config_id and write into a shared vector DB.
multi_source.py
"""
Multi-Source Remote Content
===========================
Combine multiple remote content sources in a single Knowledge instance.
Sources dispatch by ``config_id`` and write into a shared vector DB.
This cookbook runs end-to-end with only public GitHub access. Additional
providers (S3, GCS, SharePoint, Azure Blob) are registered automatically
when their environment variables are set, otherwise they are skipped.
Features demonstrated:
- Multiple configs of different providers in one ``Knowledge``
- Two GitHub configs with different auth profiles (public + authenticated)
- Per-request ``repo`` override so one stateless GitHub config can serve
many repositories (``GitHubConfig.repo`` is Optional)
- Cross-source search against the unified vector index
Requirements:
- PostgreSQL with pgvector: ./cookbook/scripts/run_pgvector.sh
Environment Variables (all optional):
GITHUB_TOKEN - private GitHub repo access (second config)
S3_BUCKET_NAME - enables S3 registration
AWS_REGION - S3 region
GCS_BUCKET_NAME - enables GCS registration
GCP_PROJECT - GCS project
SHAREPOINT_TENANT_ID - enables SharePoint registration
SHAREPOINT_CLIENT_ID
SHAREPOINT_CLIENT_SECRET
SHAREPOINT_HOSTNAME
AZURE_TENANT_ID - enables Azure Blob registration
AZURE_CLIENT_ID
AZURE_CLIENT_SECRET
AZURE_STORAGE_ACCOUNT
AZURE_CONTAINER
"""
import asyncio
from os import getenv
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.remote_content import (
AzureBlobConfig,
GcsConfig,
GitHubConfig,
S3Config,
SharePointConfig,
)
from agno.vectordb.pgvector import PgVector
content_sources: list = []
# GitHub: public repos (no token, no default repo).
# One stateless config serves many repos via per-request override.
github_public = GitHubConfig(
id="github-public",
name="GitHub (public, dynamic repo)",
branch="main",
)
content_sources.append(github_public)
# GitHub: authenticated repos (PAT, default repo).
# Only registered when GITHUB_TOKEN is set.
github_private = None
if getenv("GITHUB_TOKEN"):
github_private = GitHubConfig(
id="github-private",
name="GitHub (authenticated)",
repo=getenv("GITHUB_DEFAULT_REPO", "agno-agi/agno"),
token=getenv("GITHUB_TOKEN"),
branch="main",
)
content_sources.append(github_private)
# S3: optional.
if getenv("S3_BUCKET_NAME"):
content_sources.append(
S3Config(
id="s3-docs",
name="S3 Documents",
bucket_name=getenv("S3_BUCKET_NAME", ""),
region=getenv("AWS_REGION", "us-east-1"),
)
)
# GCS: optional.
if getenv("GCS_BUCKET_NAME"):
content_sources.append(
GcsConfig(
id="gcs-data",
name="GCS Data",
bucket_name=getenv("GCS_BUCKET_NAME", ""),
project=getenv("GCP_PROJECT", ""),
)
)
# SharePoint: optional.
if getenv("SHAREPOINT_TENANT_ID"):
content_sources.append(
SharePointConfig(
id="sharepoint-docs",
name="SharePoint Documents",
tenant_id=getenv("SHAREPOINT_TENANT_ID", ""),
client_id=getenv("SHAREPOINT_CLIENT_ID", ""),
client_secret=getenv("SHAREPOINT_CLIENT_SECRET", ""),
hostname=getenv("SHAREPOINT_HOSTNAME", ""),
site_id=getenv("SHAREPOINT_SITE_ID"),
)
)
