Cohere
Learn about using Sentry for Cohere.
Beta
The support for Cohere is in its beta phase.
We are working on supporting different AI libraries (see GitHub discussion).
If you want to try the beta features and are willing to give feedback, please let us know on Discord.
This integration connects Sentry with the Cohere Python SDK. The integration has been confirmed to work with Cohere 5.3.3.
Once you've installed this SDK, you can use Sentry LLM Monitoring, a Sentry dashboard that helps you understand what's going on with your AI pipelines.
Sentry LLM Monitoring will automatically collect information about prompts, tokens, and models from providers like Cohere. Learn more about it here.
Install sentry-sdk
and cohere
from PyPI:
pip install --upgrade 'sentry-sdk' 'cohere'
If you have the cohere
package in your dependencies, the integration will be enabled automatically when you initialize the Sentry SDK.
import sentry_sdk
from cohere import Client
sentry_sdk.init(
dsn="https://examplePublicKey@o0.ingest.sentry.io/0",
enable_tracing=True,
traces_sample_rate=1.0,
)
client = Client()
Verify that the integration works by creating an AI pipeline. The resulting data should show up in your LLM monitoring dashboard.
import sentry_sdk
from sentry_sdk.ai.monitoring import ai_track
from cohere import Client
sentry_sdk.init(...) # same as above
client = Client(api_key="(your Cohere API key)")
@ai_track("My AI pipeline")
def my_pipeline():
with sentry_sdk.start_transaction(op="ai-inference", name="The result of the AI inference"):
print(
client.chat(
model="command", message="say hello"
)
)
After running this script, a pipeline will be created in the LLM Monitoring section of the Sentry dashboard. The pipeline will have an associated Cohere span for the chat.completions.create
operation.
It may take a couple of moments for the data to appear in sentry.io.
The Cohere integration will connect Sentry with all supported Cohere methods automatically.
All exceptions caused by Cohere methods are reported to Sentry.
The supported modules are currently
chat
andembed
.Sentry considers LLM and tokenizer inputs/outputs as PII and doesn't include PII data by default. If you want to include that data, set
send_default_pii=True
in thesentry_sdk.init()
call. To explicitly exclude prompts and outputs despitesend_default_pii=True
, configure the integration withinclude_prompts=False
as shown in the Options section below.
By adding CohereIntegration
to your sentry_sdk.init()
call explicitly, you can set options for CohereIntegration
to change its behavior:
import sentry_sdk
from sentry_sdk.integrations.cohere import CohereIntegration
sentry_sdk.init(
dsn="https://examplePublicKey@o0.ingest.sentry.io/0",
enable_tracing=True,
send_default_pii=True,
traces_sample_rate=1.0,
integrations = [
CohereIntegration(
include_prompts=False, # LLM/tokenizer inputs/outputs will be not sent to Sentry, despite send_default_pii=True
),
],
)
- Cohere: 5.0+
- Python: 3.9+
Our documentation is open source and available on GitHub. Your contributions are welcome, whether fixing a typo (drat!) or suggesting an update ("yeah, this would be better").