AI Integration, Simplified
Supercharge your App with AI superpowers
No training datasets. No finetuning.
Prompt Generation
AI-assisted prompt creation with input/output pair examples
Prompt Testing
Real-time testing interface with version history
API Deployment
Instant API creation with multiple deployment options
How It Works
Provide Examples
Input your desired input-output pairs
Generate & Refine
AI creates and optimizes your prompt
Test Your Model
Validate results in real-time
Deploy API
Instantly create an API endpoint
Integrate & Use
Seamlessly add to your application
Backprompt Use Case Examples
from backprompt import BackpromptClient
# Initialize the client
client = BackpromptClient(
api_key='your_api_key_here',
api_url='your_api_url_here'
)
input_text = "The new feature is interesting, but it's a bit confusing to use."
desired_output = """
{
"sentiment": "mixed",
"positive": "interesting new feature",
"negative": "confusing to use",
"suggestion": "improve user interface"
}
"""
optimal_prompt = client.solve_prompt(input_text, desired_output)
print(optimal_prompt)from backprompt import BackpromptClient
# Initialize the client
client = BackpromptClient(
api_key='your_api_key_here',
api_url='your_api_url_here'
)
input_text = """
John Doe, a 35-year-old software engineer from New York, has been working at Tech Solutions Inc. for the past 7 years.
He specializes in machine learning and has recently completed a project on natural language processing.
"""
desired_output = """
{
"name": "John Doe",
"age": 35,
"profession": "Software Engineer",
"location": "New York",
"company": "Tech Solutions Inc.",
"years_of_experience": 7,
"specialization": "Machine Learning",
"recent_project": "Natural Language Processing"
}
"""
optimal_prompt = client.solve_prompt(input_text, desired_output)
print(optimal_prompt)Elevate Your LLM Game
Transform input-output pairs into optimized prompts. Achieve precision AI outputs today.