mirror of
https://github.com/qodo-ai/pr-agent.git
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74 lines
3.3 KiB
Python
74 lines
3.3 KiB
Python
try:
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from langchain_openai import ChatOpenAI, AzureChatOpenAI
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from langchain_core.messages import SystemMessage, HumanMessage
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except: # we don't enforce langchain as a dependency, so if it's not installed, just move on
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pass
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from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
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from pr_agent.config_loader import get_settings
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from pr_agent.log import get_logger
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from openai import APIError, RateLimitError, Timeout
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from retry import retry
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import functools
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OPENAI_RETRIES = 5
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class LangChainOpenAIHandler(BaseAiHandler):
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def __init__(self):
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# Initialize OpenAIHandler specific attributes here
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super().__init__()
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self.azure = get_settings().get("OPENAI.API_TYPE", "").lower() == "azure"
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try:
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if self.azure:
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# using a partial function so we can set the deployment_id later to support fallback_deployments
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# but still need to access the other settings now so we can raise a proper exception if they're missing
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self._chat = functools.partial(
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lambda **kwargs: AzureChatOpenAI(**kwargs),
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openai_api_key=get_settings().openai.key,
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openai_api_base=get_settings().openai.api_base,
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openai_api_version=get_settings().openai.api_version,
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)
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else:
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# for llms that compatible with openai, should use custom api base
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openai_api_base = get_settings().get("OPENAI.API_BASE", None)
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if openai_api_base is None or len(openai_api_base) == 0:
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self._chat = ChatOpenAI(openai_api_key=get_settings().openai.key)
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else:
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self._chat = ChatOpenAI(openai_api_key=get_settings().openai.key, openai_api_base=openai_api_base)
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except AttributeError as e:
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if getattr(e, "name"):
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raise ValueError(f"OpenAI {e.name} is required") from e
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else:
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raise e
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def chat(self, messages: list, model: str, temperature: float):
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if self.azure:
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# we must set the deployment_id only here (instead of the __init__ method) to support fallback_deployments
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return self._chat.invoke(input = messages, model=model, temperature=temperature, deployment_name=self.deployment_id)
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else:
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return self._chat.invoke(input = messages, model=model, temperature=temperature)
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@property
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def deployment_id(self):
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"""
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Returns the deployment ID for the OpenAI API.
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"""
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return get_settings().get("OPENAI.DEPLOYMENT_ID", None)
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@retry(exceptions=(APIError, Timeout, AttributeError, RateLimitError),
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tries=OPENAI_RETRIES, delay=2, backoff=2, jitter=(1, 3))
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async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2):
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try:
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messages = [SystemMessage(content=system), HumanMessage(content=user)]
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# get a chat completion from the formatted messages
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resp = self.chat(messages, model=model, temperature=temperature)
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finish_reason = "completed"
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return resp.content, finish_reason
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except (Exception) as e:
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get_logger().error("Unknown error during OpenAI inference: ", e)
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raise e
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