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chore(deps): update dependency ddtrace to v2.12.2 #356
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This PR contains the following updates:
2.9.2
->2.12.2
Release Notes
DataDog/dd-trace-py (ddtrace)
v2.12.2
: 2.12.2Compare Source
Bug Fixes
attrs
installed by default on some Ubuntu installations was treated as incompatible with library injectionAttributeError
exceptions were being caught, interfering with the proper application cycle.v2.12.1
: 2.12.1Compare Source
Bug Fixes
v2.12.0
Compare Source
New Features
model
tag for openai integration metrics for consistency with the OpenAI SaaS Integration. It has the same value asopenai.request.model
.server.address
tag to all<database>.query
spans (ex: postgres.query). This tag stores the name of the database host.ddtrace.trace.Context
to the public api. This class can now be used to propagate context across execution boundaries (ex: threads).Deprecation Notes
DD_TRACE_128_BIT_TRACEID_LOGGING_ENABLED
is deprecated. Trace id logging format is now configured automatically.ddtrace.contrib.[integration_name]
package. Use attributes exposed inddtrace.contrib.[integration_name].__all__
instead. The following are impacted:aioredis
,algoliasearch
.anthropic
,aredis
,asgi
,asyncpg
,aws_lambda
,boto
,botocore
,bottle
,cassandra
,celery
,cherrypy
,consul
,coverage
,django
,dogpile_cache
,dramatiq
,elasticsearch
,falcon
,fastapi
,flask
,flask_cache
,futures
,gevent
,graphql
,grpc
,httplib
,httpx
,jinja2
,kafka
,kombu
,langchain
,logbook
,logging
,loguru
,mako
,mariadb
,molten
,mongoengine
,mysql
,mysqldb
,openai
,psycopg
,pylibmc
,pymemcache
,pymongo
,pymysql
,pynamodb
,pyodbc
,pyramid
,redis
,rediscluster
,requests
,sanic
,snowflake
,sqlalchemy
,sqlite3
,starlette
,structlog
,subprocess
,tornado
,urllib
,urllib3
,vertica
,webbrowser
,wsgi
,yaaredis
Bug Fixes
CI Visibility: Resolves an issue where exceptions other than timeouts and connection errors raised while fetching the list of skippable tests for ITR were not being handled correctly and caused the tracer to crash.
CI Visibility: Fixes a bug where
.git
was incorrectly being stripped from repository URLs when extracting service names, resulting ing
,i
, ort
being removed (eg:test-environment.git
incorrectly becomingtest-environmen
)LLM Observability: Resolves an issue where custom trace filters were being overwritten in forked processes.
tracing: Fixes a side-effect issue with module import callbacks that could cause a runtime exception.
LLM Observability: Resolves an issue where
session_id
was being defaulted totrace_id
, which was causing unexpected UI behavior.LLM Observability: Resolves an issue where LLM Observability spans were not being submitted in forked processes, such as when using
celery
orgunicorn
workers. The LLM Observability writer thread now automatically restarts when a forked process is detected.tracing: Fixes an issue with some module imports with native specs that don't support attribute assignments, resulting in a
TypeError
exception at runtime.tracing: Resolves an issue where
ddtrace
package files were published with incorrect file attributes.tracing: Resolves an issue where django db instrumentation could fail.
openai: Fixes a bug where
asyncio.TimeoutError
s were not being propagated correctly from canceled OpenAI API requests.aiobotocore: Fixes an issue where the
_make_api_call
arguments were not captured correctly when using keyword arguments.tracing(django): Resolves a bug where ddtrace was exhausting a Django stream response before returning it to user.
LLM Observability: Fixes an issue in the OpenAI integration where integration metrics would still be submitted even if
LLMObs.enable(agentless_enabled=True)
was set.internal: Fixes the
Already mutably borrowed
error when rate limiter is accessed across threads.internal: Fixes the
Already mutably borrowed
error by reverting back to pure-python rate limiter.Code Security: Adds null pointer checks when creating new objects ids.
profiling: Fixes an issue where the profiler could erroneously try to load protobuf in autoinjected environments, where it is not available.
crashtracking: Fixes an issue where crashtracking environment variables for Python were inconsistent with those used by other runtimes.
