#langchain Development Tutorials & Tips | Roast Dev

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How to Build an AI Application with Quarkus and LangChain4j

In light of the LLM boom over the past year, we can conclude that virtually everyone has, for one reason or another, used a model from one of the major providers, such as Facebook, Google, Microsoft, ...

16.03.2025 0 Read More

In search of a BigQuery agent in LangChain, I built a Toolkit that acts as a BigQuery agent for Text-to-SQL.

Building an Intelligent BigQuery Chatbot with LLMs In today's data-driven world, extracting insights from data warehouses like BigQuery remains challenging for many business users without SQL...

23.03.2025 0 Read More

Building LLM-Powered Real Estate Intelligent Agents: Technical Implementation and Business Value

1. Introduction: The Need for Innovation in Real Estate Search In today's real estate market, traditional search methods have clear limitations. Users are typically forced to use rigid filter...

24.03.2025 0 Read More

Model Hallucination with React Agent

I have created a react agent using langgraph.prebuilt module that uses 3 tools generate_sql_query_tool execute_sql_query_tool analyze_query_results_tool The LLM appears to be generating fake or synth...

25.03.2025 0 Read More

Langgraph Visualization with get_graph

LangGraph is a library created to make it easier to create stateful, multi-agent applications that make use of Large Language Models (LLMs). By expressing complex agent operations as cyclic graphs, it...

25.03.2025 0 Read More

Building an E-Commerce Support Chatbot: Part 2 - Building the Knowledge Base

In this part, we’ll focus on setting up the database and preparing sample e-commerce order data that the chatbot will reference during conversations. ✅ What We'll Cover: Setting up MongoD...

26.03.2025 0 Read More

Context Without Complexity: LangChain’s In-Memory Superpower

Context, Lost and Found Picture this: you've just built a slick little chatbot. You greet it, it greets back. You ask a follow-up—and it acts like it’s never met you. You double-check you...

26.03.2025 0 Read More

🧭 Part 3: Implementing Vector Search with Pinecone

🧭 Part 3: Implementing Vector Search with Pinecone In this part, we’ll integrate Pinecone, a vector database that enables semantic search. This allows the chatbot to understand user quer...

27.03.2025 0 Read More

Building an E-Commerce Support Chatbot: Part 4 - Creating the LangChain Pipeline

🔗 Part 4: Creating the LangChain Pipeline In this part, we’ll build the LangChain-powered backend pipeline that connects your chatbot to MongoDB and Pinecone, handles data chunking, gene...

28.03.2025 0 Read More

Building an E-Commerce Support Chatbot Part 6: Building the React Frontend

Now that our backend and chatbot logic are ready, it's time to create a user-friendly chat interface using React. This part focuses on building a simple yet elegant frontend that interacts with the ba...

29.03.2025 0 Read More