feat(genai/embeddings): migrate code retrieval and model tuning examples to genai

[XrossFox]

Description

This PR migrates and introduces new code examples for Vertex AI and GenAI embeddings.

Changes:

• feat: Added model_tuning_example.py to demonstrate text embedding model tuning using Vertex AI pipelines (aiplatform).
• feat: Added code_retrieval_example.py to demonstrate source code indexing and code retrieval queries using the google-genai SDK.
• test: Created test cases for the new examples in test_embeddings_examples.py.
• chore: Updated dependencies in requirements.txt and requirements-test.txt (bumped google-genai, pytest,
  google-api-core, and added google-cloud-aiplatform).

Fixes b/540948638

Checklist

Testing

• I have tested this change on a live environment and verified it works as intended.

Compliance & Style

• I have followed the Sample Guidelines.
• The README is updated with all relevant information (if applicable).
• If this PR adds a new sample directory: I updated the CODEOWNERS file.

---

Post-Approval Actions

• Please merge this PR for me once it is approved

[gemini-code-assist]

Code Review

This pull request introduces a new example script, code_retrieval_example.py, demonstrating how to use the Google GenAI SDK for code retrieval embeddings. The feedback highlights a few areas for improvement: correcting the return type annotation of the embed_test function to return response objects instead of config objects, removing an unused and unsupported DIMENSIONALITY constant, and ensuring consistent usage of the imported types module instead of referencing genai.types directly.

[XrossFox]

/gemini review

[gemini-code-assist]

Code Review

This pull request introduces two new embedding examples: code_retrieval_example.py for indexing and searching source code using the Gemini API, and model_tuning_example.py for tuning text embedding models via Vertex AI Pipelines. It also updates dependencies and adds corresponding unit tests. Feedback highlights several improvement opportunities, including mocking the Vertex AI Pipeline job in tests to prevent executing expensive live jobs, removing unused constants in both example files, correcting an incorrect return type hint in the code retrieval example, and fixing a typo in a test function name.