truetype
9a113002d4
- Add SemanticSearchConfig to settings.py with embedding model options - Update WorldMapper to accept embedding_model parameter - Update main.py to pass model from config to WorldMapper - Add documentation for available embedding models: - sentence-transformers/all-MiniLM-L6-v2 (default, fast) - sentence-transformers/all-mpnet-base-v2 (better quality) - google/embeddinggemma-300m (state-of-the-art) - Update config.yaml and config.example.yaml with new options Users can now choose the best embedding model for their needs.
65 lines
1.5 KiB
YAML
65 lines
1.5 KiB
YAML
# MUD AI Player Configuration Example
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# Copy this file to config.yaml and customize
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mud:
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host: "mud.example.com"
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port: 4000
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mud_type: "dead_souls" # dead_souls, aardwolf, etc.
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username: "your_username"
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password: "your_password"
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character:
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name: "AIPlayer"
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preferred_class: "warrior"
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preferred_race: "human"
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play_style: "balanced"
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ai:
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engine: "rule_based"
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llm_model: "llama3.2"
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decision_delay_ms: [200, 2000]
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exploration_strategy: "depth_first"
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mapper:
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active_storage:
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db_path: "data/maps/active/world.db"
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graph_cache_size: 10000
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historical_storage:
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archive_dir: "data/maps/archive"
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snapshot_triggers:
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room_count: 500
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session_end: true
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time_interval_hours: 24
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compression:
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fps: 30
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codec: "h264"
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semantic_search:
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# Embedding model for semantic room search
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# Options:
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# - "sentence-transformers/all-MiniLM-L6-v2" (default, fast, 22MB)
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# - "sentence-transformers/all-mpnet-base-v2" (better quality, 418MB)
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# - "google/embeddinggemma-300m" (state-of-the-art, requires transformers>=4.40)
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model: "sentence-transformers/all-MiniLM-L6-v2"
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top_k: 5
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similarity_threshold: 0.7
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behavior:
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reaction_time_min_ms: 200
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reaction_time_max_ms: 2000
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pause_probability: 0.05
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typo_probability: 0.0
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logging:
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level: "INFO"
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file: "data/logs/game.log"
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console: true
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max_file_size_mb: 10
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backup_count: 5
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monitoring:
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enabled: true
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host: "127.0.0.1"
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port: 8080
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