IBM watsonx.ai

from("direct:simpleChat")
  .setBody(constant("What is the capital of France?"))
  .to("ibm-watsonx-ai:chat?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&modelId=ibm/granite-4-h-small" +
      "&operation=chat")
  .log("Response: ${body}");

from("direct:chatWithSystem")
  .setHeader("CamelIBMWatsonxAiSystemMessage",
      constant("You are a helpful assistant. Keep your answers brief."))
  .setBody(constant("What is the capital of Italy?"))
  .to("ibm-watsonx-ai:chat?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&modelId=ibm/granite-4-h-small" +
      "&operation=chat")
  .log("Response: ${body}");

import com.ibm.watsonx.ai.chat.model.UserMessage;

from("direct:streamChat")
  .process(exchange -> {
      // Set up a consumer to handle streamed chunks
      Consumer<String> streamHandler = chunk -> {
          System.out.print(chunk);
      };
      exchange.getIn().setHeader("CamelIBMWatsonxAiStreamConsumer", streamHandler);
      exchange.getIn().setHeader("CamelIBMWatsonxAiMessages", List.of(
          UserMessage.text("Tell me a joke about programming")
      ));
  })
  .to("ibm-watsonx-ai:chat?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&modelId=ibm/granite-4-h-small" +
      "&operation=chatStreaming")
  .log("Full response: ${body}");

from("direct:embed")
  .setBody(constant(List.of(
      "Apache Camel is an integration framework",
      "Quarkus is a Java framework"
  )))
  .to("ibm-watsonx-ai:embed?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&modelId=ibm/slate-125m-english-rtrvr" +
      "&operation=embedding")
  .process(exchange -> {
      List<List<Float>> embeddings = exchange.getMessage().getBody(List.class);
      System.out.println("Generated " + embeddings.size() + " embeddings");
      System.out.println("Embedding dimensions: " + embeddings.get(0).size());
  });

from("direct:embedSingle")
  .setBody(constant("Apache Camel makes integration easy"))
  .to("ibm-watsonx-ai:embed?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&modelId=ibm/slate-125m-english-rtrvr" +
      "&operation=embedding")
  .log("Embedding vector size: ${header.CamelIBMWatsonxAiEmbeddings[0].size()}");

import org.apache.camel.component.qdrant.Qdrant;
import org.apache.camel.component.qdrant.QdrantAction;
import io.qdrant.client.PointIdFactory;
import io.qdrant.client.VectorsFactory;
import io.qdrant.client.ValueFactory;
import io.qdrant.client.grpc.Points;

from("direct:embedAndStore")
  .setBody(constant("Apache Camel makes integration easy"))
  .to("ibm-watsonx-ai:embed?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&modelId=ibm/slate-125m-english-rtrvr" +
      "&operation=embedding")
  // Transform to Qdrant format and upsert
  .setHeader(Qdrant.Headers.ACTION, constant(QdrantAction.UPSERT))
  .process(exchange -> {
      List<Float> embedding = exchange.getMessage().getBody(List.class);
      exchange.getMessage().setBody(
          Points.PointStruct.newBuilder()
              .setId(PointIdFactory.id(UUID.randomUUID()))
              .setVectors(VectorsFactory.vectors(embedding))
              .putPayload("text", ValueFactory.value("Apache Camel makes integration easy"))
              .build());
  })
  .to("qdrant:embeddings?host=localhost&port=6334")
  .log("Embedding stored with ID: ${header.CamelQdrantOperationID}");

from("direct:rerank")
  .process(exchange -> {
      // Set the query to rank against
      exchange.getIn().setHeader("CamelIBMWatsonxAiRerankQuery",
          "What is the best integration framework?");
      // Set documents to rerank
      exchange.getIn().setBody(List.of(
          "Apache Camel provides enterprise integration patterns.",
          "Quarkus is great for microservices.",
          "Kubernetes orchestrates containers.",
          "Apache Kafka handles event streaming."
      ));
  })
  .to("ibm-watsonx-ai:rerank?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&modelId=cross-encoder/ms-marco-minilm-l-12-v2" +
      "&operation=rerank")
  .process(exchange -> {
      List results = exchange.getMessage().getBody(List.class);
      System.out.println("Reranked results: " + results);
  });

