Merge remote-tracking branch 'origin/main' into feat/ragas-evaluation

lightrag/llm/openai.py

@@ -27,18 +27,6 @@ from lightrag.utils import (
     logger,
 )
 
-# Try to import Langfuse for LLM observability (optional)
-# Falls back to standard OpenAI client if not available
-try:
-    from langfuse.openai import AsyncOpenAI
-
-    LANGFUSE_ENABLED = True
-    logger.info("Langfuse observability enabled for OpenAI client")
-except ImportError:
-    from openai import AsyncOpenAI
-
-    LANGFUSE_ENABLED = False
-    logger.debug("Langfuse not available, using standard OpenAI client")
 from lightrag.types import GPTKeywordExtractionFormat
 from lightrag.api import __api_version__
 
@@ -48,6 +36,32 @@ from typing import Any, Union
 
 from dotenv import load_dotenv
 
+# Try to import Langfuse for LLM observability (optional)
+# Falls back to standard OpenAI client if not available
+# Langfuse requires proper configuration to work correctly
+LANGFUSE_ENABLED = False
+try:
+    # Check if required Langfuse environment variables are set
+    langfuse_public_key = os.environ.get("LANGFUSE_PUBLIC_KEY")
+    langfuse_secret_key = os.environ.get("LANGFUSE_SECRET_KEY")
+
+    # Only enable Langfuse if both keys are configured
+    if langfuse_public_key and langfuse_secret_key:
+        from langfuse.openai import AsyncOpenAI
+
+        LANGFUSE_ENABLED = True
+        logger.info("Langfuse observability enabled for OpenAI client")
+    else:
+        from openai import AsyncOpenAI
+
+        logger.debug(
+            "Langfuse environment variables not configured, using standard OpenAI client"
+        )
+except ImportError:
+    from openai import AsyncOpenAI
+
+    logger.debug("Langfuse not available, using standard OpenAI client")
+
 # use the .env that is inside the current folder
 # allows to use different .env file for each lightrag instance
 # the OS environment variables take precedence over the .env file
@@ -382,18 +396,23 @@ async def openai_complete_if_cache(
                         )
 
                 # Ensure resources are released even if no exception occurs
-                if (
-                    iteration_started
-                    and hasattr(response, "aclose")
-                    and callable(getattr(response, "aclose", None))
-                ):
-                    try:
-                        await response.aclose()
-                        logger.debug("Successfully closed stream response")
-                    except Exception as close_error:
-                        logger.warning(
-                            f"Failed to close stream response in finally block: {close_error}"
-                        )
+                # Note: Some wrapped clients (e.g., Langfuse) may not implement aclose() properly
+                if iteration_started and hasattr(response, "aclose"):
+                    aclose_method = getattr(response, "aclose", None)
+                    if callable(aclose_method):
+                        try:
+                            await response.aclose()
+                            logger.debug("Successfully closed stream response")
+                        except (AttributeError, TypeError) as close_error:
+                            # Some wrapper objects may report hasattr(aclose) but fail when called
+                            # This is expected behavior for certain client wrappers
+                            logger.debug(
+                                f"Stream response cleanup not supported by client wrapper: {close_error}"
+                            )
+                        except Exception as close_error:
+                            logger.warning(
+                                f"Unexpected error during stream response cleanup: {close_error}"
+                            )
 
                 # This prevents resource leaks since the caller doesn't handle closing
                 try: