Merge branch 'main' into main

docs/docs/integrations/embedding-models/xinference.md

@@ -0,0 +1,43 @@
+---
+sidebar_position: 20
+---
+
+# Xinference
+
+- https://inference.readthedocs.io/
+
+
+## Maven Dependency
+
+`0.37.0` and later:
+
+```xml
+<dependency>
+    <groupId>dev.langchain4j</groupId>
+    <artifactId>langchain4j-community-xinference</artifactId>
+    <version>0.37.0</version>
+</dependency>
+```
+
+Or, you can use BOM to manage dependencies consistently:
+
+```xml
+<dependencyManagement>
+    <dependency>
+        <groupId>dev.langchain4j</groupId>
+        <artifactId>langchain4j-community-bom</artifactId>
+        <version>0.37.0</version>
+        <typ>pom</typ>
+        <scope>import</scope>
+    </dependency>
+</dependencyManagement>
+```
+
+## APIs
+
+- `XinferenceEmbeddingModel`
+
+
+## Examples
+
+- [XinferenceEmbeddingModelIT](https://github.com/langchain4j/langchain4j-community/blob/main/models/langchain4j-community-xinference/src/test/java/dev/langchain4j/community/model/xinference/XinferenceEmbeddingModelIT.java)

docs/docs/integrations/image-models/xinference.md

@@ -0,0 +1,43 @@
+---
+sidebar_position: 6
+---
+
+# Xinference
+
+- https://inference.readthedocs.io/
+
+
+## Maven Dependency
+
+`0.37.0` and later:
+
+```xml
+<dependency>
+    <groupId>dev.langchain4j</groupId>
+    <artifactId>langchain4j-community-xinference</artifactId>
+    <version>0.37.0</version>
+</dependency>
+```
+
+Or, you can use BOM to manage dependencies consistently:
+
+```xml
+<dependencyManagement>
+    <dependency>
+        <groupId>dev.langchain4j</groupId>
+        <artifactId>langchain4j-community-bom</artifactId>
+        <version>0.37.0</version>
+        <typ>pom</typ>
+        <scope>import</scope>
+    </dependency>
+</dependencyManagement>
+```
+
+## APIs
+
+- `XinferenceImageModel`
+
+
+## Examples
+
+- [XinferenceImageModelIT](https://github.com/langchain4j/langchain4j-community/blob/main/models/langchain4j-community-xinference/src/test/java/dev/langchain4j/community/model/xinference/XinferenceImageModelIT.java)

docs/docs/integrations/language-models/xinference.md

@@ -0,0 +1,46 @@
+---
+sidebar_position: 19
+---
+
+# Xinference
+
+- https://inference.readthedocs.io/
+
+
+## Maven Dependency
+
+`0.37.0` and later:
+
+```xml
+<dependency>
+    <groupId>dev.langchain4j</groupId>
+    <artifactId>langchain4j-community-xinference</artifactId>
+    <version>0.37.0</version>
+</dependency>
+```
+
+Or, you can use BOM to manage dependencies consistently:
+
+```xml
+<dependencyManagement>
+    <dependency>
+        <groupId>dev.langchain4j</groupId>
+        <artifactId>langchain4j-community-bom</artifactId>
+        <version>0.37.0</version>
+        <typ>pom</typ>
+        <scope>import</scope>
+    </dependency>
+</dependencyManagement>
+```
+
+
+## APIs
+
+- `XinferenceChatModel`
+- `XinferenceStreamingChatModel`
+
+
+## Examples
+
+- [XinferenceChatModelIT](https://github.com/langchain4j/langchain4j-community/blob/main/models/langchain4j-community-xinference/src/test/java/dev/langchain4j/community/model/xinference/XinferenceChatModelIT.java)
+- [XinferenceStreamingChatModelIT](https://github.com/langchain4j/langchain4j-community/blob/main/models/langchain4j-community-xinference/src/test/java/dev/langchain4j/community/model/xinference/XinferenceStreamingChatModelIT.java)

