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new 3b314cfb OpenAI article - Part 2 (#1472)
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commit 3b314cfbed31ecb115f408c89c46ca9e342b9250
Author: Claus Ibsen <[email protected]>
AuthorDate: Wed Jan 14 09:08:22 2026 +0100
OpenAI article - Part 2 (#1472)
* blog: Simple LLM Integration with Camel OpenAI Component
---------
Co-authored-by: Ivo Bek <[email protected]>
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+---
+title: "Simple LLM Integration with Camel OpenAI Component"
+date: 2026-01-14
+draft: false
+authors: [ ibek ]
+categories: [ "Camel", "AI" ]
+preview: "A deep dive into the new camel-openai component for chat completion
with OpenAI and OpenAI-compatible APIs"
+---
+
+The integration of Large Language Models (LLMs) into enterprise applications
has become increasingly important. Whether
+you're building intelligent document processing pipelines, automated customer
support systems, or data privacy
+solutions, the ability to seamlessly connect your integration flows with AI
capabilities is essential.
+
+Apache Camel 4.17 introduces the new `camel-openai` component, providing
native integration with OpenAI and
+OpenAI-compatible APIs for chat completion. In this post, we'll explore the
component's features and demonstrate a
+practical use case: Personal Identifiable Information (PII) redaction using
structured output.
+
+## Component Overview
+
+The `camel-openai` component leverages the official [openai-java
SDK](https://github.com/openai/openai-java) to provide
+robust integration with OpenAI's chat completion API. It offers a lightweight
alternative to LangChain4j and Spring AI
+for straightforward use cases, eliminating the need to instantiate `ChatModel`
objects. Here are the key features:
+
+- **Chat Completion**: Send prompts and receive AI-generated responses
+- **Structured Output**: Get responses in a specific format using
`outputClass` or `jsonSchema`
+- **Streaming Responses**: Process responses chunk by chunk for real-time
applications
+- **Conversation Memory**: Maintain context across multiple exchanges within a
route
+- **Multi-Modal Input**: Support for text files and images with vision-capable
models
+- **OpenAI-Compatible APIs**: Works with OpenAI, Google Vertex AI, Mistral,
Groq, vLLM, NVIDIA NIM, Ollama, Llama.cpp
+ server, and other providers
+
+**Note**: This component is not designed for autonomous agentic workflows. It
explicitly excludes function calling (
+tools). For complex agent architectures, we recommend using LangChain4j or
Spring AI.
+
+## Getting Started
+
+Add the component dependency to your project:
+
+```xml
+<dependency>
+ <groupId>org.apache.camel</groupId>
+ <artifactId>camel-openai</artifactId>
+ <version>4.17.0</version>
+</dependency>
+```
+
+### Basic Chat Completion
+
+The simplest usage sends a prompt and receives a response:
+
+```java
+from("direct:chat")
+ .setBody(constant("What is Apache Camel?"))
+ .to("openai:chat-completion")
+ .log("Response: ${body}");
+```
+
+Or using YAML DSL:
+
+```yaml
+- route:
+ from:
+ uri: direct:chat
+ steps:
+ - to:
+ uri: openai:chat-completion
+ parameters:
+ userMessage: What is Apache Camel?
+ - log: "Response: ${body}"
+```
+
+### Authentication
+
+The component requires setting the API key using, `apiKey` parameter, or
`OPENAI_API_KEY` environment variable.
+
+## PII Redaction Example: Structured Output in Action
+
+Let's explore a practical example that demonstrates the power of structured
output with JSON schemas. This example uses
+an LLM to identify and redact Personal Identifiable Information from text,
returning results in a structured JSON
+format.
+
+### The Route Definition
+
+```yaml
+- route:
+ from:
+ uri: "direct:pii-redaction"
+ steps:
+ - to:
+ uri: "openai:chat-completion"
+ parameters:
+ temperature: 0.15
+ jsonSchema: "resource:classpath:pii.schema.json"
+ systemMessage: You are a strict data privacy compliance
assistant. Your goal is to analyze the user input, redact all PII, and return
the results in the specified JSON format.
