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Merge branch 'main' into introduce-pre-commit

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Tal
2024-11-08 09:54:21 +02:00
committed by GitHub
parent 852bb371af f9380c2440
commit 5c5a3e267c
21 changed files with 377 additions and 132 deletions
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26
pr_agent/algo/ai_handlers/openai_ai_handler.py
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@ -1,5 +1,7 @@
from os import environ
from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
import openai
from openai.error import APIError, RateLimitError, Timeout, TryAgain
from openai import APIError, AsyncOpenAI, RateLimitError, Timeout
from retry import retry
from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
@ -14,7 +16,7 @@ class OpenAIHandler(BaseAiHandler):
# Initialize OpenAIHandler specific attributes here
try:
super().__init__()
openai.api_key = get_settings().openai.key
environ["OPENAI_API_KEY"] = get_settings().openai.key
if get_settings().get("OPENAI.ORG", None):
openai.organization = get_settings().openai.org
if get_settings().get("OPENAI.API_TYPE", None):
@ -24,7 +26,7 @@ class OpenAIHandler(BaseAiHandler):
if get_settings().get("OPENAI.API_VERSION", None):
openai.api_version = get_settings().openai.api_version
if get_settings().get("OPENAI.API_BASE", None):
openai.api_base = get_settings().openai.api_base
environ["OPENAI_BASE_URL"] = get_settings().openai.api_base
except AttributeError as e:
raise ValueError("OpenAI key is required") from e
@ -36,28 +38,26 @@ class OpenAIHandler(BaseAiHandler):
"""
return get_settings().get("OPENAI.DEPLOYMENT_ID", None)
@retry(exceptions=(APIError, Timeout, TryAgain, AttributeError, RateLimitError),
@retry(exceptions=(APIError, Timeout, AttributeError, RateLimitError),
tries=OPENAI_RETRIES, delay=2, backoff=2, jitter=(1, 3))
async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2):
try:
deployment_id = self.deployment_id
get_logger().info("System: ", system)
get_logger().info("User: ", user)
messages = [{"role": "system", "content": system}, {"role": "user", "content": user}]
chat_completion = await openai.ChatCompletion.acreate(
client = AsyncOpenAI()
chat_completion = await client.chat.completions.create(
model=model,
deployment_id=deployment_id,
messages=messages,
temperature=temperature,
)
resp = chat_completion["choices"][0]['message']['content']
finish_reason = chat_completion["choices"][0]["finish_reason"]
usage = chat_completion.get("usage")
resp = chat_completion.choices[0].message.content
finish_reason = chat_completion.choices[0].finish_reason
usage = chat_completion.usage
get_logger().info("AI response", response=resp, messages=messages, finish_reason=finish_reason,
model=model, usage=usage)
return resp, finish_reason
except (APIError, Timeout, TryAgain) as e:
except (APIError, Timeout) as e:
get_logger().error("Error during OpenAI inference: ", e)
raise
except (RateLimitError) as e:
@ -65,4 +65,4 @@ class OpenAIHandler(BaseAiHandler):
raise
except (Exception) as e:
get_logger().error("Unknown error during OpenAI inference: ", e)
raise TryAgain from e
raise