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Supported OS
Get cost estimation, prompt and completion sampling, error tracking, performance metrics, and more out of LangChain Python library requests using Datadog metrics, APM, and logs.
docker run -d --cgroupns host \
--pid host \
-v /var/run/docker.sock:/var/run/docker.sock:ro \
-v /proc/:/host/proc/:ro \
-v /sys/fs/cgroup/:/host/sys/fs/cgroup:ro \
-e DD_API_KEY=<DATADOG_API_KEY> \
-p 127.0.0.1:8126:8126/tcp \
-p 127.0.0.1:8125:8125/udp \
-e DD_DOGSTATSD_NON_LOCAL_TRAFFIC=true \
-e DD_APM_ENABLED=true \
gcr.io/datadoghq/agent:latest
pip install ddtrace>=1.17
ddtrace-run
.DD_SERVICE="my-service" DD_ENV="staging" DD_API_KEY=<DATADOG_API_KEY> ddtrace-run python <your-app>.py
Note: If the Agent is using a non-default hostname or port, be sure to also set DD_AGENT_HOST
, DD_TRACE_AGENT_PORT
, or DD_DOGSTATSD_PORT
.
See the APM Python library documentation for more advanced usage.
See the APM Python library documentation for all the available configuration options.
To enable log prompt and completion sampling, set the DD_LANGCHAIN_LOGS_ENABLED=1
environment variable. By default, 10% of traced requests will emit logs containing the prompts and completions.
To adjust the log sample rate, see the APM library documentation.
Note: Logs submission requires DD_API_KEY
to be specified when running ddtrace-run
.
Validate that the APM Python library can communicate with your Agent using:
ddtrace-run --info
You should see the following output:
Agent error: None
Pass the --debug
flag to ddtrace-run
to enable debug logging.
ddtrace-run --debug
This displays any errors sending data:
ERROR:ddtrace.internal.writer.writer:failed to send, dropping 1 traces to intake at http://localhost:8126/v0.5/traces after 3 retries ([Errno 61] Connection refused)
WARNING:ddtrace.vendor.dogstatsd:Error submitting packet: [Errno 61] Connection refused, dropping the packet and closing the socket
DEBUG:ddtrace.contrib._trace_utils_llm.py:sent 2 logs to 'http-intake.logs.datadoghq.com'
langchain.request.duration (gauge) | Request duration distribution. Shown as nanosecond |
langchain.request.error (count) | Number of errors. Shown as error |
langchain.tokens.completion (gauge) | Number of tokens used in the completion of a response. Shown as token |
langchain.tokens.prompt (gauge) | Number of tokens used in the prompt of a request. Shown as token |
langchain.tokens.total (gauge) | Total number of tokens used in a request and response. Shown as token |
langchain.tokens.total_cost (count) | Estimated cost in USD based on token usage. Shown as dollar |
The LangChain integration does not include any events.
The LangChain integration does not include any service checks.
Need help? Contact Datadog support.