Superpipe

Superpipe is a lightweight framework that allows users to build, evaluate, and optimize LLM (Language Model) pipelines for structured data. With Superpipe, you can easily label, extract, classify, and tag data while optimizing models and parameters for accuracy, cost-efficiency, and speed. It offers flexibility by allowing users to evaluate their pipelines on unique datasets and experiment with different models and prompts.

Key Features:

1️⃣ Build: Convert any multistep LLM workflow into a Superpipe pipeline using building blocks from popular libraries like langchain or LlamaIndex.

2️⃣ Evaluate: Measure the performance of your pipeline by defining an evaluation function that compares outputs against ground truth labels.

3️⃣ Optimize: Experiment with various combinations of models (e.g., GPT-4 vs. Mixtral), retrieval chunks (e.g., 3, 5, 7), prompting methods (e.g., chain of thought vs. direct prompting), and more to find the optimal configuration for your pipeline.

Use Cases:

1️⃣ Document Extraction: Extract entities and facts from PDFs, emails, websites to automate information extraction tasks.

2️⃣ Product Catalog Tagging: Enhance product catalogs with AI-generated tags for improved search functionality and personalized recommendations.

3️⃣ Query Analysis: Extract filter arguments from natural language search queries to enhance search accuracy.

Conclusion:

Superpipe empowers users in data labeling, extraction, classification,and tagging tasks where structured output is required. By providing an intuitive framework for building pipelines tailored to specific needs,it streamlines workflows while offering optimization capabilities.Users can leverage Superpipe's features across various domains such as document extraction,catalog tagging,and query analysis.The ability to experiment with different configurations ensures efficiency without compromising accuracy.Experience the power of Superpipe today!