promptslab/Promptify
Promptify
Promptify is a suite of tools designed for model evaluation, prompt management, token cost tracking, structured extraction, and unified API gateway access. It provides a standardized interface to manage requests and responses across multiple large language model providers.
The project features a prompt management platform for engineering and versioning prompts with structured output validation. It includes a dedicated evaluation framework to measure model performance using precision, recall, and f1 scores against labeled datasets, alongside a token cost tracker to monitor the financial expenses of model requests.
The library covers broad capabilities for natural language processing, including named entity extraction, text classification, and question answering. It supports high-volume workflows through asynchronous batch processing and ensures data consistency by converting unstructured text into typed data structures via schema validation.
Features
- LLM Evaluation Frameworks - Provides a comprehensive framework for measuring model performance with precision, recall, and f1 scores.
- Performance Metrics - Calculates precision and recall by comparing model outputs against labeled gold-standard datasets.
- LLM Gateways - Acts as a centralized gateway that aggregates and standardizes multiple LLM providers into one API.
- LLM Provider Interfaces - Provides a standardized interface for communicating with multiple large language model providers.
- Prompt Optimizers - Offers tools for refining prompts with few-shot examples and domain context to improve model output accuracy and reliability.
- Model Performance Evaluators - Quantifies model accuracy and reliability by comparing task outputs against ground truth labels.
- LLM Performance Evaluators - Measures LLM performance using precision and recall metrics against labeled datasets.
- Prompt Engineering Workflows - Provides a workflow for testing, versioning, and refining prompts to improve model accuracy.
- Prompt Management Systems - Ships a centralized platform for engineering, versioning, and deploying prompts with output validation.
- Structured Data Extraction - Extracts structured formats from model outputs using schema validation and LLMs.
- Structured Data Generation - Provides capabilities to convert unstructured text into typed data structures and machine-readable formats like JSON using schema validation.
- Schema Validators - Validates unstructured model responses against predefined structural schemas to ensure data consistency.
- LLM-to-Structured Data Converters - Converts unstructured text into typed data structures and schemas using language models.
- LLM Token Cost Tracking - Tracks token usage and monitors financial expenditures based on provider-specific pricing models.
- Unified Model Interfaces - Offers a unified abstraction layer to standardize requests and responses across different LLM providers.
- Entity and Relation Extraction - Identifies and labels specific spans of text as entities based on the provided domain.
- LLM Batch Processing - Enables concurrent execution of high-volume language model tasks to reduce total processing time.
- Text Classification - Includes functions to categorize text and assign predefined labels to determine sentiment or content categories.
- Question Answering - Implements processes for retrieving specific answers to questions by analyzing provided documents or bodies of text.
- Few-Shot Pattern Exemplification - Supports few-shot prompt engineering by injecting domain-specific examples to improve model accuracy.
- Batch Data Processing - Supports high-volume workflows through asynchronous batch processing of multiple inputs to increase total throughput.
- Batch Request Processing - Implements high-throughput asynchronous batch processing for large volumes of model requests.
- Application Development - Library for performing NLP tasks using language models.
- Prompt Engineering - Library simplifying NLP tasks using LLM-based prompt engineering.
- Prompt Engineering Tools - Tool for prompt engineering and structured output.
- Prompt Optimization Frameworks - Generates task-specific prompts for various generative models.
Star history
How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
