Cv sirazitdinov

.dockerignore

@@ -0,0 +1,7 @@
+node_modules
+npm-debug.log
+dist
+.git
+.gitignore
+.DS_Store
+*.log

.github/workflows/deploy-containerapp.yml

@@ -0,0 +1,42 @@
+name: Deploy Container App
+
+on:
+  push:
+    branches: [main]
+
+permissions:
+  contents: read
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Azure Login
+        uses: azure/login@v2
+        with:
+          client-id: ${{ secrets.AZURE_CLIENT_ID }}
+          tenant-id: ${{ secrets.AZURE_TENANT_ID }}
+          subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
+          client-secret: ${{ secrets.AZURE_CLIENT_SECRET }}
+
+      - name: Build and push image
+        run: |
+          ACR=${{ secrets.ACR_NAME }}
+          IMAGE="$ACR.azurecr.io/resume-web:${{ github.sha }}"
+          az acr login --name "$ACR"
+          docker build -f Dockerfile.chat -t "$IMAGE" .
+          docker push "$IMAGE"
+          echo "IMAGE=$IMAGE" >> $GITHUB_ENV
+
+      - name: Update Container App
+        run: |
+          az containerapp update \
+            --name ${{ secrets.CONTAINERAPP_NAME }} \
+            --resource-group ${{ secrets.RESOURCE_GROUP }} \
+            --image "$IMAGE" \
+            --set-env-vars \
+              AZURE_OPENAI_API_KEY=${{ secrets.AZURE_OPENAI_API_KEY }} \
+              AZURE_OPENAI_ENDPOINT=${{ secrets.AZURE_OPENAI_ENDPOINT }}

Dockerfile

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+FROM node:20-alpine AS builder
+
+WORKDIR /app
+
+COPY package.json package-lock.json ./
+RUN npm ci
+
+COPY . .
+RUN npm run build
+
+FROM nginx:alpine
+
+COPY --from=builder /app/docs /usr/share/nginx/html
+
+EXPOSE 80
+
+CMD ["nginx", "-g", "daemon off;"]

Dockerfile.chat

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+FROM node:20-alpine AS build
+
+WORKDIR /app
+
+COPY package.json package-lock.json ./
+RUN npm ci
+
+COPY tailwind.css postcss.config.js tailwind.config.js ./
+COPY docs ./docs
+RUN npm run build
+
+FROM python:3.11-slim
+
+WORKDIR /app
+
+COPY cv_chat/requirements.txt ./
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY cv_chat ./cv_chat
+COPY --from=build /app/docs ./docs
+
+ENV PORT=8080
+
+CMD ["gunicorn", "-w", "2", "-b", "0.0.0.0:8080", "cv_chat.app:app"]

