This comprehensive guide walks you through Claude Code model selection, API authentication, request construction, multi‑turn conversation handling, system prompts, temperature tuning, streaming responses, and clean JSON extraction, providing practical Python examples for building robust AI‑powered applications.
This guide walks you through Claude Code model choices, secure API key handling, Python SDK setup, request construction, multi‑turn conversation management, system prompts, temperature tuning, response streaming, and extracting clean structured data such as JSON, all with practical code examples and diagrams.
This tutorial walks you through creating a functional AI agent that can receive goals, plan steps, invoke tools, and iterate until task completion, covering environment setup, core loop implementation, tool integration, error handling, and testing without requiring prior programming experience.
Claude’s API now automatically caches static parts of prompts—system instructions, tool definitions, and context—so repeated calls reuse these sections at only 10% of the standard token price, dramatically reducing costs for multi‑turn agents, but developers must manage prefixes and avoid cache‑breaking changes.
By adding a single field to Claude API requests, developers can automatically cache static prompt parts, reducing token billing to just 10% of the original cost and dramatically lowering expenses for multi‑turn AI agents.
