langchain4j and research4j
LangChain4j is a comprehensive Java library for integrating LLMs into applications, while research4j is a specialized tool within the broader LangChain4j ecosystem, focused on building perplexity-like functionality for specific domains.
About langchain4j
langchain4j/langchain4j
LangChain4j is an open-source Java library that simplifies the integration of LLMs into Java applications through a unified API, providing access to popular LLMs and vector databases. It makes implementing RAG, tool calling (including support for MCP), and agents easy. LangChain4j integrates seamlessly with various enterprise Java frameworks.
Provides unified abstractions across 20+ LLM providers and 30+ vector databases, enabling provider-agnostic switching without code rewrites. Built on composable low-to-high-level primitives—from prompt templating and chat memory to agents and RAG pipelines—with multiple implementations for each pattern. Native integrations with Spring Boot, Quarkus, Helidon, and Micronaut enable seamless embedding into existing enterprise Java application stacks.
About research4j
bhavuklabs/research4j
Build your own perplexity for your applications using research4j and integrate them for any domain specific usecases
Leverages virtual threads for asynchronous processing and employs a graph-based pipeline orchestrating query analysis, dynamic citation fetching, and adaptive reasoning strategies (Chain-of-Thought, Chain-of-Table, Chain-of-Ideas). Supports multiple LLM providers (OpenAI GPT, Google Gemini) and citation sources (Google Custom Search, Tavily) through pluggable provider abstractions, with session-based context management and user profile personalization for tailored responses.
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