Streamlit LLM Hackathon Kickoff (and projects we’d love to see) Streamlit’s LLM Hackathon kicks off today and we’re thrilled to be partnering with them to bring it to life. We’ve been building
Announcing LangChain Hub Today, we're excited to launch LangChain Hub–a home for uploading, browsing, pulling, and managing your prompts. (Soon, we'll be adding
Incorporating domain specific knowledge in SQL-LLM solutions Editor's Note: This post was written in collaboration with Manuel and Francisco from the Pampa Labs team. We're always excited to
TitanTakeoff x LangChain: Supercharged Local Inference for LLMs Editor's Note: This post was written in collaboration with the TitanML team. The integration between their NLP development platform + LangChain makes inference LLMs
Boost Your Bottom Line and Performance: OpenAI’s 3.5T Fine-Tuning with LangSmith Editor's Note: This post was written in collaboration with Author Ryan Brandt from the ChatOpenSource.com team. It's a detailed look
Xata x LangChain: new vector store and memory store integrations Editor's Note: This post was written in collaboration with the Xata team. We're excited about their new integrations and really enjoyed
Chat Loaders: Fine-tune a ChatModel in your Voice Summary We are adding a new integration type, ChatLoaders, to make it easier to fine-tune models on your own unique writing style. These utilities help
Summarizing and Querying Data from Excel Spreadsheets Using eparse and a Large Language Model Editor's Note: This post was written by Chris Pappalardo, a Senior Director at Alvarez & Marsal, a leading global professional services firm. The
Evaluating RAG pipelines with Ragas + LangSmith Editor's Note: This post was written in collaboration with the Ragas team. One of the things we think and talk about a lot
Cube x LangChain: Building AI experiences with LLMs and the semantic layer Editor's Note: This post was written in collaboration with the Cube team. The semantic layer plays a key role in ensuring correctness and
Epsilla x LangChain: Retrieval Augmented Generation (RAG) in LLM-Powered Question-Answering Pipelines Editor's Note: This post was written in collaboration with the Epsilla team. As more apps rely on Retrieval Augmented Generation (RAG) for building
Tavrn x LangChain: Integrating Noah: ChatGPT with Google Drive and Notion data Editor's Note: This post was written in collaboration with the Tavrn team. They were able to build a new personal assistant app, Noah,