profiling: Fixes endpoint profiling for stack v2 when
DD_PROFILING_STACK_V2_ENABLED
is set.profiling: Turns on the new native exporter when
DD_PROFILING_TIMELINE_ENABLED=True
is set.v2.11.6
Compare Source
Bug Fixes
attrs
installed by default on some Ubuntu installations was treated as incompatible with library injectionAttributeError
exceptions were being caught, interfering with the proper application cycle.v2.11.5
: 2.11.5Compare Source
Bug Fixes
v2.11.4
Compare Source
Bug Fixes
.git
was incorrectly being stripped from repository URLs when extracting service names, resulting ing
,i
, ort
being removed (eg:test-environment.git
incorrectly becomingtest-environmen
)session_id
was being defaulted totrace_id
which was causing unexpected UI behavior.v2.11.3
: 2.11.3Compare Source
Bug Fixes
v2.11.2
: 2.11.2Compare Source
New Features
model
tag for openai integration metrics for consistency with the OpenAI SaaS Integration. It has the same value asopenai.request.model
.Bug Fixes
celery
orgunicorn
workers. The LLM Observability writer thread now automatically restarts when a forked process is detected.asyncio.TimeoutError
s were not being propagated correctly from canceled OpenAI API requests.v2.11.1
Compare Source
Bug Fixes
TypeError
exception at runtime.Already mutably borrowed
error by reverting back to pure-python rate limiter.ddtrace
package files were published with incorrect file attributes.DD_PROFILING_STACK_V2_ENABLED
set.v2.11.0
Compare Source
New Features
ASM: This update introduces new Auto User Events support.
ASM’s [Account TakeOver (ATO) detection](https://docs.datadoghq.com/security/account_takeover_protection) is now automatically monitoring [all compatible user authentication frameworks](https://docs.datadoghq.com/security/application_security/enabling/compatibility/) to detect attempted or leaked user credentials during an ATO campaign.
To do so, the monitoring of the user activity is extended to now collect all forms of user IDs, including non-numerical forms such as usernames or emails. This is configurable with 3 different working modes: identification to send the user IDs in clear text; anonymization to send anonymized user IDs; or disabled to completely turn off any type of user ID collection (which leads to the disablement of the ATO detection).
The default collection mode being used is identification and this is configurable in your remote service configuration settings in the [service catalog]( https://app.datadog.com/security/appsec/inventory/services?tab=capabilities) (clicking on a service), or with the service environment variable DD_APPSEC_AUTO_USER_INSTRUMENTATION_MODE.
You can read more [here](https://docs.datadoghq.com/security/account_takeover_protection).
New local configuration environment variables include:
Additionally, an optional argument for the public API track_user_login_success_event and `track_user_login_failure_event`: login_events_mode="auto". This allows manual instrumentation to follow remote configuration settings, enabling or disabling manual instrumentation with a single remote action on the Datadog UI.
Also prevents non numerical user ids to be reported by default without user instrumentation in Django.
Anthropic: Adds support for tracing message calls using tools.
LLM Observability: Adds support for tracing Anthropic messages using tool calls.
botocore: Adds support for overriding the default service name in botocore by either setting the environment variable
DD_BOTOCORE_SERVICE
or configuring it via ddtrace.config.botocore["service"].azure: Removes the restrictions on the tracer to only run the mini-agent on the consumption plan. The mini-agent now runs regardless of the hosting plan
ASM: Adds Threat Monitoring support for gRPC.
Code Security: add propagation for GRPC server sources.
LLM Observability: This introduces improved support for capturing tool call responses from the OpenAI and Anthropic integrations.
LLM Observability: This introduces the agentless mode configuration for LLM Observability. To enable agentless mode, set the environment variable
DD_LLMOBS_AGENTLESS_ENABLED=1
, or use the enable optionLLMObs.enable(agentless_enabled=True)
.LLM Observability: Function decorators now support tracing asynchronous functions.
LLM Observability: This introduces automatic input/output annotation for task/tool/workflow/agent/retrieval spans traced by function decorators. Note that manual annotations for input/output values will override automatic annotations.
LLM Observability: The OpenAI integration now submits embedding spans to LLM Observability.
LLM Observability: All OpenAI model parameters specified in a completion/chat completion request are now captured.
LLM Observability: This changes OpenAI-generated LLM Observability span names from
openai.request
toopenai.createCompletion
,openai.createChatCompletion
, andopenai.createEmbedding
for completions, chat completions, and embeddings spans, respectively.LLM Observability: This introduces the agent proxy mode for LLM Observability. By default, LLM Observability spans will be sent to the Datadog agent and then forwarded to LLM Observability. To continue submitting data directly to LLM Observability without the Datadog agent, set
DD_LLMOBS_AGENTLESS_ENABLED=1
or set programmatically usingLLMObs.enable(agentless_enabled=True)
.LLM Observability: The Langchain integration now submits embedding spans to LLM Observability.
