🤖🧠 LangChain: The Ultimate Framework for Building Reliable AI Agents and LLM Applications
🗓️ 24 Oct 2025
📚 AI News & Trends
As artificial intelligence continues to transform industries, developers are racing to build smarter, more adaptive applications powered by Large Language Models (LLMs). Yet, one major challenge remains how to make these models interact intelligently with real-world data and external systems in a scalable, reliable way. Enter LangChain, an open-source framework designed to make LLM-powered application ...
#LangChain #AI #LLM #ArtificialIntelligence #OpenSource #AIAgents
🗓️ 24 Oct 2025
📚 AI News & Trends
As artificial intelligence continues to transform industries, developers are racing to build smarter, more adaptive applications powered by Large Language Models (LLMs). Yet, one major challenge remains how to make these models interact intelligently with real-world data and external systems in a scalable, reliable way. Enter LangChain, an open-source framework designed to make LLM-powered application ...
#LangChain #AI #LLM #ArtificialIntelligence #OpenSource #AIAgents
In Python, handling CSV files is straightforward using the built-in
#python #csv #pandas #datahandling #fileio #interviewtips
👉 @DataScience4
csv module for reading and writing tabular data, or pandas for advanced analysis—essential for data processing tasks like importing/exporting datasets in interviews.# Reading CSV with csv module (basic)
import csv
with open('data.csv', 'r') as file:
reader = csv.reader(file)
data = list(reader) # data = [['Name', 'Age'], ['Alice', '30'], ['Bob', '25']]
# Writing CSV with csv module
import csv
with open('output.csv', 'w', newline='') as file:
writer = csv.writer(file)
writer.writerow(['Name', 'Age']) # Header
writer.writerows([['Alice', 30], ['Bob', 25]]) # Data rows
# Advanced: Reading with pandas (handles headers, missing values)
import pandas as pd
df = pd.read_csv('data.csv') # df = DataFrame with columns 'Name', 'Age'
print(df.head()) # Output: First 5 rows preview
# Writing with pandas
df.to_csv('output.csv', index=False) # Saves without row indices
#python #csv #pandas #datahandling #fileio #interviewtips
👉 @DataScience4