Skip to main content

Firebase for AI Agents - Persistent state management for AI applications

Project description

🤖 AgentState Python SDK

Firebase for AI Agents - Python SDK for persistent agent state management.

PyPI version Python versions License

🚀 Quick Start

Installation

pip install agentstate

Basic Usage

from agentstate import AgentStateClient

# Connect to AgentState server
client = AgentStateClient("http://localhost:8080", namespace="my-app")

# Create an agent
agent = client.create_agent(
    agent_type="chatbot",
    body={"name": "CustomerBot", "status": "active", "conversations": 0},
    tags={"team": "support", "environment": "production"}
)

print(f"Created agent: {agent['id']}")

# Update agent state
updated = client.create_agent(
    agent_type="chatbot", 
    body={"name": "CustomerBot", "status": "busy", "conversations": 5},
    tags={"team": "support", "environment": "production"},
    agent_id=agent['id']  # Update existing agent
)

# Query agents
support_agents = client.query_agents({"team": "support"})
print(f"Found {len(support_agents)} support agents")

# Get specific agent
retrieved = client.get_agent(agent['id'])
print(f"Agent status: {retrieved['body']['status']}")

📚 API Reference

AgentStateClient

__init__(base_url, namespace)

Initialize the client.

  • base_url: AgentState server URL (e.g., "http://localhost:8080")
  • namespace: Namespace for organizing agents (e.g., "production", "staging")

create_agent(agent_type, body, tags=None, agent_id=None)

Create or update an agent.

  • agent_type: Agent category (e.g., "chatbot", "workflow", "classifier")
  • body: Agent state data (dict)
  • tags: Key-value pairs for querying (dict, optional)
  • agent_id: Specific ID for updates (str, optional)

Returns: Agent object with id, type, body, tags, commit_seq, commit_ts

get_agent(agent_id)

Get agent by ID.

  • agent_id: Unique agent identifier

Returns: Agent object

query_agents(tags=None)

Query agents by tags.

  • tags: Tag filters (e.g., {"team": "support", "status": "active"})

Returns: List of matching agent objects

delete_agent(agent_id)

Delete an agent.

  • agent_id: Unique agent identifier

health_check()

Check server health.

Returns: True if healthy, False otherwise

🎯 Usage Examples

Multi-Agent System

from agentstate import AgentStateClient

client = AgentStateClient("http://localhost:8080", "multi-agent-system")

# Create coordinator agent
coordinator = client.create_agent("coordinator", {
    "status": "active",
    "workers": [],
    "tasks_queued": 50
}, {"role": "coordinator"})

# Create worker agents
workers = []
for i in range(3):
    worker = client.create_agent("worker", {
        "status": "idle",
        "processed_today": 0,
        "coordinator_id": coordinator["id"]
    }, {"role": "worker", "coordinator": coordinator["id"]})
    workers.append(worker)

print("Multi-agent system initialized!")

🔗 Links

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

agentstate-1.0.2.tar.gz (5.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

agentstate-1.0.2-py3-none-any.whl (6.0 kB view details)

Uploaded Python 3

File details

Details for the file agentstate-1.0.2.tar.gz.

File metadata

  • Download URL: agentstate-1.0.2.tar.gz
  • Upload date:
  • Size: 5.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.5

File hashes

Hashes for agentstate-1.0.2.tar.gz
Algorithm Hash digest
SHA256 2578877862efb692a4f3e467211eeca34b2a1f0a0260301c9577592c5d8c8d0d
MD5 1b76ac9abfadd25326e5c4e2361413aa
BLAKE2b-256 068a29332426e1632601b41eeb90c1ec13e3f764d02b772196593dbdb44d5e56

See more details on using hashes here.

File details

Details for the file agentstate-1.0.2-py3-none-any.whl.

File metadata

  • Download URL: agentstate-1.0.2-py3-none-any.whl
  • Upload date:
  • Size: 6.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.5

File hashes

Hashes for agentstate-1.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 48375add0cfee4ecb6bb09bbb37f564d3b027e471cc635b2e354f5d32c6d3bce
MD5 9c541a78efdf0a8cba1871ac384537cc
BLAKE2b-256 fcf9fcd813b63645fd7108ef32741062f826c706af1a960f47564e3cdbad4eb9

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page