LLM Observability: The
LLMObs.annotate()
method now replaces non-JSON serializable values with a placeholder string[Unserializable object: <string representation of object>]
instead of rejecting the annotation entirely.pylibmc: adds traces for memcached add command
ASM: This introduces fingerprinting with libddwaf 1.19.1
Database Monitoring: Adds Database Monitoring (DBM) trace propagation for postgres databases used through Django.
langchain: Tags tool calls on chat completions.
LLM Observability: Adds retry logic to the agentless span writer to mitigate potential networking issues, like timeouts or dropped connections.
ASM: This introduces Command Injection support for Exploit Prevention on os.system only.
ASM: This introduces suspicious attacker blocking with libddwaf 1.19.1
Upgrade Notes
Deprecation Notes
patch()
andunpatch()
are deprecated and will be removed in version 3.0.0.patch()
andunpatch()
are deprecated and will be removed in version 3.0.0.patch()
andunpatch()
are deprecated and will be removed in version 3.0.0.patch()
andunpatch()
are deprecated and will be removed in version 3.0.0.patch()
andunpatch()
are deprecated and will be removed in version 3.0.0.patch()
andunpatch()
are deprecated and will be removed in version 3.0.0.patch()
andunpatch()
are deprecated and will be removed in version 3.0.0.patch()
andunpatch()
are deprecated and will be removed in version 3.0.0.patch()
andunpatch()
are deprecated and will be removed in version 3.0.0.patch()
andunpatch()
are deprecated and will be removed in version 3.0.0.DD_EXCEPTION_DEBUGGING_ENABLED
environment variable has been deprecated in favor ofDD_EXCEPTION_REPLAY_ENABLED
. The old environment variable will be removed in a future major release.Bug Fixes
LLM Observability: Fixes an issue in the OpenAI integration where integration metrics would still be submitted even if
LLMObs.enable(agentless_enabled=True)
was set.Code Security: add null pointer checks when creating new objects ids.
Code Security: add encodings.idna to the IAST patching denylist to avoid problems with gevent.
Code Security: add the boto package to the IAST patching denylist.
Code Security: fix two small memory leaks with Python 3.11 and 3.12.
CI Visibility: Fixes an issue where the pytest plugin would crash if the git binary was absent
CI Visibility: fixes incorrect URL for telemetry intake in EU that was causing missing telemetry data and SSL error log messages.
celery: changes
error.message
span tag to no longer include the traceback that is already included in theerror.stack
span tag.CI Visibility: fixes source file information that would be incorrect in certain decorated / wrapped scenarios and forces paths to be relative to the repository root, if present.
futures: Fixes inconsistent behavior with
concurrent.futures.ThreadPoolExecutor
context propagation by passing the current trace context instead of the currently active span to tasks. This prevents edge cases of disconnected spans when the task executes after the parent span has finished.kafka: Fixes
ArgumentError
raised when injecting span context into non-existent Kafka message headers.botocore: Fixes Botocore Kinesis span parenting to use active trace context if a propagated child context is not found instead of empty context.
langchain: This fix resolves an issue where the wrong langchain class name was being used to check for Pinecone vectorstore instances.
LLM Observability: This resolves a typing hint error in the
ddtrace.llmobs.utils.Documents
helper class constructor where type hints did not accept input dictionaries with integer or float values.LLM Observability: This fix resolves an issue where the OpenAI, Anthropic, and AWS Bedrock integrations were always setting
temperature
andmax_tokens
parameters to LLM invocations. The OpenAI integration in particular was setting the wrongtemperature
default values. These parameters are now only set if provided in the request.opentelemetry: Resolves circular imports raised by the OpenTelemetry API when the
ddcontextvars_context
entrypoint is loaded. This resolves an incompatibility introduced inopentelemetry-api==1.25.0
.opentelemetry: Resolves an issue where the
get_tracer
function would raise aTypeError
when called with theattribute
argument. This resolves an incompatibility introduced inopentelemetry-api==1.26.0
.psycopg: Ensures traced async cursors return an asynchronous iterator object.
redis: This fix resolves an issue in the redis exception handling where an UnboundLocalError was raised instead of the expected BaseException.
