📄️ deploy local llm
choose proper llm to deploy
📄️ Create Knowledge Base
With the rapid development of Natural Language Processing (NLP) technology, generative language models (such as GPT, BART, etc.) have achieved excellent performance in various text generation tasks, especially in terms of language generation and context understanding. However, pure generative models have some inherent limitations when dealing with fact-based tasks. For example, because these models rely on fixed pre-trained data, they may "fabricate" information when answering questions that require the latest or real-time information, resulting in inaccurate or factually unfounded generated results. In addition, when faced with long-tail problems and complex reasoning tasks, generative models often perform poorly due to the lack of support from external knowledge in specific domains, making it difficult to provide sufficient depth and accuracy.
📄️ Create Knowledge base application
how-to
📄️ Create Agent Application
how-to
📄️ Congratulations!
You have just learned the ai agent develop basic .