GPT-4 Powered App Creation and Evals Hackathon

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TruEra Opening Words

Hackathon Guide and Lablab Platform Walk-through

OpenAI Workshop

Workshop - Retrieval Augmented Generation with Pinecone

Workshop - Advanced Evaluation Methods with TruLens

General Q&A session on Discord

Workshop - Make your app reliable, cost-efficient, and fast with Portkey

Submissions Deadline

yoso

Marco Vinciguerra

Lorenzo Padoan

Marco Perini

What is Scrapegraph-ai?

Scrapegraph-ai is a tool built to simplify and streamline web scraping by leveraging the power of large language models (LLMs).
Key Features:

Natural Language Interaction: Instead of complex scraping code, you describe the data you need in everyday language (e.g., "Get me the product titles and prices from this online store").
AI-Powered Extraction: The library uses LLMs to understand your instructions and intelligently figure out how to gather the requested information from websites.
OpenAI Integration Leverages OpenAI's language models for understanding your natural language prompts.
Langchain Support: Likely utilizes Langchain, a framework that facilitates connections between LLMs and various tools.
Benefits:

Faster Development: Potentially speeds up web scraping tasks by removing the need to grapple with the intricacies of HTML and CSS selectors.
Easier for Beginners: Makes web scraping more accessible for those without deep knowledge of traditional web scraping libraries.
Things to Note:

Accuracy: LLMs, while powerful, aren't perfect. Results might require error handling and refinement in some cases.
Costs: Integrating a service like OpenAI involves API usage costs.
Resilience to Website Changes: This type of AI-powered scraper may need more frequent adjustments if the structure of target websites changes.

A new paradigm has begun text-to-data, this is possible thanks to ScrapegraphAI a tool built to simplify and streamline web scraping by leveraging the power of large language models (LLMs).



ScrapeGraphAI

"yoso team on GPT-4 Powered App Creation and Evals Hackathon Hackathon"

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Submission