README.md

@@ -41,6 +41,98 @@ Only generate CSS that is used on the page, which results in a much smaller file
 npm run build
 ```
 
+Tutorial: What Was Done
+---------
+
+This project was updated and deployed as a static résumé site. Below is a concise walkthrough of the changes and deployment flow so you can repeat it.
+
+### 1) Update the content
+
+- Edit `docs/index.html` and replace the template content with your CV details.
+- Keep the overall structure (sections, headers, list items) so the layout stays consistent.
+
+### 2) Tailwind v4 + PostCSS fixes
+
+Tailwind v4 moved its PostCSS plugin to a separate package. The build pipeline was adjusted accordingly:
+
+```
+npm install @tailwindcss/postcss
+```
+
+In `postcss.config.js`, swap the Tailwind plugin for the new one and pass the config path:
+
+```
+require("@tailwindcss/postcss")({
+  config: "./tailwind.config.js"
+})
+```
+
+In `tailwind.css`, use the v4 import style:
+
+```
+@import "tailwindcss";
+```
+
+### 3) Two-column layout
+
+To force two columns on all screen sizes, use `col-count-2` (without the `md:` prefix) on the column container in `docs/index.html`:
+
+```
+<div class="col-count-2 print:col-count-2 col-gap-md h-letter-col print:h-letter-col col-fill-auto">
+```
+
+### 4) Replace deprecated CSS
+
+Autoprefixer warns about `color-adjust` being deprecated. Update this in `tailwind.css`:
+
+```
+print-color-adjust: exact !important;
+```
+
+### 5) Docker production container
+
+A production Docker image builds the CSS and serves the site via Nginx.
+
+```
+docker build -t universal-resume .
+docker run --rm -p 8080:80 universal-resume
+```
+
+### 6) Azure Static Website deployment
+
+This setup uses Azure Storage Static Website hosting.
+
+Install Azure CLI (Windows):
+
+```
+https://aka.ms/installazurecliwindows
+```
+
+Login (PowerShell needs the `&` call operator):
+
+```
+& "C:\Program Files\Microsoft SDKs\Azure\CLI2\wbin\az.cmd" login --use-device-code
+```
+
+Then create resources and upload:
+
+```
+$rg = "universal-resume-rg"
+$loc = "germanywestcentral"
+$sa = "resumestatic" + (Get-Random -Maximum 99999)
+
+& "C:\Program Files\Microsoft SDKs\Azure\CLI2\wbin\az.cmd" group create --name $rg --location $loc
+& "C:\Program Files\Microsoft SDKs\Azure\CLI2\wbin\az.cmd" storage account create --name $sa --resource-group $rg --location $loc --sku Standard_LRS --kind StorageV2 --allow-blob-public-access true
+& "C:\Program Files\Microsoft SDKs\Azure\CLI2\wbin\az.cmd" storage blob service-properties update --account-name $sa --static-website --index-document index.html --404-document index.html
+
+$web = & "C:\Program Files\Microsoft SDKs\Azure\CLI2\wbin\az.cmd" storage account show --name $sa --resource-group $rg --query "primaryEndpoints.web" -o tsv
+
+$key = & "C:\Program Files\Microsoft SDKs\Azure\CLI2\wbin\az.cmd" storage account keys list --account-name $sa --resource-group $rg --query "[0].value" -o tsv
+& "C:\Program Files\Microsoft SDKs\Azure\CLI2\wbin\az.cmd" storage blob upload-batch --account-name $sa --account-key $key --destination '$web' --source .\docs
+
+$web
+```
+
 Starting Point
 ---------
 

cv_chat/.gitattributes

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+# Auto detect text files and perform LF normalization
+* text=auto

cv_chat/.gitignore

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+
+# dependencies
+/.ipynb_checkpoints
+/.pnp
+.pnp.js
+
+# misc
+.DS_Store
+.env
+.env.local
+.env.development.local
+.env.test.local
+.env.production.local
+
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*

cv_chat/andrei_context.txt

@@ -0,0 +1,53 @@
+Name: Andrei Sirazitdinov
+Location: Mannheim, Germany
+Contact: dyh@list.ru | +49 176 47699707
+
+About:
+- Ph.D. in Computer Science
+- University of Heidelberg | Data Science, ML, AI, Computer Vision
+- As a researcher, I was focused on causal inference and individualized treatment effect estimation with deep learning. I also worked on explainable AI for healthcare and vision tasks. Permanent residency and full work authorization in Germany. Open to relocation.
+
+Research interests:
+- Causal inference, individualized treatment assignment, explainable ML
+- Built and evaluated deep learning models (MLPs, GANs, VAEs, GNNs) in TensorFlow, Keras, and PyTorch for healthcare decision support, privacy, and explainability.
+
+Experience:
+- University of Heidelberg, Germany (Apr 2020 – Oct 2025) — Ph.D. Candidate
+  - Individualized treatment assignment with MLPs, GANs, VAEs, and GNNs in TensorFlow/Keras.
+  - Pain patient treatment strategies using K-NN clustering and XGBoost with RCT validation.
+  - Explainable pathology patch classification with prototype learning and decision trees in PyTorch.
+  - Digital twin models using stable diffusion for patient data privacy in PyTorch.
+  - Dropout prediction model for cancer patients achieving 80% precision in TensorFlow.
+- National Institute of Informatics, Japan (Oct 2018 – Apr 2019) — Research Intern
+  - Computer vision algorithm for long-term video prediction using PyTorch.
+- Irkutsk Branch of MSTUCA, Russia (Oct 2014 – Jul 2015) — Student Assistant
+  - Built a multi-camera system to capture helicopter panel data and populate digital tables automatically.
+
+Education:
+- Ph.D. in Computer Science — University of Heidelberg, Germany (2020 – 2025)
