runway-core-workflow-a

# Runway Core Workflow A ## Overview Advanced text-to-video generation: prompt engineering, model selection, parameter tuning, and batch generation. ## Prerequisites - Completed `runway-hello-world` ## Instructions ### Step 1: Model Selection ```python from runwayml import RunwayML client = RunwayML() # Available models: # gen3a_turbo — Fast, lower cost, good quality # gen4_turbo — Latest model, highest quality task = client.image_to_video.create( model='gen4_turbo', prompt_text='A futuristic cityscape at night with flying cars and neon signs, cyberpunk aesthetic', duration=10, ratio='16:9', ) result = task.wait_for_task_output() ``` ### Step 2: Prompt Engineering Tips ```python # Structure: Subject + Action + Setting + Style + Camera prompts = [ # Good: specific, visual, stylistic "A red fox walking through a snowy forest, soft winter light, documentary style, tracking shot", # Good: detailed motion and camera "Waves of golden wheat swaying in the wind, drone flyover, warm sunset, cinematic grain", # Bad: too abstract # "Something beautiful happening" — too vague ] ``` ### Step 3: Batch Generation ```python import asyncio prompts = [ "A butterfly emerging from a cocoon, macro lens, time-lapse, studio lighting", "Rain falling on a Tokyo street at night, reflections, neon, dolly zoom", "A chef preparing sushi in a traditional kitchen, close-up, warm lighting", ] tasks = [] for prompt in prompts: task = cl...