DeepSeek Deployment Guide: Efficient Practices from Local to Cloud

01 Overview of DeepSeek Deployment DeepSeek, as a high-performance open-source large model, supports various deployment methods, including local deployment, cloud deployment, and hybrid deployment. This article will detail how to efficiently deploy DeepSeek in different environments and optimize its performance. 02 Local Deployment 1. Hardware Requirements GPU: At least 1 NVIDIA A100 or equivalent GPU … Read more

5 Python Libraries Every Data Scientist Should Know

5 Python Libraries Every Data Scientist Should Know

Author: Artem Shelamanov Translator: Chen Zhiyan Proofreader: Zhao Ruxuan This article is about 2800 words long, recommended reading time is 5 minutes. This article introduces machine learning libraries, and once you master the model architectures, you can train models to solve real-world problems. If you are a junior or mid-level machine learning engineer or data … Read more

Streamlit + FastAPI: A New Approach to Rapidly Build and Deploy AI Web Applications

Streamlit + FastAPI: A New Approach to Rapidly Build and Deploy AI Web Applications

In the field of application development, especially in data science and AI applications, choosing the right tools to create, deploy, and manage applications is crucial. This article will delve into a new approach for rapidly building and deploying AI web applications using Streamlit + FastAPI, clarifying its architecture, working mechanism, advantages, and practical use cases, … Read more

Local Deployment and Fine-Tuning Tutorial for Qwen 2.5 Model

Local Deployment and Fine-Tuning Tutorial for Qwen 2.5 Model

“ As a non-professional beginner, my initial interest in large models led me to explore related knowledge. As I read more papers and reports, I always wanted to practice with large models but didn’t know where to start. I believe many students share the same experience as I did back then. This article will guide … Read more

Building An AI Agent With Python: A Complete Guide Using PhiData, FastAPI, and Docker

Building An AI Agent With Python: A Complete Guide Using PhiData, FastAPI, and Docker

This article introduces how to use Python, PhiData, FastAPI and Docker to build a simple AI Agent, and expose it as a Web service. Main Points Using PhiData to build a simple AI Agent, which decides whether to turn on the heater or air conditioning based on temperature. Using FastAPI to create a RESTful API, … Read more

Practical Guide to Rapid IoT Platform Development with Cursor

Practical Guide to Rapid IoT Platform Development with Cursor

In the court, a young concubine is worried about writing the IoT platform. “Your Majesty, I recently received a task to develop an IoT platform, but I always feel that writing code is too slow. Is there any magical tool that can help me improve my efficiency?” “Do not worry, my dear. Today I will … Read more

Quick Start Guide to LlamaIndex RAG CLI

Quick Start Guide to LlamaIndex RAG CLI

Click 01 Magician Society Follow the official account, and never get lost in AI learning LlamaIndex is a simple and flexible data framework for connecting custom data sources with large language models. RAG is the process of optimizing LLM outputs by referencing knowledge bases outside of their training data sources before generating responses. RAG extends … Read more

Deploying Autonomous AI Agents with AgentGPT

Deploying Autonomous AI Agents with AgentGPT

Aitrainee | Public Account: AI Progress Student 🌟AgentGPT allows you to configure and deploy autonomous AI Agents. It is an improved version of AutoGPT based on Langchain, requiring no deployment, and provides a website that can be used directly. The customized agents will attempt to achieve their goals by thinking about the tasks to complete, … Read more

Phidata: 8.3K Stars! Create AI Agents with Long-Term Memory Using GPT-4o

Phidata: 8.3K Stars! Create AI Agents with Long-Term Memory Using GPT-4o

Project Overview Phidata is an open-source framework designed to build automated assistants (intelligent agents) with memory, knowledge, and tool capabilities. This framework addresses the limitations of existing large language models (LLMs) in terms of context and their inability to perform actions by adding a database to store chat history, a vector database to store business … Read more