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Attack & Defense CTFs
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Jeopardy CTFs
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Cyber Ranges
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Streaming
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Tracing & Debugging
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Tracing & Debugging
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Traces and spans
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Default tracing
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Higher level traces
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Creating traces
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Creating spans
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Sensitive data
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Custom tracing processors
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<h1 id="tracing">⚠️ Tracing</h1>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>The tracing feature is disabled as we're re-implementing it to be in-line with OpenTelemetry standards. The new implementation will be available in the future.</p>
</div>
<p>The Agents SDK includes built-in tracing, collecting a comprehensive record of events during an agent run: LLM generations, tool calls, handoffs, guardrails, and even custom events that occur. Using the <a href="https://platform.openai.com/traces">Traces dashboard</a>, you can debug, visualize, and monitor your workflows during development and in production.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Tracing is enabled by default. There are two ways to disable tracing:</p>
<ol>
<li>You can globally disable tracing by setting the env var <code>OPENAI_AGENTS_DISABLE_TRACING=1</code></li>
<li>You can disable tracing for a single run by setting <a class="autorefs autorefs-internal" title="tracing_disabled
class-attribute
instance-attribute
" href="../ref/run/#cai.sdk.agents.run.RunConfig.tracing_disabled"><code>cai.sdk.agents.run.RunConfig.tracing_disabled</code></a> to <code>True</code></li>
</ol>
</div>
<p><strong><em>For organizations operating under a Zero Data Retention (ZDR) policy using OpenAI's APIs, tracing is unavailable.</em></strong></p>
<h2 id="traces-and-spans">Traces and spans</h2>
<ul>
<li><strong>Traces</strong> represent a single end-to-end operation of a "workflow". They're composed of Spans. Traces have the following properties:<ul>
<li><code>workflow_name</code>: This is the logical workflow or app. For example "Code generation" or "Customer service".</li>
<li><code>trace_id</code>: A unique ID for the trace. Automatically generated if you don't pass one. Must have the format <code>trace_&lt;32_alphanumeric&gt;</code>.</li>
<li><code>group_id</code>: Optional group ID, to link multiple traces from the same conversation. For example, you might use a chat thread ID.</li>
<li><code>disabled</code>: If True, the trace will not be recorded.</li>
<li><code>metadata</code>: Optional metadata for the trace.</li>
</ul>
</li>
<li><strong>Spans</strong> represent operations that have a start and end time. Spans have:<ul>
<li><code>started_at</code> and <code>ended_at</code> timestamps.</li>
<li><code>trace_id</code>, to represent the trace they belong to</li>
<li><code>parent_id</code>, which points to the parent Span of this Span (if any)</li>
<li><code>span_data</code>, which is information about the Span. For example, <code>AgentSpanData</code> contains information about the Agent, <code>GenerationSpanData</code> contains information about the LLM generation, etc.</li>
</ul>
</li>
</ul>
<h2 id="default-tracing">Default tracing</h2>
<p>By default, the SDK traces the following:</p>
<ul>
<li>The entire <code>Runner.{run, run_sync, run_streamed}()</code> is wrapped in a <code>trace()</code>.</li>
<li>Each time an agent runs, it is wrapped in <code>agent_span()</code></li>
<li>LLM generations are wrapped in <code>generation_span()</code></li>
<li>Function tool calls are each wrapped in <code>function_span()</code></li>
<li>Guardrails are wrapped in <code>guardrail_span()</code></li>
<li>Handoffs are wrapped in <code>handoff_span()</code></li>
<li>Audio inputs (speech-to-text) are wrapped in a <code>transcription_span()</code></li>
<li>Audio outputs (text-to-speech) are wrapped in a <code>speech_span()</code></li>
<li>Related audio spans may be parented under a <code>speech_group_span()</code></li>
</ul>
<p>By default, the trace is named "Agent trace". You can set this name if you use <code>trace</code>, or you can can configure the name and other properties with the <a class="autorefs autorefs-internal" title="RunConfig
dataclass
" href="../ref/run/#cai.sdk.agents.run.RunConfig"><code>RunConfig</code></a>.</p>
