Add base_temperature to StateAwareLLM to fix AttributeError

[leonvanbokhorst]

Added base_temperature attribute to StateAwareLLM initialization with a default
value of 0.7. This fixes the AttributeError in the adjust_temperature method
by providing a baseline temperature that gets modified based on emotional state.

Summary by Sourcery

Introduce a new BrainLayer class for enhanced emotional processing and a StateAwareLLM class to manage state transitions and response adjustments. Fix an AttributeError in the adjust_temperature method by adding a base_temperature attribute. Remove unnecessary dependencies from requirements.txt.

New Features:

• Introduce a new BrainLayer class that enhances emotional processing, metacognition, and rest states for the AI model.
• Add a StateAwareLLM class that integrates with the BrainLayer to manage state transitions and adjust response temperature based on emotional state.

Bug Fixes:

• Fix an AttributeError in the adjust_temperature method by adding a base_temperature attribute to the StateAwareLLM class.

Enhancements:

• Enhance emotional processing by adding an EmotionalMemory class to track emotional patterns and transitions.
• Improve thought processing with a multi-layer approach, including perception, memory comparison, emotional processing, and metacognition.

Build:

• Remove unnecessary dependencies from requirements.txt, including llama-cpp-python and PyWavelets.

[sourcery-ai]

Reviewer's Guide by Sourcery

This PR implements a new brain layer system with emotional processing and state management capabilities. The core change adds a base_temperature attribute to StateAwareLLM initialization to fix an AttributeError in the adjust_temperature method. The implementation includes a comprehensive brain architecture with emotional memory, metacognition, and state transitions.

Class diagram for BrainLayer and StateAwareLLM

classDiagram
    class BrainLayer {
        -OllamaClient llm
        -ChromaClient memory
        -EmotionalMemory emotional_memory
        -List thought_history
        -BrainState brain_state
        -int rest_cycle_counter
        -int max_thoughts_before_rest
        -Collection collection
        +process_thought(input_text: str) Dict
        +add_emotional_layer(thought: str) Dict
        +add_metacognition(thought: str, embeddings: List, emotional_state: Dict) Dict
        +_initialize_memory() void
        +_check_rest_state() Tuple
        +_analyze_thought_coherence(current_thought: str, prev_thoughts: List) float
        +_analyze_patterns() float
    }
    class StateAwareLLM {
        -BrainLayer brain
        -int rest_duration
        -int max_rest_duration
        -float base_temperature
        +check_state_transition(brain_state: Dict) Optional
        +adjust_temperature(emotional_state: Dict) float
        +create_context_prompt(user_input: str, brain_state: Dict) str
        +generate_response(prompt: str, temperature: float) str
        +format_response(response: str, brain_state: Dict) str
        +respond(user_input: str) str
    }
    BrainLayer --> EmotionalMemory
    StateAwareLLM --> BrainLayer
    class EmotionalMemory {
        -List emotional_history
        -int max_history
        +add_emotion(emotion: Dict) void
        +get_emotional_trend() Dict
    }
    class BrainState {
        <<enumeration>>
        ACTIVE
        RESTING
        LEARNING
        REFLECTING
    }

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File-Level Changes

Change	Details	Files
Implemented a new brain layer system with emotional processing and state management	Created BrainState enum for tracking brain states (ACTIVE, RESTING, LEARNING, REFLECTING) Implemented EmotionalMemory class for tracking emotional patterns and transitions Added BrainLayer class with LLM and memory management capabilities Implemented metacognition and thought processing functionality Added emotional trend analysis and pattern recognition	brain/brain_layer.py
Added state-aware LLM implementation with temperature control	Added base_temperature attribute with default value of 0.7 Implemented temperature adjustment based on emotional state Added state transition logic with rest/wake cycles Created context-aware prompt generation Added response formatting based on emotional state	brain/brain_layer.py
Updated project dependencies	Removed llama-cpp-python dependency Removed PyWavelets dependency	requirements.txt

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[sourcery-ai]

Hey @leonvanbokhorst - I've reviewed your changes and they look great!

Here's what I looked at during the review

• 🟡 General issues: 2 issues found
• 🟢 Security: all looks good
• 🟢 Testing: all looks good
• 🟡 Complexity: 1 issue found
• 🟢 Documentation: all looks good

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