docs/docs/integrations/scoring-reranking-models/xinference.md

@@ -0,0 +1,43 @@
+---
+sidebar_position: 6
+---
+
+# Xinference
+
+- https://inference.readthedocs.io/
+
+
+## Maven Dependency
+
+`0.37.0` and later:
+
+```xml
+<dependency>
+    <groupId>dev.langchain4j</groupId>
+    <artifactId>langchain4j-community-xinference</artifactId>
+    <version>0.37.0</version>
+</dependency>
+```
+
+Or, you can use BOM to manage dependencies consistently:
+
+```xml
+<dependencyManagement>
+    <dependency>
+        <groupId>dev.langchain4j</groupId>
+        <artifactId>langchain4j-community-bom</artifactId>
+        <version>0.37.0</version>
+        <typ>pom</typ>
+        <scope>import</scope>
+    </dependency>
+</dependencyManagement>
+```
+
+## APIs
+
+- `XinferenceScoringModel`
+
+
+## Examples
+
+- [XinferenceScoringModelIT](https://github.com/langchain4j/langchain4j-community/blob/main/models/langchain4j-community-xinference/src/test/java/dev/langchain4j/community/model/xinference/XinferenceScoringModelIT.java)

docs/docs/tutorials/2-chat-memory.md

@@ -46,7 +46,7 @@ Currently, LangChain4j offers 2 out-of-the-box implementations:
   which also operates as a sliding window but focuses on keeping the `N` most recent **tokens**,
   evicting older messages as needed.
   Messages are indivisible. If a message doesn't fit, it is evicted completely.
-  `MessageWindowChatMemory` requires a `Tokenizer` to count the tokens in each `ChatMessage`.
+  `TokenWindowChatMemory` requires a `Tokenizer` to count the tokens in each `ChatMessage`.
 
 ## Persistence
 

docs/docs/tutorials/5-ai-services.md

@@ -780,5 +780,10 @@ I can evaluate both of them separately and find the most optimal parameters for
 or, in the long run, even fine-tune a small specialized model for each specific subtask.
 
 
+## Testing
+
+- [An example of integration testing for a Customer Support Agent](https://github.com/langchain4j/langchain4j-examples/blob/main/customer-support-agent-example/src/test/java/dev/langchain4j/example/CustomerSupportAgentIT.java)
+
+
 ## Related Tutorials
 - [LangChain4j AiServices Tutorial](https://www.sivalabs.in/langchain4j-ai-services-tutorial/) by [Siva](https://www.sivalabs.in/)

docs/docs/tutorials/spring-boot-integration.md

@@ -224,6 +224,10 @@ interface Assistant {
 For this, please import `langchain4j-reactor` module.
 See more details [here](/tutorials/ai-services#flux).
 
+## Testing
+
+- [An example of integration testing for a Customer Support Agent](https://github.com/langchain4j/langchain4j-examples/blob/main/customer-support-agent-example/src/test/java/dev/langchain4j/example/CustomerSupportAgentIT.java)
+
 ## Supported versions
 
 LangChain4j Spring Boot integration requires Java 17 and Spring Boot 3.2.

docs/docs/tutorials/testing-and-evaluation.md

@@ -0,0 +1,26 @@
+---
+sidebar_position: 33
+---
+
+# Testing and Evaluation
+
+## Examples
+
+[Here](https://github.com/langchain4j/langchain4j-examples/blob/main/customer-support-agent-example/src/test/java/dev/langchain4j/example/CustomerSupportAgentIT.java)
+is an example of an integration testing for a Customer Support Agent.
+This corresponds to [Level 1: Unit Tests](https://hamel.dev/blog/posts/evals/#level-1-unit-tests).
+
+## Recommended Reading
+
+- [Your AI Product Needs Evals](https://hamel.dev/blog/posts/evals/)
+- [Creating a LLM-as-a-Judge That Drives Business Results](https://hamel.dev/blog/posts/llm-judge/)
+- [A Practical Guide to RAG Pipeline Evaluation (Part 1: Retrieval)](https://medium.com/relari/a-practical-guide-to-rag-pipeline-evaluation-part-1-27a472b09893)
+- [A Practical Guide to RAG Pipeline Evaluation (Part 2: Generation)](https://medium.com/relari/a-practical-guide-to-rag-evaluation-part-2-generation-c79b1bde0f5d)
+- [How important is a Golden Dataset for LLM evaluation?](https://medium.com/relari/how-important-is-a-golden-dataset-for-llm-pipeline-evaluation-4ef6deb14dc5)
+- [Case Study: Reference-free vs Reference-based evaluation of RAG pipeline](https://medium.com/relari/case-study-reference-free-vs-reference-based-evaluation-of-rag-pipeline-9a49ef49866c)
+- [How to evaluate complex GenAI Apps: a granular approach](https://medium.com/relari/how-to-evaluate-complex-genai-apps-a-granular-approach-0ab929d5b3e2)
+- [Generate Synthetic Data to Test LLM Applications](https://medium.com/relari/generate-synthetic-data-to-test-llm-applications-4bffeb51b80e)
+
+:::note
+More information coming soon.
+:::