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plugins/phoenix/skills/phoenix-tracing/references/sessions-python.md

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+# Sessions (Python)
+
+Track multi-turn conversations by grouping traces with session IDs.
+
+## Setup
+
+```python
+from openinference.instrumentation import using_session
+
+with using_session(session_id="user_123_conv_456"):
+    response = llm.invoke(prompt)
+```
+
+## Best Practices
+
+**Bad: Only parent span gets session ID**
+
+```python
+from openinference.semconv.trace import SpanAttributes
+from opentelemetry import trace
+
+span = trace.get_current_span()
+span.set_attribute(SpanAttributes.SESSION_ID, session_id)
+response = client.chat.completions.create(...)
+```
+
+**Good: All child spans inherit session ID**
+
+```python
+with using_session(session_id):
+    response = client.chat.completions.create(...)
+    result = my_custom_function()
+```
+
+**Why:** `using_session()` propagates session ID to all nested spans automatically.
+
+## Session ID Patterns
+
+```python
+import uuid
+
+session_id = str(uuid.uuid4())
+session_id = f"user_{user_id}_conv_{conversation_id}"
+session_id = f"debug_{timestamp}"
+```
+
+Good: `str(uuid.uuid4())`, `"user_123_conv_456"`
+Bad: `"session_1"`, `"test"`, empty string
+
+## Multi-Turn Chatbot Example
+
+```python
+import uuid
+from openinference.instrumentation import using_session
+
+session_id = str(uuid.uuid4())
+messages = []
+
+def send_message(user_input: str) -> str:
+    messages.append({"role": "user", "content": user_input})
+
+    with using_session(session_id):
+        response = client.chat.completions.create(
+            model="gpt-4",
+            messages=messages
+        )
+
+    assistant_message = response.choices[0].message.content
+    messages.append({"role": "assistant", "content": assistant_message})
+    return assistant_message
+```
+
+## Additional Attributes
+
+```python
+from openinference.instrumentation import using_attributes
+
+with using_attributes(
+    user_id="user_123",
+    session_id="conv_456",
+    metadata={"tier": "premium", "region": "us-west"}
+):
+    response = llm.invoke(prompt)
+```
+
+## LangChain Integration
+
+LangChain threads are automatically recognized as sessions:
+
+```python
+from langchain.chat_models import ChatOpenAI
+
+response = llm.invoke(
+    [HumanMessage(content="Hi!")],
+    config={"metadata": {"thread_id": "user_123_thread"}}
+)
+```
+
+Phoenix recognizes: `thread_id`, `session_id`, `conversation_id`
+
+## See Also
+
+- **TypeScript sessions:** `sessions-typescript.md`
+- **Session docs:** https://docs.arize.com/phoenix/tracing/sessions