# CredoAI Python SDK

Credo AI SDK

## Quick Start

### Using Environment Variables (Recommended)

Set the following environment variables:

```bash
export CREDOAI_API_KEY="your-api-key"
export CREDOAI_API_URL="https://api.credo.ai"  # optional, this is the default
export CREDOAI_TENANT="your-tenant"            # required, your CredoAI tenant
```

Then use the client without any arguments:

```python
from credoai import CredoAI, UseCaseCreate

# No arguments needed when env vars are set
client = CredoAI()

# Create a use case
use_case = client.use_cases.create(
    data=UseCaseCreate(name="My AI Model", description="A machine learning model")
)
print(f"Created: {use_case.id}")
```

### Synchronous Client

```python
from credoai import CredoAI, UseCaseCreate, UseCaseUpdate

# Option 1: Using environment variables (recommended)
client = CredoAI()

# Option 2: Using explicit arguments (overrides env vars)
client = CredoAI(
    base_url="https://api.credo.ai",  # optional - defaults to CREDOAI_API_URL or https://api.credo.ai
    api_key="your-api-key",      # required if CREDOAI_API_KEY not set
    tenant="your-tenant"              # optional - defaults to CREDOAI_TENANT or "credoai"
)

# Create a use case with Pydantic model
use_case_data = UseCaseCreate(
    name="My AI Model",
    description="A machine learning model for predictions"
)
use_case = client.use_cases.create(data=use_case_data)

# Get a use case
use_case = client.use_cases.get(use_case_id="123")

# Update a use case with Pydantic model
update_data = UseCaseUpdate(description="Updated description")
updated_use_case = client.use_cases.update(use_case_id="123", data=update_data)

# Health checks
status = client.system.ping()
liveness = client.health.check_liveness()
readiness = client.health.check_readiness()
```

### Asynchronous Client

```python
import asyncio
from credoai import AsyncCredoAI, UseCaseCreate, UseCaseUpdate

async def main():
    # Option 1: Using environment variables (recommended)
    client = AsyncCredoAI()

    # Option 2: Using explicit arguments
    client = AsyncCredoAI(
        base_url="https://api.credo.ai",
        api_key="your-api-key"
    )

    # Create a use case with Pydantic model
    use_case_data = UseCaseCreate(
        name="My AI Model",
        description="A machine learning model for predictions"
    )
    use_case = await client.use_cases.create(data=use_case_data)

    # Get a use case
    use_case = await client.use_cases.get(use_case_id="123")

    # Update a use case with Pydantic model
    update_data = UseCaseUpdate(description="Updated description")
    updated_use_case = await client.use_cases.update(use_case_id="123", data=update_data)

    # Health checks
    status = await client.system.ping()
    liveness = await client.health.check_liveness()
    readiness = await client.health.check_readiness()

# Run async code
asyncio.run(main())
```

## Configuration

### Environment Variables

The SDK supports configuration via environment variables. This is the recommended approach for production deployments:

| Variable          | Description                    | Default                |
| ----------------- | ------------------------------ | ---------------------- |
| `CREDOAI_API_KEY` | API key for authentication     | _(required)_           |
| `CREDOAI_API_URL` | Base URL of the API service    | `https://api.credo.ai` |
| `CREDOAI_TENANT`  | Your CredoAI tenant identifier | _(required)_           |

**Note:** The SDK automatically appends `/api/v1/integration` to the base URL. You only need to provide the base domain (e.g., `https://api.credo.ai`).

```bash
# Set environment variables
export CREDOAI_API_KEY="your-api-key"
export CREDOAI_API_URL="https://api.credo.ai"
export CREDOAI_TENANT="your-tenant"
```

```python
from credoai import CredoAI

# Client automatically uses environment variables
client = CredoAI()
```

Constructor arguments always take precedence over environment variables:

```python
# Explicit arguments override env vars
client = CredoAI(
    api_key="your-api-key",  # Overrides CREDOAI_API_KEY
    tenant="other-tenant"    # Overrides CREDOAI_TENANT
    # base_url uses CREDOAI_API_URL since not specified
)
```

### Authentication

The SDK uses API key authentication with automatic JWT token exchange:

```python
from credoai import CredoAI

# Using environment variables (recommended)
client = CredoAI()

# Or with explicit arguments
client = CredoAI(
    base_url="https://api.credo.ai",
    api_key="your-api-key",
    tenant="your-tenant"
)
```

