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https://github.com/princeton-nlp/tree-of-thought-llm
synced 2024-11-16 05:24:05 +00:00
45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
import os
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import openai
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import backoff
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completion_tokens = prompt_tokens = 0
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api_key = os.getenv("OPENAI_API_KEY", "")
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if api_key != "":
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openai.api_key = api_key
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else:
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print("Warning: OPENAI_API_KEY is not set")
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api_base = os.getenv("OPENAI_API_BASE", "")
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if api_base != "":
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print("Warning: OPENAI_API_BASE is set to {}".format(api_base))
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openai.api_base = api_base
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@backoff.on_exception(backoff.expo, openai.error.OpenAIError)
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def completions_with_backoff(**kwargs):
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return openai.ChatCompletion.create(**kwargs)
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def gpt(prompt, model="gpt-4", temperature=0.7, max_tokens=1000, n=1, stop=None) -> list:
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messages = [{"role": "user", "content": prompt}]
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return chatgpt(messages, model=model, temperature=temperature, max_tokens=max_tokens, n=n, stop=stop)
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def chatgpt(messages, model="gpt-4", temperature=0.7, max_tokens=1000, n=1, stop=None) -> list:
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global completion_tokens, prompt_tokens
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outputs = []
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while n > 0:
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cnt = min(n, 20)
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n -= cnt
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res = completions_with_backoff(model=model, messages=messages, temperature=temperature, max_tokens=max_tokens, n=cnt, stop=stop)
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outputs.extend([choice["message"]["content"] for choice in res["choices"]])
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# log completion tokens
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completion_tokens += res["usage"]["completion_tokens"]
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prompt_tokens += res["usage"]["prompt_tokens"]
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return outputs
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def gpt_usage(backend="gpt-4"):
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global completion_tokens, prompt_tokens
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if backend == "gpt-4":
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cost = completion_tokens / 1000 * 0.06 + prompt_tokens / 1000 * 0.03
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elif backend == "gpt-3.5-turbo":
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cost = (completion_tokens + prompt_tokens) / 1000 * 0.0002
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return {"completion_tokens": completion_tokens, "prompt_tokens": prompt_tokens, "cost": cost} |