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Spring AI 1.0.0-SNAPSHOT

- Overview
  - AI Concepts
- Getting Started
- Chat Client API
  - Advisors
- AI Models
  - Chat Models
  - Embedding Models
    - Amazon Bedrock
      - Cohere
      - Titan
    - Azure OpenAI
    - Mistral AI
    - MiniMax
    - OCI GenAI
    - Ollama
    - (ONNX) Transformers
    - OpenAI
    - PostgresML
    - QianFan
    - VertexAI
      - Text Embedding
      - Multimodal Embedding
    - ZhiPu AI
  - Image Models
    - Azure OpenAI
    - OpenAI
    - Stability
    - ZhiPuAI
    - QianFan
  - Audio Models
    - Transcription API
      - Azure OpenAI
      - OpenAI
    - Text-To-Speech (TTS) API
      - OpenAI
  - Moderation Models
    - OpenAI
- Vector Databases
  - Azure AI Service
  - Azure Cosmos DB
  - Apache Cassandra Vector Store
  - Chroma
  - Couchbase
  - Elasticsearch
  - GemFire
  - MariaDB Vector Store
  - Milvus
  - MongoDB Atlas
  - Neo4j
  - OpenSearch
  - Oracle
  - PGvector
  - Pinecone
  - Qdrant
  - Redis
  - SAP Hana
  - Typesense
  - Weaviate
- Retrieval Augmented Generation (RAG)
  - ETL Pipeline
- Structured Output
- Chat Memory
- Tool Calling
  - Migrating to ToolCallback API
- Model Context Protocol (MCP)
- Multimodality
- Observability
- Prompt Engineering
  - Prompts
  - Prompt Engineering Patterns
- AI Model Evaluation
- Service Connections
- Contribution Guidelines
- Upgrade Notes

QianFan Embeddings

This functionality has been moved to the Spring AI Community repository.spring-doc.cn

Please visit github.com/spring-ai-community/qianfan for the latest version.spring-doc.cn

Spring AI
AI Models
Embedding Models
QianFan

PostgresML VertexAI

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