Abhishek
@abhishekasthana-251Python AI Backend Developer | LLMs, RAG, LangChain, LangGraph, LangSmith, FastAPI, Django, MySQL | Developing production-ready AI and backend systems.
Language Breakdown
Lines of code distribution across 11 owned repositories
T-Shaped Developer
T-shapedDeep in Jupyter Notebook with broad versatility
Collaboration Network
Global Impact visualization
Repos
11
PRs
0
Growth
+18%
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Coding Streak
Contribution activity over the past year
Matteo Veroni
@mavek87
Chris
@ccamel
Diego
@Dieg0Code
Keith skaggs
@ksksrbiz-arch
SparkDev
@Spark0914724
Top Repositories
Production-style AI-first CRM platform for pharmaceutical sales representatives featuring LangGraph multi-tool agents, conversational interaction logging, AI-powered insights, FastAPI, React, Redux Toolkit, SQLAlchemy, and Groq LLM integration.
Learning Agentic AI workflows using LangGraph — Sequential, Conditional, Parallel, Iterative workflows, StateGraph architecture, Agents, Memory, Tool Calling, and Multi-Agent Systems.
Developed an intelligent document assistant using LangChain, FastAPI, and vector databases to provide semantic search and AI-generated answers from PDFs and text documents.
YouTube video Q&A system using RAG: extracts transcripts, builds embeddings, and answers user queries with LLMs.
LangChain learning journey from basics to RAG — Models, Prompts, Chains, Runnables, Document Loaders, Text Splitters, Vector Stores (Chroma + Pinecone), and Retrievers
Built and tested multiple REST API endpoints to understand real-world backend workflows. Covers CRUD operations, request validation, error handling, and structured API design using [your tech stack]. This repository reflects practical learning through implementation rather than theory.
OOPs Understanding
A program to check live running status and schedule information of Indian trains using IRCTC API
DSA
Open Source Impact
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