ASM: This fix resolves an issue where the requests integration would not propagate when apm is opted out (i.e. in ASM Standalone).
profiling: Fixes an issue where task information coming from echion was encoded improperly, which could segfault the application.
tracing: fixes a potential crash where using partial flushes and
tracer.configure()
could result in an IndexErrortracer: This fix resolves an issue where the tracer was not starting properly on a read-only file system.
internal: fixes an issue where some pathlib functions return OSError on Windows.
ASM: This fix resolves an issue where the WAF could be disabled if the ASM_DD rule file was not found in Remote Config.
flask: Fix scenarios when using flask-like frameworks would cause a crash because of patching issues on startup.
Code Security: Logs warning instead of throwing an exception in the native module if IAST is not enabled by env var.
Code Security: fix potential infinite loop with path traversal when the analyze quota has been exceeded.
wsgi: Ensures the status of wsgi Spans are not set to error when a
StopIteration
exception is raised marked the span as an error. With this change,StopIteration
exceptions in this context will be ignored.langchain: tag non-dict inputs to LCEL chains appropriately. Non-dict inputs are stringified, and dict inputs are tagged by key-value pairs.
tracing: Updates
DD_HEADER_TAGS
andDD_TAGS
to support the following formats:key1,key2,key3
,key1:val,key2:val,key3:val3
,key1:val key2:val key3:val3
, andkey1 key2 key3
. Key value pairs that do not match an expected format will be logged and ignored by the tracer.loguru: This fix avoids copying attributes from a log record's "extras" field to the record's top level if those attributes were not added by the Datadog integration.
opentelemetry: Resolves an edge case where distributed tracing headers could be generated before a sampling decision is made, resulting in dropped spans in downstream services.
profiling: captures lock usages with
with
context managers, e.g.with lock:
profiling: propagates
runtime_id
tag to libdatadog exporter. It is a unique string identifier for the profiled process. For example, Thread Timeline visualization uses it to distinguish different processes.profiling: show lock init location in Lock Name and hide profiler internal frames from Stack Frame in Timeline Details tab.
ASM: This fix resolves an issue where ASM one click feature could fail to deactivate ASM.
redis: This fix resolves an issue in redis utils where a variable may not be declared within a try/catch
Other Changes
LLMObs.submit_evaluation()
requires a Datadog API key to send custom evaluations to LLM Observability. If an API key is not set using eitherDD_API_KEY
orLLMObs.enable(api_key="<api-key>")
, this method will log a warning and returnNone
.v2.10.7
: 2.10.7Compare Source
Bug Fixes
.git
was incorrectly being stripped from repository URLs when extracting service names, resulting ing
,i
, ort
being removed (eg:test-environment.git
incorrectly becomingtest-environmen
)asyncio.TimeoutError
s were not being propagated correctly from canceled OpenAI API requests.DD_PROFILING_STACK_V2_ENABLED
is set.v2.10.6
Compare Source
Bug Fixes
ddtrace
was exhausting a Django stream response before returning it to user.Already mutably borrowed
error by reverting back to pure-python rate limiter.v2.10.5
: 2.10.5Compare Source
Bug Fixes
Already mutably borrowed
error when rate limiter is accessed across threads.v2.10.4
Compare Source
Bug Fixes
v2.10.3
Compare Source
Bug Fixes
v2.10.2
Compare Source
Bug Fixes
with
context managers, e.g.with lock:
runtime_id
tag to libdatadog exporter. It is a unique string identifier for the profiled process. For example, Thread Timeline visualization uses it to distinguish different processes.v2.10.1
Compare Source
Bug Fixes
ddcontextvars_context
entrypoint is loaded. This resolves an incompatibility introduced inopentelemetry-api==1.25.0
.get_tracer
function would raise aTypeError
when called with theattribute
argument. This resolves an incompatibility introduced inopentelemetry-api==1.26.0
.v2.10.0
Compare Source
New Features
botocore: Adds support for overriding the default service name in botocore by either setting the environment variable
DD_BOTOCORE_SERVICE
or configuring it viaddtrace.config.botocore["service"]
.Database Monitoring: Adds Database Monitoring (DBM) trace propagation for postgres databases used through Django.
Anthropic: Adds support for tracing message calls using tools.
LLM Observability: Adds support for tracing Anthropic messages using tool calls.
azure: Removes the restrictions on the tracer to only run the mini-agent on the consumption plan. The mini-agent now runs regardless of the hosting plan
Anthropic: Adds support for tracing synchronous and asynchronous message streaming.
LLM Observability: Adds support for tracing synchronous and asynchronous message streaming.
