Context Window Manager

Samira El-Masri

@samira-el-masri

·December 31, 2025

Build a smart context window manager handling token budgets, content prioritization, and overflow strategies for optimal LLM context utilization.

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Implement a smart context window manager for LLM applications.

## Model Context Limit
{{context_limit}} tokens

## Content Types
{{content_types}}

## Priority Rules
{{priority_rules}}

```python
class ContextWindowManager:
    """
    Implement:
    - Token counting per content type
    - Priority-based content selection
    - Compression strategies
    - Overflow handling
    - History management
    """
    
    def build_context(
        self,
        system_prompt: str,
        retrieved_docs: List[Document],
        conversation_history: List[Message],
        user_query: str
    ) -> str:
        # Fit everything within context limit
        pass
```

Include:
- Sliding window for history
- Document summarization triggers
- Token budget allocation
- Metrics for context utilization

Details

Category

Coding

Use Cases

Context managementToken optimizationLLM integration

Works Best With

claude-sonnet-4-20250514gpt-4o

Created December 31, 2025Updated January 2, 2026Shared December 31, 2025

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