langchain4j-spring-boot-integration

Name: langchain4j-spring-boot-integration
Author: giuseppe-trisciuoglio

1.6kinstalls36forks

How to install langchain4j-spring-boot-integration?

giuseppe-trisciuoglio/developer-kit/langchain4j-spring-boot-integration

$npx -y skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-spring-boot-integration

Installs into the current project.

Summary

Provides integration patterns for LangChain4j with Spring Boot. Configures AI model beans, sets up chat memory with Spring context, integrates RAG pipelines with Spring Data, and handles auto-configuration, dependency injection, and Spring ecosystem integration. Use when embeddin

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SKILL.md

1	# LangChain4j Spring Boot Integration
2
3	Integrate LangChain4j with Spring Boot using declarative AI Services, auto-configuration, and Spring Boot starters. Configure AI model beans, set up chat memory, implement RAG pipelines with Spring Data, and build production-ready AI applications.
4
5	## When to Use
6
7	Use this skill when:
8	- Integrating LangChain4j into existing Spring Boot applications
9	- Building AI-powered microservices with Spring Boot
10	- Configuring AI model beans with `@Bean` annotations
11	- Setting up auto-configuration for AI models and services
12	- Creating declarative AI Services with Spring dependency injection
13	- Implementing RAG systems with Spring Data integrations
14	- Setting up chat memory with Spring context management
15	- Configuring multiple AI providers (OpenAI, Azure, Ollama, Anthropic)
16	- Building production-ready AI applications with Spring Boot
17
18	## Overview
19
20	LangChain4j Spring Boot integration provides declarative AI Services through Spring Boot starters, enabling automatic configuration of AI components based on properties. Combine Spring dependency injection with LangChain4j's AI capabilities using interface-based definitions with annotations.
21
22	## Instructions
23
24	### 1. Add Dependencies
25
26	```xml
27	<!-- Core LangChain4j Spring Boot Starter -->
28	<dependency>
29	<groupId>dev.langchain4j</groupId>
30	<artifactId>langchain4j-spring-boot-starter</artifactId>
31	<version>1.8.0</version>
32	</dependency>
33
34	<!-- OpenAI Spring Boot Starter -->
35	<dependency>
36	<groupId>dev.langchain4j</groupId>
37	<artifactId>langchain4j-open-ai-spring-boot-starter</artifactId>
38	<version>1.8.0</version>
39	</dependency>
40	```
41
42	### 2. Configure Application Properties
43
44	```properties
45	# application.properties
46	langchain4j.open-ai.chat-model.api-key=${OPENAI_API_KEY}
47	langchain4j.open-ai.chat-model.model-name=gpt-4o-mini
48	langchain4j.open-ai.chat-model.temperature=0.7
49	langchain4j.open-ai.chat-model.timeout=PT60S
50	langchain4j.open-ai.chat-model.max-tokens=1000
51	```
52
53	Or using YAML:
54
55	```yaml
56	langchain4j:
57	open-ai:
58	chat-model:
59	api-key: ${OPENAI_API_KEY}
60	model-name: gpt-4o-mini
61	temperature: 0.7
62	timeout: 60s
63	max-tokens: 1000
64	```
65
66	### 3. Create Declarative AI Service
67
68	```java
69	import dev.langchain4j.service.spring.AiService;
70
71	@AiService
72	public interface CustomerSupportAssistant {
73
74	@SystemMessage("You are a helpful customer support agent for TechCorp.")
75	String handleInquiry(String customerMessage);
76
77	@UserMessage("Translate to {{language}}: {{text}}")
78	String translate(String text, String language);
79	}
80	```
81
82	### 4. Enable Component Scanning
83
84	```java
85	@SpringBootApplication
86	@ComponentScan(basePackages = {
87	"com.yourcompany",
88	"dev.langchain4j.service.spring"
89	})
90	public class Application {
91	public static void main(String[] args) {
92	SpringApplication.run(Application.class, args);
93	}
94	}
95	```
96
97	### 5. Inject and Use the AI Service
98
99	```java
100	@Service
101	public class CustomerService {
102
103	private final CustomerSupportAssistant assistant;
104
105	public CustomerService(CustomerSupportAssistant assistant) {
106	this.assistant = assistant;
107	}
108
109	public String processCustomerQuery(String query) {
110	return assistant.handleInquiry(query);
111	}
112	}
113	```
114
115	### 6. Verify the Integration
116
117	After setup, verify the configuration:
118	1. Start the application and check logs for `LangChain4jSpringBootAutoConfiguration` activation
119	2. Confirm AI service beans are registered: look for `CustomerSupportAssistant` in Spring context
120	3. Test the service: invoke `assistant.handleInquiry("test")` and verify a response is returned
121
122	## Configuration
123
124	Property-Based Configuration: Configure AI models through `application.properties` for different providers.
125
126	Manual Bean Configuration: For advanced configurations, define beans manually:
127
128	```java
129	@Configuration
130	public class AiConfig {
131
132	@Bean
133	public ChatModel chatModel(@Value("${OPENAI_API_KEY}") String apiKey) {
134	return OpenAiChatModel.builder()
135	.apiKey(apiKey)
136	.modelName("gpt-4o-mini")
137	.temperature(0.7)
138	.build();
139	}
140	}
141	```
142
143	Multiple Providers: Use explicit wiring when configuring multiple AI providers:
144
145	```java
146	@AiService(wiringMode = WiringMode.EXPLICIT)
147	interface MultiProviderAssistant {
148	@AiServiceAnnotation
149	ChatModel openAiModel;
150
151	@AiServiceAnnotation
152	ChatModel azureModel;
153	}
154	```
155
156	## Declarative AI Services
157
158	Basic AI Service: Create interfaces with `@A