SSI: Introduces generic safeguards for automatic instrumentation when using single step install in the form of early exit conditions. Early exit from instrumentation is triggered if a version of software in the environment is not explicitly supported by ddtrace. The Python runtime itself and many Python packages are checked for explicit support on the basis of their version.
langchain: Introduces support for
langchain==0.2.0
by conditionally patching thelangchain-community
module if available, which is an optional dependency forlangchain>=0.2.0
. See the langchain integration docs for more details.LLM Observability: Adds support to automatically submit Anthropic chat messages to LLM Observability.
tracer: This introduces the tracer flare functionality. Currently the tracer flare includes the tracer logs and tracer configurations.
Code Security: Expands SSRF vulnerability support for Code Security and Exploit Prevention for the modules
urllib3
,http.client
,webbrowser
andurllib.request
.ASM: This introduces full support for exploit prevention in the python tracer.
with monitoring and blocking feature, telemetry and span metrics reports.
ASM: This introduces SQL injection support for exploit prevention.
anthropic: This introduces tracing support for anthropic chat messages.
See the docs for more information.
ASM: This introduces "Standalone ASM", a feature that disables APM in the tracer but keeps ASM enabled. In order to enable it, set the environment variables
DD_APPSEC_ENABLED=1
andDD_EXPERIMENTAL_APPSEC_STANDALONE_ENABLED=1
.LLM Observability: This introduces the LLM Observability SDK, which enhances the observability of Python-based LLM applications. See the LLM Observability Overview or the SDK documentation for more information about this feature.
opentelemetry: Adds support for span events.
tracing: Ensures the following OpenTelemetry environment variables are mapped to an equivalent Datadog configuration (datadog environment variables taking precedence in cases where both are configured):
otel: Adds support for generating Datadog trace metrics using OpenTelemetry instrumentations
Known Issues
builtins.open
function is experimental and may not be stable. This aspect is not replaced by default.grpc.aio
clients and servers is experimental and may not be stable. This integration is now disabled by default.Deprecation Notes
DD_LLMOBS_APP_NAME
is deprecated and will be removed in the next major version of ddtrace. As an alternative toDD_LLMOBS_APP_NAME
, you can useDD_LLMOBS_ML_APP
instead. See the SDK setup documentation for more details on how to configure the LLM Observability SDK.Bug Fixes
Code Security: Logs warning instead of throwing an exception in the native module if IAST is not enabled by env var.
redis: This fix resolves an issue in redis utils where a variable may not be declared within a try/catch
Code Security: Adds the
boto
package to the IAST patching denylist.celery: Changes
error.message
span tag to no longer include the traceback that is already included in theerror.stack
span tag.CI Visibility: Fixes source file information that would be incorrect in certain decorated / wrapped scenarios and forces paths to be relative to the repository root, if present.
LLM Observability: This resolves a typing hint error in the
ddtrace.llmobs.utils.Documents
helper class constructor where type hints did not accept input dictionaries with integer or float values.LLM Observability: This fix resolves an issue where the OpenAI, Anthropic, and AWS Bedrock integrations were always setting
temperature
andmax_tokens
parameters to LLM invocations. The OpenAI integration in particular was setting the wrongtemperature
default values. These parameters are now only set if provided in the request.redis: This fix resolves an issue in the redis exception handling where an UnboundLocalError was raised instead of the expected BaseException.
ASM: This fix resolves an issue where the requests integration would not propagate when apm is opted out (i.e. in ASM Standalone).
profiling: Fixes an issue where task information coming from echion was encoded improperly, which could segfault the application.
tracing: Fixes a potential crash where using partial flushes and
tracer.configure()
could result in anIndexError
.flask: Fixes scenarios when using flask-like frameworks would cause a crash because of patching issues on startup.
wsgi: Ensures the status of wsgi Spans are not set to error when a
StopIteration
exception is raised marked the span as an error. With this change,StopIteration
exceptions in this context will be ignored.langchain: Tags non-dict inputs to LCEL chains appropriately. Non-dict inputs are stringified, and dict inputs are tagged by key-value pairs.
langchain: Fixes an issue of langchain patching errors due to the
langchain-community
module becoming an optional dependency inlangchain>=0.2.0
. The langchain integration now conditionally patcheslangchain-community
methods if it is available. See the langchain integration docs for more details.ASM: This fix resolves an issue where an org could not customize actions through remote config.
ASM: Protects against potentially returning
None
when tainting a gRPC message.botocore: This fix adds additional key name checking and appropriate defaults for responses from Cohere and Amazon models.
