valkey_db.py
"""
Per-User Isolation: Valkey
==========================
Each user gets a private view of one shared knowledge base. Documents
uploaded with a user_id are visible only to that user; documents uploaded
without one are shared with everyone.
Valkey stores the owner in a user_id TAG field on each hash; shared chunks
get a __shared__ sentinel tag and scoped reads match caller OR sentinel.
- Search as Alice: her chunks plus shared content, never Bob's
- Search as Bob: his chunks plus shared content, never Alice's
- Search with user_id=None: admin view, sees everything
Redis and Valkey both bind port 6379, so run only one of them at a time.
Use the valkey-bundle image; plain valkey/valkey ships no search module.
Requirements:
- ./cookbook/scripts/run_valkey.sh
- uv pip install valkey-glide-sync
- OPENAI_API_KEY
"""
import asyncio
from typing import List
from agno.agent import Agent
from agno.knowledge.document import Document
from agno.knowledge.knowledge import Knowledge
from agno.models.openai import OpenAIResponses
from agno.vectordb.search import SearchType
from agno.vectordb.valkey import ValkeyDb
# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
ALICE_SALARY = "Alice's salary is $180,000. Reviewed annually in March."
BOB_SALARY = "Bob's salary is $215,000. Reviewed annually in June."
HOLIDAYS = "The company is closed on January 1, July 4, and December 25."
VALKEY_HOST = "localhost"
VALKEY_PORT = 6379
INDEX_NAME = "per_user_isolation_valkey"
def show(label: str, results: List[Document]) -> None:
"""Print one search result set."""
print(f"{label} -> {len(results)} results")
for d in results:
print(f" - {d.content[:80]}")
print()
# ---------------------------------------------------------------------------
# Create Knowledge Base
# ---------------------------------------------------------------------------
vector_db = ValkeyDb(
index_name=INDEX_NAME,
host=VALKEY_HOST,
port=VALKEY_PORT,
search_type=SearchType.vector,
)
# Start clean: hashes from an earlier run keep their owner tag and would show up as extra results.
if vector_db.exists():
vector_db.drop()
vector_db.create()
knowledge = Knowledge(
name="per_user_demo",
description="Per-user RAG isolation demo (Valkey)",
vector_db=vector_db,
)
# ---------------------------------------------------------------------------
# Run Demo
# ---------------------------------------------------------------------------
if __name__ == "__main__":
async def main() -> None:
await knowledge.ainsert(
name="alice_salary",
text_content=ALICE_SALARY,
user_id="alice",
)
await knowledge.ainsert(
name="bob_salary",
text_content=BOB_SALARY,
user_id="bob",
)
# The last upload has no user_id, which makes it shared with everyone.
await knowledge.ainsert(
name="company_holidays",
text_content=HOLIDAYS,
)
print("\n" + "=" * 60)
print("SCOPED SEARCH: three callers, one corpus")
print("=" * 60 + "\n")
alice_view = await knowledge.asearch(query="salary", user_id="alice")
show("Alice (user_id='alice')", alice_view)
alice_text = " ".join(d.content for d in alice_view)
assert "180,000" in alice_text, (
"Alice cannot retrieve her own document. If every write also failed, "
"check that VALKEY_PORT points at a Valkey with the search module."
)
assert "January 1" in alice_text, (
"Shared content is unreachable from Alice's scoped view"
)
assert "215,000" not in alice_text, (
"Isolation broken: Alice's scoped view leaked Bob's salary"
)
bob_view = await knowledge.asearch(query="salary", user_id="bob")
show("Bob (user_id='bob')", bob_view)
bob_text = " ".join(d.content for d in bob_view)
assert "215,000" in bob_text, "Bob cannot retrieve his own document"
assert "January 1" in bob_text, (
"Shared content is unreachable from Bob's scoped view"
)
assert "180,000" not in bob_text, (
"Isolation broken: Bob's scoped view leaked Alice's salary"
)
admin_view = await knowledge.asearch(query="salary", user_id=None)
show("Admin (user_id=None)", admin_view)
admin_text = " ".join(d.content for d in admin_view)
for expected in ("180,000", "215,000", "January 1"):
assert expected in admin_text, (
f"Admin view is missing {expected}, it has to see every owner"
)
assert all(d.content in admin_text for d in alice_view), (
"Admin view has to be a superset of a scoped user's view"
)
print("Alice and Bob each see their own chunk plus the shared one.")
print("Admin sees the whole corpus.")
print("\n" + "=" * 60)
print("AGENT-MEDIATED RETRIEVAL: the owner has to survive the handoff")
print("=" * 60 + "\n")
alice_agent = Agent(
name="Alice's Assistant",
model=OpenAIResponses(id="gpt-5.5"),
knowledge=knowledge,
search_knowledge=True,
user_id="alice",
instructions=[
"Answer questions using ONLY the knowledge you can retrieve.",
"If you don't know, say so - do not invent salary figures.",
],
markdown=True,
)
response = await alice_agent.arun("What is Bob's salary?")
print("Alice's agent on 'What is Bob's salary?':")
print(response.content)
# Assert on what retrieval returned, not on the model's prose.
retrieved = " ".join(
item["content"]
for ref in (response.references or [])
for item in (ref.references or [])
if isinstance(item, dict) and item.get("content")
)
assert retrieved, (
"Retrieval returned no documents, so the isolation check below would pass on nothing"
)
assert "215,000" not in retrieved, (
"Isolation broken: Alice's agent retrieved Bob's salary. The owner was "
"dropped between the run context and the vector DB, so retrieval ran "
"unscoped (user_id=None, the admin view)."
)
print("\nisolation holds: Bob's salary never reached Alice's agent")
print("\nDone.")
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 openai valkey-glide-sync
3
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Run Valkey
docker run -d --name my-valkey -p 6379:6379 valkey/valkey-bundle
5
Run the example
Save the code above as
valkey_db.py, then run:python valkey_db.py