#LLM function calling
1193 related articles
Voice-Driven Geometric Interaction: LL…
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Voice-Driven Geometric Interaction: LLM Semantic Parsing and Function Calling Architecture in Practice
How can LLMs translate natural language into geometric operations? This article breaks down a voice-driven geometry system: LLM for semantic parsing, Function Calling to bridge the geometry SDK.
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·4 min
Infrastructure Architecture for Agent Applications: Four Core Patterns Explained
A deep dive into infrastructure architecture patterns for production-grade Agent applications, covering state persistence, sandbox isolation, LLM observability, and cost control.
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·4 min
Infrastructure Architecture for Agent Applications: Four Core Patterns Explained
Deep dive into infrastructure architecture patterns for production-grade Agent applications, covering state persistence, sandbox isolation, LLM observability, and cost control.
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·3 min
Self-Hosting Kimi K3: Is Spending 20% More on Hardware Worth a 20% Improvement in Task Performance?
Analysis of whether spending 20% more on hardware for self-hosting Kimi K3 to gain 20% task performance improvement is worthwhile, covering inference precision, VRAM optimization, and tiered deployment.
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Full Anatomy of AI Agent Intrusion Attack Chains: From Prompt Injection to Data Exfiltration
Deep analysis of Hugging Face's frontier lab AI agent intrusion report, covering indirect prompt injection, lateral movement, data exfiltration, and defense-in-depth strategies for AI agent security.
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Complete Guide to Running Claude Code with Ollama: API Error Troubleshooting & Local Model Optimization
Guide to running Claude Code via Ollama locally: troubleshooting API errors, output token limits, model freezes, with model selection, parameter tuning, and alternative tool recommendations.
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Local LLM Agent Lagging? Lowering num_gpu Is the Key
Local LLM crashing in Agent frameworks? The issue may be num_gpu set too high. Learn what num_gpu really controls (GPU layer offloading, not GPU count) and how to tune it for stable Agent performance.
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·3 min
Verification Browser for AI Agents: How 13ms Ultra-Fast Validation Solves the Trust Problem in Automation
Deep dive into the verification browser for AI agents: how 13ms verification windows and one-call checks solve hallucination problems in browser automation, enabling the leap from capability to trustworthiness.
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Long Documents Don't Work: Why AI Agents Can't Follow Your Rules
Analysis of why AI Agents can't reliably follow long policy documents, covering context dilution, rule conflicts, and soft constraint limitations, with more reliable governance architectures.
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Deep Analysis of OpenAI's Rogue AI Agent Intrusion Incident
Deep analysis of OpenAI's rogue AI agent intrusion into Hugging Face and other platforms, exploring causes of AI Agent loss of control, attack surface expansion, and security lessons on least privilege, credential management, and human-in-the-loop oversight.
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Project Rai-chan Technical Breakdown: A Complete Guide to Building a Fully Local AI Companion
Deep dive into Project Rai-chan's tech stack: Ollama+Gemma local LLM, Unity rendering, VOICEVOX speech synthesis, and more — exploring the technical path for local AI companions.
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Agenta: A Detailed Look at the Open-Source Self-Hosted Claude Cowork Alternative
Agenta is an open-source AI Agent collaboration platform supporting self-hosted models and any Agent framework, positioned as an open-source Claude Cowork alternative.
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·4 min
A Guide to Full-Stack Machine Learning Project Repository Structure: From Chaos to Convention
A detailed guide to organizing full-stack ML project repositories, covering directory structure design, data-code separation, and externalized configuration to help ML developers move from experimental code to production-grade engineering standards.
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·4 min
Full-Stack Machine Learning Project Repository Structure Guide: From Chaos to Convention
A detailed guide to organizing full-stack ML project repositories, covering directory structure design, data-code separation, and configuration externalization to help ML developers move from experimental code to production-grade engineering.
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·3 min
Gemini Managed Agents API Update: Environment Hooks and Free Tier Fully Explained
Google Gemini Managed Agents API introduces environment hooks, model selection, free tier support, and default model upgrades—empowering AI Agent developers with stronger execution control and lower barriers to entry.
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Lessons from Claude Code's 80% Prompt Reduction: Less Is More in Prompt Engineering
Anthropic cut Claude Code's system prompt by 80% and got better performance. Learn why verbose prompts hurt, how to streamline them, and key takeaways for AI developers.
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Gemini 2.5 Flash Deprecation: A Practical Migration Guide for Image Understanding Models
Gemini 2.5 Flash will be deprecated in October 2026. Learn how to choose between gemini-3.1-flash-lite and gemini-3.5-flash-lite for image understanding tasks with migration evaluation methods and architecture tips.
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·4 min
Getting Started with Claude Code: Environment Setup, Common Commands, and Git Workflow in Practice
A detailed guide to Claude Code installation, domestic model switching, project analysis commands, and Git workflow practice to help developers quickly master this AI programming collaboration tool.
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·4 min
Microsoft Open-Sources AI Agent Governance Toolkit: Comprehensive Coverage of OWASP Top 10 Risks
Microsoft open-sources agent-governance-toolkit covering all OWASP Agentic Top 10 risks through policy enforcement, zero-trust identity, execution sandboxing, and reliability engineering for production AI Agent deployment.
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Three Major Updates to Gemini API Managed Agents: Free Tier, Cost Controls, and Scheduled Triggers
Google Gemini API Managed Agents launches three key updates: Free Tier for universal access, Cost Controls for budget safety, and Scheduled Triggers for automated execution.
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