Intent-based Prompt Calibration (IPC)

A system for automatic prompt optimization using Claude 3.5 models. IPC enables dynamic prompt refinement through iterative testing and improvement cycles, particularly useful for complex tasks like content moderation.

Features

• Automatic prompt optimization through systematic testing
• Synthetic test case generation for edge cases
• Comprehensive error analysis and tracking
• Multi-model architecture using Claude 3.5 models
• Simple configuration and usage

Intent-based Prompt Calibration: Enhancing prompt optimization with synthetic boundary cases: https://arxiv.org/abs/2402.03099

Quick Start

from ipc_system import AdvancedIPCConfig, EnhancedIPCSystem
import anthropic

# Initialize client
client = anthropic.Anthropic(api_key="your-api-key")

# Configure system
config = AdvancedIPCConfig(
    task_description="Your task description",
    labels=["label1", "label2"],
    initial_prompt="Your initial prompt"
)

# Run IPC
ipc = EnhancedIPCSystem(client, config)
best_prompt, history = ipc.calibrate()