Batch Predict with Gemini using BigQuery data

Perform batch text prediction with Gemini using BigQuery data source as input.

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For detailed documentation that includes this code sample, see the following:

Code sample

Java

Before trying this sample, follow the Java setup instructions in the Vertex AI quickstart using client libraries . For more information, see the Vertex AI Java API reference documentation .

To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

  import static 
  
 com.google.genai.types.JobState.Known.JOB_STATE_CANCELLED 
 ; 
 import static 
  
 com.google.genai.types.JobState.Known.JOB_STATE_FAILED 
 ; 
 import static 
  
 com.google.genai.types.JobState.Known.JOB_STATE_PAUSED 
 ; 
 import static 
  
 com.google.genai.types.JobState.Known.JOB_STATE_SUCCEEDED 
 ; 
 import 
  
 com.google.genai.Client 
 ; 
 import 
  
 com.google.genai.types.BatchJob 
 ; 
 import 
  
 com.google.genai.types.BatchJobDestination 
 ; 
 import 
  
 com.google.genai.types.BatchJobSource 
 ; 
 import 
  
 com.google.genai.types.CreateBatchJobConfig 
 ; 
 import 
  
 com.google.genai.types.GetBatchJobConfig 
 ; 
 import 
  
 com.google.genai.types.HttpOptions 
 ; 
 import 
  
 com.google.genai.types.JobState 
 ; 
 import 
  
 java.util.EnumSet 
 ; 
 import 
  
 java.util.Set 
 ; 
 import 
  
 java.util.concurrent.TimeUnit 
 ; 
 public 
  
 class 
 BatchPredictionWithBq 
  
 { 
  
 public 
  
 static 
  
 void 
  
 main 
 ( 
 String 
 [] 
  
 args 
 ) 
  
 throws 
  
 InterruptedException 
  
 { 
  
 // TODO(developer): Replace these variables before running the sample. 
  
 // To use a tuned model, set the model param to your tuned model using the following format: 
  
 // modelId = "projects/{PROJECT_ID}/locations/{LOCATION}/models/{MODEL_ID} 
  
 String 
  
 modelId 
  
 = 
  
 "gemini-2.5-flash" 
 ; 
  
 String 
  
 outputUri 
  
 = 
  
 "bq://your-project.your_dataset.your_table" 
 ; 
  
 createBatchJob 
 ( 
 modelId 
 , 
  
 outputUri 
 ); 
  
 } 
  
 // Creates a batch prediction job with Google BigQuery. 
  
 public 
  
 static 
  
 JobState 
  
 createBatchJob 
 ( 
 String 
  
 modelId 
 , 
  
 String 
  
 outputUri 
 ) 
  
 throws 
  
 InterruptedException 
  
 { 
  
 // Client Initialization. Once created, it can be reused for multiple requests. 
  
 try 
  
 ( 
 Client 
  
 client 
  
 = 
  
 Client 
 . 
 builder 
 () 
  
 . 
 location 
 ( 
 "us-central1" 
 ) 
  
 . 
 vertexAI 
 ( 
 true 
 ) 
  
 . 
 httpOptions 
 ( 
 HttpOptions 
 . 
 builder 
 (). 
 apiVersion 
 ( 
 "v1" 
 ). 
 build 
 ()) 
  
 . 
 build 
 ()) 
  
 { 
  
 // See the documentation: 
  
 // https://googleapis.github.io/java-genai/javadoc/com/google/genai/Batches.html 
  
 BatchJobSource 
  
 batchJobSource 
  
 = 
  
 BatchJobSource 
 . 
 builder 
 () 
  
 . 
 bigqueryUri 
 ( 
 "bq://storage-samples.generative_ai.batch_requests_for_multimodal_input" 
 ) 
  
 . 
 format 
 ( 
 "bigquery" 
 ) 
  
 . 
 build 
 (); 
  
 CreateBatchJobConfig 
  
 batchJobConfig 
  
 = 
  
 CreateBatchJobConfig 
 . 
 builder 
 () 
  
 . 
 displayName 
 ( 
 "your-display-name" 
 ) 
  
 . 
 dest 
 ( 
 BatchJobDestination 
 . 
 builder 
 (). 
 bigqueryUri 
 ( 
 outputUri 
 ). 
 format 
 ( 
 "bigquery" 
 ). 
 build 
 ()) 
  
 . 
 build 
 (); 
  
 BatchJob 
  
 batchJob 
  
 = 
  
 client 
 . 
 batches 
 . 
 create 
 ( 
 modelId 
 , 
  
 batchJobSource 
 , 
  
 batchJobConfig 
 ); 
  
 String 
  
 jobName 
  
 = 
  
 batchJob 
 . 
 name 
 (). 
 orElseThrow 
 (() 
  
 - 
>  
 new 
  
 IllegalStateException 
 ( 
 "Missing job name" 
 )); 
  
 JobState 
  
 jobState 
  
 = 
  
 batchJob 
 . 
 state 
 (). 
 orElseThrow 
 (() 
  
 - 
>  
 new 
  
 IllegalStateException 
 ( 
 "Missing job state" 
 )); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Job name: " 
  
 + 
  
 jobName 
 ); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Job state: " 
  
 + 
  
 jobState 
 ); 
  
 // Job name: 
  
 // projects/.../locations/.../batchPredictionJobs/3189981423167602688 
  
 // Job state: JOB_STATE_PENDING 
  
 // See the documentation: 
  
 // https://googleapis.github.io/java-genai/javadoc/com/google/genai/types/BatchJob.html 
  
 Set<JobState 
 . 
 Known 
>  
 completedStates 
  
 = 
  
 EnumSet 
 . 
 of 
 ( 
 JOB_STATE_SUCCEEDED 
 , 
  
 JOB_STATE_FAILED 
 , 
  
 JOB_STATE_CANCELLED 
 , 
  
 JOB_STATE_PAUSED 
 ); 
  
 while 
  
 ( 
 ! 
 completedStates 
 . 
 contains 
 ( 
 jobState 
 . 
 knownEnum 
 ())) 
  
 { 
  
 TimeUnit 
 . 
 SECONDS 
 . 
 sleep 
 ( 
 30 
 ); 
  
 batchJob 
  
 = 
  
 client 
 . 
 batches 
 . 
 get 
 ( 
 jobName 
 , 
  
 GetBatchJobConfig 
 . 
 builder 
 (). 
 build 
 ()); 
  
 jobState 
  
 = 
  
 batchJob 
  
 . 
 state 
 () 
  
 . 
 orElseThrow 
 (() 
  
 - 
>  
 new 
  
 IllegalStateException 
 ( 
 "Missing job state during polling" 
 )); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Job state: " 
  
 + 
  
 jobState 
 ); 
  
 } 
  
 // Example response: 
  
 // Job state: JOB_STATE_QUEUED 
  
 // Job state: JOB_STATE_RUNNING 
  
 // Job state: JOB_STATE_RUNNING 
  
 // ... 
  
 // Job state: JOB_STATE_SUCCEEDED 
  
 return 
  
 jobState 
 ; 
  
 } 
  
 } 
 }

Python

Before trying this sample, follow the Python setup instructions in the Vertex AI quickstart using client libraries . For more information, see the Vertex AI Python API reference documentation .