โ Days of Learning โ Day 41
๐ค Configured chat models with LangGraph agents
๐ ๏ธ Added tool calling support
๐งช Built a working example
๐ Also brushed up on HTTP & domain names
Blending AI with backend logic!
#AI#LangGraph#LLM#GenAI#BackendDev#HTTP#LearningJourney
โ Days of Learning โ Day 40 ๐ฏ
๐ Deep dive into LangGraph docs:
Pre-built agents
Execution flow
Streaming agents in action
Big milestone, still hungry to learn more!
#AI#LangGraph#LLM#Day40#GenAI#LangChain#LearningJourney
โ Days of Learning โ Day 39
๐ Revised HITL in LangGraph
๐ง Explored customized states
๐ Tried different streaming modes
Repetition = clarity. One step closer to mastery!
#AI#LangGraph#LLM#GenAI#LangChain#LearningJourney
โ Days of Learning โ Day 38
Explored Human-in-the-Loop (HITL) in LangGraph
โข Used interrupt() for human input
โข Studied Command and Interrupt docs
โข Built a working demo!
Making LLMs smarter with humans in the flow
#AI#LangGraph#LLM#HITL#Interrupt#GenAI#LearningJourney
โ Days of Learning โ Day 36
๐ง Explored tools in LangGraph
โ๏ธ Worked with ToolNode
๐ ๏ธ Implemented tools with LLM agents
Love how tools extend LLM capabilities in structured workflows.
#AI#LangGraph#LangChain#LLM#GenAI#ToolNode#LearningInPublic
โ Days of Learning โ Day 35
๐ ๏ธ Built a basic LangGraph chatbot
๐ Learned about TypedDict
๐ Explored StateGraph, START, and add_message()
Loving how modular LangGraph is for structured LLM workflows!
#AI#LangGraph#LangChain#Python#Chatbot#GenAI#LLM
โ Days of Learning โ Day 34
Back after a short break! ๐
โข Explored core of LangGraph
โข Understood Agent State
โข create-react-agent method
โข Compared invoke, ainvoke, stream, astream
LangGraph is ๐ฅ for structured LLM flows.
#AI#LangChain#LangGraph#LLM#GenAI
โ Days of Learning โ Day 33
Tried implementing LLM streaming with logs (thoughts/actions).
Didnโt get it right (yet), but learned a ton through the process.
Debugging is where the real growth happens!
#AI#LangChain#LLM#FastAPI#GenAI#LearningInPublic
โ Days of Learning โ Day 32
๐ง Explored:
โข Why use pre-trained models
โข Key things to consider & their limitations
โข Streaming LLM responses with FastAPI ๐
Efficiency meets practicality in real-world GenAI apps.
#AI#LLM#ML#FastAPI#PreTrainedModels#GenAI
โ Days of Learning โ Day 31
๐ง GenAI foundations today:
โข LLMs
โข Training vs Inference
โข Embeddings & Vector DBs
โข AI Agents
โข RAG (Retrieval-Augmented Generation)
Understanding the backbone of modern AI systems.
#AI#GenAI#LLM#ML#RAG#Embeddings#AIagents
โ Days of Learning โ Day 30
๐ง Understood LangGraph's full flow
๐ Wrapped MCP Server using FastAPI as an MCP Client
Connecting everything is ๐
#AI#ML#LangGraph#MC
โ Days of Learning โ Day 29
๐ง Built an MCP Server
๐ง Explored tools, prompts & resources
๐ต๏ธโโ๏ธ Debugged flows using MCP Debugger
Building real AI workflows is ๐ฅ
#AI#ML#LangChain#LangGraph#MCP#LLM#LearningJourney
โ Days of Learning โ Day 28
Today was all about data distribution! ๐
โข Skewness & Kurtosis
โข Quartiles & Percentiles
โข Five Number Summary
Data tells a story โ stats help you hear it.
#AI#ML#DataScience#Statistics#LearningJourney
โ Days of Learning โ Day 27
Started with Statistics today!
โข Why do we need it in ML?
โข Mean, Median, Mode
โข Standard Deviation & Variance ๐
Numbers with meaning โ not just math.
#AI#ML#Statistics#DataScience#LearningJourney
โ Days of Learning โ Day 26
MCP Server = a rulebook to inject external context into an LLM.
๐ง Spent time understanding it deeply.
๐ผ๏ธ Shared a small diagram to explain how it works!
LLMs get smarter when context is clean.
#AI#LLM#MCP#LangGraph#LearningJourney
โ Days of Learning โ Day 24
โข Built a simple MCP server in a full stack setup
โข Understood MCP server โ๏ธ client interaction
โข Learned LangGraph routing logic
LLM apps are all about clean orchestration!
#AI#LangGraph#MCP#LLM#LearningJourney
๏ฟฝ๏ฟฝ Days of Learning โ Day 23
Split day:
โข Understood MCP architecture
โข Explored StateGraph, start, end in LangGraph
โข Geometric view of eigenvalues & eigenvectors
Design + math = power!
#AI #LangGraph #LLM #LinearAlgebra #LearningJourney
โ Days of Learning โ Day 22
LangGraph exploration continues:
โข Intro to Chains
โข start node & graph state
โข Built a simple graph to test the flow
Structured LLM apps just make sense!
#AI#LangGraph#LangChain#LLM#LearningJourney