krishp091205/gemini-config/bigquery-ai-ml

BigQuery AI & ML

BigQuery integrates with Vertex AI to provide powerful machine learning and generative AI capabilities directly within SQL queries using built-in functions like AI.FORECAST, AI.KEY_DRIVERS, AI.DETECT_ANOMALIES, and AI.GENERATE.

[!IMPORTANT]

You MUST read and follow the global constraints and mandatory function routing rules in

ai_function_best_practices.md before writing any BQML AI/ML SQL query.

Reference Directory

• Best Practices:

ai_function_best_practices.md

• Functions Reference:

• AI.AGG: ai_agg.md - Multi-row semantic

aggregation and summarization.

• AI.CLASSIFY: ai_classify.md -

Classify text.

• AI.DETECT_ANOMALIES:

ai_detect_anomalies.md - Detect anomalies.

• AI.EVALUATE: ai_evaluate.md -

Evaluate models.

• AI.FORECAST: ai_forecast.md -

Time-series forecasting.

• AI.GENERATE: ai_generate.md -

Generate text using LLMs.

• AI.GENERATE_EMBEDDING:

ai_generate_embedding.md - Generate embeddings.

• AI.GENERATE_TABLE:

ai_generate_table.md - Table-valued AI generation.

• AI.IF: ai_if.md - Evaluate semantic

conditions.

• AI.KEY_DRIVERS:

ai_key_drivers.md - Identifies key drivers, this is a TVF.

• AI.SCORE: ai_score.md - Score data.
• AI.SEARCH: ai_search.md - Semantic

search.

• AI.SIMILARITY:

ai_similarity.md - Semantic similarity.

• Remote Models:

remote_models.md - Working with remote models (Vertex AI).

• CONTRIBUTION_ANALYSIS:

ml_contribution_analysis.md

• Finds contributing factors, key drivers of change. Requires creating

a MODEL entity.

• VECTOR_SEARCH:

vector_search.md - Vector search best practices.