from("direct:rerankTopN")
  .setHeader("CamelIBMWatsonxAiRerankQuery", constant("Cloud computing platform"))
  .setHeader("CamelIBMWatsonxAiRerankTopN", constant(3))
  .setBody(constant(List.of(
      "AWS is a cloud computing platform.",
      "Azure provides cloud services.",
      "IBM Cloud offers cloud solutions.",
      "PostgreSQL is a database.",
      "Infinispan is an in-memory store."
  )))
  .to("ibm-watsonx-ai:rerank?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&modelId=cross-encoder/ms-marco-minilm-l-12-v2" +
      "&operation=rerank")
  .log("Top 3 results: ${body}");

from("direct:tokenize")
  .setBody(constant("Hello, how are you today?"))
  .to("ibm-watsonx-ai:tokenize?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&modelId=ibm/granite-4-h-small" +
      "&operation=tokenize")
  .log("Token count: ${header.CamelIBMWatsonxAiTokenCount}")
  .log("Tokens: ${header.CamelIBMWatsonxAiTokens}");

from("direct:detect")
  .setBody(constant("Contact John Smith at john.smith@example.com or call 555-123-4567"))
  .to("ibm-watsonx-ai:detect?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&operation=detect" +
      "&detectPii=true")
  .choice()
    .when(header("CamelIBMWatsonxAiDetected").isEqualTo(true))
      .log("PII detected! Count: ${header.CamelIBMWatsonxAiDetectionCount}")
      .log("Detection details: ${header.CamelIBMWatsonxAiDetectionResults}")
    .otherwise()
      .log("No PII detected in content")
  .end();

from("direct:detectHap")
  .setBody(constant("Some text that might contain harmful content"))
  .to("ibm-watsonx-ai:detect?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&operation=detect" +
      "&detectHap=true" +
      "&detectionThreshold=0.5")
  .choice()
    .when(header("CamelIBMWatsonxAiDetected").isEqualTo(true))
      .log("ALERT: Harmful content detected!")
    .otherwise()
      .log("Content is safe")
  .end();

import com.ibm.watsonx.ai.detection.detector.Pii;
import com.ibm.watsonx.ai.detection.detector.Hap;

from("direct:detectCustom")
  .process(exchange -> {
      exchange.getIn().setBody("Check this email: user@domain.com");
      exchange.getIn().setHeader("CamelIBMWatsonxAiDetectors", List.of(
          Pii.ofDefaults(),
          Hap.builder().threshold(0.3).build()
      ));
  })
  .to("ibm-watsonx-ai:detect?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&operation=detect")
  .log("Detections: ${body}");

from("direct:extract")
  .setBody(constant("documents/report.pdf"))  // Path in COS bucket
  .to("ibm-watsonx-ai:extract?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&operation=textExtraction" +
      "&cosUrl=https://s3.us-south.cloud-object-storage.appdomain.cloud" +
      "&documentConnectionId=your-cos-connection-id" +
      "&documentBucket=your-input-bucket" +
      "&resultConnectionId=your-cos-connection-id" +
      "&resultBucket=your-output-bucket")
  .process(exchange -> {
      String extractionId = exchange.getMessage().getHeader("CamelIBMWatsonxAiExtractionId", String.class);
      String status = exchange.getMessage().getHeader("CamelIBMWatsonxAiExtractionStatus", String.class);
      System.out.println("Extraction job started: " + extractionId);
      System.out.println("Status: " + status);
  });

from("direct:fetchExtraction")
  .setHeader("CamelIBMWatsonxAiExtractionId", constant("your-extraction-job-id"))
  .to("ibm-watsonx-ai:extract?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&operation=textExtractionFetch" +
      "&cosUrl=https://s3.us-south.cloud-object-storage.appdomain.cloud" +
      "&documentConnectionId=your-cos-connection-id" +
      "&documentBucket=your-input-bucket" +
      "&resultConnectionId=your-cos-connection-id" +
      "&resultBucket=your-output-bucket")
  .log("Extraction status: ${header.CamelIBMWatsonxAiExtractionStatus}");

from("file:/path/to/documents?noop=true")
  .to("ibm-watsonx-ai:extract?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&operation=textExtractionUploadAndFetch" +
      "&cosUrl=https://s3.us-south.cloud-object-storage.appdomain.cloud" +
      "&documentConnectionId=your-cos-connection-id" +
      "&documentBucket=your-input-bucket" +
      "&resultConnectionId=your-cos-connection-id" +
      "&resultBucket=your-output-bucket")
  .log("Extracted text: ${body}")
  .log("File processed: ${header.CamelFileName}");

