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Sathvik-1007/README.md

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"When you have eliminated the impossible, whatever remains, however improbable, must be the truth."
— Sir Arthur Conan Doyle

> whoami

class SathvikGilakamsetty:

    education  = "B.Tech CSE, NIT Andhra Pradesh '25"
    location   = "India"
    focus      = "Agentic AI Systems & Advanced RAG Pipelines"

    languages  = ["Python", "TypeScript", "Rust", "C++"]
    frameworks = ["FastAPI", "LangChain", "PyTorch", "HuggingFace"]
    databases  = ["PostgreSQL", "Qdrant", "SQLite", "Redis"]
    platforms  = ["Azure", "OVH Cloud", "AWS", "Docker"]

    approach   = "Observe. Hypothesize. Build. Verify. Ship."

> investigations

Jantar

Sovereign AI for 137K Indian government APIs. 5-stage hybrid RAG: BGE-M3 dense+sparse on CUDA, cross-encoder reranking, plan-and-execute agent orchestration, 22 languages.

Python FastAPI Qdrant CUDA

GraphMem-MCP

Persistent memory layer for AI agents. Published on PyPI, 28 MCP tools, sqlite-vec + FTS5, ONNX embeddings, hybrid RRF search, multi-hop graph traversal.

Python SQLite ONNX MCP

CRPB

Idea-to-repository code generation. Multi-phase LLM pipeline, DAG task planning, deterministic synthesis, holistic validation with repair convergence.

Python Pydantic LLM Typer


> toolkit

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> evidence

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The game is always afoot.

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  1. jantar jantar Public

    Agentic Layer for Indian Government Services — Advanced RAG indexing 137,362 APIs with BGE-M3 + cross-encoder reranking + multi-step planning + 22 Indian languages

    Python 1

  2. GraphMem-MCP GraphMem-MCP Public

    Production-grade Graph-RAG MCP server with local embeddings — persistent knowledge graphs for any LLM-powered CLI agent

    Python 1

  3. CRPB CRPB Public

    Python