diff --git a/src/monocle_apptrace/instrumentor.py b/src/monocle_apptrace/instrumentor.py
index 84b07e3..1ba6b70 100644
--- a/src/monocle_apptrace/instrumentor.py
+++ b/src/monocle_apptrace/instrumentor.py
@@ -18,7 +18,7 @@
 
 logger = logging.getLogger(__name__)
 
-_instruments = ("langchain >= 0.0.346",)
+_instruments = ()
 
 class MonocleInstrumentor(BaseInstrumentor):
 
diff --git a/src/monocle_apptrace/wrap_common.py b/src/monocle_apptrace/wrap_common.py
index bcc785a..c7b6fea 100644
--- a/src/monocle_apptrace/wrap_common.py
+++ b/src/monocle_apptrace/wrap_common.py
@@ -191,6 +191,7 @@ def get_input_from_args(chain_args):
     return ""
 
 def update_span_from_llm_response(response, span: Span):
+    
     # extract token uasge from langchain openai
     if (response is not None and hasattr(response, "response_metadata")):
         response_metadata = response.response_metadata
@@ -201,15 +202,19 @@ def update_span_from_llm_response(response, span: Span):
             span.set_attribute("total_tokens", token_usage.get("total_tokens"))
     # extract token usage from llamaindex openai
     if(response is not None and hasattr(response, "raw")):
-        if response.raw is not None:
-            token_usage = response.raw.get("usage")
-            if token_usage is not None:
-                if hasattr(token_usage, "completion_tokens"):
-                    span.set_attribute("completion_tokens", token_usage.completion_tokens)
-                if hasattr(token_usage, "prompt_tokens"):
-                    span.set_attribute("prompt_tokens", token_usage.prompt_tokens)
-                if hasattr(token_usage, "total_tokens"):
-                    span.set_attribute("total_tokens", token_usage.total_tokens)
+        try:
+            if response.raw is not None:
+                token_usage = response.raw.get("usage") if isinstance(response.raw, dict) else getattr(response.raw, "usage", None)
+                if token_usage is not None:
+                    if getattr(token_usage, "completion_tokens", None):
+                        span.set_attribute("completion_tokens", getattr(token_usage, "completion_tokens"))
+                    if getattr(token_usage, "prompt_tokens", None):
+                        span.set_attribute("prompt_tokens", getattr(token_usage, "prompt_tokens"))
+                    if getattr(token_usage, "total_tokens", None):
+                        span.set_attribute("total_tokens", getattr(token_usage, "total_tokens"))
+        except AttributeError:
+            token_usage = None
+
 
 def update_workflow_type(to_wrap, span: Span):
     package_name = to_wrap.get('package')
diff --git a/tests/helpers.py b/tests/helpers.py
index c2d6c92..27f366f 100644
--- a/tests/helpers.py
+++ b/tests/helpers.py
@@ -10,6 +10,17 @@
 )
 from llama_index.core.llms.callbacks import llm_completion_callback
 
+class TestChatCompletion:
+    
+    def __init__(self, usage):
+        self.usage = usage 
+
+class TestCompletionUsage:
+    
+    def __init__(self, completion_tokens, prompt_tokens, total_tokens):
+        self.completion_tokens = completion_tokens
+        self.prompt_tokens = prompt_tokens 
+        self.total_tokens = total_tokens
 
 class OurLLM(CustomLLM):
     context_window: int = 3900
@@ -28,7 +39,15 @@ def metadata(self) -> LLMMetadata:
 
     @llm_completion_callback()
     def complete(self, prompt: str, **kwargs: Any) -> CompletionResponse:
-        return CompletionResponse(text=self.dummy_response)
+        return CompletionResponse(
+            text=self.dummy_response,
+            raw= {
+                "usage": TestCompletionUsage(
+                    completion_tokens=1,
+                    prompt_tokens = 2,
+                    total_tokens=3
+                )
+            })
 
     @llm_completion_callback()
     def stream_complete(
diff --git a/tests/llama_index_test.py b/tests/llama_index_test.py
index 4279e58..95151a7 100644
--- a/tests/llama_index_test.py
+++ b/tests/llama_index_test.py
@@ -28,7 +28,7 @@
     llm_wrapper,
 )
 from monocle_apptrace.wrapper import WrapperMethod
-from opentelemetry.sdk.trace.export import BatchSpanProcessor
+from opentelemetry.sdk.trace.export import BatchSpanProcessor, ConsoleSpanExporter
 
 logger = logging.getLogger(__name__)
 
@@ -55,7 +55,8 @@ def test_llama_index(self, mock_post):
         setup_monocle_telemetry(
             workflow_name="llama_index_1",
             span_processors=[
-                    BatchSpanProcessor(HttpSpanExporter(os.environ["HTTP_INGESTION_ENDPOINT"]))
+                    BatchSpanProcessor(HttpSpanExporter(os.environ["HTTP_INGESTION_ENDPOINT"])),
+                    BatchSpanProcessor(ConsoleSpanExporter())
                 ],
             wrapper_methods=[
                         WrapperMethod(
@@ -119,9 +120,13 @@ def get_event_attributes(events, key):
         assert output_event_attributes[RESPONSE] == llm.dummy_response
 
         span_names: List[str] = [span["name"] for span in dataJson['batch']]
+        llm_span = [x for x in  dataJson["batch"] if "llamaindex.OurLLM" in x["name"]][0]
         for name in ["llamaindex.retrieve", "llamaindex.query", "llamaindex.OurLLM"]:
             assert name in span_names
-
+        assert llm_span["attributes"]["completion_tokens"] == 1
+        assert llm_span["attributes"]["prompt_tokens"] == 2
+        assert llm_span["attributes"]["total_tokens"] == 3
+        
         type_found = False
         model_name_found = False