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Description
How do you use Sentry?
Sentry Saas (sentry.io)
Version
2.33.0
Steps to Reproduce
Integration problem with langchain for Vertex AI models
I noticed that all my calls to Vertex AI models are missing token usage. When I checked your implementation, I see that you are counting tokens based on tiktoken which contains only OpenAI encoders. Also, you are using the attribute ChatResponse.llm_output of langchain to get the token_usage, which seems to be empty for all Vertex AI responses.
import json
import sentry_sdk
from google.oauth2.service_account import Credentials
from langchain_google_vertexai import ChatVertexAI
sentry_sdk.init(dsn=YOUR_DSN, traces_sample_rate=1.0, send_default_pii=True)
with open(
YOUR_PATH_TO_CRED
) as f:
creds = json.load(f)
vertex_ai_credentials = Credentials.from_service_account_info(creds)
model = ChatVertexAI(
model_name="gemini-2.0-flash-001",
credentials=vertex_ai_credentials,
)
with sentry_sdk.start_transaction(op="llm_call", name="test_vertex_ai") as transaction:
model.invoke("hello world")
Expected Result
Token usage should be available in the chat span
Actual Result
Current token usage in the span (input, output and total) are all 0.
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