+- route:
+ from:
+ uri: stream
+ parameters:
+ kind: in
+ steps:
+ - to:
+ uri: direct
+ parameters:
+ name: pii-redaction
+ - to: "stream:out"
+```
+
+NOTE: We should set the temperature because in 4.17.0 release, temperature
default is being set to 1.0 (this will be
+removed to respect inference server's configuration in the next release)
+
+The route uses:
+- **Low Temperature (0.15)**: For consistent, deterministic responses
+- **JSON Schema**: Enforces the structure of the output
+- **System Message**: Instructs the model on its role and behavior
+
+### The JSON Schema
+
+The `pii.schema.json` defines the expected output structure:
+
+```json
+{
+ "type": "object",
+ "properties": {
+ "detectedPII": {
+ "type": "array",
+ "description": "A list of all PII entities detected and redacted.",
+ "items": {
+ "type": "object",
+ "properties": {
+ "span": {
+ "type": "string",
+ "description": "The original text value that was detected."
+ },
+ "type": {
+ "type": "string",
+ "enum": [
+ "PERSON",
+ "EMAIL",
+ "PHONE",
+ "CREDIT_CARD",
+ "NATIONAL_ID",
+ "ADDRESS",
+ "OTHER"
+ ],
+ "description": "The category of the detected PII"
+ },
+ "action": {
+ "type": "string",
+ "enum": [
+ "MASKED",
+ "REDACTED"
+ ],
+ "description": "The action taken on the data"
+ }
+ },
+ "required": [
+ "span",
+ "type",
+ "action"
+ ],
+ "additionalProperties": false
+ }
+ },
+ "sanitizedText": {
+ "type": "string",
+ "description": "The input text with all PII replaced by placeholders"
+ }
+ },
+ "required": [
+ "detectedPII",
+ "sanitizedText"
+ ],
+ "additionalProperties": false
+}
+```
+
+### Configuration
+
+Configure the component in `application.properties`:
+
+```properties
+camel.jbang.dependencies=camel-openai
+camel.component.openai.apiKey={{env:OPENAI_API_KEY}}
+camel.component.openai.baseUrl={{env:OPENAI_BASE_URL}}
+camel.component.openai.model={{env:OPENAI_MODEL}}
+camel.main.durationMaxMessages=1
+```
+
+### Running the Example
+
+Set up your environment variables:
+
+```shell
+export OPENAI_API_KEY=<your-openai-api-key>
+export OPENAI_BASE_URL=http://localhost:8181/v1
+export OPENAI_MODEL=unsloth/Ministral-3-8B-Instruct-2512-GGUF
+```
+
+Run with Camel JBang:
+
+```shell
+echo 'Customer John Doe (email: [email protected]) requested a refund for
order #998877.' | camel run *
+```
+
+### Expected Output
+
+```json
+{
+ "detectedPII": [
+ {
+ "span": "John Doe",
+ "type": "PERSON",
+ "action": "REDACTED"
+ },
+ {
+ "span": "[email protected]",
+ "type": "EMAIL",
+ "action": "REDACTED"
+ }
+ ],
+ "sanitizedText": "Customer [REDACTED] ([REDACTED]) requested a refund for
order #998877."
+}
+```
+
+## Conclusion
+
+The `camel-openai` component in Apache Camel 4.17 provides a powerful and
flexible way to integrate LLM capabilities
+into your integration flows. With support for structured output, streaming,
conversation memory, and compatibility with
+various OpenAI-compatible providers, you can build sophisticated AI-powered
integrations with minimal code.
+
+The PII redaction example demonstrates how structured output with JSON schemas
enables reliable, parseable responses
+from LLMs - a critical capability for enterprise applications where consistent
data formats are required.
+
+For more information, check out:
+
+- [Apache Camel OpenAI Component
Documentation](/components/next/openai-component.html)
+- [Camel OpenAI
examples](https://github.com/apache/camel-jbang-examples/openai)
+- [Apache Camel 4.17 Release Notes](/releases/release-4.17.0/)
+- [Apache Camel 4.17 What's New](/blog/2026/01/camel417-whatsnew/)
+
+We'd love to hear about what you build with the OpenAI component. Share your
experiences on the Apache Camel mailing
+list or join us on Zulip chat!
+
+Happy integrating!
