In the second part, we explored the principles of modular design. We discussed strategies for decomposing the Agent system by borrowing the bounded context concept from microservices to determine the scope of each sub-Agent. We also hinted that modularization introduces a need for a well-thought-out interaction model between agents and sub-Agents. Today, we will delve … Read more
At Doctolib, our mission is not just to build the healthcare system we dream of — we are changing the way health professionals interact with technology. Two ambitious goals drive us: to ensure satisfaction for health professionals using our solutions and to accelerate our pace of innovation. But ambition comes with great responsibility, especially in … Read more
Cover AI Generated CyberDaily： AI Takes Its First Step Out of the Cave Generative AI has been a hot technology and application in LLM since ChatGPT. Recently, Agentic AI has become a trend, also known as the next frontier, a way out after the ceiling of LLM. What is Agentic AI? Agentic AI refers to … Read more
↑ ClickBlue Text Follow the Jishi Platform Author丨Tech Beast Editor丨Jishi Platform Jishi Introduction SpinQuant combines learnable rotation matrices to achieve optimal network accuracy, quantizing weights, activations, and KV cache to a 4-bit width. On the LLaMA-2 7B model, SpinQuant reduces the accuracy gap in Zero-Shot inference tasks to only 2.9 points compared to the full-precision … Read more
GPT Source: Machine Heart ChatGPT has become the manager of hundreds of models. In recent months, the successive popularity of ChatGPT and GPT-4 has showcased the extraordinary capabilities of large language models (LLMs) in language understanding, generation, interaction, and reasoning, attracting significant attention from both academia and industry, and revealing the potential of LLMs in … Read more
As one of the earliest LLM application development frameworks alongside LangChain and LlamaIndex, Microsoft’s AutoGen has undergone a complete redesign and restructuring after a series of personnel changes last year, launching the completely revamped AutoGen 0.4 version (the previous version was 0.2), with the latest stable version 0.4.2 released in early 2025. You may have … Read more
When using model-based decision-making non-deterministic systems (e.g., LLM-driven agents), it is useful to closely examine their decision-making processes: 🤔 Understanding Reasoning: Analyzing the steps that lead to successful outcomes. 🐞 Debugging Errors: Identifying where and why errors occur. 🔍 Exploring Alternatives: Testing different paths to discover better solutions. We refer to these debugging techniques as … Read more
LangGraph provides a hands-on approach to how humans can interact with agents. `LangGraph` is a library for building stateful, multi-participant applications using `LLM`, designed for creating agent and multi-agent workflows. Compared to other `LLM` frameworks, it has the following core advantages: loops, controllability, and persistence. `LangGraph` allows you to define processes that involve loops, which … Read more
The human-computer interaction feature allows us to involve the user in the decision-making process of the graph. The following guide demonstrates how to implement human-computer interaction workflows in the graph. The human-computer interaction workflow integrates user input into automated processes, allowing for decision-making, validation, or correction at critical stages. This is particularly useful in applications … Read more
An agent is a system that uses LLM to determine the control flow of applications. As you develop these systems, they may become more complex over time, making them harder to manage and scale. For example, we may encounter the following issues: There are too many tools that agents can use, making it overly complex … Read more