teradata-agentstack-20.00.00.00

teradata-agentstack

A Python SDK package that dynamically generates client classes from OpenAPI specifications for Teradata AI/ML platform services.

Version: 20.00.00.00 | Python: ≥ 3.9 (64-bit) | Platform: Windows, macOS, Linux

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Overview

teradata-agentstack provides a unified framework for interacting with Teradata platform REST APIs. Instead of hand-writing API wrappers, each SDK module reads the bundled OpenAPI JSON specification at import time and automatically creates Python classes and methods:

• OpenAPI Tags are converted to CamelCase Python classes.
• Operation IDs are converted to snake_case instance methods.
• A blueprint() helper lists all generated classes for a module.

Included SDKs

Module	Client Class	Generated Classes	Service
teradata_agentstack.sqlgen	SqlGenClient	SqlGenApi, ...	Teradata SQL Generation
teradata_agentstack.agentops	AgentOpsClient	Definitions, Deployments, Secrets, Health	Teradata AgentOps
teradata_agentstack.rayops	RayClusterManagementClient	RayClusterManagement, ...	Ray Cluster Management
teradata_agentstack.agento11y	AgentO11yClient	Traces, Projects, Evaluations, ...	Agent Observability
teradata_agentstack.access_manager	AccessManagerClient	Keys, Admin, Proxy	API Access Manager
teradata_agentstack.inference_engine	InferenceEngineClient	Secrets, Pools, Endpoints, ...	Inference Engine
teradata_agentstack.mcp_management	MCPManagementClient	Servers, ...	MCP Management Service
teradata_agentstack.mcp_endpoint_management	MCPEndpointManagementClient	Endpoints, ...	MCP Endpoint Management

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Installation

pip install teradata-agentstack

Note: A 64-bit Python environment is required. Installation will fail on 32-bit platforms.

Dependencies

Package	Version
teradataml	>=20.00.00.10
requests	≥ 2.33.0
oauthlib	≥ 3.2.2
requests-oauthlib	≥ 2.0.0
pydantic	≥ 2.10.6
PyYAML	≥ 6.0.2
pandas	≥ 0.22

---

Authentication

All SDK clients accept the same authentication objects, imported from the top-level package:

from teradata_agentstack import ClientCredentialsAuth, DeviceCodeAuth, BearerAuth
from teradata_agentstack._auth_modes import BasicAuth

ClientCredentialsAuth — OAuth2 Client Credentials

auth = ClientCredentialsAuth(
    auth_token_url="https://your-sso/token",
    auth_client_id="your_client_id",
    auth_client_secret="your_client_secret"
)

DeviceCodeAuth — OAuth2 Device Code Flow

auth = DeviceCodeAuth(
    auth_token_url="https://your-sso/token",
    auth_device_auth_url="https://your-sso/device_authorization",
    auth_client_id="your_client_id"
)

Tokens are cached at ~/.teradataml/sdk/.token and reused on subsequent calls.

BearerAuth — Static Bearer Token

auth = BearerAuth(auth_bearer="your_bearer_token")

BasicAuth — Username / Password

auth = BasicAuth(username="user", password="pass")

Authentication Precedence Order

Each configuration value (base_url, auth, ssl_verify) is resolved in the following order. The first source that provides a value wins:

1. Constructor arguments — values passed directly to the client (e.g., base_url=..., auth=...).
2. Environment variables — values read from the process environment (e.g., BASE_URL, BASE_API_AUTH_MODE).
3. YAML config file — values loaded from the config file (explicit config_file path, or the default ~/.teradataml/sdk/config.yaml).

If none of the three sources supplies a required value, a TeradataMlException is raised.

Authentication via Environment Variables

You can configure authentication without passing an auth object by setting environment variables:

Variable	Description
BASE_URL	Base URL of the API endpoint
BASE_API_AUTH_MODE	client_credentials, device_code, bearer, or basic
BASE_SSL_VERIFY	true or false
BASE_API_AUTH_CLIENT_ID	OAuth2 client ID
BASE_API_AUTH_CLIENT_SECRET	OAuth2 client secret
BASE_API_AUTH_TOKEN_URL	OAuth2 token endpoint URL
BASE_API_AUTH_DEVICE_AUTH_URL	OAuth2 device authorization URL
BASE_API_AUTH_BEARER_TOKEN	Static bearer token

Authentication via YAML Config File

# config.yaml
base_url: https://your-server
ssl_verify: true
auth_mode: client_credentials
auth_client_id: your_client_id
auth_client_secret: your_client_secret
auth_token_url: https://your-sso/token

Pass the path using the config_file argument on any client.

