Serve Knowledge with AgentOS
Serve one local knowledge base through an AgentOS and share the same instance with an agent so successfully processed uploads are available for search.
"""
Serve Knowledge with AgentOS
============================
Serve one local knowledge base through an AgentOS and share the same instance
with an agent so uploaded content is immediately available for search.
Prerequisites: OPENAI_API_KEY
Run: .venvs/demo/bin/python cookbook/05_agent_os/10_knowledge/basic.py
Try: Run rest_api_knowledge.py from this folder in another terminal
"""
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.knowledge.embedder.openai import OpenAIEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.models.openai import OpenAIResponses
from agno.os import AgentOS
from agno.vectordb.chroma import ChromaDb
# ---------------------------------------------------------------------------
# Create Knowledge-Aware AgentOS
# ---------------------------------------------------------------------------
db = SqliteDb(
id="knowledge-db",
db_file="tmp/knowledge.db",
)
knowledge = Knowledge(
name="AgentOS Knowledge",
description="Local content managed through the AgentOS knowledge API.",
contents_db=db,
vector_db=ChromaDb(
collection="agentos_knowledge",
path="tmp/knowledge_chroma",
persistent_client=True,
embedder=OpenAIEmbedder(id="text-embedding-3-small"),
),
)
knowledge_assistant = Agent(
id="knowledge-assistant",
name="Knowledge Assistant",
model=OpenAIResponses(id="gpt-5.5"),
db=db,
knowledge=knowledge,
search_knowledge=True,
instructions=(
"Answer concisely. Search the knowledge base before answering questions "
"about stored content."
),
)
agent_os = AgentOS(
id="knowledge-os",
description="AgentOS serving one local knowledge base.",
db=db,
agents=[knowledge_assistant],
knowledge=[knowledge],
)
app = agent_os.get_app()
# ---------------------------------------------------------------------------
# Run Knowledge Server
# ---------------------------------------------------------------------------
if __name__ == "__main__":
knowledge.insert(
name="AgentOS knowledge overview",
text_content=(
"AgentOS exposes content upload, processing status, listing, "
"semantic search, and deletion through the knowledge REST API."
),
metadata={"source": "10_knowledge/basic.py"},
skip_if_exists=True,
)
agent_os.serve(app=app)Uploads return HTTP 202 with a processing status before ingestion and embedding finish. Use the returned content ID with GET /knowledge/content/{content_id}/status and wait for completed before expecting all content to be searchable. A partial status means some chunks failed; inspect status_message and re-ingest after resolving the cause. The source docstring's “immediately available” wording refers to the shared knowledge instance, not synchronous indexing.
Run the Example
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activateInstall dependencies
uv pip install -U "agno[os]" chromadb openaiExport your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"Run the example
Save the code above as basic.py, then run:
python basic.pyFull source: cookbook/05_agent_os/10_knowledge/basic.py