# AI Studio SDK

## Krutrim Cloud SDK Guide (Python)

### 1. Overview

The Krutrim Python SDK (`krutrim-cloud`) provides a simple and consistent interface to interact with various AI and infrastructure services offered by Krutrim Cloud. It supports synchronous and asynchronous workflows, allowing developers to integrate image generation, text completion, and speech services into their applications with ease.

Supported Python Versions: **3.10 – 3.12**\
Package: <https://pypi.org/project/krutrim-cloud>

***

### 2. Installation

Install the SDK via pip:

```bash
pip install krutrim-cloud
```

#### System Dependencies

Some modules require `ffmpeg` and `ffprobe` to be available in your environment:

```bash
# macOS (with Homebrew)
brew install ffmpeg

# Ubuntu/Debian
sudo apt-get install ffmpeg
```

***

### 3. Authentication

You need an API key to authenticate your requests. This can be provided as an environment variable or passed directly into the client.

#### Environment Variable (Recommended)

```bash
export KRUTRIM_CLOUD_API_KEY="your_api_key_here"
```

#### Manual Key Injection

```python
from krutrim_cloud import KrutrimCloud
client = KrutrimCloud(api_key="your_api_key_here")
```

***

### 4. Client Initialization

#### Synchronous Client

```python
from krutrim_cloud import KrutrimCloud
client = KrutrimCloud()
```

#### Asynchronous Client

```python
from krutrim_cloud import KrutrimCloudAsync
client = KrutrimCloudAsync()
```

***

### 5. Core Functionalities

#### 5.1 Image Generation (Diffusion)

```python
response = client.images.generations.diffusion(
    model_name="diffusion1XL",
    image_height=1024,
    image_width=1024,
    prompt="a cyberpunk cityscape at night"
)

print(response.generated_images)
```

#### 5.2 Text Completion

```python
response = client.texts.completions.bhashini(
    prompt="Write a short story about a robot and a child.",
    language="en"
)
print(response.generated_text)
```

#### 5.3 Speech APIs (DIS / Bhashik Speech)

```python
response = client.speech.tts.bhashik(
    text="Namaste, Krutrim Cloud!",
    voice="hi_female_1"
)

with open("output.mp3", "wb") as f:
    f.write(response.audio)
```

***

### 6. Error Handling

API responses may raise exceptions for invalid input, network issues, or internal errors.

Basic handling:

```python
try:
    response = client.texts.completions.bhashini(prompt="Hello")
except Exception as e:
    print(f"Error: {str(e)}")
```

***

### 7. Using Async Workflows

```python
import asyncio
from krutrim_cloud import KrutrimCloudAsync

async def run():
    client = KrutrimCloudAsync()
    result = await client.images.generations.diffusion(
        model_name="diffusion1XL",
        image_height=512,
        image_width=512,
        prompt="a futuristic AI city"
    )
    print(result.generated_images)

asyncio.run(run())
```

***

### 8. Examples & Sample Projects

Explore example notebooks and scripts:

* [Basic Inference](https://github.com/ola-krutrim/krutrim-cloud-python/tree/main/examples)
* \[Fine-Tuning (Coming Soon)]
* \[CLI Wrapper (WIP)]

***

### 9. Versioning & Updates

To upgrade the SDK:

```bash
pip install --upgrade krutrim-cloud
```

Check the [GitHub repo](https://github.com/ola-krutrim/krutrim-cloud-python) for changelogs and release notes.

***

### 10. Support & Contribution

* For issues, submit a GitHub Issue [here](https://github.com/ola-krutrim/krutrim-cloud-python/issues)
* For API key access, contact the Krutrim team
* For feedback or enhancements, reach out via your internal Slack or community portal

***


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.cloud.olakrutrim.com/sdk-guide/ai-studio-sdk.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.