Move ai handlers to specific folder

pr_agent/algo/ai_handlers/openai_ai_handler.py

@@ -0,0 +1,67 @@
+from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
+import openai
+from openai.error import APIError, RateLimitError, Timeout, TryAgain
+from retry import retry
+
+from pr_agent.config_loader import get_settings
+from pr_agent.log import get_logger
+
+OPENAI_RETRIES = 5
+
+
+class OpenAIHandler(BaseAiHandler):
+    def __init__(self):
+        # Initialize OpenAIHandler specific attributes here
+        try:
+            super().__init__()
+            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):
+                if get_settings().openai.api_type == "azure":
+                    self.azure = True
+                    openai.azure_key = get_settings().openai.key
+            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
+
+        except AttributeError as e:
+            raise ValueError("OpenAI key is required") from e
+    @property
+    def deployment_id(self):
+        """
+        Returns the deployment ID for the OpenAI API.
+        """
+        return get_settings().get("OPENAI.DEPLOYMENT_ID", None)
+    
+    @retry(exceptions=(APIError, Timeout, TryAgain, 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(
+                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")
+            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:
+            get_logger().error("Error during OpenAI inference: ", e)
+            raise
+        except (RateLimitError) as e:
+            get_logger().error("Rate limit error during OpenAI inference: ", e)
+            raise
+        except (Exception) as e:
+            get_logger().error("Unknown error during OpenAI inference: ", e)
+            raise TryAgain from e