Add code samples for Agent Search

[sailobo]

Description

Adds 9 supportability-driven Python code samples for Vertex AI Search (Agent Search / Discovery Engine) addressing high-frequency customer implementation patterns:

1. converse_conversation_sample.py (genappbuilder_converse_conversation): Multi-turn conversational search using ConversationalSearchServiceClient (session initialization and continuation).
2. create_document_metadata_sample.py (genappbuilder_create_document_metadata): Structured document ingestion passing dictionary metadata directly into Document(struct_data=...).
3. enable_gemini_layout_parser_sample.py (genappbuilder_enable_gemini_layout_parser): Data store creation with Gemini LLM layout parsing, table/image annotations, and chunking config.
4. update_data_store_gemini_parser_sample.py (genappbuilder_update_data_store_gemini_parser): Dedicated sample to update an existing data store to enable Gemini layout parser with update_mask.
5. import_custom_chunks_sample.py (genappbuilder_import_custom_chunks): Bring-Your-Own-Chunks (BYOC) document ingestion with inlined BYOC JSON schema explanation.
6. poll_lro_robust_sample.py (genappbuilder_poll_lro_robust): Exponential backoff polling for long-running operations (Operation.metadata and error unpacking).
7. search_chunks_sample.py (genappbuilder_search_chunks): Chunk-mode search query returning chunk content, parent document metadata, and adjacent previous/next snippets.
8. search_extractive_segments_sample.py (genappbuilder_search_extractive_segments): Multi-data store search with extractive segments and relevance confidence scores.
9. write_user_event_sample.py (genappbuilder_write_user_event): User event ingestion with search attribution tokens for search quality feedback loops.

Includes comprehensive unit tests in discoveryengine/supportability_samples_test.py.

Reviewers: @holtskinner, @janeday
Internal Reference: cl/972770246

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.

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Post-Approval Actions

• Please merge this PR for me once it is approved

[snippet-bot]

Here is the summary of changes.

You are about to add 9 region tags.

• discoveryengine/converse_conversation_sample.py:17, tag genappbuilder_converse_conversation
• discoveryengine/create_document_metadata_sample.py:17, tag genappbuilder_create_document_metadata
• discoveryengine/enable_gemini_layout_parser_sample.py:17, tag genappbuilder_enable_gemini_layout_parser
• discoveryengine/import_custom_chunks_sample.py:17, tag genappbuilder_import_custom_chunks
• discoveryengine/poll_lro_robust_sample.py:17, tag genappbuilder_poll_lro_robust
• discoveryengine/search_chunks_sample.py:17, tag genappbuilder_search_chunks
• discoveryengine/search_extractive_segments_sample.py:17, tag genappbuilder_search_extractive_segments
• discoveryengine/update_data_store_gemini_parser_sample.py:17, tag genappbuilder_update_data_store_gemini_parser
• discoveryengine/write_user_event_sample.py:17, tag genappbuilder_write_user_event

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[gemini-code-assist]

Code Review

This pull request introduces several Python code samples and corresponding unit tests for Google Cloud Discovery Engine (Agent Search), covering features like multi-turn conversational search, structured document ingestion, Gemini layout parsing, custom chunk imports, robust LRO polling, and user event recording. The review feedback highlights several improvement opportunities: avoiding the hasattr anti-pattern on Protobuf messages in converse_conversation_sample.py, adding defensive None checks to prevent potential AttributeErrors in create_document_metadata_sample.py and search_extractive_segments_sample.py, and using the idiomatic GetCurrentTime() method for Protobuf timestamps in write_user_event_sample.py.

[gemini-code-assist]

Using hasattr to check for the presence of fields on Protobuf or proto-plus messages is an anti-pattern because these attributes are always defined on the class descriptor, meaning hasattr will always return True regardless of whether the field is set. Instead, directly check the truthiness of the fields, which is more idiomatic and robust.

    if response.reply.summary and response.reply.summary.summary_text:
      reply_text = response.reply.summary.summary_text
    elif response.reply.reply:
      reply_text = response.reply.reply

[gemini-code-assist]

Instead of manually calculating seconds and nanoseconds from time.time(), you can use the built-in GetCurrentTime() method on the Protobuf Timestamp object. This simplifies the code and makes it more idiomatic.

  # Set accurate UTC event timestamp
  event_time = timestamp_pb2.Timestamp()
  event_time.GetCurrentTime()

[holtskinner]

@sailobo Be sure to register your GitHub account with Google internally. Also address the lint isses https://github.com/GoogleCloudPlatform/python-docs-samples/actions/runs/34269115170/job/102206281775?pr=14591 and the Gemini Code Assist comments

[sailobo]

@sailobo Be sure to register your GitHub account with Google internally. Also address the lint isses https://github.com/GoogleCloudPlatform/python-docs-samples/actions/runs/34269115170/job/102206281775?pr=14591 and the Gemini Code Assist comments

@holtskinner I have applied the batched suggestions from the Gemini Code Assist bot to address the review feedback and lint issues. Also, I have double-checked, and my GitHub account is successfully registered internally (I will need to follow up in aligning ldap as per a previous registration error )

Could you please approve the workflow runs so the checks can proceed against these new commits?