Me

.github/agents/my-agent.agent.md

@@ -0,0 +1,13 @@
+---
+# Fill in the fields below to create a basic custom agent for your repository.
+# The Copilot CLI can be used for local testing: https://gh.io/customagents/cli
+# To make this agent available, merge this file into the default repository branch.
+# For format details, see: https://gh.io/customagents/config
+
+name:
+description:
+---
+
+# My Agent
+
+Describe what your agent does here...

.github/workflows/deploy-pages.yml

@@ -0,0 +1,38 @@
+name: Deploy to GitHub Pages
+
+on:
+  push:
+    branches:
+      - main
+  workflow_dispatch:
+
+permissions:
+  contents: read
+  pages: write
+  id-token: write
+
+concurrency:
+  group: "pages"
+  cancel-in-progress: false
+
+jobs:
+  deploy:
+    environment:
+      name: github-pages
+      url: ${{ steps.deployment.outputs.page_url }}
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Setup Pages
+        uses: actions/configure-pages@v4
+
+      - name: Upload artifact
+        uses: actions/upload-pages-artifact@v3
+        with:
+          path: '.'
+
+      - name: Deploy to GitHub Pages
+        id: deployment
+        uses: actions/deploy-pages@v4

.github/workflows/generator-generic-ossf-slsa3-publish.yml

@@ -0,0 +1,66 @@
+# This workflow uses actions that are not certified by GitHub.
+# They are provided by a third-party and are governed by
+# separate terms of service, privacy policy, and support
+# documentation.
+
+# This workflow lets you generate SLSA provenance file for your project.
+# The generation satisfies level 3 for the provenance requirements - see https://slsa.dev/spec/v0.1/requirements
+# The project is an initiative of the OpenSSF (openssf.org) and is developed at
+# https://github.com/slsa-framework/slsa-github-generator.
+# The provenance file can be verified using https://github.com/slsa-framework/slsa-verifier.
+# For more information about SLSA and how it improves the supply-chain, visit slsa.dev.
+
+name: SLSA generic generator
+on:
+  workflow_dispatch:
+  release:
+    types: [created]
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    outputs:
+      digests: ${{ steps.hash.outputs.digests }}
+
+    steps:
+      - uses: actions/checkout@v4
+
+      # ========================================================
+      #
+      # Step 1: Build your artifacts.
+      #
+      # ========================================================
+      - name: Build artifacts
+        run: |
+            # These are some amazing artifacts.
+            echo "artifact1" > artifact1
+            echo "artifact2" > artifact2
+
+      # ========================================================
+      #
+      # Step 2: Add a step to generate the provenance subjects
+      #         as shown below. Update the sha256 sum arguments
+      #         to include all binaries that you generate
+      #         provenance for.
+      #
+      # ========================================================
+      - name: Generate subject for provenance
+        id: hash
+        run: |
+          set -euo pipefail
+
+          # List the artifacts the provenance will refer to.
+          files=$(ls artifact*)
+          # Generate the subjects (base64 encoded).
+          echo "hashes=$(sha256sum $files | base64 -w0)" >> "${GITHUB_OUTPUT}"
+
+  provenance:
+    needs: [build]
+    permissions:
+      actions: read   # To read the workflow path.
+      id-token: write # To sign the provenance.
+      contents: write # To add assets to a release.
+    uses: slsa-framework/slsa-github-generator/.github/workflows/generator_generic_slsa3.yml@v1.4.0
+    with:
+      base64-subjects: "${{ needs.build.outputs.digests }}"
+      upload-assets: true # Optional: Upload to a new release

.gitignore

@@ -159,9 +159,38 @@ cython_debug/
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
 
+# Node.js
 node_modules/
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+package-lock.json
+yarn.lock
+pnpm-lock.yaml
+.npm
+.yarn/
+dist/
+.next/
+out/
+.nuxt/
+.cache/
+.parcel-cache/
 
+# OS artifacts – macOS
 .DS_Store
+.AppleDouble
+.LSOverride
+._*
+
+# OS artifacts – Windows
+Thumbs.db
+ehthumbs.db
+Desktop.ini
+$RECYCLE.BIN/
+
+# OS artifacts – Linux
+*~
 
 # downloaded stuff for 08-building-search-applications
 08-building-search-applications/scripts/transcripts_the_ai_show/

08-building-search-applications/scripts/transcript_download.py

@@ -79,7 +79,8 @@ def gen_metadata(playlist_item):
     metadata["description"] = playlist_item["snippet"]["description"]
 
     # save the metadata as a .json file
-    json.dump(metadata, open(filename, "w", encoding="utf-8"))
+    with open(filename, "w", encoding="utf-8") as f:
+        json.dump(metadata, f)
 
 
 def get_transcript(playlist_item, counter_id):

08-building-search-applications/scripts/transcript_enrich_embeddings.py

@@ -119,7 +119,6 @@ def process_queue(progress, task):
         output_segments.append(segment.copy())
         progress.update(task, advance=1)
         q.task_done()
-        time.sleep(0.2)
 
 
 logger.debug("Total segments to be processed: %s", len(segments))

08-building-search-applications/scripts/transcript_enrich_speaker.py

@@ -154,7 +154,7 @@ def clean_text(text):
 def get_first_segment(file_name):
     """Gets the first segment from the filename"""
 
-    text = ""
+    text_parts = []
     current_seconds = None
     segment_begin_seconds = None
     segment_finish_seconds = None
@@ -176,9 +176,9 @@ def get_first_segment(file_name):
 
             if current_seconds < segment_finish_seconds:
                 # add the text to the transcript
-                text += clean_text(segment.get("text")) + " "
+                text_parts.append(clean_text(segment.get("text")))
 
