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Source channel @githubtrending · Post #14800 · Jun 7

#java#anthropic#chatgpt#chroma#embeddings#gemini#gpt#huggingface#java#langchain#llama#milvus#ollama#onnx#openai#openai_api#pgvector#pinecone#vector_database#weaviate LangChain4j helps you add powerful AI to your Java applications by making it easy to use Large Language Models (LLMs). It provides a simple way to switch between different LLMs and embedding stores without needing to learn each one's specific API. This means you can easily experiment with different models and tools, making your development process faster and more flexible. LangChain4j also offers many examples and tools to help you build complex AI applications quickly, such as chatbots and retrieval systems. This simplifies the integration of AI into your projects, allowing you to focus on creating better applications. https://github.com/langchain4j/langchain4j

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#java #anthropic #chatgpt #chroma #embeddings #gemini #gpt #huggingface #langchain #llama #milvus #ollama #onnx #openai #openai_api #pgvector #pinecone #vector_database #weaviate

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@githubtrending · Post #15348 · 12/20/2025, 12:00 PM

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#go#gemma3#go#gpt_oss#granite4#llama#llama3#llm#on_device_ai#phi3#qwen3#qwen3vl#sdk#stable_diffusion#vlm NexaSDK runs AI models locally on CPUs, GPUs, and NPUs with a single command, supports GGUF/MLX/.nexa formats, and offers NPU-first Android and macOS support for fast, multimodal (text, image, audio) inference, plus an OpenAI‑compatible API for easy integration. This gives you low-latency, private on-device AI across laptops, phones, and embedded systems, reduces cloud costs and data exposure, and lets you deploy and test new models immediately on target hardware for faster development and better user experience. https://github.com/NexaAI/nexa-sdk

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#go #gemma3 #gpt_oss #granite4 #llama #llama3 #llm #on_device_ai #phi3 #qwen3 #qwen3vl #sdk #stable_diffusion #vlm