#### Authentication Flow

- The client calls `/api/v1/integration/auth/token` at initialization to exchange your API key for a JWT token
- All API requests use `Authorization: Bearer <jwt-token>` header format internally

### Advanced Configuration

```python
import httpx
from credoai import CredoAI

# Full configuration with all options
client = CredoAI(
    base_url="https://api.credo.ai",  # Or set CREDOAI_API_URL
    api_key="your-api-key",           # Or set CREDOAI_API_KEY
    tenant="your-tenant",             # Or set CREDOAI_TENANT
    timeout=30.0,
    verify_ssl=True,
    headers={"Custom-Header": "value"},
    cookies={"session": "token"}
)

# Custom httpx configuration
client = CredoAI(
    api_key="your-api-key",  # Other params from env vars
    httpx_args={
        "proxies": "http://localhost:8080",
        "event_hooks": {
            "request": [lambda request: print(f"Request: {request.method} {request.url}")],
            "response": [lambda response: print(f"Response: {response.status_code}")]
        }
    }
)
```

## Context Managers

Both clients support context managers for automatic resource cleanup:

### Synchronous

```python
from credoai import CredoAI

with CredoAI(base_url="https://api.example.com", api_key="your-api-key") as client:
    use_case = client.use_cases.get(use_case_id="123")
    # Connection automatically closed
```

### Asynchronous

```python
from credoai import AsyncCredoAI

async def main():
    async with AsyncCredoAI(base_url="https://api.example.com", api_key="your-api-key") as client:
        use_case = await client.use_cases.get(use_case_id="123")
        # Connection automatically closed

asyncio.run(main())
```

## API Examples

### Use Cases

Create, list, read, update, and delete use cases.

#### Create a Use Case

```python
from credoai import CredoAI, UseCaseCreate

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Create with Pydantic model
data = UseCaseCreate(
    name="Risk Assessment Model",
    description="ML model for credit risk assessment"
)
use_case = client.use_cases.create(data=data)
print(f"Created use case with ID: {use_case.id}")
```

#### List Use Cases

```python
from credoai import CredoAI

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# List all use cases
use_cases = client.use_cases.lists()
for uc in use_cases:
    print(f"- {uc.name}: {uc.description}")
```

#### Get a Use Case

```python
from credoai import CredoAI

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Get by ID
use_case = client.use_cases.get(use_case_id="123")
print(f"Name: {use_case.name}")
print(f"Description: {use_case.description}")
```

#### Update a Use Case

```python
from credoai import CredoAI, UseCaseUpdate

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Update with Pydantic model
data = UseCaseUpdate(
    name="Updated Risk Model",
    description="Updated description for the model"
)
updated = client.use_cases.update(use_case_id="123", data=data)
print(f"Updated: {updated.name}")
```

#### Delete a Use Case

```python
from credoai import CredoAI

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Delete by ID
client.use_cases.delete(use_case_id="123")
print("Use case deleted")
```

### Models

Create, list, read, update, and delete models.

#### Create a Model

```python
from credoai import CredoAI, ModelCreate

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Create with Pydantic model
data = ModelCreate(
    name="GPT-4 Classification",
    description="LLM-based text classification model"
)
model = client.models.create(data=data)
print(f"Created model with ID: {model.id}")
```

#### List Models

```python
from credoai import CredoAI

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# List all models
models = client.models.lists()
for m in models:
    print(f"- {m.name}: {m.description}")
```

#### Get a Model

```python
from credoai import CredoAI

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Get by ID
model = client.models.get(model_id="456")
print(f"Name: {model.name}")
print(f"Description: {model.description}")
```

#### Update a Model

```python
from credoai import CredoAI, ModelUpdate

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Update with Pydantic model
data = ModelUpdate(
    name="GPT-4 Classification v2",
    description="Improved classification model"
)
updated = client.models.update(model_id="456", data=data)
print(f"Updated: {updated.name}")
```

#### Delete a Model

```python
from credoai import CredoAI

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Delete by ID
client.models.delete(model_id="456")
print("Model deleted")
```

### Vendors

Full CRUD operations for managing vendors.