Tracer: This fix resolves an issue where importing
asyncio
after a trace has already been started will reset the currently active span.CI Visibility: Fixes traces that were not properly being sent in agentless mode, and were otherwise not properly attached to the test that started them
grpc: Fixes a bug in the
grpc.aio
support specific to streaming responses.openai: This fix resolves an issue where specifying
n=None
for streamed chat completions resulted in aTypeError
.openai: This fix removes patching for the edits and fine tunes endpoints, which have been removed from the OpenAI API.
openai: This fix resolves an issue where streamed OpenAI responses raised errors when being used as context managers.
tracing: Ensures span links generated by distributed tracing headers record the correct sampling decision.
telemetry: This fix resolves an issue when using
pytest
+gevent
where the telemetry writer was eager initialized bypytest
entrypoints loading of our plugin causing a potential dead lock.tracing: Fixes an issue where
DD_TRACE_SPAN_TRACEBACK_MAX_SIZE
was not applied to exception tracebacks.Code Security: This fixes a bug in the AST patching process where
ImportError
exceptions were being caught, interfering with the proper application cycle if anImportError
was expected."Code Security: Ensure IAST propagation does not raise side effects related to Magic methods.
Code Security: Fixes a potential memory corruption when the context was reset.
langchain: This fix resolves an issue where specifying inputs as a keyword argument for batching on chains caused a crash.
Code Security: Avoids calling terminate on the extend and join aspect when an exception is raised.
tracing: Ensures spans are rate limited at the expected rate (100 spans per second by default). Previously long running spans would set the rate limiter to set an invalid window and this could cause the next trace to be dropped.
RemoteConfig: This fix resolves an issue where remote config did not work for the tracer when using an agent that would add a flare item to the remote config payload. With this fix, the tracer will now correctly pull out the lib_config we need from the payload in order to implement remote config changes properly.
opentelemetry: Records exceptions on spans in a manner that is consistent with the otel specification
tracing: Ensures W3C tracecontext headers take precedence over all other header formats when incoming headers reference different spans in the same trace.
Other Changes
LLM Observability: The SDK allowed users to submit an unsupported
numerical
evaluation metric type. All evaluation metric types submitted withnumerical
type will now be automatically converted to ascore
type. As an alternative to using thenumerical
type, usescore
instead.lib-injection: Updates base Alpine image to 3.20.
v2.9.6
: 2.9.6Compare Source
New Features
Bug Fixes
.git
was incorrectly being stripped from repository URLs when extracting service names, resulting ing
,i
, ort
being removed (eg:test-environment.git
incorrectly becomingtest-environmen
)DD_PROFILING_STACK_V2_ENABLED
set.v2.9.5
Compare Source
Bug Fixes
with
context managers, e.g.with lock:
runtime_id
tag to libdatadog exporter. It is a unique string identifier for the profiled process. For example, Thread Timeline visualization uses it to distinguish different processes.v2.9.4
Compare Source
Bug Fixes
ddcontextvars_context
entrypoint is loaded. This resolves an incompatibility introduced inopentelemetry-api==1.25.0
.get_tracer
function would raise aTypeError
when called with theattribute
argument. This resolves an incompatibility introduced inopentelemetry-api==1.26.0
.redis
exception handling where anUnboundLocalError
was raised instead of the expectedBaseException
.langchain
patching errors due to thelangchain-community
module becoming an optional dependency inlangchain>=0.2.0
. Thelangchain
integration now conditionally patcheslangchain-community
methods if it is available. See the langchain integration docs for more details.v2.9.3
Compare Source
Bug Fixes
encodings.idna
to the IAST patching denylist to avoid problems with gevent.error.message
span tag to no longer include the traceback that is already included in theerror.stack
span tag.ddtrace.llmobs.utils.Documents
helper class constructor where type hints did not accept input dictionaries with integer or float values.temperature
andmax_tokens
parameters to LLM invocations. The OpenAI integration in particular was setting the wrongtemperature
default values. These parameters are now only set if provided in the request.echion
was encoded improperly, which could segfault the application.tracer.configure()
could result in anIndexError
.pathlib
functions returnOSError
g on Windows.StopIteration
exception is raised marked the span as an error. With this change,StopIteration
exceptions in this context will be ignored.Other Changes
numerical
evaluation metric type. All evaluation metric types submitted withnumerical
type will now be automatically converted to ascore
type. As an alternative to using thenumerical
type, usescore
instead.Configuration
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