Generalized Omni-dimensional Development

User Tools

Site Tools

Trace:
ai_orchestrator

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revisionPrevious revision
Next revision		Previous revision
ai_orchestrator [2025/05/28 20:42] – [Advanced Features] eagleeyenebulaai_orchestrator [2025/05/28 20:43] (current) – [Best Practices] eagleeyenebula
Line 250: Line 250:
  
 1. **Dynamic Configurations**:   1. **Dynamic Configurations**:  
-   * Load configurations dynamically via JSON or YAML files for flexible and modular pipeline setups.+   * Load configurations dynamically via **JSON** or **YAML** files for flexible and modular pipeline setups.
  
 2. **Feedback Quality Control**:   2. **Feedback Quality Control**:  
Line 266: Line 266:
  
 1. **Custom Feedback Handlers**:   1. **Custom Feedback Handlers**:  
-   Write extensions for domain-specific feedback loops or annotation pipelines.+   * Write extensions for domain-specific feedback loops or annotation pipelines.
  
 2. **Model Deployment Validators**:   2. **Model Deployment Validators**:  
-   Add validation routines to ensure retrained models meet production quality standards.+   * Add validation routines to ensure retrained models meet production quality standards.
  
 3. **Hybrid Model Support**:   3. **Hybrid Model Support**:  
-   Enable workflows that support hybrid models (e.g., combining ML and rule-based systems).+   * Enable workflows that support hybrid models (e.g., combining ML and rule-based systems).
  
 4. **Cloud Integration**:   4. **Cloud Integration**:  
-   Extend the `AIOrchestrator` to work with cloud platforms like AWS Sagemaker, Azure ML, or GCP AI. +   * Extend the `AIOrchestrator` to work with cloud platforms like AWS Sagemaker, Azure ML, or GCP AI.
- +
---- +
 ===== Best Practices ===== ===== Best Practices =====
  
-- **Monitor Drift Regularly**:   + **Monitor Drift Regularly**:   
-  Schedule routine model drift checks using cron jobs or pipeline automation tools. +  * Schedule routine model drift checks using cron jobs or pipeline automation tools.
- +
-- **Validate Feedback Data**:   +
-  Ensure that feedback data is clean, labeled accurately, and suitable for training before integration. +
- +
-- **Leverage Modular Components**:   +
-  Use each module (feedback, retraining, reporting) separately as needed to ensure scalability and maintainability.+
  
-- **Secure Data**:   + **Validate Feedback Data**:   
-  Protect training datasets, feedback records, and reports from unauthorized access.+  * Ensure that feedback data is clean, labeled accurately, and suitable for training before integration.
  
-- **Log Everything**:   + **Leverage Modular Components**:   
-  Maintain comprehensive logs for the entire pipeline to aid in debugging and compliance.+  * Use each module (feedback, retraining, reporting) separately as needed to ensure scalability and maintainability.
  
----+ **Secure Data**:   
 +  * Protect training datasets, feedback records, and reports from unauthorized access.
  
 + **Log Everything**:  
 +  * Maintain comprehensive logs for the entire pipeline to aid in debugging and compliance.
 ===== Conclusion ===== ===== Conclusion =====
  
ai_orchestrator.1748464940.txt.gz · Last modified: 2025/05/28 20:42 by eagleeyenebula