#Question Answering

Explore the workings of advanced RAG pipelines using LLMs for effective question-answering. Learn how frameworks such as LlamaIndex and Haystack enable transparency while streamlining operations. Address components like the Sub-question Query Engine and evaluate challenges in question sensitivity and cost. Gain insights into developing RAG pipelines that provide current information and reliable source tracking.

This project features a chatbot implementation primarily for question answering within LangChain documentation, utilizing LangChain.js and Next.js frameworks. It incorporates advanced tools for document processing and query handling, including RecursiveUrlLoader, SitemapLoader, and Weaviate vectorstore, complemented by GPT-3.5 for generating relevant responses. The project is easily deployable locally with adaptable front-end and back-end configurations and is supported by detailed documentation that facilitates modification and deployment.

WebGLM is a groundbreaking question-answering system that incorporates web search and retrieval functions powered by a 10-billion-parameter General Language Model. It features LLM-augmented retrieval for precise web content accuracy, a generator for coherent responses, and quality estimation aligned with human preferences, ensuring cost-effective and high-performing solutions for real-world deployments.

The course provides a comprehensive guide for developers interested in utilizing the LangChain framework to enhance language model applications. Topics covered include interacting with LLMs, crafting prompts, utilizing memory capabilities, and constructing operational chains to improve reasoning and data processing. Hosted by LangChain creator Harrison Chase and Andrew Ng, the course facilitates rapid development of dynamic applications, optimizing proprietary data use within just an hour.

PrimeQA is an open-source repository designed for the training and testing of advanced question answering models. It helps researchers replicate cutting-edge experiments from recent NLP conferences and supports diverse functionalities such as Information Retrieval using models like BM25 and ColBERT, Multilingual Machine Reading Comprehension, and multilingual Question Generation. Utilizing the Transformers toolkit allows for easy access to pre-trained models. PrimeQA also includes retrieval-augmented generation with GPT models and excels in multiple leaderboard challenges, making it a top resource for exploring multilingual functionality and domain adaptation.