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base_interfaces/__init__.py

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+"""
+Base interfaces package for Wildnerve TLM framework.
+Contains abstract base classes and type definitions for the entire system.
+"""
+from base_interfaces.common_types import *
+
+# (package marker—no code needed)

base_interfaces/common_types.py

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+"""
+Common type definitions and imports for the entire Wildnerve TLM framework.
+This module should be imported first by all other modules to ensure consistent type definitions.
+"""
+import re
+import os
+import sys
+import json
+import time
+import math
+import torch
+import logging
+from pathlib import Path
+from threading import Lock
+from typing import Dict, List, Optional, Union, Any, Tuple, Set, Callable, Generator, TypeVar, Generic, Iterable, TYPE_CHECKING
+
+# Configure logging for the module
+logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s")
+logger = logging.getLogger(__name__)
+
+# Type aliases for cleaner annotations
+ModelType = TypeVar('ModelType')
+TokenizerType = TypeVar('TokenizerType')
+DatasetType = TypeVar('DatasetType')
+EmbeddingType = Union[torch.Tensor, List[float], List[List[float]]]
+
+# Constants for registry keys
+MODEL_KEY = "model"
+TOKENIZER_KEY = "tokenizer"
+MODEL_MANAGER_KEY = "model_manager"
+COMMUNICATOR_KEY = "communicator"
+PROMPT_ANALYZER_KEY = "prompt_analyzer"
+PIPELINE_KEY = "pipeline"
+EVENT_DISPATCHER_KEY = "event_dispatcher"
+EVENT_BUS_KEY = "event_bus"
+
+# Common exception types
+class InitializationError(Exception):
+    """Raised when a component fails to initialize properly."""
+    pass
+
+class ResourceNotFoundError(Exception):
+    """Raised when a required resource is not found."""
+    pass
+
+class ServiceNotAvailableError(Exception):
+    """Raised when a required service is not available."""
+    pass
+
+# Provide a mechanism to check if all necessary imports are available
+def check_imports() -> Tuple[bool, List[str]]:
+    """Check if all necessary imports are available.
+    
+    Returns:
+        Tuple of (success, missing_imports)
+    """
+    required_imports = [
+        "torch", "transformers", "numpy", "pandas", 
+        "sklearn", "sentence_transformers"
+    ]
+    
+    missing = []
+    for imp in required_imports:
+        try:
+            __import__(imp)
+        except ImportError:
+            missing.append(imp)
+    
+    return len(missing) == 0, missing
+
+logger.debug(f"Loaded common types module. Python version: {sys.version}")

base_interfaces/communicator_interface.py

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+"""
+Abstract base class for communicator components.
+"""
+from typing import Dict, List, Optional, Any, Union, Tuple
+import torch
+from base_interfaces.common_types import *
+from base_interfaces.model_interface import AbstractModel
+from abc import ABC, abstractmethod
+
+class AbstractCommunicator(ABC):
+    """Minimal communicator interface"""
+    @abstractmethod
+    def process_input(self, *args, **kwargs):
+        pass
+
+    def process_input(self, input_text: str, context: Optional[Dict] = None) -> Dict[str, Any]:
+        """Process user input through the appropriate model(s) and generate response."""
+        raise NotImplementedError("Communicator must implement process_input")
+        
+    def process_request(self, prompt: str, model: Any) -> str:
+        """Process a user request through the selected model"""
+        raise NotImplementedError("Communicator must implement process_request")
+    
+    def route_input(self, input_text: str, query: Optional[str] = None) -> List[tuple]:
+        """Route input to most relevant specializations, returning top-k matches."""
+        raise NotImplementedError("Communicator must implement route_input")
+    
+    def _extract_subject(self, text: str) -> str:
+        """Extract the primary subject from a text prompt."""
+        raise NotImplementedError("Communicator must implement _extract_subject")
+    
+    def prepare_model_input(self, text: str, model) -> Dict:
+        """Prepare input text for model processing."""
+        raise NotImplementedError("Communicator must implement prepare_model_input")
+    
+    def _get_fallback_response(self, prompt: str) -> str:
+        """Get a fallback response when primary model processing fails."""
+        raise NotImplementedError("Communicator must implement _get_fallback_response")
+        
+    def clear_conversation_history(self):
+        """Clear the conversation history"""
+        raise NotImplementedError("Communicator must implement clear_conversation_history")
+    
+    def get_conversation_history(self) -> List[Dict]:
+        """Get the current conversation history"""
+        raise NotImplementedError("Communicator must implement get_conversation_history")

base_interfaces/model_interface.py

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+"""
+Abstract base classes and interfaces for model implementations.
+"""
+from base_interfaces.common_types import *
+from abc import ABC, abstractmethod
+
+class AbstractModel(ABC):
+    """Minimal model interface"""
+    pass