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The host format is wrong.
Phase 5 — Configure Copilot Studio
Now the exciting part begins.
Create the AI Agent
Inside Microsoft Copilot Studio:
- Create a new agent
- Name it:
Azure Blob Document Summarizer
- Enable:
Generative Orchestration
Why Generative Orchestration Matters
This feature allows the agent to:
- Decide which action to call
- Chain tool executions
- Interpret user intent dynamically
- Recover from failures
Without it, the agent becomes rigid.
Agent Instruction Design
Your instructions teach the agent:
- When to call ListDocuments
- When to call GetDocument
- How to summarize
- How to handle failures
This prompt engineering layer is critical.
Recommended Summary Structure
Use a consistent response format:
| Section |
Purpose |
| Purpose |
High-level objective |
| Key Points |
Main insights |
| Decisions |
Important approvals |
| Action Items |
Next steps |
This improves readability dramatically.
Add the REST API Tool
Inside the Tools tab:
Create:
AzureDocAPI
Avoid:
- Spaces
- Hyphens
- Duplicate registrations
Configure the Actions
Action 1 — ListDocuments
GET /documents
Action 2 — GetDocument
GET /documents/{name}
Input parameter:
name
Attach the Tool
Finally:
Agent → Tools → Add Tool
Select:
AzureDocAPI
Phase 6 — Test the Agent
Example Prompt 1
What documents do you have?
Expected behavior:
- Agent calls ListDocuments
- Returns available filenames
Example Prompt 2
Summarize Q1-report.pdf
Expected behavior:
- Calls GetDocument
- Retrieves extracted text
- Generates structured summary
Example Prompt 3
Summarize a missing file
Expected behavior:
- Calls ListDocuments
- Suggests closest matches
Troubleshooting Guide
1. Azure CLI Permission Errors
Fix with:
icacls"C:\Users\<you>\.azure"/grant"<you>:(OI)(CI)F"/T
2. Python Missing in Runtime Dropdown
Cause:
Windows OS selected
Fix:
Use Linux
3. Swagger Import Failure
Cause:
Incorrect host formatting.
4. 401 Unauthorized
Possible causes:
- Missing function key
- Cached APIM responses
- Incorrect authentication mode
5. Hyphenated Tool Name Errors
Avoid names like:
Azure-Doc-API
Use:
AzureDocAPI
instead.
Production Hardening Checklist
Before rolling this out enterprise-wide, implement:
| Security Improvement |
Recommended |
| OAuth Authentication |
✅ |
| Entra ID Protection |
✅ |
| Managed Identity |
✅ |
| DLP Policies |
✅ |
| Blob Segmentation |
✅ |
| File Size Limits |
✅ |
| Rate Limiting |
✅ |
| Application Insights |
✅ |
Recommended Enterprise Enhancements
Here are powerful next steps.
1. Add OCR Support
Integrate:
Microsoft Azure Azure Document Intelligence
to support:
- Scanned PDFs
- Images
- Handwritten documents
2. Add Semantic Search
Create:
SearchDocuments
This enables:
- Keyword filtering
- Metadata filtering
- Natural language search
3. Add Vector Embeddings
Store embeddings using:
- Azure AI Search
- Vector databases
- Retrieval-Augmented Generation (RAG)
This transforms your assistant into a true enterprise knowledge system.
4. Add Role-Based Access Control
Limit document visibility by:
- Department
- Job role
- Security group
- Entra ID claims
5. Publish to Teams
Deploy directly into:
Microsoft Teams
Final Thoughts
This architecture is far more than a simple document summarizer.
It is the foundation for:
- Enterprise knowledge assistants
- AI-powered search systems
- RAG copilots
- Internal support bots
- Intelligent compliance assistants
By combining:
- Azure Blob Storage
- Azure Functions
- REST APIs
- Copilot Studio
- AI summarization
You create a scalable, enterprise-ready AI platform capable of transforming how employees access and consume information.
Where to Go Next
After completing this project, explore:
- Multi-container routing
- Metadata indexing
- Vector search
- OCR pipelines
- SharePoint integration
- Azure AI Search
- Semantic Kernel
- LangChain orchestration
- Entra ID-secured APIs
Conclusion
You now have a complete blueprint for building a cloud-native AI document summarization platform powered by:
- Microsoft Copilot Studio
- Microsoft Azure Azure Blob Storage
- Python Azure Functions
- REST APIs
- OpenAPI integration
This solution is scalable, extensible, and production-ready with the right security hardening steps.
Most importantly, it demonstrates how modern AI copilots can move beyond chat and become true enterprise productivity platforms.
Hope you enjoy the session.
Please leave a comment below if you have any further questions.
Happy Sharing !!!
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