---

Quick Start

SqlGen SDK

from teradata_agentstack import BearerAuth
from teradata_agentstack.sqlgen import SqlGenClient

auth = BearerAuth(auth_bearer="your_bearer_token")

client = SqlGenClient(
    base_url="http://your-server:port",
    auth=auth,
    hostname="your_db_host",
    database="your_database",
    vectorstore="your_vectorstore",
    ssl_verify=False
)

AgentOps SDK

from teradata_agentstack import DeviceCodeAuth
from teradata_agentstack.agentops import AgentOpsClient
from teradata_agentstack.agentops import Definitions, Deployments, Secrets, Health
from teradata_agentstack.agentops.models import (
    AgentDefinitionCreateRequest,
    DeploymentCreateRequest,
)

auth = DeviceCodeAuth(
    auth_token_url="https://your-sso/token",
    auth_device_auth_url="https://your-sso/device_authorization",
    auth_client_id="your_client_id"
)

client = AgentOpsClient(
    base_url="https://your-agentops-server",
    auth=auth,
    workspace_id="your-workspace-id",
    namespace="your-k8s-namespace"
)

# Create API instances
agent_definitions = Definitions(client=client)
deployments = Deployments(client=client)
secrets = Secrets(client=client)

# Create an agent definition — pass Pydantic model directly to body=
created = agent_definitions.create(
    body=AgentDefinitionCreateRequest(
        name="my-agent",
        framework="LangGraph",
        artifacts={"storage_type": "zip"},
    ),
    file="/path/to/agent.zip",
)

# Poll until status reaches terminal state (published/failed)
agent_definitions.poll(id=created.id)

# Create a deployment
deployment = deployments.create(body=DeploymentCreateRequest(...))

# Poll until deployment is active/failed/stopped
deployments.poll(id=deployment.agent_id)

Note: The old class names (AgentDefinitions, AgentDeployments, AgentSecrets) still work as backward-compatible aliases.

### Ray Cluster Management SDK

```python
from teradata_agentstack import ClientCredentialsAuth
from teradata_agentstack.rayops import RayClusterManagementClient

auth = ClientCredentialsAuth(
    auth_token_url="https://your-sso/token",
    auth_client_id="your_client_id",
    auth_client_secret="your_client_secret"
)

client = RayClusterManagementClient(
    base_url="https://your-ray-server",
    auth_data=auth
)

Agent Observability SDK

from teradata_agentstack._auth_modes import BearerAuth
from teradata_agentstack.agento11y import AgentO11yClient

auth = BearerAuth(auth_bearer="your_bearer_token")

client = AgentO11yClient(
    base_url="https://your-agento11y-server",
    auth=auth,
    project_id="your-project-id"
)

Access Manager SDK

from teradata_agentstack._auth_modes import BearerAuth
from teradata_agentstack.access_manager import AccessManagerClient

auth = BearerAuth(auth_bearer="your_bearer_token")

client = AccessManagerClient(
    base_url="https://your-server:9876",
    auth=auth
)

Inference Engine SDK

from teradata_agentstack import ClientCredentialsAuth
from teradata_agentstack.inference_engine import InferenceEngineClient

auth = ClientCredentialsAuth(
    auth_token_url="https://your-sso/token",
    auth_client_id="your_client_id",
    auth_client_secret="your_client_secret"
)

client = InferenceEngineClient(
    base_url="https://your-inference-server",
    auth=auth,
    workspace="your-workspace"
)

MCP Management SDK

from teradata_agentstack import ClientCredentialsAuth
from teradata_agentstack.mcp_management import MCPManagementClient

auth = ClientCredentialsAuth(
    auth_token_url="https://your-sso/token",
    auth_client_id="your_client_id",
    auth_client_secret="your_client_secret"
)

client = MCPManagementClient(
    base_url="https://your-mcp-server",
    auth=auth
)

MCP Endpoint Management SDK

from teradata_agentstack._auth_modes import BasicAuth
from teradata_agentstack.mcp_endpoint_management import MCPEndpointManagementClient

auth = BasicAuth(username="user", password="pass")

client = MCPEndpointManagementClient(
    base_url="https://your-mcp-server:8001",
    auth=auth
)

---

Pydantic Model Support

All SDK modules support passing Pydantic models directly to request body parameters. The SDK automatically serializes models before sending:

from teradata_agentstack.agentops.models import AgentDefinitionCreateRequest

# Pass Pydantic model directly — no need to call .model_dump()
result = agent_definitions.create(
    body=AgentDefinitionCreateRequest(name="my-agent", framework="LangGraph", ...),
    file="/path/to/agent.zip",
)

# Equivalent to manually serializing (still supported)
result = agent_definitions.create(
    body=AgentDefinitionCreateRequest(...).model_dump_json(by_alias=True, exclude_unset=True),
    file="/path/to/agent.zip",
)

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Polling Asy...