## PRD: Implement CPU Frequency Adjustment Rate Limiter

This PRD focuses on implementing a rate limiter to smooth CPU frequency adjustments, preventing rapid fluctuations based on CPU load.

### GPM-046: Implement Basic Rate Limiter Class
**Goal:** Create a reusable rate limiter class with configurable parameters.
**Acceptance Criteria:**
- A `RateLimiter` class exists.
- The class constructor accepts `max_rate` (adjustments per second) and `burst_size` (maximum adjustments allowed in a short period) as arguments.
- The class has a method `allow()` that returns `True` if an adjustment is allowed within the rate limits, and `False` otherwise.
- The `allow()` method updates the internal state of the rate limiter to track usage.
**Files:** `aiva/cpu_frequency/rate_limiter.py`
**Spawns:** Add unit tests for the RateLimiter class

### GPM-047: Add Unit Tests for RateLimiter
**Goal:** Ensure the `RateLimiter` class functions correctly through unit tests.
**Acceptance Criteria:**
- Unit tests cover cases where adjustments are allowed within the rate limits.
- Unit tests cover cases where adjustments are blocked due to exceeding the rate limits.
- Unit tests cover cases where the burst size is exceeded.
- Unit tests cover cases where the rate limits are met again after a period of inactivity.
**Files:** `tests/aiva/cpu_frequency/test_rate_limiter.py`
**Spawns:** Integrate the rate limiter into the CPU frequency adjustment logic

### GPM-048: Integrate Rate Limiter into Frequency Adjustment Logic
**Goal:** Incorporate the rate limiter into the CPU frequency adjustment process.
**Acceptance Criteria:**
- The CPU frequency adjustment logic uses the `RateLimiter` class to control the frequency of adjustments.
- The `max_rate` and `burst_size` parameters are configurable (e.g., through a configuration file).
- The system logs when an adjustment is blocked by the rate limiter.
**Files:** `aiva/cpu_frequency/cpu_frequency_manager.py` (modified), `aiva/config.py` (modified)
**Spawns:** Implement monitoring of the rate limiter's performance.

### GPM-049: Configure Initial Rate Limiter Parameters
**Goal:** Define reasonable default values for the rate limiter's parameters.
**Acceptance Criteria:**
- The `max_rate` and `burst_size` are set to default values that prevent overly aggressive adjustments but still allow responsiveness to CPU load changes.
- The default values are documented.
- The default values are configurable through the configuration file.
**Files:** `aiva/config.py` (modified), `docs/configuration.md` (updated)
**Spawns:** Add real-time monitoring of CPU frequency adjustments and rate limiting.

### GPM-050: Log Rate Limiter Statistics
**Goal:** Capture and log statistics about the rate limiter's operation.
**Acceptance Criteria:**
- The system logs the number of adjustments allowed and blocked by the rate limiter over a specific period.
- These statistics are logged in a structured format that is easily parsed for analysis.
- Logged data includes timestamps.
**Files:** `aiva/cpu_frequency/cpu_frequency_manager.py` (modified)
**Spawns:** Create a dashboard to visualize the rate limiter's performance.

### GPM-051: Implement Graceful Shutdown Handling for Rate Limiter
**Goal:** Ensure the rate limiter's state is preserved during shutdown.
**Acceptance Criteria:**
- The rate limiter's current state (e.g., the number of allowed adjustments remaining) is saved to disk before shutdown.
- The rate limiter's state is restored from disk on startup.
- Shutdown and startup operations do not cause data corruption or unexpected behavior in the rate limiter.
**Files:** `aiva/cpu_frequency/rate_limiter.py` (modified), `aiva/system_manager.py` (modified)
**Spawns:** Explore adaptive rate limiting based on system conditions.
