Workflow example

# Step 1: Compress your context with ScaleDown
compressed_response = requests.post(
    "[https://api.scaledown.xyz/compress/raw/](https://api.scaledown.xyz/compress/raw/)",
    headers=headers,
    json={
        "context": "Long context about your topic...",
        "prompt": "What specific question you want answered",
        "model": "gpt-4o",
        "scaledown": {"rate": "auto"}
    }
)

compressed_context = compressed_response.json()["compressed_prompt"]

# Step 2: Use compressed context with your AI provider
your_actual_question = "What specific question you want answered"

final_prompt = f"""
System: You are a helpful assistant that answers questions using the provided context
Context: {compressed_context}
User: {your_actual_question}
"""

# Step 3: Send to your AI provider (OpenAI, etc.)
import openai
ai_response = openai.ChatCompletion.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": final_prompt}]
)

# Example: Compress context about Messi
payload = {
    "context": "Lionel Messi is an Argentine professional footballer who plays as a forward...",
    "prompt": "How many Ballon d'Or awards does Messi have?",
    "model": "gpt-4o",
    "scaledown": {
        "rate": "auto"
    }
}

# The response will contain compressed context that you can use
# to build your final prompt for the AI model