Docugami, in collaboration with LangChain and Rechat, explored the challenges and solutions for deploying large language models (LLMs) in production during a recent webinar. Docugami has been working with language models to transform documents into data, initially using smaller models for tasks like text completion and OCR correction, and later expanding to more complex models for question answering and Retrieval Augmented Generation (RAG) with their Document XML Knowledge Graph. They emphasized the importance of understanding documents as more than just flat text, highlighting their structural and semantic complexities. The webinar also covered the use of LangChain’s expressive API for building complex chains and LangSmith for debugging and monitoring LLM operations, showcasing how these tools help manage real-world challenges in LLM deployments. The session concluded with an overview of Docugami's end-to-end LLM operations, utilizing LangChain and LangSmith to improve model deployment and monitoring processes.