Automodels detects the intent of your prompts and maps them to the best model for the given task, based on your preferences for cost and quality.

Use our tools to restructure your prompts auto-magically to improve performance and quality of your LLM calls, tailored to the model you're using.

Our library of tools is easy to integrate into your existing workflows. Call our API directly, or start with our npm or pip packages:

from llm_automodels import AutoModels

client = AutoModels("your-api-key")
prompt = "Explain the key aspects of special relativity."

response = client.get_best_model(
    prompt,
    profile="cost"
)

print("Identified task type: ", response.task_type)
print("Best model: ", response.best_model)

reponse = client.optimize_prompt(
    prompt,
    model=reponse.best_model
)

print("Optimized prompt: ", response.optimized_prompt)

Our API can compress your prompts using advanced semantic analysis, reducing token usage by up to 70% while maintaining context and quality.

Get detailed insights into your token usage, compression rates, and optimization opportunities with our comprehensive analytics dashboard or via API.