Block or report Santhosh-p653
Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.
You must be logged in to block users.
Contact GitHub support about this user’s behavior. Learn more about reporting abuse.
Report abuse╔══════════════════════════════════════════════════════════════════╗ ║ SANTHOSH · AI/ML Engineering Runtime · ACTIVE ║ ╚══════════════════════════════════════════════════════════════════╝
$ whoami┌─────────────────────────────────────────────────────────────────────┐ │ IDENTITY BLOCK │ │ ───────────────────────────────────────────────────────────────── │ │ Role : AI / ML Engineer (2nd Year CSE — Karpagam Institute) │ │ Focus : Agentic systems · RAG pipelines · Production MLOps │ │ Output : Deployed systems — not prototypes │ │ Mantra : "Make it work. Make it right. Make it fast." │ └─────────────────────────────────────────────────────────────────────┘
A self-operating system for turning ambiguous problems into deployed AI infrastructure.
╔════════════════════════════════════════════════════════════════════════╗ ║ SANTHOSH ENGINEER OS · RUNTIME SPEC ║ ╠══════════════╦═════════════════════════════════════════════════════════╣ ║ INPUT ║ Problem statements · Research papers · Broken systems ║ ╠══════════════╬═════════════════════════════════════════════════════════╣ ║ PROCESSOR ║ Agentic reasoning (LangGraph) ║ ║ ║ System design thinking → microservice decomposition ║ ║ ║ Architecture-first, code-second approach ║ ╠══════════════╬═════════════════════════════════════════════════════════╣ ║ MEMORY ║ Qdrant / ChromaDB vector stores ║ ║ ║ BM25 sparse retrieval + dense embedding fusion ║ ║ ║ Past project patterns as reusable mental models ║ ╠══════════════╬═════════════════════════════════════════════════════════╣ ║ OUTPUT ║ Containerized · CI/CD-wired · Security-hardened ║ ║ ║ JSON-logged · Rate-limited · Production-ready ║ ╠══════════════╬═════════════════════════════════════════════════════════╣ ║ OS TRAITS ║ ✓ Docker from commit one ║ ║ ║ ✓ GitHub Actions in every repo ║ ║ ║ ✓ Agents / API / ML as separate bounded services ║ ║ ║ ✓ Security baked in — never bolted on ║ ╚══════════════╩═════════════════════════════════════════════════════════╝
LOADING MODULE REGISTRY... ████████████████████████ 100%
[MODULE 01] AI CORE ENGINE
| Component | Tech | Status |
|---|---|---|
| Agent Orchestration | LangGraph · LangChain | 🟢 ACTIVE |
| Vision & Detection | PyTorch · OpenCV · Transformers | 🟢 ACTIVE |
| STT · Multi-language | Whisper · Sarvam AI Saaras v3 | 🟢 ACTIVE |
| TTS Synthesis | edge-tts · Neural Voices | 🟢 ACTIVE |
[MODULE 02] DATA & RETRIEVAL LAYER
| Component | Tech | Status |
|---|---|---|
| Vector Store | Qdrant · ChromaDB · FAISS | 🟢 ACTIVE |
| Sparse Retrieval | BM25 · Reciprocal Rank Fusion | 🟢 ACTIVE |
| Document Ingestion | MarkItDown · PDF · DOCX · PPTX | 🟢 ACTIVE |
| Embedding Models | MiniLM-L6 · HuggingFace Hub | 🟢 ACTIVE |
[MODULE 03] BACKEND SYSTEMS
| Component | Tech | Status |
|---|---|---|
| API Framework | FastAPI | 🟢 ACTIVE |
| Primary Language | Python | 🟢 ACTIVE |
| Relational Store | PostgreSQL | 🟢 ACTIVE |
| Object Storage | MinIO | 🟢 ACTIVE |
[MODULE 04] INFRASTRUCTURE & DEVOPS
| Component | Tech | Status |
|---|---|---|
| Containerization | Docker · Docker Compose | 🟢 ACTIVE |
| CI / CD Pipelines | GitHub Actions | 🟢 ACTIVE |
| Security Scanning | Bandit · detect-secrets · ruff | 🟢 ACTIVE |
| Log Monitoring | Dozzle · JSON stdout | 🟢 ACTIVE |
[MODULE 05] FRONTEND & UX
| Component | Tech | Status |
|---|---|---|
| Web Framework | Next.js · TypeScript | 🟢 ACTIVE |
| Rapid Prototyping | Gradio | 🟢 ACTIVE |
| Static Generation | Node.js · GitHub Pages | 🟢 ACTIVE |
| Runtime | Linux | 🟢 ACTIVE |
SCANNING PROJECT REGISTRY... 4 SYSTEMS FOUND
Problem: Deepfake media is proliferating faster than detection tooling can scale. Existing solutions are monolithic and brittle — one model, one failure point, no auditability.
Solution: Forensic deepfake detection architected as a production microservices mesh.
flowchart LR
U[Upload] --> API[API Gateway]
API --> AG[Agent Orchestrator]
AG --> ML[ML Service]
ML --> RF[RetinaFace]
ML --> XC[Xception CNN]
ML --> TR[Transformers]
AG --> CH[(ChromaDB)]
AG --> PG[(PostgreSQL)]
PG --> MI[(MinIO Object Store)]
MI --> EX[Auto-Expiry 30d]
style U fill:#5B8DEF,stroke:#333,color:#fff
style API fill:#1a0d0f,stroke:#5B8DEF,color:#fff
style AG fill:#1a0d0f,stroke:#5B8DEF,color:#fff
style ML fill:#1a0d0f,stroke:#5B8DEF,color:#fff
stateDiagram-v2
[*] --> pending
pending --> temp_stored
temp_stored --> processing
processing --> processed
processed --> deleted
deleted --> [*]
Stack: Python · FastAPI · LangGraph · Docker Compose
PostgreSQL · ChromaDB · MinIO · RetinaFace · Xception
CI/CD: GitHub Actions · network audit · logging validation
Architecture: Multi-Dockerfile services (Dockerfile.api / Dockerfile.agents / Dockerfile.ml) sharing a single docker-compose.yml. JSON-structured logging across every module with live Dozzle viewer.
Design decision: FLAG_FOR_REVIEW is treated as an honest middle state, not a failure mode — multi-signal weighted aggregation surfaces uncertainty instead of forcing a binary call.
Problem: Enterprise manuals exist in a graveyard of PDFs and PPTX files. Users either search manually or get generic LLM hallucinations. No voice support for Indic languages. No agentic troubleshooting.
Solution: Production RAG system with hybrid search, voice layer, and LangGraph-powered diagnostic engine.
flowchart TD
A[PDF · DOCX · PPTX · XLSX · TXT] --> B[MarkItDown Parser]
B --> C[Chunker + Overlap Windows]
C --> D[MiniLM-L6 Embeddings]
D --> E[(Qdrant Vector Store)]
flowchart LR
Q[Query] --> M1[Exact Match]
M1 --> M2[Family Match]
M2 --> M3[Global Match]
M1 --> DV[Dense Vector]
M2 --> BM[BM25 Sparse]
M3 --> RRF[RRF Fusion]
DV --> RRF
BM --> RRF
RRF --> LLM[LLM]
flowchart LR
subgraph eng["English Path"]
EA[English Audio] --> W[Whisper STT] --> R1[Response] --> T1[edge-tts]
end
subgraph indic["Indic Path"]
IA[Indic Audio] --> S[Sarvam Saaras v3] --> R2[Response] --> T2[edge-tts]
end
SECURITY STACK:
slowapi rate limiting · MIME-type guards · regex prompt injection
isolated RAG prompts · 24-test suite (unit + integration + security)
Stack: Python · FastAPI · LangGraph · Qdrant · BM25 · MiniLM-L6
Whisper · Sarvam AI · edge-tts · Next.js · TypeScript · Docker
CI/CD: GitHub Actions · ruff · black · bandit · detect-secrets
Architecture: Full-stack monorepo (backend/ + frontend/). Prompt injection filtered at both the regex layer and the LLM system prompt level. Admin upload panel in Next.js.
In progress: Phase 3 hardening — multi-provider LLM key rotation (Gemini → Groq → SambaNova → HF → OpenAI), VLM-based image captioning, parent-child chunking, BGE reranker.
Problem: E-commerce discovery still relies on keyword search. Users describe what they want in natural language — the product catalog doesn't speak that.
Solution: LLM-powered natural language product discovery deployed publicly on Hugging Face Spaces.
flowchart TD
U[User Query - Natural Language] --> G[Gradio UI Layer - app.py]
G --> IL[Inference Logic]
IL --> API[LLM API]
IL --> DL[Data Layer]
DL --> VDB[FAISS / ChromaDB ready]
G --> DK[Docker Container]
DK --> HF[HuggingFace Spaces]
Stack: Python · Gradio · Transformers / LLM APIs · Docker · HF Spaces CI/CD: GitHub Actions
Architecture: Prompt-orchestration-first design, modular for async inference and vector DB integration with zero structural changes.
Problem: Markdown documentation has no navigable web presence without a full CMS or framework overhead.
Solution: Zero-config static site generator with incremental builds and auto-deploy on push.
flowchart TD
A[Markdown Source] --> B[Node.js Build]
B --> C[HTML + Dark Mode + Search]
C --> D[GitHub Actions]
D --> E[GitHub Pages]
B --> F[Incremental - only changed files regenerated]
Stack: JavaScript · Node.js · GitHub Actions · GitHub Pages
╔══════════════════════════════════════════════════════════════╗ ║ SYSTEM METRICS · GITHUB TELEMETRY ║ ╚══════════════════════════════════════════════════════════════╝
| Metric | Value |
|---|---|
| Deployed production repos | 4 |
| Independent microservices shipped | 8+ (API · Agents · ML across 2 systems) |
| CI/CD pipelines maintained | 100% of repos (lint · security scan · deploy) |
| Containerized services | 100% (Docker/Compose on every project) |
| Languages in active rotation | Python · TypeScript · JavaScript |
| Voice/ASR languages supported | English · Tamil · Hindi |
Note: the stats/streak/activity widgets above render live from GitHub's public API at view time — they'll always reflect real, current numbers rather than a static snapshot.
Every system in this portfolio ships with the same non-negotiables.
╔═══════════════════════════════════════════════════════════════╗ ║ ENGINEERING INVARIANTS ║ ╠═══════════════════════════════════════════════════════════════╣ ║ [✓] Containerized from commit one — Docker / Compose ║ ║ [✓] CI/CD in every repo — lint · security · deploy ║ ║ [✓] JSON structured logging — stdout, never print() ║ ║ [✓] Security-first APIs — rate limit · MIME guard · scan ║ ║ [✓] Separation of concerns — agents ≠ API ≠ ML ║ ╚═══════════════════════════════════════════════════════════════╝
// Open to roles in AI engineering, MLOps, and agentic systems. // I build production systems, not demos. Let's build.
╔══════════════════════════════════════════════════════════════════╗ ║ SANTHOSH.OS · SYSTEM HALT · All services nominal. ✓ ║ ╚══════════════════════════════════════════════════════════════════╝
Pinned Loading
If the problem persists, check the GitHub status page or contact support.