63 lines
2.1 KiB
YAML
63 lines
2.1 KiB
YAML
# Example ContextManager Configuration
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# Central orchestrator for context engineering with proactive budget management
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name: 'default_context_manager'
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description: 'Default context manager with task-adaptive strategies'
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# Storage backends (multi-tier architecture)
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hot_store_name: 'ram_context_store' # Hot tier: fast in-memory access
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warm_store_name: 'redis_context_store' # Warm tier: persistent with TTL
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cold_store_name: 'chroma_context_store' # Cold tier: long-term archival with vector search
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# LLM for token counting
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llm_name: 'default_llm'
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# Compression and routing (Phase 2)
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compressor_name: 'adaptive_compressor' # Intelligent compression strategy selector
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router_name: 'context_router' # Task-specific routing engine
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enable_compression: true # Enable intelligent compression in _make_room()
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# Default budget configuration
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default_max_tokens: 8000
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default_reserved_tokens: 1000
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# Task-specific configurations
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# These override defaults based on task_type
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task_configs:
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code_generation:
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max_tokens: 10000
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reserved_tokens: 1500
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budget_ratios:
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workspace: 0.5 # 50% for code files
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knowledge: 0.2 # 20% for documentation
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memory: 0.15 # 15% for conversation history
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system: 0.05 # 5% for system prompts
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task: 0.1 # 10% for current task
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compression_strategy: 'selective'
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data_analysis:
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max_tokens: 12000
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reserved_tokens: 2000
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budget_ratios:
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background: 0.4 # 40% for data context
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workspace: 0.3 # 30% for notebooks/scripts
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knowledge: 0.15 # 15% for documentation
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memory: 0.1 # 10% for conversation
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system: 0.05 # 5% for system prompts
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compression_strategy: 'summarize'
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dialogue:
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max_tokens: 8000
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reserved_tokens: 1000
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budget_ratios:
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conversation: 0.5 # 50% for chat history
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background: 0.25 # 25% for context
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system: 0.15 # 15% for system prompts
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memory: 0.1 # 10% for long-term memory
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compression_strategy: 'adaptive'
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metadata:
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type: 'CONTEXT_MANAGER'
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module: 'agentuniverse.agent.context.context_manager'
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class: 'ContextManager'
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