#### Create a Vendor

```python
from credoai import CredoAI, VendorCreate

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Create with Pydantic model
data = VendorCreate(
    name="OpenAI",
    description="AI research and deployment company"
)
vendor = client.vendors.create(data=data)
print(f"Created vendor with ID: {vendor.id}")
```

#### List Vendors

```python
from credoai import CredoAI

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# List all vendors
vendors = client.vendors.lists()
for v in vendors:
    print(f"- {v.name}: {v.description}")
```

#### Get a Vendor

```python
from credoai import CredoAI

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Get by ID
vendor = client.vendors.get(vendor_id="789")
print(f"Name: {vendor.name}")
print(f"Description: {vendor.description}")
```

#### Update a Vendor

```python
from credoai import CredoAI, VendorUpdate

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Update with Pydantic model
data = VendorUpdate(
    name="OpenAI Inc.",
    description="Updated vendor description"
)
updated = client.vendors.update(vendor_id="789", data=data)
print(f"Updated: {updated.name}")
```

#### Delete a Vendor

```python
from credoai import CredoAI

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Delete by ID
client.vendors.delete(vendor_id="789")
print("Vendor deleted")
```

### System & Health

System status and health check endpoints.

#### Ping

```python
from credoai import CredoAI

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Check system status
status = client.system.ping()
print(f"System status: {status}")
```

#### Metrics

```python
from credoai import CredoAI

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Get system metrics
metrics = client.system.metrics_metrics()
print(f"Metrics: {metrics}")
```

#### Liveness Check

```python
from credoai import CredoAI

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Check if service is alive
liveness = client.health.check_liveness()
print(f"Liveness: {liveness}")
```

#### Readiness Check

```python
from credoai import CredoAI

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

# Check if service is ready to accept requests
readiness = client.health.check_readiness()
print(f"Readiness: {readiness}")
```

### Async Examples

All endpoints are available with async versions using `AsyncCredoAI`:

```python
import asyncio
from credoai import (
    AsyncCredoAI,
    UseCaseCreate, UseCaseUpdate,
    ModelCreate, ModelUpdate,
    VendorCreate, VendorUpdate,
)

async def main():
    client = AsyncCredoAI(base_url="https://api.example.com", api_key="your-api-key")

    # Use Cases
    use_case = await client.use_cases.create(
        data=UseCaseCreate(name="Async Use Case", description="Created async")
    )
    use_cases = await client.use_cases.lists()
    use_case = await client.use_cases.get(use_case_id=use_case.id)
    use_case = await client.use_cases.update(
        use_case_id=use_case.id,
        data=UseCaseUpdate(description="Updated async")
    )
    await client.use_cases.delete(use_case_id=use_case.id)

    # Models
    model = await client.models.create(
        data=ModelCreate(name="Async Model", description="Created async")
    )
    models = await client.models.lists()
    model = await client.models.get(model_id=model.id)
    model = await client.models.update(
        model_id=model.id,
        data=ModelUpdate(description="Updated async")
    )
    await client.models.delete(model_id=model.id)

    # Vendors
    vendor = await client.vendors.create(
        data=VendorCreate(name="Async Vendor", description="Created async")
    )
    vendors = await client.vendors.lists()
    vendor = await client.vendors.get(vendor_id=vendor.id)
    vendor = await client.vendors.update(
        vendor_id=vendor.id,
        data=VendorUpdate(description="Updated async")
    )
    await client.vendors.delete(vendor_id=vendor.id)

    # System & Health
    status = await client.system.ping()
    metrics = await client.system.metrics_metrics()
    liveness = await client.health.check_liveness()
    readiness = await client.health.check_readiness()

asyncio.run(main())
```

## API Reference

### Use Cases

| Method                                                                       | Description             |
| ---------------------------------------------------------------------------- | ----------------------- |
| `use_cases.create(data: UseCaseCreate) -> UseCaseResponse`                   | Create a new use case   |
| `use_cases.lists() -> List[UseCaseResponse]`                                 | List all use cases      |
| `use_cases.get(use_case_id: str) -> UseCaseResponse`                         | Get a specific use case |
| `use_cases.update(use_case_id: str, data: UseCaseUpdate) -> UseCaseResponse` | Update a use case       |
| `use_cases.delete(use_case_id: str)`                                         | Delete a use case       |

### Models

| Method                                                             | Description          |
| ------------------------------------------------------------------ | -------------------- |
| `models.create(data: ModelCreate) -> ModelResponse`                | Create a new model   |
| `models.lists() -> List[ModelResponse]`                            | List all models      |
| `models.get(model_id: str) -> ModelResponse`                       | Get a specific model |
| `models.update(model_id: str, data: ModelUpdate) -> ModelResponse` | Update a model       |
| `models.delete(model_id: str)`                                     | Delete a model       |

