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85 lines
2.1 KiB
Python
85 lines
2.1 KiB
Python
import hashlib
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import json
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import backoff
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import openai
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import requests
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# from diskcache import Cache
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from openai.error import (
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APIConnectionError,
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APIError,
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RateLimitError,
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ServiceUnavailableError,
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Timeout,
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)
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CACHE_PATH = "~/.aider.send.cache.v1"
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CACHE = None
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# CACHE = Cache(CACHE_PATH)
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@backoff.on_exception(
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backoff.expo,
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(
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Timeout,
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APIError,
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ServiceUnavailableError,
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RateLimitError,
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APIConnectionError,
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requests.exceptions.ConnectionError,
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),
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max_tries=10,
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on_backoff=lambda details: print(
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f"{details.get('exception','Exception')}\nRetry in {details['wait']:.1f} seconds."
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),
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)
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def send_with_retries(model_name, messages, functions, stream):
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kwargs = dict(
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model=model_name,
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messages=messages,
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temperature=0,
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stream=stream,
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)
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if functions is not None:
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kwargs["functions"] = functions
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# we are abusing the openai object to stash these values
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if hasattr(openai, "api_deployment_id"):
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kwargs["deployment_id"] = openai.api_deployment_id
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if hasattr(openai, "api_engine"):
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kwargs["engine"] = openai.api_engine
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if "openrouter.ai" in openai.api_base:
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kwargs["headers"] = {
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"HTTP-Referer": "http://aider.chat",
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"X-Title": "Aider"
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}
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key = json.dumps(kwargs, sort_keys=True).encode()
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# Generate SHA1 hash of kwargs and append it to chat_completion_call_hashes
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hash_object = hashlib.sha1(key)
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if not stream and CACHE is not None and key in CACHE:
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return hash_object, CACHE[key]
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res = openai.ChatCompletion.create(**kwargs)
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if not stream and CACHE is not None:
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CACHE[key] = res
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return hash_object, res
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def simple_send_with_retries(model_name, messages):
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try:
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_hash, response = send_with_retries(
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model_name=model_name,
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messages=messages,
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functions=None,
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stream=False,
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)
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return response.choices[0].message.content
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except (AttributeError, openai.error.InvalidRequestError):
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return
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