In this video, we'll use the ‪@LangChain‬ CSV agent that allows you to interact with your data through natural language queries. Here's what we'll cover:
✅ Quick introduction to LangChain
✅ Setting up the environment and installing necessary libraries
✅ Loading and preprocessing multiple CSV files
✅ Implementing the LangChain CSV agent for intelligent data analysis
✅ Demonstrating querying and extracting data insights using agents
✅ What is a REPL?

TIMESTAMPS:
============
0:00 Intro
0:06 Project overview and LangChain CSV agent architecture
3:10 Setting up the environment and loading CSV files
8:51 Implementing the LangChain CSV agent
11:24 Querying CSV data to generate insights with Natural Language
16:24 What is a Python REPL?
21:36 Why vector databases are not great for structured data
23:18 Conclusion and next steps
23:54 Outro

LINKS:
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GitHub repo: https://github.com/tonykipkemboi/lang...
LangChain documentation: https://python.langchain.com/v0.2/doc...
Pandas documentation: https://pandas.pydata.org/docs/
Government datasets: https://data.gov/
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#ai #rag #csv #aiagents #langchain #gpt #llm #colab #googlecolab