azure.py
"""
Azure Integration: Blob Storage
=================================
Load files and folders from Azure Blob Storage containers into your Knowledge base.
Features:
- Load single files or entire prefixes (folders)
- Uses Azure AD client credentials for authentication
Requirements:
- Azure AD App Registration with Storage Blob Data Reader role
- Client ID, Client Secret, and Tenant ID
Environment Variables:
AZURE_TENANT_ID - Azure AD tenant ID
AZURE_CLIENT_ID - App registration client ID
AZURE_CLIENT_SECRET - App registration client secret
AZURE_STORAGE_ACCOUNT_NAME - Storage account name
AZURE_CONTAINER_NAME - Container name
"""
import asyncio
from os import getenv
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.remote_content import AzureBlobConfig
from agno.vectordb.qdrant import Qdrant
# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
azure_blob = AzureBlobConfig(
id="company-blob",
name="Company Blob Storage",
tenant_id=getenv("AZURE_TENANT_ID"),
client_id=getenv("AZURE_CLIENT_ID"),
client_secret=getenv("AZURE_CLIENT_SECRET"),
storage_account=getenv("AZURE_STORAGE_ACCOUNT_NAME"),
container=getenv("AZURE_CONTAINER_NAME"),
)
knowledge = Knowledge(
name="Azure Blob Knowledge",
vector_db=Qdrant(
collection="azure_blob_knowledge",
url="http://localhost:6333",
),
content_sources=[azure_blob],
)
# ---------------------------------------------------------------------------
# Run Demo
# ---------------------------------------------------------------------------
if __name__ == "__main__":
async def main():
# Single file
print("\n" + "=" * 60)
print("Azure Blob Storage: single file")
print("=" * 60 + "\n")
await knowledge.ainsert(
name="Report",
remote_content=azure_blob.file("reports/annual-report.pdf"),
)
# Folder
print("\n" + "=" * 60)
print("Azure Blob Storage: folder")
print("=" * 60 + "\n")
await knowledge.ainsert(
name="All Docs",
remote_content=azure_blob.folder("documents/"),
)
results = knowledge.search("What were the annual results?")
for doc in results:
print("- %s" % doc.name)
asyncio.run(main())
Run the Example
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U agno azure-identity azure-storage-blob openai pypdf qdrant-client
3
Export environment variables
export AZURE_CLIENT_ID="your_azure_client_id_here"
export AZURE_CLIENT_SECRET="your_azure_client_secret_here"
export AZURE_CONTAINER_NAME="your_azure_container_name_here"
export AZURE_STORAGE_ACCOUNT_NAME="your_azure_storage_account_name_here"
export AZURE_TENANT_ID="your_azure_tenant_id_here"
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:AZURE_CLIENT_ID="your_azure_client_id_here"
$Env:AZURE_CLIENT_SECRET="your_azure_client_secret_here"
$Env:AZURE_CONTAINER_NAME="your_azure_container_name_here"
$Env:AZURE_STORAGE_ACCOUNT_NAME="your_azure_storage_account_name_here"
$Env:AZURE_TENANT_ID="your_azure_tenant_id_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Run Qdrant
docker run -d --name qdrant -p 6333:6333 qdrant/qdrant:latest
5
Add the Blob Storage documents
Upload a readable PDF as
reports/annual-report.pdf and at least one supported file under documents/ in AZURE_CONTAINER_NAME, or update both hard-coded paths in the saved file to match your container.6
Run the example
Save the code above as
azure.py, then run:python azure.py