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馃 Handle Anthropic RateLimitError #45

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馃 Handle Anthropic RateLimitError #45

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daee647
馃 Update call_llm.py
lcombaldieu Apr 23, 2025
d32eea7
:adhesive_bandage: Fixed time dependency
lcombaldieu Apr 23, 2025
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馃 Update call_llm.py 
Handle Anthropic RateLimitError
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@lcombaldieu
lcombaldieu authored Apr 23, 2025
commit daee6474875bfd58a09f081faa7db14fcd32f211
30 changes: 18 additions & 12 deletions utils/call_llm.py
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Expand Up @@ -85,19 +85,25 @@ def call_llm(prompt: str, use_cache: bool = True) -> str:

# # Use Anthropic Claude 3.7 Sonnet Extended Thinking
# def call_llm(prompt, use_cache: bool = True):
# from anthropic import Anthropic
# from anthropic import Anthropic, RateLimitError
# client = Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY", "your-api-key"))
# response = client.messages.create(
# model="claude-3-7-sonnet-20250219",
# max_tokens=21000,
# thinking={
# "type": "enabled",
# "budget_tokens": 20000
# },
# messages=[
# {"role": "user", "content": prompt}
# ]
# )
# try:
# response = client.messages.create(
# model="claude-3-7-sonnet-20250219",
# max_tokens=21000,
# thinking={
# "type": "enabled",
# "budget_tokens": 20000
# },
# messages=[
# {"role": "user", "content": prompt}
# ]
# )
# except RateLimitError:
# for i in range(70):
# print(f"Rate limit exceeded. Waiting {70-i}s before retrying", end='\r', flush=True)
# time.sleep(1)
# return call_llm(prompt)
# return response.content[1].text

# # Use OpenAI o1
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