olbrain-python-sdk 0.2.2

Official Python SDK for Olbrain AI agents

Olbrain Python SDK

Official Python SDK for integrating Olbrain AI agents into your applications.

Installation

pip install olbrain-python-sdk

Quick Start

from olbrain import AgentClient

# Initialize client
client = AgentClient(
    agent_id="your-agent-id",
    api_key="sk_live_your_api_key"
)

# Create a session and send a message
session_id = client.create_session(title="My Chat")
response = client.send_and_wait(session_id, "Hello!")

print(response.text)
client.close()

Features

• Simple API - Just agent_id and api_key to get started
• Session Management - Create, update, archive sessions with metadata
• Sync & Streaming - Both request-response and real-time streaming
• Token Tracking - Monitor usage and costs per request
• Model Override - Switch models per-message
• Error Handling - Comprehensive exception hierarchy

Usage

Synchronous Messaging

from olbrain import AgentClient

with AgentClient(agent_id="your-agent-id", api_key="sk_live_your_key") as client:
    session_id = client.create_session()
    response = client.send_and_wait(session_id, "What is Python?")

    print(response.text)
    print(f"Tokens: {response.token_usage.total_tokens}")

Real-Time Streaming

from olbrain import AgentClient

client = AgentClient(agent_id="your-agent-id", api_key="sk_live_your_key")

def on_message(msg):
    print(f"[{msg['role']}]: {msg['content']}")

session_id = client.create_session(on_message=on_message)
client.send(session_id, "Tell me a story")
client.run()  # Blocks and processes messages

Session Management

# Create session with metadata
session_id = client.create_session(
    title="Support Chat",
    user_id="user-123",
    metadata={"source": "web"},
    mode="production"
)

# Get session info
info = client.get_session(session_id)
print(f"Messages: {info.message_count}")

# Get message history
messages = client.get_messages(session_id, limit=20)

# Archive session
client.delete_session(session_id)

Model Override

response = client.send_and_wait(
    session_id,
    "Complex question here",
    model="gpt-4"  # Override default model
)

Error Handling

from olbrain import AgentClient
from olbrain.exceptions import (
    AuthenticationError,
    SessionNotFoundError,
    RateLimitError,
    OlbrainError
)

try:
    client = AgentClient(agent_id="...", api_key="...")
    response = client.send_and_wait(session_id, "Hello")
except AuthenticationError:
    print("Invalid API key")
except RateLimitError as e:
    print(f"Rate limited. Retry after {e.retry_after}s")
except OlbrainError as e:
    print(f"Error: {e}")

Configuration

Environment Variables

export OLBRAIN_API_KEY="sk_live_your_api_key"
export OLBRAIN_AGENT_ID="your-agent-id"

Logging

import logging
logging.basicConfig(level=logging.DEBUG)

API Reference

AgentClient

Method	Description
create_session()	Create a new chat session
send(session_id, message)	Send message (async, use callback)
send_and_wait(session_id, message)	Send message and wait for response
get_session(session_id)	Get session details
update_session(session_id, ...)	Update session title/metadata
delete_session(session_id)	Archive a session
get_messages(session_id)	Get message history
get_session_stats(session_id)	Get token usage stats
close()	Clean up resources

Response Objects

ChatResponse

• text - Response text
• success - Success status
• token_usage - TokenUsage object
• model_used - Model that generated response

TokenUsage

• prompt_tokens - Input tokens
• completion_tokens - Output tokens
• total_tokens - Total tokens
• cost - Cost in USD

Exceptions

Exception	Description
OlbrainError	Base exception
AuthenticationError	Invalid API key
SessionNotFoundError	Session not found
RateLimitError	Rate limit exceeded
NetworkError	Connection issues
ValidationError	Invalid input
StreamingError	Streaming error

Examples

See the examples/ directory:

• basic_usage.py - Core SDK features
• session_management.py - Session CRUD operations
• streaming_responses.py - Real-time streaming
• error_handling.py - Error handling patterns
• advanced_features.py - Advanced usage

License

MIT License - see LICENSE

Links

• PyPI
• GitHub
• Issues