Using OpenAI and Anthropic Python SDKs Part 2

# script_id: day_011_openai_anthropic_sdks_part2/unified_llm_wrapper
from openai import OpenAI
from anthropic import Anthropic

class UnifiedLLM:
    """A unified interface for both OpenAI and Anthropic."""

    def __init__(self):
        self.openai = OpenAI()
        self.anthropic = Anthropic()

    def chat(
        self,
        messages: list,
        provider: str = "openai",
        model: str = None,
        system: str = None,
        temperature: float = 0.7,
        max_tokens: int = 1000
    ) -> dict:
        """
        Send a chat message to either provider.

        Args:
            messages: List of {"role": "user/assistant", "content": "..."}
            provider: "openai" or "anthropic"
            model: Model name (defaults based on provider)
            system: System prompt
            temperature: 0 = focused/deterministic, higher = more varied (see Day 4)
            max_tokens: Maximum response tokens
        """
        if provider == "openai":
            return self._openai_chat(messages, model, system, temperature, max_tokens)
        elif provider == "anthropic":
            return self._anthropic_chat(messages, model, system, temperature, max_tokens)
        else:
            raise ValueError(f"Unknown provider: {provider}")

    def _openai_chat(self, messages, model, system, temperature, max_tokens):
        model = model or "gpt-4o-mini"

        # Add system message if provided
        full_messages = []
        if system:
            full_messages.append({"role": "system", "content": system})
        full_messages.extend(messages)

        response = self.openai.chat.completions.create(
            model=model,
            messages=full_messages,
            temperature=temperature,
            max_tokens=max_tokens
        )

        return {
            "content": response.choices[0].message.content,
            "input_tokens": response.usage.prompt_tokens,
            "output_tokens": response.usage.completion_tokens,
            "model": response.model,
            "provider": "openai"
        }

    def _anthropic_chat(self, messages, model, system, temperature, max_tokens):
        model = model or "claude-sonnet-4-6"

        kwargs = {
            "model": model,
            "messages": messages,
            "max_tokens": max_tokens,
        }

        if system:
            kwargs["system"] = system
        # Anthropic's default temperature is already 1.0, so only send it when the caller wants something different.
        if temperature != 1.0:
            kwargs["temperature"] = temperature

        response = self.anthropic.messages.create(**kwargs)

        return {
            "content": response.content[0].text,
            "input_tokens": response.usage.input_tokens,
            "output_tokens": response.usage.output_tokens,
            "model": response.model,
            "provider": "anthropic"
        }

# Usage - same interface for both!
llm = UnifiedLLM()

# OpenAI
result1 = llm.chat(
    messages=[{"role": "user", "content": "Hello!"}],
    provider="openai",
    system="Be brief."
)
print("OpenAI:", result1["content"])

# Anthropic
result2 = llm.chat(
    messages=[{"role": "user", "content": "Hello!"}],
    provider="anthropic",
    system="Be brief."
)
print("Anthropic:", result2["content"])

# script_id: day_011_openai_anthropic_sdks_part2/error_handling_retry
from openai import OpenAI, APIError, RateLimitError, APIConnectionError
import time

client = OpenAI()

def robust_openai_call(messages: list, max_retries: int = 3) -> str:
    """Make an OpenAI call with retry logic."""

    for attempt in range(max_retries):
        try:
            response = client.chat.completions.create(
                model="gpt-4o-mini",
                messages=messages
            )
            return response.choices[0].message.content

        except RateLimitError as e:
            # Rate limited - wait and retry
            wait_time = 2 ** attempt  # Exponential backoff
            print(f"Rate limited. Waiting {wait_time}s... (Attempt {attempt + 1})")
            time.sleep(wait_time)

        except APIConnectionError as e:
            # Network issue - retry
            print(f"Connection error: {e}. Retrying...")
            time.sleep(1)

        except APIError as e:
            # Other API error
            print(f"API error: {e}")
            if getattr(e, 'status_code', 0) >= 500:
                # Server error - might be temporary
                time.sleep(2)
            else:
                # Client error - don't retry
                raise

    raise Exception("Max retries exceeded")

# Usage
try:
    result = robust_openai_call([{"role": "user", "content": "Hello!"}])
    print(result)
except Exception as e:
    print(f"Failed: {e}")

# script_id: day_011_openai_anthropic_sdks_part2/gemini_basic_usage
# pip install google-genai
from google import genai

client = genai.Client()  # Uses GOOGLE_API_KEY env var

response = client.models.generate_content(
    model="gemini-2.0-flash",
    contents="Explain quantum computing in one paragraph."
)
print(response.text)

# script_id: day_011_openai_anthropic_sdks_part2/quick_reference_templates
# OpenAI Quick Template
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

# Anthropic Quick Template
from anthropic import Anthropic
client = Anthropic()
response = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.content[0].text)