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langchain4j-spring-boot-integration

1.6kinstalls36forks

View on GitHub

How to install langchain4j-spring-boot-integration?

giuseppe-trisciuoglio/developer-kit/langchain4j-spring-boot-integration

$npx -y skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-spring-boot-integration

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# LangChain4j Spring Boot Integration
2
3	Integrate LangChain4j with Spring Boot using declarative AI Services, auto-configuration, and Spring Boot starters. Configure AI model beans, set up chat memory, implement RAG pipelines with Spring Data, and build production-ready AI applications.
4
5	## When to Use
6
7	Use this skill when:
8	- Integrating LangChain4j into existing Spring Boot applications
9	- Building AI-powered microservices with Spring Boot
10	- Configuring AI model beans with `@Bean` annotations
11	- Setting up auto-configuration for AI models and services
12	- Creating declarative AI Services with Spring dependency injection
13	- Implementing RAG systems with Spring Data integrations
14	- Setting up chat memory with Spring context management
15	- Configuring multiple AI providers (OpenAI, Azure, Ollama, Anthropic)
16	- Building production-ready AI applications with Spring Boot
17
18	## Overview
19
20	LangChain4j Spring Boot integration provides declarative AI Services through Spring Boot starters, enabling automatic configuration of AI components based on properties. Combine Spring dependency injection with LangChain4j's AI capabilities using interface-based definitions with annotations.
21
22	## Instructions
23
24	### 1. Add Dependencies
25
26	```xml
27	<!-- Core LangChain4j Spring Boot Starter -->
28	<dependency>
29	<groupId>dev.langchain4j</groupId>
30	<artifactId>langchain4j-spring-boot-starter</artifactId>
31	<version>1.8.0</version>
32	</dependency>
33
34	<!-- OpenAI Spring Boot Starter -->
35	<dependency>
36	<groupId>dev.langchain4j</groupId>
37	<artifactId>langchain4j-open-ai-spring-boot-starter</artifactId>
38	<version>1.8.0</version>
39	</dependency>
40	```
41
42	### 2. Configure Application Properties
43
44	```properties
45	# application.properties
46	langchain4j.open-ai.chat-model.api-key=${OPENAI_API_KEY}
47	langchain4j.open-ai.chat-model.model-name=gpt-4o-mini
48	langchain4j.open-ai.chat-model.temperature=0.7
49	langchain4j.open-ai.chat-model.timeout=PT60S
50	langchain4j.open-ai.chat-model.max-tokens=1000
51	```
52
53	Or using YAML:
54
55	```yaml
56	langchain4j:
57	open-ai:
58	chat-model:
59	api-key: ${OPENAI_API_KEY}
60	model-name: gpt-4o-mini
61	temperature: 0.7
62	timeout: 60s
63	max-tokens: 1000
64	```
65
66	### 3. Create Declarative AI Service
67
68	```java
69	import dev.langchain4j.service.spring.AiService;
70
71	@AiService
72	public interface CustomerSupportAssistant {
73
74	@SystemMessage("You are a helpful customer support agent for TechCorp.")
75	String handleInquiry(String customerMessage);
76
77	@UserMessage("Translate to {{language}}: {{text}}")
78	String translate(String text, String language);
79	}
80	```
81
82	### 4. Enable Component Scanning
83
84	```java
85	@SpringBootApplication
86	@ComponentScan(basePackages = {
87	"com.yourcompany",
88	"dev.langchain4j.service.spring"
89	})
90	public class Application {
91	public static void main(String[] args) {
92	SpringApplication.run(Application.class, args);
93	}
94	}
95	```
96
97	### 5. Inject and Use the AI Service
98
99	```java
100	@Service
101	public class CustomerService {
102
103	private final CustomerSupportAssistant assistant;
104
105	public CustomerService(CustomerSupportAssistant assistant) {
106	this.assistant = assistant;
107	}
108
109	public String processCustomerQuery(String query) {
110	return assistant.handleInquiry(query);
111	}
112	}
113	```
114
115	### 6. Verify the Integration
116
117	After setup, verify the configuration:
118	1. Start the application and check logs for `LangChain4jSpringBootAutoConfiguration` activation
119	2. Confirm AI service beans are registered: look for `CustomerSupportAssistant` in Spring context
120	3. Test the service: invoke `assistant.handleInquiry("test")` and verify a response is returned
121
122	## Configuration
123
124	Property-Based Configuration: Configure AI models through `application.properties` for different providers.
125
126	Manual Bean Configuration: For advanced configurations, define beans manually:
127
128	```java
129	@Configuration
130	public class AiConfig {
131
132	@Bean
133	public ChatModel chatModel(@Value("${OPENAI_API_KEY}") String apiKey) {
134	return OpenAiChatModel.builder()
135	.apiKey(apiKey)
136	.modelName("gpt-4o-mini")
137	.temperature(0.7)
138	.build();
139	}
140	}
141	```
142
143	Multiple Providers: Use explicit wiring when configuring multiple AI providers:
144
145	```java
146	@AiService(wiringMode = WiringMode.EXPLICIT)
147	interface MultiProviderAssistant {
148	@AiServiceAnnotation
149	ChatModel openAiModel;
150
151	@AiServiceAnnotation
152	ChatModel azureModel;
153	}
154	```
155
156	## Declarative AI Services
157
158	Basic AI Service: Create interfaces with `@A

People who liked this also viewed

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Type