Discover documentation to enhance your AI agent's capabilities.
| Name | Contains | Score |
|---|---|---|
LangChain4j integration for Mistral AI providing chat completion, streaming, embedding, moderation, and code completion capabilities | Docs | — |
Java implementation of the Model Context Protocol (MCP) client for the LangChain4j framework, enabling integration with MCP servers for tools, resources, and prompts | Docs | — |
JDK HttpClient implementation for LangChain4j HTTP client interface | Docs | — |
LangChain4j integration for Azure OpenAI providing chat, streaming, embeddings, image generation, audio transcription, and token counting capabilities | Docs | — |
Terminal User Interface framework for Java that ports the Charmbracelet ecosystem (Bubble Tea, Bubbles, Lipgloss, Harmonica) from Go, enabling developers to build interactive CLI applications using The Elm Architecture pattern. | Docs | — |
JAX-RS HTTP Client implementation for Quarkus LangChain4j | Docs | — |
Common shared infrastructure for integrating Google Gemini AI models with Quarkus applications through the LangChain4j framework, providing base chat model functionality, schema mapping, and embedding model support. | Docs | — |
JavaPoet is a Java API for generating .java source files programmatically with support for modern Java features including records and sealed types | Docs | — |
Quarkus extension for integrating IBM watsonx.ai foundation models with LangChain4j. Provides chat models, generation models, streaming models, embedding models, and scoring models for IBM watsonx.ai. Includes comprehensive configuration options, support for tool/function calling, text extraction from documents in Cloud Object Storage, and experimental built-in services for Google search, weather, and web crawling. Designed for enterprise Java applications using the Quarkus framework with built-in dependency injection and native compilation support. | Docs | — |
Quarkus build-time deployment extension for Model Context Protocol (MCP) client integration, handling configuration processing, synthetic bean generation, and framework integration | Docs | — |
Quarkus extension that integrates Hugging Face language models with Quarkus applications through LangChain4j | Docs | — |
Easy RAG extension for Quarkus LangChain4j that dramatically simplifies implementing Retrieval Augmented Generation pipelines with automatic document ingestion and embedding store management | Docs | — |
Quarkus extension for integrating Chroma vector database as an embedding store with LangChain4j | Docs | — |
Quarkus extension for Azure OpenAI integration with LangChain4j, providing ChatModel, StreamingChatModel, EmbeddingModel, and ImageModel implementations with Azure-specific authentication and configuration support. | Docs | — |
Java integration library enabling LangChain4j applications to use Ollama's local language models with support for chat, streaming, embeddings, and advanced reasoning features | Docs | — |
In-process all-minilm-l6-v2 (quantized) embedding model | Docs | — |
This package provides an integration layer between the LangChain4j framework and Anthropic's Claude language models, enabling Java developers to seamlessly incorporate Anthropic's AI capabilities into their applications. | Docs | — |
LangChain4j integration for Google AI Gemini models providing chat, streaming, embeddings, image generation, and batch processing capabilities | Docs | — |
Internal testing utilities for Quarkus LangChain4j that provide a WiremockAware base class for mocking HTTP-based LLM API calls in integration tests. NOTE: This is an internal-only module not published to Maven Central. | Docs | — |
Quarkus extension for integrating LangChain4j with PostgreSQL pgvector for embedding storage | Docs | — |
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