### Vendors

| Method                                                                 | Description           |
| ---------------------------------------------------------------------- | --------------------- |
| `vendors.create(data: VendorCreate) -> VendorResponse`                 | Create a new vendor   |
| `vendors.lists() -> List[VendorResponse]`                              | List all vendors      |
| `vendors.get(vendor_id: str) -> VendorResponse`                        | Get a specific vendor |
| `vendors.update(vendor_id: str, data: VendorUpdate) -> VendorResponse` | Update a vendor       |
| `vendors.delete(vendor_id: str)`                                       | Delete a vendor       |

### System

| Method                            | Description                  |
| --------------------------------- | ---------------------------- |
| `system.ping() -> PingResponse`   | Health check / ping endpoint |
| `system.metrics_metrics() -> Any` | Get system metrics           |

### Health

| Method                                       | Description                |
| -------------------------------------------- | -------------------------- |
| `health.check_liveness() -> HealthResponse`  | Kubernetes liveness probe  |
| `health.check_readiness() -> HealthResponse` | Kubernetes readiness probe |

### Client Configuration

Both `CredoAI` and `AsyncCredoAI` inherit from the base client classes and support these parameters:

| Parameter          | Type                            | Description                                               | Default                                             |
| ------------------ | ------------------------------- | --------------------------------------------------------- | --------------------------------------------------- |
| `base_url`         | `str \| None`                   | Base URL for the API (without `/api/v1/integration` path) | `CREDOAI_API_URL` env var or `https://api.credo.ai` |
| `api_key`          | `str \| None`                   | Your API key for authentication                           | `CREDOAI_API_KEY` env var _(required)_              |
| `tenant`           | `str \| None`                   | Your CredoAI tenant identifier                            | `CREDOAI_TENANT` env var _(required)_               |
| `timeout`          | `float \| httpx.Timeout`        | Request timeout configuration                             | `30.0`                                              |
| `verify_ssl`       | `bool \| str \| ssl.SSLContext` | SSL certificate verification                              | `True`                                              |
| `headers`          | `dict[str, str]`                | Additional headers for all requests                       | `{}`                                                |
| `cookies`          | `dict[str, str]`                | Cookies to include with all requests                      | `{}`                                                |
| `follow_redirects` | `bool`                          | Whether to follow HTTP redirects                          | `False`                                             |
| `httpx_args`       | `dict`                          | Additional arguments passed to httpx client               | `{}`                                                |

## Low-Level API Access

For advanced users who need direct access to the underlying HTTP client:

```python
from credoai import AuthenticatedClient
from credoai.models import UseCaseCreate
import httpx

# Using the lower-level authenticated client directly
client = AuthenticatedClient(
    base_url="https://api.example.com",
    token="your-api-key",
    auth_header_name="X-API-Key",
    prefix=""
)

# Manual HTTP request construction
use_case_data = UseCaseCreate(name="Test", description="A test use case")
json_data = use_case_data.model_dump()

with client as httpx_client:
    # Direct HTTP requests
    response = httpx_client.post("/api/v1/use_cases", json=json_data)
    print(f"Status: {response.status_code}, Data: {response.json()}")

    # Get request
    response = httpx_client.get("/api/v1/integration/ping")
    print(f"Ping: {response.json()}")
```

## Error Handling

```python
from credoai import CredoAI
from credoai.errors import ApiError
import httpx

client = CredoAI(base_url="https://api.example.com", api_key="your-api-key")

try:
    use_case = client.use_cases.get(use_case_id="invalid-id")
except ApiError as e:
    print(f"API error: {e.status_code} - {e.message}")
except httpx.HTTPStatusError as e:
    if e.response.status_code == 404:
        print("Use case not found")
    elif e.response.status_code == 422:
        print("Validation error")
        # Parse validation errors if needed
        if e.response.headers.get("content-type") == "application/json":
            error_data = e.response.json()
            print(f"Validation details: {error_data}")
    else:
        print(f"HTTP error: {e.response.status_code}")
except httpx.RequestError as e:
    print(f"Request failed: {e}")
```

## Development

This package is generated using the Credo AI SDK generator.

To regenerate the client:

1. Ensure the API server is running with updated OpenAPI spec
2. Run the generation script from the parent repository
3. The client will be updated with any API changes

## Contributing

1. Make changes to the API server and update OpenAPI specifications
2. Regenerate the client using the provided generation scripts
3. Test the generated client thoroughly
4. Submit pull requests to the main repository

## License

This project is licensed under the terms specified in the parent repository.
