How to be scaling up Copilot Studio Agent

I understand you're facing challenges scaling up your Copilot Studio Agent to handle 7,000 PDF files and encountering the AsyncResponsePayloadTooLarge error. This is a common issue when dealing with large-scale document processing. Here are the best practices and strategies to handle this efficiently:

The AsyncResponsePayloadTooLarge error indicates your response exceeded payload limits. Here are the recommended solutions for processing 7,000 PDFs efficiently:

Immediate Solutions

1. Document Chunking

• Break PDFs into smaller segments (1000-2000 tokens)
• Process documents in batches of 10-50 files
• Implement pagination for large result sets

2. Architecture Optimization

• Pre-process documents offline using Azure Document Intelligence
• Create searchable indexes with vector embeddings
• Design agents to retrieve relevant chunks, not full documents
• Implement streaming responses for large outputs

3. Multi-Agent Strategy

├── Document Ingestion Agent (offline processing)

├── Query Processing Agent (retrieval)

└── Response Coordination Agent (result assembly)

4. Error Mitigation

• Add retry logic with exponential backoff
• Implement circuit breaker patterns
• Use asynchronous processing queues
• Monitor token usage per operation

Best Practice Implementation

• Offline: Index all 7,000 PDFs into Azure AI Search
• Runtime: Query relevant document chunks only
• Response: Return summarized answers with source references
• Monitoring: Track processing metrics and payload sizes

This approach will resolve the payload error while maintaining performance at scale.

Thanks,  

Karan Shewale. 

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