mirror of
https://github.com/JamesTheGiblet/BuddAI.git
synced 2026-01-08 21:58:40 +00:00
59 lines
2.9 KiB
Markdown
59 lines
2.9 KiB
Markdown
# BuddAI Development Changelog
|
|
|
|
## Version 3.2 - Self-Learning & Optimization System
|
|
|
|
### 📊 Phase 1: Data Collection
|
|
|
|
Implemented comprehensive data logging to track user interactions and code quality.
|
|
|
|
- **Correction Logging**: Added `save_correction()` to store original vs. corrected code with user reasoning.
|
|
- **Compilation Logs**: Added `log_compilation_result()` to track hardware-specific compilation success rates.
|
|
- **Feedback System**: Enhanced `record_feedback()` to support comments and trigger failure analysis on negative feedback.
|
|
- **Database Updates**: Added tables for `corrections`, `compilation_log`, `feedback` (enhanced), and `code_rules`.
|
|
|
|
### 🔬 Phase 2: Pattern Extraction
|
|
|
|
Added intelligence to learn from the collected data.
|
|
|
|
- **Smart Learner**: Created `SmartLearner` class to diff code and extract patterns (e.g., `analogWrite` -> `ledcWrite`).
|
|
- **Hardware Profiles**: Created `HardwareProfile` class to manage hardware-specific syntax (ESP32 vs Arduino).
|
|
- **Rule Storage**: Learned patterns are stored in `code_rules` with confidence scores.
|
|
- **Prompt Injection**: `build_enhanced_prompt()` now dynamically injects high-confidence rules into the system prompt.
|
|
|
|
### ✅ Phase 3: Validation
|
|
|
|
Implemented pre-flight checks to ensure code quality before display.
|
|
|
|
- **Code Validator**: Created `CodeValidator` class to check for:
|
|
- ESP32 PWM usage (ledcWrite enforcement).
|
|
- Blocking delays in motor code.
|
|
- Missing safety timeouts.
|
|
- **Auto-Fix**: The system can now automatically patch critical errors (like incorrect PWM calls) before showing code to the user.
|
|
- **Hardware Detection**: Automatically detects target hardware (ESP32, Arduino, Pico) from user prompts.
|
|
|
|
### 🔄 Phase 4: Feedback Loop
|
|
|
|
Established continuous improvement cycles.
|
|
|
|
- **Adaptive Learner**: Created `AdaptiveLearner` to analyze session history for implicit corrections ("actually, use X") and preferences.
|
|
- **Session Analysis**: Added `/analyze` command to scan the current session for learned lessons.
|
|
- **Explicit Teaching**: Added `/teach <rule>` command for manual rule insertion.
|
|
|
|
### 📈 Metrics & Fine-Tuning
|
|
|
|
Added tools to measure and cement progress.
|
|
|
|
- **Learning Metrics**: Created `LearningMetrics` to calculate accuracy trends and correction rates over 30 days.
|
|
- **Fine-Tuning Prep**: Created `ModelFineTuner` to export corrections into JSONL format for training local LLMs (Qwen).
|
|
|
|
### 🛠 New CLI Commands
|
|
|
|
- `/learn`: Extract patterns from stored corrections.
|
|
- `/analyze`: Analyze current session for implicit feedback.
|
|
- `/correct <reason>`: Mark previous response as wrong and save correction.
|
|
- `/good`: Mark previous response as correct.
|
|
- `/teach <rule>`: Explicitly teach a coding rule.
|
|
- `/validate`: Run validation checks on the last response.
|
|
- `/rules`: Display currently learned rules.
|
|
- `/metrics`: Show accuracy and improvement stats.
|
|
- `/train`: Export training data for fine-tuning.
|