refactor(ai_handler): move streaming response handling and Azure token generation to helpers

pr_agent/algo/ai_handlers/litellm_helpers.py

@@ -0,0 +1,113 @@
+import json
+
+import openai
+from azure.identity import ClientSecretCredential
+
+from pr_agent.config_loader import get_settings
+from pr_agent.log import get_logger
+
+
+async def _handle_streaming_response(response):
+    """
+    Handle streaming response from acompletion and collect the full response.
+
+    Args:
+        response: The streaming response object from acompletion
+
+    Returns:
+        tuple: (full_response_content, finish_reason)
+    """
+    full_response = ""
+    finish_reason = None
+
+    try:
+        async for chunk in response:
+            if chunk.choices and len(chunk.choices) > 0:
+                choice = chunk.choices[0]
+                delta = choice.delta
+                content = getattr(delta, 'content', None)
+                if content:
+                    full_response += content
+                if choice.finish_reason:
+                    finish_reason = choice.finish_reason
+    except Exception as e:
+        get_logger().error(f"Error handling streaming response: {e}")
+        raise
+
+    if not full_response and finish_reason is None:
+        get_logger().warning("Streaming response resulted in empty content with no finish reason")
+        raise openai.APIError("Empty streaming response received without proper completion")
+    elif not full_response and finish_reason:
+        get_logger().debug(f"Streaming response resulted in empty content but completed with finish_reason: {finish_reason}")
+        raise openai.APIError(f"Streaming response completed with finish_reason '{finish_reason}' but no content received")
+    return full_response, finish_reason
+
+
+class MockResponse:
+    """Mock response object for streaming models to enable consistent logging."""
+
+    def __init__(self, resp, finish_reason):
+        self._data = {
+            "choices": [
+                {
+                    "message": {"content": resp},
+                    "finish_reason": finish_reason
+                }
+            ]
+        }
+
+    def dict(self):
+        return self._data
+
+
+def _get_azure_ad_token():
+    """
+    Generates an access token using Azure AD credentials from settings.
+    Returns:
+        str: The access token
+    """
+    from azure.identity import ClientSecretCredential
+    try:
+        credential = ClientSecretCredential(
+            tenant_id=get_settings().azure_ad.tenant_id,
+            client_id=get_settings().azure_ad.client_id,
+            client_secret=get_settings().azure_ad.client_secret
+        )
+        # Get token for Azure OpenAI service
+        token = credential.get_token("https://cognitiveservices.azure.com/.default")
+        return token.token
+    except Exception as e:
+        get_logger().error(f"Failed to get Azure AD token: {e}")
+        raise
+
+
+def _process_litellm_extra_body(kwargs: dict) -> dict:
+    """
+    Process LITELLM.EXTRA_BODY configuration and update kwargs accordingly.
+
+    Args:
+        kwargs: The current kwargs dictionary to update
+
+    Returns:
+        Updated kwargs dictionary
+
+    Raises:
+        ValueError: If extra_body contains invalid JSON, unsupported keys, or colliding keys
+    """
+    allowed_extra_body_keys = {"processing_mode", "service_tier"}
+    extra_body = getattr(getattr(get_settings(), "litellm", None), "extra_body", None)
+    if extra_body:
+        try:
+            litellm_extra_body = json.loads(extra_body)
+            if not isinstance(litellm_extra_body, dict):
+                raise ValueError("LITELLM.EXTRA_BODY must be a JSON object")
+            unsupported_keys = set(litellm_extra_body.keys()) - allowed_extra_body_keys
+            if unsupported_keys:
+                raise ValueError(f"LITELLM.EXTRA_BODY contains unsupported keys: {', '.join(unsupported_keys)}. Allowed keys: {', '.join(allowed_extra_body_keys)}")
+            colliding_keys = kwargs.keys() & litellm_extra_body.keys()
+            if colliding_keys:
+                raise ValueError(f"LITELLM.EXTRA_BODY cannot override existing parameters: {', '.join(colliding_keys)}")
+            kwargs.update(litellm_extra_body)
+        except json.JSONDecodeError as e:
+            raise ValueError(f"LITELLM.EXTRA_BODY contains invalid JSON: {str(e)}")
+    return kwargs