AgentOS Knowledge API

Prerequisites

Start an AgentOS server with knowledge configured:

from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.db.sqlite import SqliteDb
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.embedder.openai import OpenAIEmbedder
from agno.vectordb.chroma import ChromaDb
from agno.os import AgentOS

db = SqliteDb(db_file="tmp/app.db")

knowledge = Knowledge(
    vector_db=ChromaDb(
        path="tmp/chromadb",
        collection="docs",
        embedder=OpenAIEmbedder(id="text-embedding-3-small"),
    ),
    contents_db=db,  # Required for upload/management endpoints
)

agent = Agent(
    name="Knowledge Agent",
    model=Claude(id="claude-sonnet-4-5"),
    knowledge=knowledge,
    search_knowledge=True,
    db=db,
)

agent_os = AgentOS(agents=[agent], knowledge=[knowledge])
agent_os.serve()

Default: Use the CLI Script

Always try the provided script first. It covers listing content, uploading files, uploading raw text, searching the knowledge base, checking processing status, and deleting content — all from the command line with no custom code needed.

The script is at: scripts/manage_knowledge.py

List all content

uv run scripts/manage_knowledge.py --base-url http://localhost:7777

Search the knowledge base

uv run scripts/manage_knowledge.py --base-url http://localhost:7777 \
  --search "What is Agno?" --limit 5

Upload a text file

uv run scripts/manage_knowledge.py --base-url http://localhost:7777 \
  --upload README.md

Upload raw text

uv run scripts/manage_knowledge.py --base-url http://localhost:7777 \
  --upload-text "Agno is an AI agent framework" --name "Agno Intro"

Check processing status

uv run scripts/manage_knowledge.py --base-url http://localhost:7777 \
  --status content-id-123

Delete specific content

uv run scripts/manage_knowledge.py --base-url http://localhost:7777 \
  --delete content-id-123

Full CLI reference

uv run scripts/manage_knowledge.py --help

When to Write Custom Python

Only write ad-hoc Python when the CLI script cannot handle your use case:

Get knowledge config (readers, chunkers, embedder info)
Pagination and sorting when listing content
Update content metadata (name, description)
Delete all content at once
Chaining multiple operations in a single script (e.g., upload then search)
Custom error handling or retry logic
Integration tests that assert on response content

API Endpoints

Method	Path	Description
GET	`/knowledge/config`	Get knowledge config
GET	`/knowledge/content`	List all content (paginated)
GET	`/knowledge/content/{content_id}`	Get content by ID
GET	`/knowledge/content/{content_id}/status`	Get content status
POST	`/knowledge/search`	Search knowledge base
POST	`/knowledge/content`	Upload content
PATCH	`/knowledge/content/{content_id}`	Update content metadata
DELETE	`/knowledge/content`	Delete all content
DELETE	`/knowledge/content/{content_id}`	Delete content by ID

Custom Python Examples

Get Knowledge Config

import asyncio
from agno.client import AgentOSClient

async def main():
    client = AgentOSClient(base_url="http://localhost:7777")

    config = await client.get_knowledge_config()
    print(f"Readers: {config.readers if hasattr(config, 'readers') else 'N/A'}")
    print(f"Chunkers: {config.chunkers if hasattr(config, 'chunkers') else 'N/A'}")

asyncio.run(main())

List Content with Pagination

async def main():
    client = AgentOSClient(base_url="http://localhost:7777")

    content = await client.list_knowledge_content()
    print(f"Found {len(content.data)} content items")

    for item in content.data:
        print(f"  {item.id}: {item.name} ({item.status})")

Supports pagination via limit and page parameters, and sorting via sort_by and sort_order.

Update Content Metadata

updated = await client.update_content(
    content_id="content-id-here",
    name="Updated Name",
    description="Updated description",
)

Delete All Content

await client.delete_all_content()

Full Upload and Search Workflow

import asyncio
from agno.client import AgentOSClient

async def main():
    client = AgentOSClient(base_url="http://localhost:7777")

    # Upload
    result = await client.upload_knowledge_content(
        text_content="""
        # Agno Framework Guide
        Agno is a powerful framework for building AI agents.
        Key features: agent creation, team coordination, workflows.
        """,
        name="Agno Guide",
        description="A guide to the Agno framework",
    )
    print(f"Uploaded: {result.id}")

    # Check status
    status = await client.get_content_status(result.id)
    print(f"Status: {status.status}")

    # Search
    results = await client.search_knowledge(query="What is Agno?", limit=5)
    for r in results.data:
        print(f"  {str(r.content)[:100]}...")

    # List
    content = await client.list_knowledge_content()
    print(f"Total items: {len(content.data)}")

asyncio.run(main())

Anti-Patterns

Don't write custom Python for basic operations — use the CLI script for listing, uploading, searching, status checks, and deleting
Don't forget contents_db= on Knowledge — required for upload/management endpoints
Don't forget knowledge=[...] on AgentOS — registers knowledge API endpoints
Don't assume instant processing — content is processed asynchronously; check status
Don't skip error handling — knowledge endpoints may not be configured on all instances

agentos-api-knowledge