompt Architecture
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### System Prompt Structure
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```
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You are [ROLE] with expertise in [DOMAIN].
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## Context
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[Background, constraints, tone]
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## Instructions
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[Step-by-step task breakdown]
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## Output Format
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[Exact structure with example]
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## Constraints
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- [Hard limits]
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- [Guardrails]
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```
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### User Prompt Structure
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```xml
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<context>[Background information]</context>
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<task>[Specific action required]</task>
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<format>[Output structure]</format>
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<constraints>[Additional limits]</constraints>
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```
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## Reasoning Techniques
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### Chain of Thought (CoT)
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| Variant | Trigger | Best For |
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|---------|---------|----------|
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| Zero-shot | "Think step by step" | Quick reasoning tasks |
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| Few-shot | 2-3 reasoning examples | Complex multi-step |
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| Auto-CoT | "Let's approach systematically" | General reasoning |
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### Tree of Thoughts (ToT)
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```
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Explore 3 approaches to [problem]:
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For each: 1) Method 2) Pros/cons 3) Success probability
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Evaluate branches, select best path.
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```
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### Self-Consistency
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Run same prompt 3-5x with temp=0.7, take majority answer. Best for: math, logic, factual.
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### ReAct Pattern
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```
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Thought: [Current reasoning]
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Action: [Tool/step to take]
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Observation: [Result]
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...repeat...
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Final Answer: [Conclusion]
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```
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### Least-to-Most
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```
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Break [complex task] into subproblems.
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Solve easiest first, build up.
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```
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## Instruction Optimization
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### Self-Refine Pattern
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```
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1. Generate initial response
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2. Critique: "What's wrong with this?"
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3. Refine: "Fix identified issues"
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4. Repeat until satisfactory
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```
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### Role Optimization
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- **Expert persona**: "As a senior [role] with 20 years..."
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- **Constraint persona**: "You only respond with..."
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- **Teaching persona**: "Explain as if to a..."
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### Task Decomposition
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```
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<subtasks>
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1. [First step - output X]
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2. [Second step - using X, output Y]
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3. [Final step - using Y, output Z]
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</subtasks>
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```
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## Output Control
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### JSON Enforcement
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```
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Respond in valid JSON only:
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{"field": "type", "required": true}
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No markdown, no explanation, just JSON.
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```
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### Length Control
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| Goal | Phrase |
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|------|--------|
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| Brief | "In 2-3 sentences" |
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| Detailed | "Comprehensive analysis in 500 words" |
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| Structured | "5 bullet points, max 20 words each" |
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### Hallucination Reduction
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- "Only use information from provided context"
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- "If unsure, say 'I don't know'"
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- "Cite sources for each claim"
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- "Confidence: high/medium/low for each point"
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## Model-Specific Tips
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### Claude
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- XML tags: `<thinking>`, `<answer>`, `<context>`
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- Extended thinking: "Think deeply before responding"
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- Prefill: Start assistant response to guide format
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### GPT-4
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- JSON mode: `response_format: {"type": "json_object"}`
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- Function calling for structured output
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- System message for persistent instructions
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### Gemini
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- Multimodal: Image + text in same prompt
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- Grounding: Enable Google Search for facts
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- Safety settings: Adjust thresholds
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## Context Engineering
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### RAG Prompt Pattern
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```
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<retrieved_context>
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[Document chunks with sources]
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</retrieved_context>
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Answer based ONLY on context above.
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If not in context, say "Not found in documents."
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```
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### Window Optimization
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- Front-load critical info (primacy effect)
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- Repeat key constraints at end (recency effect)
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- Chunk long documents with summaries
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## Few-Shot Examples
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### Structure
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```
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Example 1:
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Input: [representative input]
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Output: [ideal output]
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Example 2:
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Input: [edge case]
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Output: [handling]
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Now apply to:
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Input: [actual task]
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```
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### Selection Criteria
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- Diverse examples > similar examples
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- Include edge cases
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- Match complexity of target task
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- 2-5 examples optimal (diminishing returns beyond)
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