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Clean obsolate README files

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Christian Tzolov
2024-02-14 06:40:35 +01:00
parent 12d3ae40c4
commit f6447f420e
11 changed files with 21 additions and 138 deletions
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spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chatclient.adoc
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//
// TBD
== API Docs (OUTDATED!!!)
You can find the Javadoc https://docs.spring.io/spring-ai/docs/current-SNAPSHOT/[here].
== Feedback and Contributions
The project's https://github.com/spring-projects/spring-ai/discussions[GitHub discussions] is a great place to send feedback.
// == Related Resources
//
// TBD

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spring-ai-docs/src/main/antora/modules/ROOT/pages/api/index.adoc
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* xref:api/vectordbs.adoc[Vector Database API]
* xref:api/[Image Generation API](WIP)
== API Docs
You can find the Javadoc https://docs.spring.io/spring-ai/docs/current-SNAPSHOT/[here].
== Feedback and Contributions
The project's https://github.com/spring-projects/spring-ai/discussions[GitHub discussions] is a great place to send feedback.
== Spring AI Generic Model API [[generic-model-api]]
image::spring-ai-generic-model-api.jpg[width=900, align="center"]

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[Azure AI Search Vector Store Documentation](https://docs.spring.io/spring-ai/reference/api/vectordbs/azure.html)

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[Chroma Vector Store Documentation](https://docs.spring.io/spring-ai/reference/api/vectordbs/chroma.html)

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[Milvus Vector Store Documentation](https://docs.spring.io/spring-ai/reference/api/vectordbs/milvus.html)

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[Neo4j Vector Store Documentation](https://docs.spring.io/spring-ai/reference/api/vectordbs/neo4j.html)

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[PGvector Vector Store Documentation](https://docs.spring.io/spring-ai/reference/api/vectordbs/pgvector.html)

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# Pinecone Vector Store
This readme walks you through setting up the Pinecone `VectorStore` to store document embeddings and perform similarity searches.
## What is Pinecone?
[Pinecone](https://www.pinecone.io/) is a popular cloud-based vector database, which allows you to store and search vectors efficiently.
## Prerequisites
1. Pinecone Account: Before you start, sign up for a [Pinecone account](https://app.pinecone.io/).
2. Pinecone Project: Once registered, create a new project, an index, and generate an API key. You'll need these details for configuration.
3. OpenAI Account: Create an account at [OpenAI Signup](https://platform.openai.com/signup) and generate the token at [API Keys](https://platform.openai.com/account/api-keys)
## Configuration
To set up `PineconeVectorStore`, gather the following details from your Pinecone account:
* Pinecone API Key
* Pinecone Environment
* Pinecone Project ID
* Pinecone Index Name
* Pinecone Namespace
> **Note**
> This information is available to you in the Pinecone UI portal.
When setting up embeddings, select a vector dimension of `1536`. This matches the dimensionality of OpenAI's model `text-embedding-ada-002`, which we'll be using for this guide.
Additionally, you'll need to provide your OpenAI API Key. Set it as an environment variable like so:
```bash
export SPRING_AI_OPENAI_API_KEY='Your_OpenAI_API_Key'
```
## Repository
To acquire Spring AI artifacts, declare the Spring Snapshot repository:
```xml
<repository>
<id>spring-snapshots</id>
<name>Spring Snapshots</name>
<url>https://repo.spring.io/snapshot</url>
<releases>
<enabled>false</enabled>
</releases>
</repository>
```
## Dependencies
Add these dependencies to your project:
1. OpenAI: Required for calculating embeddings.
```xml
<dependency>
<groupId>org.springframework.experimental.ai</groupId>
<artifactId>spring-ai-openai-spring-boot-starter</artifactId>
<version>0.8.0-SNAPSHOT</version>
</dependency>
```
2. Pinecone
```xml
<dependency>
<groupId>org.springframework.experimental.ai</groupId>
<artifactId>spring-ai-pinecone</artifactId>
<version>0.8.0-SNAPSHOT</version>
</dependency>
```
## Sample Code
To configure Pinecone in your application, you can use the following setup:
```java
@Bean
public PineconeVectorStoreConfig pineconeVectorStoreConfig() {
return PineconeVectorStoreConfig.builder()
.withApiKey(<PINECONE_API_KEY>)
.withEnvironment("gcp-starter")
.withProjectId("89309e6")
.withIndexName("spring-ai-test-index")
.withNamespace("") // the free tier doesn't support namespaces.
.build();
}
```
Integrate with OpenAI's embeddings by adding the Spring Boot OpenAI starter to your project.
This provides you with an implementation of the Embeddings client:
```java
@Bean
public VectorStore vectorStore(PineconeVectorStoreConfig config, EmbeddingClient embeddingClient) {
return new PineconeVectorStore(config, embeddingClient);
}
```
In your main code, create some documents:
```java
List<Document> documents = List.of(
new Document("Spring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!!", Map.of("meta1", "meta1")),
new Document("The World is Big and Salvation Lurks Around the Corner"),
new Document("You walk forward facing the past and you turn back toward the future.", Map.of("meta2", "meta2")));
```
Add the documents to Pinecone:
```java
vectorStore.add(List.of(document));
```
And finally, retrieve documents similar to a query:
```java
List<Document> results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(5));
```
If all goes well, you should retrieve the document containing the text "Spring AI rocks!!".
[Pinecone Vector Store Documentation](https://docs.spring.io/spring-ai/reference/api/vectordbs/pinecone.html)

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vector-stores/spring-ai-redis/README.md Normal file
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[Redis Vector Store Documentation](https://docs.spring.io/spring-ai/reference/api/vectordbs/redis.html)

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vector-stores/spring-ai-redis/pom.xml
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<url>https://github.com/spring-projects/spring-ai</url>
<scm>
<url>https://github.com/spring-projects-experimental/spring-ai</url>
<connection>git://github.com/spring-projects-experimental/spring-ai.git</connection>
<developerConnection>git@github.com:spring-projects-experimental/spring-ai.git</developerConnection>
<url>https://github.com/spring-projects/spring-ai</url>
<connection>git://github.com/spring-projects/spring-ai.git</connection>
<developerConnection>git@github.com:spring-projects/spring-ai.git</developerConnection>
</scm>
<properties>
<testcontainers-redis.version>2.0.1</testcontainers-redis.version>
<jedis.version>5.1.0</jedis.version>
@@ -39,7 +39,7 @@
<artifactId>jedis</artifactId>
<version>${jedis.version}</version>
</dependency>
<!-- TESTING -->
<dependency>
<groupId>org.springframework.ai</groupId>

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vector-stores/spring-ai-weaviate/README.md Normal file
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[Weaviate Vector Store Documentation](https://docs.spring.io/spring-ai/reference/api/vectordbs/weaviate.html)