Add Batch Processing for Enhanced Performance and Cost Optimization

[AhmedProab]

Dear Roo-Code Development Team,

I would like to propose the addition of a Batch Processing feature to improve the efficiency and cost-effectiveness of the platform. This feature has proven successful in other major AI services like:
• Anthropic Claude 3.7 Sonnet – Offering a 50% discount on processing costs when utilizing batch processing.
• OpenAI API – Providing 50% savings on both input and output costs via the Batch API, which enables asynchronous task execution over a 24-hour period.

🔹 Why Batch Processing is Important
• Cost Efficiency: Users can save significantly when processing large volumes of data.
• Improved Performance: Efficiently handles bulk operations, reducing API request overhead.
• Enhanced Flexibility: Enables task scheduling and deferred execution, allowing better resource management.

🔹 Proposed Implementation

I suggest adding:
1. A Batch Processing API that allows users to submit bulk requests.
2. An Asynchronous Execution Model that enables tasks to be processed over a defined period, similar to OpenAI’s 24-hour model.
3. Integration with existing Roo-Code models to ensure seamless compatibility.

🔹 Use Case Examples
• Bulk data analysis for e-commerce insights.
• Large-scale product description generation and SEO content updates.
• Efficient customer data processing for targeted marketing strategies.

I believe implementing this feature will significantly enhance Roo-Code’s capabilities and attract users seeking cost-effective and scalable solutions.

I would be grateful if the team could consider this request, and I’m happy to provide additional ideas or contribute to the development process if needed.

Looking forward to your thoughts on this!

Best regards,