AI & Automation

Voice AI has matured significantly. VAPI makes it straightforward to build voice assistants that can actually do things—not just chat, but call APIs, look up data, and take actions. Why VAPI? VAPI handles the hard parts of voice: Speech-to-text transcription LLM integration (OpenAI, Anthropic, custom) Text-to-speech with natural voices (ElevenLabs, etc.) Real-time streaming for low latency Tool/function calling during conversations You focus on what your assistant does. VAPI handles how it speaks and listens. ...

Integrating LLM APIs into production applications requires more than just making API calls. These patterns address the real challenges: rate limits, token costs, latency, and reliability. Basic Client Setup 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 import os from anthropic import Anthropic client = Anthropic( api_key=os.environ.get("ANTHROPIC_API_KEY"), timeout=60.0, max_retries=3, ) def chat(message: str, system: str = None) -> str: """Simple completion with sensible defaults.""" messages = [{"role": "user", "content": message}] response = client.messages.create( model="claude-sonnet-4-20250514", max_tokens=1024, system=system or "You are a helpful assistant.", messages=messages, ) return response.content[0].text Retry with Exponential Backoff Built-in retries help, but custom logic handles edge cases: ...