// From local file system
from("file:/documents/incoming?noop=true")
  .to("ibm-watsonx-ai:extract?operation=textExtractionUploadAndFetch...")
  .log("Extracted text from ${header.CamelFileName}: ${body}");

// From FTP/SFTP
from("sftp://server/documents?username=xxx&password=xxx")
  .to("ibm-watsonx-ai:extract?operation=textExtractionUploadAndFetch...")
  .log("Extracted: ${header.CamelIBMWatsonxAiExtractedText}");

// From AWS S3
from("aws2-s3://my-bucket?region=us-east-1&prefix=docs/")
  .to("ibm-watsonx-ai:extract?operation=textExtractionUploadAndFetch...")
  .log("Extracted text from S3 object");

// From Azure Blob Storage
from("azure-storage-blob://mycontainer?prefix=documents/")
  .to("ibm-watsonx-ai:extract?operation=textExtractionUploadAndFetch...")
  .log("Extracted text from blob");

from("direct:headerInput")
  .setHeader("CamelIBMWatsonxAiInput", constant("What is machine learning?"))
  .to("ibm-watsonx-ai:gen?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&modelId=ibm/granite-13b-instruct-v2" +
      "&operation=textGeneration")
  .log("Generated text: ${body}");

from("direct:metadata")
  .setBody(constant("Summarize the benefits of cloud computing"))
  .to("ibm-watsonx-ai:gen?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&modelId=ibm/granite-13b-instruct-v2" +
      "&operation=textGeneration")
  .log("Generated: ${body}")
  .log("Input tokens: ${header.CamelIBMWatsonxAiInputTokenCount}")
  .log("Output tokens: ${header.CamelIBMWatsonxAiOutputTokenCount}")
  .log("Stop reason: ${header.CamelIBMWatsonxAiStopReason}");

import com.ibm.watsonx.ai.timeseries.InputSchema;
import com.ibm.watsonx.ai.timeseries.ForecastData;

from("direct:forecast")
  .process(exchange -> {
      // Define the schema
      InputSchema schema = InputSchema.builder()
          .timestampColumn("date")
          .addIdColumn("series_id")
          .build();

      // Create forecast data
      ForecastData data = ForecastData.create()
          .addAll("date", "2024-01-01T00:00:00", "2024-01-02T00:00:00", "2024-01-03T00:00:00")
          .add("series_id", "S1", 3)
          .addAll("value", 10.5, 12.3, 11.8);

      exchange.getIn().setHeader("CamelIBMWatsonxAiForecastInputSchema", schema);
      exchange.getIn().setHeader("CamelIBMWatsonxAiForecastData", data);
  })
  .to("ibm-watsonx-ai:forecast?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&projectId=yourProjectId" +
      "&modelId=ibm/granite-ttm-1536-96-r2" +
      "&operation=forecast")
  .log("Forecast results: ${body}");

from("direct:listModels")
  .to("ibm-watsonx-ai:models?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&operation=listModels")
  .process(exchange -> {
      List models = exchange.getMessage().getBody(List.class);
      models.forEach(model -> System.out.println("Model: " + model));
  });

from("direct:listTasks")
  .to("ibm-watsonx-ai:tasks?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&operation=listTasks")
  .log("Available tasks: ${body}");

import com.ibm.watsonx.ai.chat.model.UserMessage;

from("direct:deploymentChat")
  .setBody(constant("What is the capital of France?"))
  .to("ibm-watsonx-ai:deploy?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&deploymentId=your-deployment-id" +
      "&operation=deploymentChat")
  .log("Response: ${body}");

from("direct:runTool")
  .process(exchange -> {
      // Set tool name
      exchange.getIn().setHeader("CamelIBMWatsonxAiToolName", "GoogleSearch");
      // Set structured input
      exchange.getIn().setBody(Map.of("q", "Apache Camel integration framework"));
      // Optional: set config
      exchange.getIn().setHeader("CamelIBMWatsonxAiToolConfig", Map.of("maxResults", 5));
  })
  .to("ibm-watsonx-ai:tool?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&operation=runTool")
  .log("Tool result: ${body}");

from("direct:listTools")
  .to("ibm-watsonx-ai:tools?apiKey=RAW(yourApiKey)" +
      "&baseUrl=https://us-south.ml.cloud.ibm.com" +
      "&operation=listTools")
  .process(exchange -> {
      List tools = exchange.getMessage().getBody(List.class);
      System.out.println("Available tools: " + tools.size());
  });