#Pydantic LLM
57 related articles
Tutorials·2 min
LangChain AI Agent in Practice: Complete Tutorial on Streaming Output + Parallel Tool Calling
Learn how to build a production-grade AI Agent chat app with LangChain and FastAPI, covering streaming tokens, asyncio parallel tool calling, SerpAPI async conversion, and structured output.
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Tutorials·4 min
Langmanus Multi-Agent Framework Deep Dive: Architecture Principles and Agent Extension in Practice
Deep dive into Langmanus multi-agent framework architecture, explaining LangGraph orchestration with Coordinator, Planner, Supervisor and execution agents, plus a hands-on guide to adding custom agents.
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Tutorials·3 min
LangChain 1.3 Event Stream in Practice: Real-Time Agent Monitoring from 4 Perspectives
Master LangChain 1.3 Event Stream V3 with 4 monitoring perspectives: run.messages, tool_cause, and more for real-time Agent debugging, streaming output, tool tracking, and token cost control.
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Tutorials·3 min
FastAPI Beginner's Guide: Four Core Advantages and ASGI Architecture Explained
Deep dive into FastAPI's four core advantages: high-performance async IO, type hints, automatic API docs, and ease of use. Learn the CGI to WSGI to ASGI protocol evolution.
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Tech Frontiers·2 min
LLM 0.32 Refactoring Deep Dive: Message Sequence Input and Streaming Multi-Type Response Design
Deep dive into LLM 0.32 alpha's two core refactorings: message sequence API aligned with OpenAI format, stream_events for typed streaming responses, serialization design, and backward compatibility.
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Deep Dives·3 min
LangGraph Deep Dive: An Open-Source Framework for Building Resilient AI Agents
Deep dive into LangGraph's core architecture, StateGraph design, multi-Agent collaboration, and deployment. Learn how this 31K+ Star project helps build reliable AI Agents.
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Tutorials·3 min
Hands-On Intelligent Agent Development with LangGraph: From Getting Started to Full Project Architecture
A deep dive into intelligent Agent development with LangGraph, covering core concepts, project architecture, state management, and practical tips for building AI agents in Python.
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Product Reviews·3 min
Skill-Agent: A Production-Grade AI Agent Framework Built on FastAPI with 100+ LLM Support
Deep dive into Skill-Agent, an open-source FastAPI framework integrating 100+ LLM providers, MCP tool protocol, multi-agent collaboration, RAG knowledge base, and sandbox execution for enterprise AI Agent development.
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Tutorials·3 min
LangGraph E-commerce AI Agent in Practice: From RAG Q&A to Automated Return Workflows
Deep dive into the E-commerce-Smart-Agent open-source framework built with LangGraph and FastAPI, covering RAG knowledge base Q&A, return workflow automation, and graph-based orchestration.
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Product Reviews·3 min
Micro-Agent: Fudan University's Open-Source Lightweight AI Agent Framework Built for Vertical Domains
Micro-Agent is a lightweight AI Agent framework open-sourced by Fudan University, focused on vertical domain applications. It offers streamlined architecture, low learning costs, and high customization flexibility compared to heavyweight frameworks like LangChain.
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Tech Frontiers·2 min
JetBrains Open-Sources Koog Framework: Building Enterprise-Grade AI Agents with Kotlin
JetBrains open-sources Koog AI Agent framework built on Kotlin Multiplatform for full JVM deployment. Explore Koog's core features, fault-tolerant design, and advantages over Python frameworks.
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Tech Frontiers·2 min
LLM 0.32a0 Major Refactor: A Deep Dive into Message Sequences and Typed Streaming Responses
Simon Willison releases LLM Python library 0.32a0 alpha with message sequence prompts and typed streaming responses, redesigning model interaction abstractions for multimodal output, tool calls, and modern LLM features.
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Deep Dives·3 min
LLM 0.32 Refactoring Deep Dive: Message Sequence Input and Typed Streaming Response Design
Deep dive into Simon Willison's LLM 0.32a0 refactoring: message sequence inputs, typed streaming events, SQLite-decoupled serialization, and backward-compatible API evolution strategies.
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Tutorials·5 min
Google Open-Sources Full-Stack AI Agent Tutorial: Gemini 2.5 + LangGraph Deep Dive
Google open-sources gemini-fullstack-langgraph-quickstart with 18,000+ Stars. Deep dive into the technical architecture, state machine design patterns, and tool-calling mechanisms of building full-stack AI Agents with Gemini 2.5 and LangGraph.
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Product Reviews·3 min
AgentChat Open Source Project: An AI Agent Platform Integrating MCP, RAG, and LangChain
Deep analysis of AgentChat, an open-source AI agent platform integrating MCP protocol, RAG retrieval-augmented generation, LangChain framework, and Function Call for multi-Agent collaboration and custom workflows.
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Product Reviews·3 min
Tianshu: Open-Source AI Document Parsing Platform — A One-Stop Solution for PDF to Markdown Conversion
Tianshu (mineru-tianshu) is an enterprise-grade open-source AI document preprocessing platform supporting PDF/Office to Markdown conversion, MCP protocol AI assistant integration, with a Vue3+FastAPI full-stack architecture for RAG systems and enterprise knowledge bases.
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Deep Dives·3 min
LLM 0.32a0 Major Refactor Analysis: How a Backward-Compatible Architecture Upgrade Tackles the Multimodal and Tool-Calling Era
Deep analysis of Simon Willison's LLM Python library 0.32a0 alpha: message sequences, streaming typed parts, tool calling, and the design philosophy behind backward-compatible refactoring.
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