aws.py
"""
AWS Integration: S3 Content Source
====================================
Load files and folders from S3 buckets into your Knowledge base.
Supports any S3-compatible storage with AWS credentials.
Features:
- Load single files or entire prefixes (folders) recursively
- Automatic file type detection and reader selection
- Metadata tagging per file (bucket, key, region)
Requirements:
- AWS credentials configured (env vars, profile, or IAM role)
- S3 bucket with read access
Environment Variables:
AWS_ACCESS_KEY_ID - AWS access key
AWS_SECRET_ACCESS_KEY - AWS secret key
AWS_REGION - AWS region (default: us-east-1)
"""
import asyncio
from os import getenv
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.remote_content import S3Config
from agno.vectordb.qdrant import Qdrant
# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
# Configure S3 content source
s3_config = S3Config(
id="my-bucket",
name="My S3 Bucket",
bucket_name=getenv("AWS_S3_BUCKET", "my-bucket"),
region=getenv("AWS_REGION", "us-east-1"),
)
knowledge = Knowledge(
name="S3 Knowledge",
vector_db=Qdrant(
collection="s3_knowledge",
url="http://localhost:6333",
),
content_sources=[s3_config],
)
# ---------------------------------------------------------------------------
# Run Demo
# ---------------------------------------------------------------------------
if __name__ == "__main__":
async def main():
# Insert a single file from S3
print("\n" + "=" * 60)
print("Loading single file from S3")
print("=" * 60 + "\n")
await knowledge.ainsert(
name="Report",
remote_content=s3_config.file("reports/quarterly-report.pdf"),
)
# Insert an entire folder (prefix)
print("\n" + "=" * 60)
print("Loading folder from S3")
print("=" * 60 + "\n")
await knowledge.ainsert(
name="All Reports",
remote_content=s3_config.folder("reports/"),
)
# Search
results = knowledge.search("What were the quarterly 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 aioboto3 boto3 openai pypdf qdrant-client
3
Export environment variables
export AWS_ACCESS_KEY_ID="your_aws_access_key_id_here"
export AWS_REGION="your_aws_region_here"
export AWS_S3_BUCKET="your_aws_s3_bucket_here"
export AWS_SECRET_ACCESS_KEY="your_aws_secret_access_key_here"
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:AWS_ACCESS_KEY_ID="your_aws_access_key_id_here"
$Env:AWS_REGION="your_aws_region_here"
$Env:AWS_S3_BUCKET="your_aws_s3_bucket_here"
$Env:AWS_SECRET_ACCESS_KEY="your_aws_secret_access_key_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
Run the example
Save the code above as
aws.py, then run:python aws.py