Context A Dify instance was deployed locally on a GPU server, integrated with Xinference hosting the THUDM/glm-4-9b-chat model. A RAG workflow was built using Dify’s default task flow template and a local knowledge base. During chat execution, the knowledge retrieval node failed with an error: Model...
Large language models inherently lack memory, as they process each input independently without retaining context from previous interactions. In practical applications, memory is simulated by appending the entire conversation history to each new prompt, allowing the model to generate contextually rel...
ChatGLM3-6B is a powerful open-source bilingual (Chinese-English) dialogue model based on the General Language Model (GLM) architecture. Developed by Zhipu AI and Tsinghua University, it features 6.2 billion parameters and offers lower deployment requirements compared to larger models. Running this...
Legacy String Handling in Python 2 In Python 2, managing text requires careful distinction between byte strings and Unicode objects. To prevent encoding conflicts during concatenation, ensure all strings share the same type. # Converting to Unicode using the 'u' prefix text_unicode = u'\u4e2d\u56fd'...
Ollama is an effective tool for runing open-source large language models (LLMs) locally. It provides a straightforward command-line interface for managing models and includes Python and JavaScript SDKs for building chatbot interfaces. This guide demonstrates the setup process using a cloud GPU insta...