-    return text
+    return " ".join(text_parts) + " " if text_parts else ""
 
 
 def process_queue(progress, task):
@@ -206,10 +206,10 @@ def process_queue(progress, task):
                 print(f"From function call: {filename}\t{speakers}")
 
             metadata["speaker"] = speakers
-            json.dump(metadata, open(filename, "w", encoding="utf-8"))
+            with open(filename, "w", encoding="utf-8") as f:
+                json.dump(metadata, f)
 
         q.task_done()
-        time.sleep(0.2)
 
 
 logger.debug("Transcription folder %s", TRANSCRIPT_FOLDER)

09-building-image-applications/python/oai-app-variation.py

@@ -17,11 +17,12 @@
 # ---creating variation below---
 try:
     print("LOG creating variation")
-    response = openai.images.create_variation(
-        image=open("generated-image.png", "rb"),
-        n=1,
-        size="1024x1024"
-    )
+    with open("generated-image.png", "rb") as image_file:
+        response = openai.images.create_variation(
+            image=image_file,
+            n=1,
+            size="1024x1024"
+        )
 
     image_path = os.path.join(image_dir, 'generated_variation.png')
 

09-building-image-applications/python/oai-app.py

@@ -47,8 +47,9 @@
 # ---creating variation below---
 
 
-response = client.images.create_variation(
-  image=open(image_path, "rb"),
-  n=1,
-  size="1024x1024"
-)
+with open(image_path, "rb") as image_file:
+    response = client.images.create_variation(
+      image=image_file,
+      n=1,
+      size="1024x1024"
+    )

DEPLOYMENT.md

@@ -0,0 +1,50 @@
+# GitHub Pages Deployment Setup
+
+This repository is configured to deploy to GitHub Pages using GitHub Actions.
+
+## Configuration Required
+
+To enable GitHub Pages deployment for this repository:
+
+1. Go to your repository's **Settings** > **Pages**
+2. Under **Build and deployment**, select:
+   - **Source**: GitHub Actions
+3. The deployment workflow (`.github/workflows/deploy-pages.yml`) will automatically run on:
+   - Pushes to the `main` branch
+   - Manual workflow dispatch
+
+## Accessing the Site
+
+Once GitHub Pages is enabled and the workflow runs successfully, your site will be available at:
+- `https://<username>.github.io/<repository-name>/`
+
+For this repository:
+- `https://vepretski.github.io/generative-ai-for-beginners/`
+
+## Local Development
+
+To preview the site locally:
+
+1. Start a local web server in the repository root:
+   ```bash
+   # Using Python
+   python -m http.server 8000
+
+   # Or using Node.js
+   npx http-server
+   ```
+
+2. Open your browser to `http://localhost:8000`
+
+The site uses [Docsify](https://docsify.js.org/) to render documentation from Markdown files dynamically.
+
+## Workflow Details
+
+The deployment workflow:
+- Triggers on pushes to `main` or manual dispatch
+- Checks out the repository
+- Configures GitHub Pages
+- Uploads the entire repository as a Pages artifact
+- Deploys the artifact to GitHub Pages
+
+No build step is required since Docsify renders the documentation client-side.

README.md

@@ -105,6 +105,65 @@ Special thanks to [**John Aziz**](https://www.linkedin.com/in/john0isaac/) for c
 
 [**Bernhard Merkle**](https://www.linkedin.com/in/bernhard-merkle-738b73/) for making key contributions to each lesson to improve the learner and code experience. 
 
+---
+
+This fork is maintained by [Igor Vepretski](https://7ya.io) - Empowering the next generation of AI builders. Learn more at [7YA.IO](https://7ya.io)
+
+## 📁 Project Structure
+
+This repository is organised so that beginners can find everything they need quickly.
+
+```
+generative-ai-for-beginners/
+├── src/
+│   └── main.py          # Starter script – run this to verify your setup
+├── docs/
+│   └── setup.md         # Detailed environment setup guide
+├── tests/
+│   └── test_main.py     # Unit tests (run with: pytest tests/)
+├── 00-course-setup/     # Lesson 0: setting up your development environment
+├── 01-introduction-to-genai/ … 21-meta/   # Course lessons
+├── .gitignore           # Ignores Python, Node.js, and OS artefacts
+└── README.md            # You are here
+```
+
+### ✨ Features
+
+- **21 structured lessons** covering all core Generative AI topics, from fundamentals to advanced techniques.
+- **Dual-language code samples** – every Build lesson includes both **Python** and **TypeScript** examples.
+- **Multiple LLM provider support** – Azure OpenAI, GitHub Marketplace Models, and the OpenAI API all work out of the box.
+- **Hands-on projects** – chat apps, image generators, RAG pipelines, AI agents, and more.
+- **Beginner-friendly layout** – each lesson is self-contained with a README, code samples, and extra-learning links.
+
+### 🛠️ Quick Setup
+
+1. **Clone** the repo and create a virtual environment:
+
+   ```bash
+   git clone https://github.com/microsoft/generative-ai-for-beginners.git
+   cd generative-ai-for-beginners
+   python -m venv .venv && source .venv/bin/activate  # Windows: .venv\Scripts\Activate.ps1
+   pip install -r requirements.txt
+   ```
+
+2. **Configure** your LLM provider by copying `.env.copy` to `.env` inside the lesson folder and filling in your API key.
+
+3. **Verify** the setup by running the starter script:
+
+   ```bash
+   python src/main.py
+   ```
+
+4. **Run the tests** to make sure everything is working:
+
+   ```bash
+   pytest tests/
+   ```
+
+> 📖 For full details see [docs/setup.md](./docs/setup.md).
+
+---
+
 ## 🎒 Other Courses
 
 Our team produces other courses! Check out: