Mastering Gen AI ,RAG & LLM app development using Langchain

Explore Langchain adapters for offline API tasks, converting between dictionary and message formats to enable one-line chat completions and large-scale applications.

Build a graphical user interface to chat with your csv file using LangChain and OpenAI, with a Streamlit interface for uploading data and querying a pandas data frame agent.

Learn to chat with json files using a json agent and OpenAI, leveraging json toolkit and json spec to parse and answer questions about API documentation.

Learn to chat with a SQL server database using Langchain and OpenAI, leveraging a Sequel agent to generate and run SQL queries from natural language.

Learn how to integrate Google search with a LangChain agent using the Google search API and OpenAI for filtering, by building and running a search tool.

learn how to save OpenAI chat message history to AWS DynamoDB using LangChain, including configuring the database, creating a table, and persisting user and system messages.

Explore how to solve programming problems with a LangChain agent and the Python repl tool, generating reasoning and source code for LeetCode and Hackerrank questions.

Learn to build a file management agent with LangChain and OpenAI, using the file management toolkit to query and manage files, with setup, tool loading, and zero-shot React style execution.

Learn to log, trace, and monitor LangChain agent execution using Port Key, including setup, API keys, and reviewing logs in the Port Key dashboard.

Learn how to use a file callback handler with Langchain to log API usage, token costs, and results to a file, with a practical agent setup and Google search tools.

Learn how to enable the verbose flag in LangChain agents to format inputs and outputs for clearer debugging and understand how it differs from debug logs.

Learn to chat with an Excel file using LangChain by loading the data with the unstructured Excel loader, creating a vector store, and building a retrieval QA chain with OpenAI.

Learn to load multiple csv files with LangChain's document loader using multithreading, and compare directory loading times for 44 csv files with and without multithreading.

Learn to extract insights from documents using langchain document loaders, loading various file types with a directory loader, and accessing document content and source metadata to derive insights.

Learn how to load HTML files with Langchain document loaders, using unstructured and BeautifulSoup HTML loaders, and load multiple files from a directory for fast HTML content.

learn how to load PDF files in LangChain using the Pi PDF loader, load pages as documents with metadata, and optionally extract images.

Develop an end-to-end Streamlit app that loads YouTube videos via LangChain's YouTube loader, splits long transcripts, and summarizes them into bullet points using OpenAI.

Learn to build a multimodal rag workflow with LangChain and OpenAI vision to extract text and images from PDFs, then summarize images and prepare for multimodal question answering.

Learn to build a multimodal rag cooking assistant using LangChain and OpenAI Vision, combining text, images, and tables from PDFs with a vector store and Streamlit interface.