<p>In addition, you can set up <a href="#custom-tracing-processors">custom trace processors</a> to push traces to other destinations (as a replacement, or secondary destination).</p>
<h2 id="higher-level-traces">Higher level traces</h2>
<p>Sometimes, you might want multiple calls to <code>run()</code> to be part of a single trace. You can do this by wrapping the entire code in a <code>trace()</code>.</p>
<div class="language-python highlight"><pre><span></span><code><span id="__span-0-1"><span class="kn">from</span><span class="w"> </span><span class="nn">cai.sdk.agents</span><span class="w"> </span><span class="kn">import</span> <span class="n">Agent</span><span class="p">,</span> <span class="n">Runner</span><span class="p">,</span> <span class="n">trace</span>
</span><span id="__span-0-2">
</span><span id="__span-0-3"><span class="k">async</span> <span class="k">def</span><span class="w"> </span><span class="nf">main</span><span class="p">():</span>
</span><span id="__span-0-4"> <span class="n">agent</span> <span class="o">=</span> <span class="n">Agent</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Joke generator&quot;</span><span class="p">,</span> <span class="n">instructions</span><span class="o">=</span><span class="s2">&quot;Tell funny jokes.&quot;</span><span class="p">)</span>
</span><span id="__span-0-5">
</span><span id="__span-0-6"> <span class="k">with</span> <span class="n">trace</span><span class="p">(</span><span class="s2">&quot;Joke workflow&quot;</span><span class="p">):</span> <span class="c1"># (1)!</span>
</span><span id="__span-0-7"> <span class="n">first_result</span> <span class="o">=</span> <span class="k">await</span> <span class="n">Runner</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">agent</span><span class="p">,</span> <span class="s2">&quot;Tell me a joke&quot;</span><span class="p">)</span>
</span><span id="__span-0-8"> <span class="n">second_result</span> <span class="o">=</span> <span class="k">await</span> <span class="n">Runner</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">agent</span><span class="p">,</span> <span class="sa">f</span><span class="s2">&quot;Rate this joke: </span><span class="si">{</span><span class="n">first_result</span><span class="o">.</span><span class="n">final_output</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
</span><span id="__span-0-9"> <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Joke: </span><span class="si">{</span><span class="n">first_result</span><span class="o">.</span><span class="n">final_output</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
</span><span id="__span-0-10"> <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Rating: </span><span class="si">{</span><span class="n">second_result</span><span class="o">.</span><span class="n">final_output</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
</span></code></pre></div>
<ol>
<li>Because the two calls to <code>Runner.run</code> are wrapped in a <code>with trace()</code>, the individual runs will be part of the overall trace rather than creating two traces.</li>
</ol>
<h2 id="creating-traces">Creating traces</h2>
<p>You can use the <a class="autorefs autorefs-internal" title="trace" href="../ref/tracing/#cai.sdk.agents.tracing.trace"><code>trace()</code></a> function to create a trace. Traces need to be started and finished. You have two options to do so:</p>
<ol>
<li><strong>Recommended</strong>: use the trace as a context manager, i.e. <code>with trace(...) as my_trace</code>. This will automatically start and end the trace at the right time.</li>
<li>You can also manually call <a class="autorefs autorefs-internal" title="start
abstractmethod
" href="../ref/tracing/#cai.sdk.agents.tracing.Trace.start"><code>trace.start()</code></a> and <a class="autorefs autorefs-internal" title="finish
abstractmethod
" href="../ref/tracing/#cai.sdk.agents.tracing.Trace.finish"><code>trace.finish()</code></a>.</li>
</ol>
<p>The current trace is tracked via a Python <a href="https://docs.python.org/3/library/contextvars.html"><code>contextvar</code></a>. This means that it works with concurrency automatically. If you manually start/end a trace, you'll need to pass <code>mark_as_current</code> and <code>reset_current</code> to <code>start()</code>/<code>finish()</code> to update the current trace.</p>
<h2 id="creating-spans">Creating spans</h2>
<p>You can use the various <a class="autorefs autorefs-internal" title="create" href="../ref/tracing/create/#cai.sdk.agents.tracing.create"><code>*_span()</code></a> methods to create a span. In general, you don't need to manually create spans. A <a class="autorefs autorefs-internal" title="custom_span" href="../ref/tracing/#cai.sdk.agents.tracing.custom_span"><code>custom_span()</code></a> function is available for tracking custom span information.</p>
