docs: Dagster.io, Solon integrations (#1533)

* docs: Dagster integration Signed-off-by: Anush008 <anushshetty90@gmail.com> * docs: Solon Signed-off-by: Anush008 <anushshetty90@gmail.com> * Update dagster.md --------- Signed-off-by: Anush008 <anushshetty90@gmail.com>
2026-10-03 01:48:32 +02:00 · 2025-04-15 18:20:05 +05:30
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@@ -13,6 +13,7 @@ partition: build
 | [Canopy](/documentation/frameworks/canopy/)                   | Framework from Pinecone for building RAG applications using LLMs and knowledge bases.                                |
 | [Cheshire Cat](/documentation/frameworks/cheshire-cat/)       | Framework to create personalized AI assistants using custom data.                                                    |
 | [CrewAI](/documentation/frameworks/crewai/)                   | CrewAI is a framework to build automated workflows using multiple AI agents that perform complex tasks.              |
+| [Dagster](/documentation/frameworks/dagster/)                 | Python framework for data orchestration with integrated lineage, observability.                                      |
 | [DeepEval](/documentation/frameworks/deepeval/)               | Python framework for testing large language model systems.                                                           |
 | [DocArray](/documentation/frameworks/docarray/)               | Python library for managing data in multi-modal AI applications.                                                     |
 | [DSPy](/documentation/frameworks/dspy/)                       | Framework for algorithmically optimizing LM prompts and weights.                                                     |
@@ -38,6 +39,7 @@ partition: build
 | [Rig-rs](/documentation/frameworks/rig-rs/)                   | Rust library for building scalable, modular, and ergonomic LLM-powered applications.                                 |
 | [Semantic Router](/documentation/frameworks/semantic-router/) | Python library to build a decision-making layer for AI applications using vector search.                             |
 | [SmolAgents](/documentation/frameworks/smolagents/)           | Barebones library for agents. Agents write python code to call tools and orchestrate other agent.                    |
+| [Solon](/documentation/frameworks/solon/)                     | A lightweight, high-performance Java enterprise framework                                                            |
 | [Spring AI](/documentation/frameworks/spring-ai/)             | Java AI framework for building with Spring design principles such as portability and modular design.                 |
 | [Superduper](/documentation/frameworks/superduper/)           | Framework for building flexible, compositional AI apps which may be applied directly to databases.                   |
 | [Swarm](/documentation/frameworks/swarm/)                     | Python framework for managing multiple AI agents that can work together.                                             |
@@ -0,0 +1,59 @@
+---
+title: Dagster
+---
+
+# Dagster
+
+[Dagster](https://dagster.io) is a Python framework for data orchestration built for data engineers, with integrated lineage, observability, a declarative programming model, and best-in-class testability.
+
+The `dagster-qdrant` library lets you integrate Qdrant's vector database with Dagster, making it easy to build AI-driven data pipelines. You can run vector searches and manage data directly within Dagster.
+
+### Installation
+
+```bash
+pip install dagster dagster-qdrant
+```
+
+### Example
+
+```py
+from dagster_qdrant import QdrantConfig, QdrantResource
+
+import dagster as dg
+
+
+@dg.asset
+def my_table(qdrant_resource: QdrantResource):
+    with qdrant_resource.get_client() as qdrant:
+        qdrant.add(
+            collection_name="test_collection",
+            documents=[
+                "This is a document about oranges",
+                "This is a document about pineapples",
+                "This is a document about strawberries",
+                "This is a document about cucumbers",
+            ],
+        )
+        results = qdrant.query(
+            collection_name="test_collection", query_text="hawaii", limit=3
+        )
+
+
+defs = dg.Definitions(
+    assets=[my_table],
+    resources={
+        "qdrant_resource": QdrantResource(
+            config=QdrantConfig(
+                host="xyz-example.eu-central.aws.cloud.qdrant.io",
+                api_key="<your-api-key>",
+            )
+        )
+    },
+)
+```
+
+## Next steps
+
+- Dagster [documentation](https://docs.dagster.io)
+
+- Dagster [examples](https://github.com/dagster-io/dagster/tree/b985d57aadc7d9bf88d8dcbd32b16d3487e433cc/examples)
@@ -0,0 +1,94 @@
+---
+title: Solon
+---
+
+# Solon
+
+[Solon](https://solon.noear.org) is a lightweight, high-performance Java enterprise framework designed for efficient, eco-friendly development. It enhances concurrency, reduces memory usage, speeds up startup, minimizes packaging size, and supports Java 8 to Java 23, offering a flexible alternative to Spring.
+
+Qdrant is available as a component in Solon-AI for efficient vector indexing and retrievals.
+
+## Installation
+
+```xml
+<dependency>
+    <groupId>org.noear</groupId>
+    <artifactId>solon-ai-repo-qdrant</artifactId>
+</dependency>
+```
+
+This is the main extension plugin for **solon-ai**, which provides the `QdrantRepository` knowledge base.
+
+## Configuration
+
+When using `QdrantRepository`, an embedding model needs to be configured.
+
+```yaml
+solon.ai.embed:
+  bgem3:
+    apiUrl: "http://127.0.0.1:11434/api/embed"
+    provider: "ollama"
+    model: "bge-m3:latest"
+    
+solon.ai.repo:
+  qdrant:
+    host: "localhost"
+    port: 6334
+    useSsl: false
+```
+
+You can now instantiate the embedding model and Qdrant.
+
+```java
+@Configuration
+public class DemoConfig {
+    
+    // Create the embedding model
+    @Bean
+    public EmbeddingModel embeddingModel(@Inject("${solon.ai.embed.bgem3}") EmbeddingConfig config) {
+        return EmbeddingModel.of(config).build();
+    }
+    
+    // Configure the QdrantClient using QdrantGrpcClient
+    @BindProps(prefix = "solon.ai.repo.qdrant")
+    @Bean
+    public QdrantClient qdrantClient(@Value("${solon.ai.repo.qdrant.host}") String host, 
+                                     @Value("${solon.ai.repo.qdrant.port}") int port, 
+                                     @Value("${solon.ai.repo.qdrant.useSsl}") boolean useSsl) {
+        return new QdrantClient(
+                QdrantGrpcClient.newBuilder(host, port, useSsl).build()
+        );
+    }
+    
+    // Initialize the Qdrant knowledge base
+    @Bean
+    public QdrantRepository repository(EmbeddingModel embeddingModel, QdrantClient client) {
+        return new QdrantRepository(embeddingModel, client);
+    }
+}
+```
+
+## Usage
+
+```java
+@Component
+public class DemoService {
+    @Inject
+    private QdrantRepository repository;
+    
+    // Add documents to the repository
+    public void addDocument(List<Document> docs) {
+        repository.insert(docs);
+    }
+    
+    // Search for documents based on a query
+    public List<Document> findDocument(String query) {
+        return repository.search(query);
+    }
+}
+```
+
+## Next steps
+
+- Solon [Documentation](https://solon.noear.org).
+- Solon [Source](https://github.com/opensolon/solon)