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- - week1-prompt-engineering-quiz.xml
- .DS_Store
- gemini_helpers.py
- l2-guidelines-exercise.ipynb
- l2-guidelines.ipynb
- l3-iterative-prompt-development-exercise.ipynb
- l3-iterative-prompt-development.ipynb
- l4-summarizing-exercise.ipynb
- l4-summarizing.ipynb
- l5-inferring-exercise.ipynb
- l5-inferring.ipynb
- l6-transforming-exercise.ipynb
- l6-transforming.ipynb
- l7-expanding-exercise.ipynb
- l7-expanding.ipynb
- l8-chatbot-exercise.ipynb
- l8-chatbot.ipynb
- requirements.txt
- gemini_helpers.py
- lesson_2.ipynb
- lesson_3.ipynb
- lesson_4.ipynb
- lesson_5.ipynb
- project.ipynb
- pydantic-lecture-transcript.md
- requirements.txt
- helper.py
- L1_Router_Engine.ipynb
- L2_Tool_Calling.ipynb
- L3_Building_an_Agent_Reasoning_Loop.ipynb
- L4_Building_a_Multi-Document_Agent.ipynb
- longlora.pdf
- metagpt.pdf
- rag-agent-lecture-transcript.md
- requirements.txt
- utils.py
- - default.sqlite
  - eBook-How-to-Build-a-Career-in-AI.pdf
  - eval_questions.txt
  - IPCC_AR6_WGII_Chapter03.pdf
  - L1-Advanced_RAG_Pipeline.ipynb
  - L2-RAG_Triad_of_metrics.ipynb
  - transcript.txt
  - utils.py
- - eBook-How-to-Build-a-Career-in-AI.pdf
  - eval_questions.txt
  - L2-RAG_Triad_of_metrics.ipynb
  - transcript.txt
  - utils.py
- - eBook-How-to-Build-a-Career-in-AI.pdf
  - generated_questions.text
  - generated_questions_01_05.text
  - generated_questions_06_10.text
  - generated_questions_11_15.text
  - generated_questions_16_20.text
  - generated_questions_21_24.text
  - L3-Sentence_window_retrieval.ipynb
  - transcript.txt
  - utils.py
- - eBook-How-to-Build-a-Career-in-AI.pdf
  - generated_questions.text
  - L4-Auto-merging_Retrieval.ipynb
  - transcript.txt
  - utils.py
- helper.py
- LECTURE_TRANSCRIPT.md
- requirements.txt
- - __init__.py
  - hello_workflow.py
  - NOTES.md
- - __init__.py
  - activities.py
  - NOTES.md
  - workflows.py
- - __init__.py
  - activities.py
  - NOTES.md
  - workflows.py
- - __init__.py
  - activities.py
  - NOTES.md
  - workflows.py
- - __init__.py
  - activities.py
  - NOTES.md
  - workflows.py
- - __init__.py
  - activities.py
  - NOTES.md
  - workflows.py
- - __init__.py
  - ai_backend.py
  - config.py
  - gemini_ai.py
  - mock_ai.py
  - models.py
  - temporal_client.py
- .env.example
- __init__.py
- docker-compose.yml
- LECTURE_TRANSCRIPT.md
- README.md
- requirements.txt
- starter.py
- worker.py
- - Appendix.ipynb
- - allfiles.tar.gz
  - L11.ipynb
  - utils.py
- - helper.py
  - L3.ipynb
- - helper.py
  - L5.ipynb
- - L7.ipynb
  - utils.py
- - L9.ipynb
  - utils.py
- .env.example
- gemini_helpers.py
- helper.py
- lecture-slides.html
- LECTURE_TRANSCRIPT.md
- mock_llm.py
- phoenix_compat.py
- README.md
- requirements.txt
- Untitled.ipynb
- - agent-evaluation.md
  - course-syllabus.md
  - prompting.md
  - pydantic-contracts.md
  - rag-retrieval.md
  - temporal-orchestration.md
  - week8-lesson2.md
- - L0.png
  - L1.png
  - overview.png
- - __init__.py
  - activities.py
  - NOTES.md
  - workflows.py
- - __init__.py
  - NOTES.md
  - workflows.py
- - __init__.py
  - NOTES.md
  - workflows.py
- - __init__.py
  - NOTES.md
  - workflows.py
- - __init__.py
  - activities.py
  - NOTES.md
  - workflows.py
- - __init__.py
  - NOTES.md
  - workflows.py
- - __init__.py
  - ai_backend.py
  - config.py
  - desk_activities.py
  - eval_report.py
  - gemini_ai.py
  - mock_ai.py
  - models.py
  - prompts.py
  - retriever.py
  - temporal_client.py
  - tracing.py
- - conftest.py
  - test_api.py
  - test_fallback.py
  - test_l0_skeleton.py
  - test_l1_contracts.py
  - test_l2_retriever.py
  - test_l3_router.py
  - test_l4_pipeline.py
  - test_l5_eval_report.py
- .env.example
- __init__.py
- api.py
- docker-compose.yml
- lecture-slides.html
- LECTURE_TRANSCRIPT.md
- pytest.ini
- README.md
- requirements.txt
- starter.py
- worker.py
- - config.py
  - dlai.py
  - install.sh
  - start_server.sh
- - helper.py
  - Lesson_1.ipynb
- - config.py
  - helper.py
  - Lesson_3.ipynb
  - requirements.txt
- - helper.py
  - Lesson_4.ipynb
- - helper.py
  - Lesson_5.ipynb
- - config.py
  - helper.py
  - Lesson_6.ipynb
  - local_config.py
  - on_topic_config.py
- - config.py
  - helper.py
  - Lesson_7.ipynb
- - config.py
  - helper.py
  - Lesson_8.ipynb
- .env.example
- gemini_helpers.py
- guardrails_local.py
- LECTURE_TRANSCRIPT.md
- mock_llm.py
- requirements-lock.txt
- requirements.txt
- Untitled.ipynb
.env.example
.gitignore
LICENSE
README.md

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Course materials for prompt engineering, adapted to use Google's Gemini API (free tier) instead of OpenAI.

## Setup

1. Install dependencies:

```bash
pip install -r week_1/requirements.txt
```

2. Get a free API key from [Google AI Studio](https://aistudio.google.com/apikey).

3. Create a `.env` file in the project root (copy from `.env.example`):

```
GOOGLE_API_KEY=your-api-key-here
```

4. Open and run the notebooks in `week_1/`. They import helper functions from `week_1/gemini_helpers.py`, which uses the `gemini-2.0-flash` model by default.

## Weeks

| Week | Topic |
|------|--------|
| `week_1/` | Prompt engineering (Gemini) |
| `week_2/` | Pydantic for LLM workflows |
| `week_3/` | Agentic RAG (LlamaIndex) |
| `week_4/` | Advanced RAG evaluation |
| `week_5/` | Temporal workflow orchestration — see [`week_5/README.md`](week_5/README.md) |
| `week_7/` | Evaluating AI agents (Phoenix) — Gemini with mock fallback; see [`week_7/README.md`](week_7/README.md) |
| `week_8/` | Knowledge Desk integration — see [`week_8/README.md`](week_8/README.md) |

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