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AINative Python SDK

Official Python SDK for AINative Studio APIs - unified database and AI operations platform.

Features

  • 🚀 Simple Integration - Get started with just an API key
  • 🗄️ ZeroDB Operations - Full support for vector storage, search, and memory management
  • 🤖 Agent Swarm - Orchestrate multiple AI agents for complex tasks
  • 🔐 Enterprise Security - Multi-tenant authentication with API key management
  • ⚡ High Performance - Async support and connection pooling
  • 📊 Analytics - Built-in usage tracking and performance metrics

Installation

pip install ainative-python

For the development version:

pip install git+https://github.com/AINative-Studio/python-sdk.git

Quick Start

from ainative import AINativeClient

# Initialize client
client = AINativeClient(api_key="your-api-key")

# Create a project
project = client.zerodb.projects.create(
    name="My First Project",
    description="Testing AINative SDK"
)

# Store vectors
client.zerodb.vectors.upsert(
    project_id=project["id"],
    vectors=[[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]],
    metadata=[{"text": "Hello"}, {"text": "World"}]
)

# Search vectors
results = client.zerodb.vectors.search(
    project_id=project["id"],
    vector=[0.15, 0.25, 0.35],
    top_k=5
)

# Create memory
memory = client.zerodb.memory.create(
    content="Important information to remember",
    tags=["tutorial", "example"]
)

Authentication

Using Environment Variables

export AINATIVE_API_KEY="your-api-key"
export AINATIVE_API_SECRET="your-api-secret"  # Optional
export AINATIVE_ORG_ID="your-org-id"  # For multi-tenant scenarios
from ainative import AINativeClient

# Automatically uses environment variables
client = AINativeClient()

Direct Configuration

from ainative import AINativeClient, AuthConfig

auth_config = AuthConfig(
    api_key="your-api-key",
    api_secret="your-api-secret",  # Optional for enhanced security
    environment="production"  # or "staging", "development"
)

client = AINativeClient(auth_config=auth_config)

ZeroDB Operations

Project Management

# List all projects
projects = client.zerodb.projects.list(limit=10)

# Get project details
project = client.zerodb.projects.get(project_id="proj_123")

# Update project
client.zerodb.projects.update(
    project_id="proj_123",
    name="Updated Name",
    metadata={"version": "2.0"}
)

# Suspend/Activate project
client.zerodb.projects.suspend(project_id="proj_123", reason="Maintenance")
client.zerodb.projects.activate(project_id="proj_123")

Vector Operations

import numpy as np

# Upsert vectors with numpy arrays
vectors = np.random.rand(10, 768)  # 10 vectors of dimension 768
metadata = [{"doc_id": i, "category": "test"} for i in range(10)]

client.zerodb.vectors.upsert(
    project_id="proj_123",
    vectors=vectors,
    metadata=metadata,
    namespace="documents"
)

# Search vectors
query_vector = np.random.rand(768)
results = client.zerodb.vectors.search(
    project_id="proj_123",
    vector=query_vector,
    top_k=5,
    namespace="documents",
    filter={"category": "test"}
)

# Delete vectors
client.zerodb.vectors.delete(
    project_id="proj_123",
    ids=["vec_1", "vec_2"],
    namespace="documents"
)

NoSQL Table Operations

# Create a table with schema
table = client.zerodb.tables.create_table(
    table_name="users",
    schema={
        "fields": {
            "email": "string",
            "name": "string",
            "age": "number",
            "active": "boolean"
        },
        "indexes": ["email"]
    }
)

# Insert rows
result = client.zerodb.tables.insert_rows("users", [
    {"email": "user@example.com", "name": "John", "age": 30, "active": True},
    {"email": "jane@example.com", "name": "Jane", "age": 25, "active": True}
])

# Query rows with filters
users = client.zerodb.tables.query_rows(
    "users",
    filter={"age": {"$gte": 25}, "active": True},
    sort={"age": -1},
    limit=10
)

# Update rows
client.zerodb.tables.update_rows(
    "users",
    filter={"email": "user@example.com"},
    update={"$set": {"age": 31}}
)

# Delete rows
client.zerodb.tables.delete_rows(
    "users",
    filter={"age": {"$lt": 18}}
)

# Count rows
total = client.zerodb.tables.count_rows("users")
active_users = client.zerodb.tables.count_rows("users", filter={"active": True})

See the complete Table Operations Guide for advanced usage.

Memory Management

from ainative.zerodb.memory import MemoryPriority

# Create memory with priority
memory = client.zerodb.memory.create(
    content="Critical system configuration",
    title="System Config",
    tags=["config", "system"],
    priority=MemoryPriority.HIGH,
    metadata={"version": "1.0"}
)

# Search memories
results = client.zerodb.memory.search(
    query="system configuration",
    semantic=True,  # Use semantic search
    limit=10
)

# List memories with filters
memories = client.zerodb.memory.list(
    tags=["config"],
    priority=MemoryPriority.HIGH
)

# Get related memories
related = client.zerodb.memory.get_related(
    memory_id=memory["id"],
    limit=5
)

Agent Swarm

Starting a Swarm

from ainative.agent_swarm import AgentType

# Define agents
agents = [
    {
        "id": "researcher_1",
        "type": AgentType.RESEARCHER.value,
        "capabilities": ["web_search", "document_analysis"]
    },
    {
        "id": "coder_1",
        "type": AgentType.CODER.value,
        "capabilities": ["python", "javascript", "testing"]
    }
]

# Start swarm
swarm = client.agent_swarm.start_swarm(
    project_id="proj_123",
    agents=agents,
    objective="Research and implement a new feature"
)

# Orchestrate task
result = client.agent_swarm.orchestrate(
    swarm_id=swarm["id"],
    task="Find best practices for implementing OAuth2",
    context={"language": "Python", "framework": "FastAPI"}
)

Managing Swarms

# Get swarm status
status = client.agent_swarm.get_status(swarm_id="swarm_123")

# Get performance metrics
metrics = client.agent_swarm.get_metrics(swarm_id="swarm_123")

# Configure specific agent
client.agent_swarm.configure_agent(
    swarm_id="swarm_123",
    agent_id="coder_1",
    config={"temperature": 0.7, "max_tokens": 2000}
)

# Pause/Resume swarm
client.agent_swarm.pause_swarm(swarm_id="swarm_123")
client.agent_swarm.resume_swarm(swarm_id="swarm_123")

# Stop swarm
client.agent_swarm.stop_swarm(swarm_id="swarm_123")

Analytics

from datetime import datetime, timedelta

# Get usage analytics
usage = client.zerodb.analytics.get_usage(
    project_id="proj_123",
    start_date=datetime.now() - timedelta(days=30),
    end_date=datetime.now(),
    granularity="daily"
)

# Get performance metrics
performance = client.zerodb.analytics.get_performance_metrics(
    project_id="proj_123",
    metric_type="latency"
)

# Get cost analysis
costs = client.zerodb.analytics.get_cost_analysis(
    project_id="proj_123"
)

# Export analytics report
report = client.zerodb.analytics.export_report(
    report_type="detailed",
    project_id="proj_123",
    format="pdf"
)

Async Support

import asyncio
from ainative import AsyncAINativeClient

async def main():
    async with AsyncAINativeClient(api_key="your-api-key") as client:
        # Async operations
        project = await client.zerodb.projects.create(
            name="Async Project"
        )
        
        # Concurrent operations
        tasks = [
            client.zerodb.vectors.search(project_id, vector)
            for vector in vectors
        ]
        results = await asyncio.gather(*tasks)

asyncio.run(main())

Error Handling

from ainative.exceptions import (
    AuthenticationError,
    RateLimitError,
    ValidationError,
    ResourceNotFoundError
)

try:
    result = client.zerodb.projects.get("invalid_id")
except ResourceNotFoundError as e:
    print(f"Project not found: {e.resource_id}")
except AuthenticationError:
    print("Invalid API credentials")
except RateLimitError as e:
    print(f"Rate limited. Retry after {e.retry_after} seconds")
except ValidationError as e:
    print(f"Invalid input: {e.message}")

Configuration

Custom Base URL

client = AINativeClient(
    api_key="your-api-key",
    base_url="https://custom.ainative.studio"
)

Timeout and Retries

from ainative.client import ClientConfig

config = ClientConfig(
    timeout=60,  # 60 seconds
    max_retries=5,
    retry_delay=2.0
)

client = AINativeClient(
    api_key="your-api-key",
    config=config
)

CLI Tool

The SDK includes a CLI tool for quick operations:

# Configure credentials
ainative config set api_key YOUR_API_KEY

# List projects
ainative projects list

# Create project
ainative projects create --name "CLI Project"

# Search vectors
ainative vectors search --project proj_123 --query "test"

Examples

Full examples are available in the examples/ directory:

Development

Setting up development environment

# Clone repository
git clone https://github.com/AINative-Studio/core.git
cd core/developer-tools/sdks/python

# Install in development mode
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black ainative/
isort ainative/

# Type checking
mypy ainative/

Running Tests

# All tests
pytest

# With coverage
pytest --cov=ainative

# Specific module
pytest tests/test_zerodb.py

Support

Contributing

We welcome contributions! Fork this repo, make your change, and open a pull request — see CONTRIBUTING.md for setup, style, and testing details.

License

MIT License - see LICENSE file for details.

Changelog

See CHANGELOG.md for release history.

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AINative Studio Python SDK

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