# Azure Blob: optional.
if getenv("AZURE_TENANT_ID"):
content_sources.append(
AzureBlobConfig(
id="azure-blob",
name="Azure Blob",
tenant_id=getenv("AZURE_TENANT_ID", ""),
client_id=getenv("AZURE_CLIENT_ID", ""),
client_secret=getenv("AZURE_CLIENT_SECRET", ""),
storage_account=getenv("AZURE_STORAGE_ACCOUNT", ""),
container=getenv("AZURE_CONTAINER", ""),
)
)
knowledge = Knowledge(
name="Multi-Source Knowledge",
vector_db=PgVector(
table_name="multi_source_knowledge",
db_url="postgresql+psycopg://ai:ai@localhost:5532/ai",
),
content_sources=content_sources,
)
if __name__ == "__main__":
async def main():
print("\n" + "=" * 60)
print("Registered content sources:")
print("=" * 60)
for src in content_sources:
print("- [%s] %s (%s)" % (src.id, src.name, type(src).__name__))
# Load two different public repos through one stateless GitHub config.
# Distinct names to avoid the content_hash collision that occurs when
# two uploads share the same logical name across different providers.
print("\n" + "=" * 60)
print("Loading README.md from agno-agi/agno (github-public)")
print("=" * 60 + "\n")
await knowledge.ainsert(
name="Agno README",
remote_content=github_public.file("README.md", repo="agno-agi/agno"),
)
print("\n" + "=" * 60)
print("Loading LICENSE from anthropics/anthropic-sdk-python (github-public)")
print("=" * 60 + "\n")
await knowledge.ainsert(
name="Anthropic SDK LICENSE",
remote_content=github_public.file(
"LICENSE", repo="anthropics/anthropic-sdk-python"
),
)
# Load through the authenticated GitHub config if it was registered.
if github_private is not None:
print("\n" + "=" * 60)
print("Loading README.md from default repo (github-private)")
print("=" * 60 + "\n")
await knowledge.ainsert(
name="Private Repo README",
remote_content=github_private.file("README.md"),
)
# Cross-source search against the unified vector index.
print("\n" + "=" * 60)
print("Searching across all registered sources")
print("=" * 60 + "\n")
results = await knowledge.asearch("What is Agno?")
for doc in results:
print("- %s" % doc.name)
asyncio.run(main())
Run the Example
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
Install dependencies
uv pip install -U agno aioboto3 boto3 msal openai pgvector psycopg-binary sqlalchemy
Export environment variables
export AZURE_CLIENT_ID="your_azure_client_id_here"
export AZURE_CLIENT_SECRET="your_azure_client_secret_here"
export AZURE_SAS_TOKEN="your_azure_sas_token_here"
export AZURE_TENANT_ID="your_azure_tenant_id_here"
export GITHUB_TOKEN="your_github_token_here"
export OPENAI_API_KEY="your_openai_api_key_here"
export SHAREPOINT_CLIENT_ID="your_sharepoint_client_id_here"
export SHAREPOINT_CLIENT_SECRET="your_sharepoint_client_secret_here"
export SHAREPOINT_SITE_ID="your_sharepoint_site_id_here"
export SHAREPOINT_TENANT_ID="your_sharepoint_tenant_id_here"
$Env:AZURE_CLIENT_ID="your_azure_client_id_here"
$Env:AZURE_CLIENT_SECRET="your_azure_client_secret_here"
$Env:AZURE_SAS_TOKEN="your_azure_sas_token_here"
$Env:AZURE_TENANT_ID="your_azure_tenant_id_here"
$Env:GITHUB_TOKEN="your_github_token_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
$Env:SHAREPOINT_CLIENT_ID="your_sharepoint_client_id_here"
$Env:SHAREPOINT_CLIENT_SECRET="your_sharepoint_client_secret_here"
$Env:SHAREPOINT_SITE_ID="your_sharepoint_site_id_here"
$Env:SHAREPOINT_TENANT_ID="your_sharepoint_tenant_id_here"
Run PgVector
docker run -d \
-e POSTGRES_DB=ai \
-e POSTGRES_USER=ai \
-e POSTGRES_PASSWORD=ai \
-e PGDATA=/var/lib/postgresql \
-v pgvolume:/var/lib/postgresql \
-p 5532:5432 \
--name pgvector \
agnohq/pgvector:18