<p>Spans are automatically part of the current trace, and are nested under the nearest current span, which is tracked via a Python <a href="https://docs.python.org/3/library/contextvars.html"><code>contextvar</code></a>.</p>
<h2 id="sensitive-data">Sensitive data</h2>
<p>Certain spans may capture potentially sensitive data.</p>
<p>The <code>generation_span()</code> stores the inputs/outputs of the LLM generation, and <code>function_span()</code> stores the inputs/outputs of function calls. These may contain sensitive data, so you can disable capturing that data via <a class="autorefs autorefs-internal" title="trace_include_sensitive_data
class-attribute
instance-attribute
" href="../ref/run/#cai.sdk.agents.run.RunConfig.trace_include_sensitive_data"><code>RunConfig.trace_include_sensitive_data</code></a>.</p>
<p>Similarly, Audio spans include base64-encoded PCM data for input and output audio by default. You can disable capturing this audio data by configuring <a class="autorefs autorefs-internal" title="trace_include_sensitive_audio_data
class-attribute
instance-attribute
" href="../ref/voice/pipeline_config/#cai.sdk.agents.voice.pipeline_config.VoicePipelineConfig.trace_include_sensitive_audio_data"><code>VoicePipelineConfig.trace_include_sensitive_audio_data</code></a>.</p>
<h2 id="custom-tracing-processors">Custom tracing processors</h2>
<p>The high level architecture for tracing is:</p>
<ul>
<li>At initialization, we create a global <a class="autorefs autorefs-internal" title="TraceProvider" href="../ref/tracing/setup/#cai.sdk.agents.tracing.setup.TraceProvider"><code>TraceProvider</code></a>, which is responsible for creating traces.</li>
<li>We configure the <code>TraceProvider</code> with a <a class="autorefs autorefs-internal" title="BatchTraceProcessor" href="../ref/tracing/processors/#cai.sdk.agents.tracing.processors.BatchTraceProcessor"><code>BatchTraceProcessor</code></a> that sends traces/spans in batches to a <a class="autorefs autorefs-internal" title="BackendSpanExporter" href="../ref/tracing/processors/#cai.sdk.agents.tracing.processors.BackendSpanExporter"><code>BackendSpanExporter</code></a>, which exports the spans and traces to the OpenAI backend in batches.</li>
</ul>
<p>To customize this default setup, to send traces to alternative or additional backends or modifying exporter behavior, you have two options:</p>
<ol>
<li><a class="autorefs autorefs-internal" title="add_trace_processor" href="../ref/tracing/#cai.sdk.agents.tracing.add_trace_processor"><code>add_trace_processor()</code></a> lets you add an <strong>additional</strong> trace processor that will receive traces and spans as they are ready. This lets you do your own processing in addition to sending traces to OpenAI's backend.</li>
<li><a class="autorefs autorefs-internal" title="set_trace_processors" href="../ref/tracing/#cai.sdk.agents.tracing.set_trace_processors"><code>set_trace_processors()</code></a> lets you <strong>replace</strong> the default processors with your own trace processors. This means traces will not be sent to the OpenAI backend unless you include a <code>TracingProcessor</code> that does so.</li>
</ol>
<h2 id="external-tracing-processors-list">External tracing processors list</h2>
<ul>
<li><a href="https://weave-docs.wandb.ai/guides/integrations/openai_agents">Weights &amp; Biases</a></li>
<li><a href="https://docs.arize.com/phoenix/tracing/integrations-tracing/openai-agents-sdk">Arize-Phoenix</a></li>
<li><a href="https://mlflow.org/docs/latest/tracing/integrations/openai-agent">MLflow (self-hosted/OSS</a></li>
<li><a href="https://docs.databricks.com/aws/en/mlflow/mlflow-tracing#-automatic-tracing">MLflow (Databricks hosted</a></li>
<li><a href="https://braintrust.dev/docs/guides/traces/integrations#openai-agents-sdk">Braintrust</a></li>
<li><a href="https://logfire.pydantic.dev/docs/integrations/llms/openai/#openai-agents">Pydantic Logfire</a></li>
<li><a href="https://docs.agentops.ai/v1/integrations/agentssdk">AgentOps</a></li>
<li><a href="https://docs.scorecard.io/docs/documentation/features/tracing#openai-agents-sdk-integration">Scorecard</a></li>
<li><a href="https://docs.keywordsai.co/integration/development-frameworks/openai-agent">Keywords AI</a></li>
<li><a href="https://docs.smith.langchain.com/observability/how_to_guides/trace_with_openai_agents_sdk">LangSmith</a></li>
<li><a href="https://www.getmaxim.ai/docs/observe/integrations/openai-agents-sdk">Maxim AI</a></li>
<li><a href="https://www.comet.com/docs/opik/tracing/integrations/openai_agents">Comet Opik</a></li>
<li><a href="https://langfuse.com/docs/integrations/openaiagentssdk/openai-agents">Langfuse</a></li>
<li><a href="https://docs.langtrace.ai/supported-integrations/llm-frameworks/openai-agents-sdk">Langtrace</a></li>
</ul>
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