Finalize GenAI exam: simplify qabilah+q2, add q5 LangChain agent

README.md

@@ -15,8 +15,8 @@ You are interviewing to join the team that builds **agents like Cumin** — the
 
 1. Introduce yourself to the Arabic tech ecosystem (**Qabilah** + **Mortakaz**).
 2. Design a **memory module** for an agent like Cumin, and show how to use it.
-3. Plan how to **fine-tune an Arabic TTS or STT** model.
-4. Sign up to **Ghaymah** and **deploy a simple static website**.
+3. Propose an **Arabic TTS or STT** model + dataset.
+4. Sign up to **Ghaymah**, **deploy a static website**, and build a **LangChain agent** on Ghaymah's GenAI services.
 
 ## What we are evaluating
 
@@ -24,8 +24,9 @@ You are interviewing to join the team that builds **agents like Cumin** — the
 |---|---|
 | Arabic tech ecosystem awareness | Qabilah + Mortakaz tasks |
 | Agent engineering intuition (memory, retrieval, storage trade-offs) | Q1 |
-| Arabic NLP depth (data, diacritization, evaluation, fine-tuning) | Q2 |
-| Shipping — can you actually deploy something live | Q3 + Q4 |
+| Arabic NLP depth (model + dataset selection) | Q2 |
+| Shipping — deploy something live | Q3 + Q4 |
+| Agent building with real tooling (LangChain) | Q5 |
 
 ## The stack you will touch
 
@@ -34,19 +35,20 @@ You are interviewing to join the team that builds **agents like Cumin** — the
 | **Qabilah (قبيلة)** | Arabic tech social / community platform | https://qabilah.com |
 | **Mortakaz (مُرتكز)** | Directory of ~686 Arab-built products | https://mortakaz.com |
 | **Ghaymah (غيمة)** | Arabic cloud platform (PaaS) | https://ghaymah.systems |
-| **Ghaymah Dashboard** | Where you sign up and deploy | https://deploy.ghaymah.systems |
+| **Ghaymah Dashboard** | Where you sign up, get AI models, and deploy | https://deploy.ghaymah.systems |
 
 ## Time budget (60 min total)
 
 | Task | Folder | Budget |
 |---|---|---|
 | Read this README + set up | — | 5 min |
-| Qabilah profile + ecosystem note | `common-qabilah/` | 8 min |
+| Qabilah profile + check-in | `common-qabilah/` | 3 min |
 | Mortakaz discovery + integration proposal | `common-mortakaz/` | 10 min |
 | Q1 — Cumin memory module design | `q1-cumin-memory/` | 15 min |
-| Q2 — Arabic TTS or STT fine-tune plan | `q2-arabic-tts-stt/` | 15 min |
-| Q3 — Ghaymah signup | `q3-ghaymah-signup/` | 5 min |
-| Q4 — Deploy a static site on Ghaymah | `q4-static-site-deploy/` | 12 min |
+| Q2 — Arabic TTS/STT model + dataset proposal | `q2-arabic-tts-stt/` | 6 min |
+| Q3 — Ghaymah signup | `q3-ghaymah-signup/` | 4 min |
+| Q4 — Deploy a static site on Ghaymah | `q4-static-site-deploy/` | 8 min |
+| Q5 — LangChain agent on Ghaymah's GenAI services | `q5-llm-agent/` | 9 min |
 | **Total** | | **≈ 60 min** |
 
 > ⏱️ Be honest about your time. A focused, complete 60-minute submission beats a half-finished 2-hour one. We look at commit timestamps.
@@ -56,7 +58,7 @@ You are interviewing to join the team that builds **agents like Cumin** — the
 1. Work **inside this repo**. Each question has its own folder with a task description and an answer template. Fill in your answers **in place**.
 2. Do not rename or move the question folders.
 3. Never commit real credentials, tokens, or passwords — use placeholders like `<REDACTED>`.
-4. For Q4, commit your actual site source under `q4-static-site-deploy/site/`.
+4. For Q4, commit your actual site source under `q4-static-site-deploy/site/`; for Q5 under `q5-llm-agent/`.
 5. You may use any public resources (docs, model cards, papers, blogs) — cite them inline.
 
 ## Repository structure
@@ -71,14 +73,18 @@ ghaymah-genai-exam/
 ├── q1-cumin-memory/
 │   └── cumin-memory-module.md     ← task + answer template
 ├── q2-arabic-tts-stt/
-│   └── arabic-tts-stt-finetune.md ← task + answer template
+│   └── arabic-tts-stt-proposal.md ← task + answer template
 ├── q3-ghaymah-signup/
 │   └── ghaymah-signup.md          ← task + answer template
-└── q4-static-site-deploy/
-    ├── static-site-deploy.md      ← task + answer template
-    └── site/                      ← put your site files here
-        ├── index.html
-        └── style.css
+├── q4-static-site-deploy/
+│   ├── static-site-deploy.md      ← task + answer template
+│   └── site/
+│       ├── index.html
+│       └── style.css
+└── q5-llm-agent/
+    ├── llm-agent.md               ← task + answer template
+    ├── agent.py                   ← starter LangChain agent
+    └── requirements.txt
 ```
 
 ## How to submit (GitPasha)
@@ -89,18 +95,19 @@ ghaymah-genai-exam/
    git add . && git commit -m "q1: memory module design"
    ```
 3. `git push origin main` when done.
-4. Verify on GitPasha that every file (including your Q4 site source) is present.
+4. Verify on GitPasha that every file (including your Q4 site source and Q5 code) is present.
 
 ## Scoring rubric
 
 | Question | Weight | What “excellent” looks like |
 |---|---|---|
-| common-qabilah | 10% | Real profile URL + a note showing genuine exploration, not copy-paste |
+| common-qabilah | 5% | Real profile URL |
 | common-mortakaz | 15% | Two concrete products, technically-grounded integration with Ghaymah's AI stack, honest challenges |
-| Q1 memory module | 30% | Clear memory taxonomy, concrete storage choices, sensible write/read policy, runnable pseudocode, Ghaymah integration |
-| Q2 TTS/STT | 25% | Correct Arabic data/preprocessing/eval, realistic training config, deployable plan |
+| Q1 memory module | 25% | Clear memory taxonomy, concrete storage choices, sensible write/read policy, runnable pseudocode, Ghaymah integration |
+| Q2 TTS/STT | 15% | A well-justified model + dataset with correct Arabic specifics (dialect, diacritization, license) |
 | Q3 signup | 5% | Confirmed signup + thoughtful platform observations |
 | Q4 static site | 15% | A live URL that resolves + source committed + a short write-up |
+| Q5 LangChain agent | 20% | A working agent wired to Ghaymah's LLM endpoint, with at least one tool and clear code |
 
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