+- M.Sc. in Visual Computing — Saarland University, Germany (2016 – 2019)
+- B.Sc. in Applied Informatics and Mathematics — Irkutsk State University, Russia (2012 – 2016)
+- High School — Irkutsk, Russia (2010 – 2012)
+
+Projects:
+- Trading Bots (Python) — WebSocket API | Docker | GitHub Actions
+- Local ChatGPT Clone — Streamlit | OpenAI API | SQLite
+- Databricks Integration — Centralized storage for chats and user authentication
+
+Skills:
+- ML/AI: TensorFlow, PyTorch, Scikit-learn, Keras
+- Data tools: Pandas, NumPy
+- Tools and platforms: Python, SQL, R, Docker, Kubernetes, MLflow, Azure (beginner), Git, Linux, Windows
+
+Languages:
+- English (Fluent speaking, reading, and writing)
+- German (B1 certificate, completed C1 courses)
+- Russian (Native)
+
+Selected publications:
+- A. Sirazitdinov et al., "Graph Neural Networks for Individual Treatment Effect Estimation," IEEE Access, 2024.
+- A. Sirazitdinov et al., "Review of Deep Learning Methods for Individual Treatment Effect Estimation with Automatic Hyperparameter Optimization," TechRxiv, 2022.
+
+Git Repos:
+- https://github.com/dyh1265/Causal-Inference-Library — Causal inference library for GNN-TARNet and related models; includes notebooks and code for the GNN-ITE paper.
+- https://github.com/dyh1265/PerPain-allocation — PerPain patient allocation system with two approaches: an R Shiny clustering app and Python ML models (TARnet, GNN-TARnet, GAT-TARnet, T-Learner) for individualized treatment recommendations.

cv_chat/app.py

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+import os
+import re
+from html import unescape
+from html.parser import HTMLParser
+from pathlib import Path
+
+import dotenv
+from flask import Flask, request, send_from_directory
+from openai import AzureOpenAI
+
+dotenv.load_dotenv()
+
+BASE_DIR = Path(__file__).resolve().parent
+DOCS_DIR = BASE_DIR.parent / "docs"
+
+app = Flask(__name__, static_folder=str(DOCS_DIR), static_url_path="")
+
+client = AzureOpenAI(
+    api_key=os.getenv("AZURE_OPENAI_API_KEY"),
+    api_version="2024-02-15-preview",
+    azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT")
+)
+
+
+
+context_path = BASE_DIR / "andrei_context.txt"
+
+
+class _CVTextParser(HTMLParser):
+    def __init__(self):
+        super().__init__()
+        self._chunks = []
+        self._skip = False
+
+    def handle_starttag(self, tag, attrs):
+        if tag in {"script", "style"}:
+            self._skip = True
+        if tag in {"h1", "h2", "h3", "p", "li"}:
+            self._chunks.append("\n")
+
+    def handle_endtag(self, tag):
+        if tag in {"script", "style"}:
+            self._skip = False
+        if tag in {"h1", "h2", "h3", "p", "li"}:
+            self._chunks.append("\n")
+
+    def handle_data(self, data):
+        if self._skip:
+            return
+        text = data.strip()
+        if text:
+            self._chunks.append(text)
+
+    def text(self):
+        raw = " ".join(self._chunks)
+        normalized = re.sub(r"[ \t]+", " ", raw)
+        normalized = re.sub(r"\n{2,}", "\n", normalized)
+        return normalized.strip()
+
+
+def build_context_from_cv(cv_path: Path, extra_context: str) -> str:
+    if not cv_path.exists():
+        return extra_context
+    parser = _CVTextParser()
+    parser.feed(cv_path.read_text(encoding="utf-8"))
+    cv_text = unescape(parser.text())
+    cv_text = re.sub(r"[ \t]+\n", "\n", cv_text)
+
+    git_block = ""
+    if "Git Repos:" in extra_context:
+        parts = extra_context.split("Git Repos:", 1)
+        git_block = "Git Repos:\n" + parts[1].strip()
+
+    if git_block:
+        return f"{cv_text}\n\n{git_block}"
+    return cv_text
+
+
+if context_path.exists():
+    raw_context = context_path.read_text(encoding="utf-8").strip()
+else:
+    raw_context = ""
+
+andrei_context = build_context_from_cv(DOCS_DIR / "index.html", raw_context)
+
+conversation = [
+    {
+        "role": "system",
+        "content": (
+            "You are a concise assistant that only answers questions about Andrei Sirazitdinov's skills, competencies, prrojects, and background. "
+            "Reply in short bullet points (no bold). If the question is not about Andrei's skills, competencies, projects, and background, say you can only answer "
+            "questions about his skills, competencies, projects, and background and ask the user to rephrase."
+            + (f"\n\nContext about Andrei:\n{andrei_context}" if andrei_context else "")
+        ),
+    }
+]
+
+@app.route("/")
+def index():
+    return send_from_directory(DOCS_DIR, "index.html")
+
+
+@app.route("/<path:filename>")
+def static_files(filename):
+    return send_from_directory(DOCS_DIR, filename)
+
+@app.route("/chat", methods=["POST"])
+def chat():
+    user_input = request.json.get("message")
+    conversation.append({"role": "user", "content": user_input})
+
+    response = client.chat.completions.create(
+        model="gpt-5.2-chat",
+        messages=conversation
+    )
+
+    reply = response.choices[0].message.content
+    conversation.append({"role": "assistant", "content": reply})
+
+    return reply
+
+if __name__ == '__main__':
+    port = int(os.getenv("PORT", "8080"))
+    app.run(host="0.0.0.0", port=port, debug=False)

cv_chat/requirements.txt

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+flask==3.0.2
+python-dotenv==1.0.1
+openai==1.59.7
+gunicorn==22.0.0