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Python SDK 🐍

Installation 📦​

pip install flymyai

Quick Start 🚀​

from flymyai import client, FlyMyAIPredictException

# Set your API key
apikey = "fly-***" 

# Initialize the client
fma_client = client(apikey=apikey)

# Set the model name
model = "flymyai/hidream-i1-dev"

# Prepare the input data
payload = {
    "prompt": "A beautiful sunset over mountains, digital art",
    "negative_prompt": "blurry, low quality",
    "width": 512,
    "height": 512,
    "num_inference_steps": 30,
    "guidance_scale": 7.5,
    "seed": 42
}

try:
    # Make the prediction
    response = fma_client.predict(
        model=model,
        payload=payload
    )
    
    # Process the output data
    print(f"Generated image URL: {response.output_data['image_url']}")
except FlyMyAIPredictException as e:
    print(f"Error: {e}")

Advanced Examples 🎯​

Image Generation with HiDream​

from flymyai import client, FlyMyAIPredictException

apikey = "fly-***"
model = "flymyai/hidream-i1-dev"

payload = {
    "prompt": "A futuristic cityscape with flying cars, neon lights, cyberpunk style",
    "negative_prompt": "blurry, low quality, distorted",
    "width": 768,
    "height": 512,
    "num_inference_steps": 50,
    "guidance_scale": 8.5,
    "seed": 12345
}

fma_client = client(apikey=apikey)
try:
    response = fma_client.predict(model=model, payload=payload)
    print(f"Generated image URL: {response.output_data['image_url']}")
except FlyMyAIPredictException as e:
    print(f"Error: {e}")

Video Generation with wan2-img-to-video-lora​

from flymyai import client, FlyMyAIPredictException

apikey = "fly-***"
model = "flymyai/wan2-img-to-video-lora"

payload = {
    "prompt": "A cinematic shot of a spaceship flying through a nebula",
    "negative_prompt": "blurry, low quality, distorted",
    "width": 512,
    "height": 512,
    "num_frames": 24,
    "num_inference_steps": 50,
    "guidance_scale": 7.5,
    "input_image": "https://example.com/input.jpg",
    "lora_url": "https://example.com/model.safetensors",
    "fps": 8,
    "acceleration_factor": 1
}

fma_client = client(apikey=apikey)
try:
    response = fma_client.predict(model=model, payload=payload)
    print(f"Generated video URL: {response.output_data['video_url']}")
except FlyMyAIPredictException as e:
    print(f"Error: {e}")

LoRA Training with flux-lora-trainer​

from flymyai import client, FlyMyAIPredictException

apikey = "fly-***"
model = "flymyai/flux-lora-trainer"

payload = {
    "lora_name": "Hello World",
    "trigger_word": "Hello World",
    "dataset_url": "https://example.com/dataset.zip",
    "training_steps": 1000,
    "huggingface_model_name": "black-forest-labs/FLUX.1-dev"
}

fma_client = client(apikey=apikey)
try:
    response = fma_client.predict(model=model, payload=payload)
    print(f"Trained model: {response.output_data['model']}")
    print(f"Config: {response.output_data['config']}")
except FlyMyAIPredictException as e:
    print(f"Error: {e}")

Using Flux Models​

from flymyai import client, FlyMyAIPredictException

apikey = "fly-***"
model = "flymyai/flux-dev"

payload = {
    "prompt": "A magical forest with glowing mushrooms and fairies",
    "height": 512,
    "width": 512,
    "num_inference_steps": 30,
    "guidance_scale": 7.5,
    "seed": 42
}

fma_client = client(apikey=apikey)
try:
    response = fma_client.predict(model=model, payload=payload)
    print(f"Generated image URL: {response.output_data['image_url']}")
except FlyMyAIPredictException as e:
    print(f"Error: {e}")

Error Handling 🛡️​

The SDK provides detailed error handling through the FlyMyAIPredictException class:

try:
    response = fma_client.predict(model=model, payload=payload)
except FlyMyAIPredictException as e:
    print(f"Error code: {e.code}")
    print(f"Error message: {e.message}")
    print(f"Error details: {e.details}")

Best Practices 💡​

  1. Always use try-except blocks to handle potential errors
  2. Set appropriate timeouts for long-running operations
  3. Validate input parameters before making API calls
  4. Use environment variables for API keys
  5. Implement proper error logging

Additional Resources 📚​