Build an MCP Server for Your LLM Agent
MCP standardizes how LLM agents reach your tools and data. A hands-on guide to building an MCP server in Python, picking a transport, and where it breaks.
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Cancelling an LLM Stream in React with AbortController
A user hits stop or switches chats and the old LLM stream keeps writing tokens and running up cost. How to cancel a streaming fetch in React the right way.
Getting Reliable JSON Out of an LLM
Getting an LLM to return JSON is easy; getting valid JSON every time is not. How to use JSON Schema, constrained decoding, and validation to make it reliable.
Streaming LLM Markdown in React Without Flicker
LLM tokens arrive one at a time, and re-parsing Markdown on every token flickers and drags. How to render streaming Markdown in React without the jank.
LLM KV Cache: Why GPU Memory Runs Out
A long prompt or a long agent run can hit CUDA out of memory, and the KV cache is usually why. How it grows, the per-token math, and how to shrink it.
Handling LLM API Rate Limits: Retries and Backoff
Your LLM backend returns 429s the moment traffic bursts. How to retry with backoff and jitter, respect Retry-After, and pace fan-out to stay under the limit.
How HNSW Vector Search Actually Works
Every RAG stack leans on HNSW but treats it as a black box. Here is how the layered graph index finds nearest neighbors fast, and the knobs that matter.
Cross-Encoder Reranking for RAG Pipelines
Retrieval puts the right chunk at rank 8, but the generator only reads the top few. How a cross-encoder reranker reorders RAG candidates, and where it fails.
Chunking Strategies for RAG Pipelines
How to chunk documents for a RAG pipeline: why fixed-size splitting fails, structure-aware splitting, size and overlap tradeoffs, and the failure modes.
Running LLM-Generated Code in a Sandbox
An LLM that writes and runs code needs real isolation, not a try/except. How to sandbox AI-generated code with E2B microVMs, and the failure modes.
Measuring RAG Retrieval Quality: recall@k, MRR
Changed your embeddings or added a reranker? Measure it. Build a golden set and score retrieval with recall@k, MRR, and nDCG before you trust the change.
Hybrid Search for RAG: BM25 + Vectors
Vector search alone misses exact IDs and error codes. Here's how to combine BM25 keyword search with dense retrieval, fuse the rankings with RRF, and rerank.
How an LLM Agent Tool-Calling Loop Works
A practical look at the agent loop behind LLM tools: how the model asks to call a tool, your code runs it, and the result feeds back until the answer is done.
Streaming LLM Responses from FastAPI with SSE
Stream LLM output token by token from a FastAPI backend with Server-Sent Events: working code, the EventSource client, proxy buffering, and failure modes.
Incremental Indexing for RAG Pipelines
How to keep a RAG index fresh without full rebuilds: detect changed files with checksums, re-embed only what changed, and handle deletions safely.
CloudCanvasAI
AI-powered document creation platform pairing Claude with a live .docx / .pptx / .pdf / .xlsx preview. Chat on the left, documents render live on the right, each user gets their own isolated E2B sandbox.
Argusa AI Challenge 2025 · Runner-Up 🥈
Secured 2nd place at the Argusa AI Challenge 2025 by building ARGRAG, a RAG system for complex enterprise document corpora with multi-modal analysis, metadata intelligence, and real-time performance.
LLM DevMate
A VSCode extension that streamlines pasting code context into LLMs. One-click copy, token-aware, works with OpenAI and other providers.
Gemini Alchemy
A Gemini-powered tool that turns abstract ideas and complex concepts into visually appealing mindmaps. FastAPI backend, Streamlit frontend.
What’s Cooking? Predicting Cuisines from Recipe Ingredients
Semester Project - Information Retrieval and Artificial Intelligence - CS317 & CS401 - FAST NUCES (Karachi)