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chandantochandan/README.md

Chandan Kumar

AI Infrastructure Builder & Open Source Maintainer

I leverage AI to build high-complexity, local-first infrastructure tools. My focus is on solving the Context Window Bottleneck in developer workflows through semantic compression and distributed system design.


πŸš€ Architect of Vidurai

I am the creator and lead maintainer of Vidurai (v2.0.0), a local context middleware ecosystem.

I designed Vidurai to act as an abstraction layer between high-velocity developer telemetry (IDE, Terminal) and LLM context windows. It solves Information Entropy problems by treating developer context as a graph, not a log.

System Architecture Designed:

  • Distributed Topology: Orchestrated a Hub-and-Spoke architecture connecting VS Code, Chrome, and Python daemons via WebSockets.
  • Concurrency: Implemented non-blocking event ingestion using Python's asyncio and SQLite WAL mode.
  • Deterministic Logic: Designed the SF-V2 Algorithm to semantically compress code history, reducing token overhead by ~70%.

πŸ›  Tech Stack

I build with a focus on latency, local-first principles, and modularity.

  • Core: Python 3.9+ (FastAPI, AsyncIO), TypeScript
  • Data: SQLite (Advanced configurations), JSONL
  • Transport: WebSockets, HTTP/JSON-RPC, IPC
  • DevOps: Docker, GitHub Actions, PyPI Automation

πŸ“Œ Pinned Projects

Popular repositories Loading

  1. vidurai vidurai Public

    Local-first context infrastructure. Semantic compression (SF-V2) and temporal memory for developer workflows.

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  2. excel_spliter excel_spliter Public

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  3. vidurai-website vidurai-website Public

    Documentation and status portal for the Vidurai v2.0.0 context infrastructure stack.

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  4. vidurai-docs vidurai-docs Public

    Documentation for the Vidurai ecosystem β€” architecture, API, guides

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  5. chandantochandan chandantochandan Public

    AI Infrastructure Builder. Architecting local-first middleware for LLM workflows and distributed systems.

  6. vidurai-proxy vidurai-proxy Public

    HTTP middleware for injecting compressed SF-V2 context into OpenAI-compatible API calls.

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