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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
Search: #asynchronously
@djangoproject · Post #585 · 03/23/2018, 02:43 AM
https://www.fullstackpython.com/celery.html #Celery is a task #queue implementation for Python web applications used to #asynchronously execute work outside the HTTP request-response cycle.
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@djangoproject · Post #262 · 02/16/2017, 07:24 AM
http://masnun.com/2015/11/20/python-asyncio-future-task-and-the-event-loop.html On any platform, when we want to do something #asynchronously, it usually involves an #event loop. An event loop is a loop that can register #tasks to be executed, execute them, delay or even cancel them and handle different events related to these operations. Generally, we #schedule multiple async functions to the event loop. The loop runs one function, while that function waits for #IO, it pauses it and runs another. When the first function completes IO, it is resumed. Thus two or more functions can #co_operatively run together. This the main goal of an event loop.