Workshop Toolkit: A Quick Tour of the 11 Tools We'll Use Throughout the Course

import tiktoken
 
enc = tiktoken.encoding_for_model("gpt-4o")
tokens = enc.encode("Merhaba dünya, ben bir LLM mühendisiyim.")
print(f"Token sayısı: {len(tokens)}")  # 14
print(f"Token ID'leri: {tokens}")
# decoded
print([enc.decode([t]) for t in tokens])
# ['Mer', 'haba', ' dünya', ',', ' ben', ' bir', ' L', 'LM', ...]

from anthropic import Anthropic
client = Anthropic()  # ANTHROPIC_API_KEY gerekli
 
response = client.messages.count_tokens(
    model="claude-sonnet-4-6",
    messages=[{"role": "user", "content": "Merhaba dünya, ben bir LLM mühendisiyim."}]
)
print(f"Claude'un saydığı token: {response.input_tokens}")

from langfuse.openai import openai  # drop-in replacement
 
response = openai.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Merhaba"}],
    metadata={"user_id": "user_42", "feature": "chat"}
)
# ✅ Otomatik Langfuse'a yazıldı: prompt, output, tokens, cost, latency

from litellm import completion
 
# Aynı API ile 4 farklı sağlayıcı
for model in ["gpt-4o-mini", "claude-haiku-4-5", "gemini/gemini-2.5-flash", "deepseek/deepseek-chat"]:
    response = completion(
        model=model,
        messages=[{"role": "user", "content": "Selam, kendini tanıt."}],
    )
    print(f"{model}: {response.usage.total_tokens} tokens, "
          f"${response._hidden_params['response_cost']:.5f}")