Tool Calling
7 articles tagged with this topic
Tool calling, not LLMs, is where 90% of AI Agent projects die
Tool calling is AI Agent's action layer: the model declares the function, code runs it. This plumbing decides whether enterprise AI is real—or just a
Ornith Fine-tunes Beat Qwen Original, Near 27B Full Power on 32GB GPU
Reddit dev tested Qwen3.6-35B-A3B fine-tunes on tool calling for 300+ hrs on 32GB V100. Ornith 1.5 and Tiel-Coder beat original, near Qwen3.8-27B.
Agent Learning's Real Threshold: Reciting Concepts ≠ Using Them Correctly
After Agent basics, a developer's 6 Q&As: Chatbot vs Agent, streaming Tool Calling, Loop stopping, context trade-offs. Demo proves chain, not producti
Speculative Decoding Finally Enters Agent Tool Calls — AI Thinks and Acts in Parallel
A new paper brings speculative decoding into Agent tool calls, aiming to make AI faster at "thinking + acting." Key for local-deploy Agents.
LangChain Standardizes AI Tool Calling: LLMs Shift from Talking to Doing
LangChain updates tool APIs for LLMs to interact with external systems. AI shifts from chatbots to executors; tool calling is key to enterprise AI ado
Build Your Own Mini Cursor: Why This Tutorial Deser ves More Attention
A L angChain tutorial lets one API Key spin up a local AI agent that reads files, runs terminal commands, and scaff olds a full React pr
Fine-Tune Qwen 2.5 for Tool Calling with SageMaker RLVR
AWS SageMaker serverless RLVR fine-tuning improved Qwen 2.5 7B tool-call accuracy by 57% without GPU management.