fix: move to start_observation from start_span

components-mdx/get-started/python-sdk.mdx

@@ -30,12 +30,12 @@ from langfuse import get_client
 langfuse = get_client()
 
 # Create a span using a context manager
-with langfuse.start_as_current_span(name="process-request") as span:
+with langfuse.start_as_current_observation(name="process-request") as span:
     # Your processing logic here
     span.update(output="Processing complete")
 
     # Create a nested generation for an LLM call
-    with langfuse.start_as_current_generation(name="llm-response", model="gpt-3.5-turbo") as generation:
+    with langfuse.start_as_current_observation(name="llm-response", model="gpt-3.5-turbo", as_type="generation") as generation:
         # Your LLM call logic here
         generation.update(output="Generated response")
 
@@ -57,13 +57,13 @@ from langfuse import get_client
 langfuse = get_client()
 
 # Create a span without a context manager
-span = langfuse.start_span(name="user-request")
+span = langfuse.start_observation(name="user-request")
 
 # Your processing logic here
 span.update(output="Request processed")
 
 # Child spans must be created using the parent span object
-nested_span = span.start_span(name="nested-span")
+nested_span = span.start_observation(name="nested-span")
 nested_span.update(output="Nested span output")
 
 # Important: Manually end the span

components-mdx/integration-learn-more.mdx

@@ -51,7 +51,7 @@ from langfuse import get_client
 
 langfuse = get_client()
 
-with langfuse.start_as_current_span(name="my-trace") as span:
+with langfuse.start_as_current_observation(name="my-trace") as span:
 
     # Run your application here
     output = my_llm_call(input)

components-mdx/prompt-linking.mdx

@@ -32,10 +32,11 @@ langfuse = get_client()
 
 prompt = langfuse.get_prompt("movie-critic")
 
-with langfuse.start_as_current_generation(
+with langfuse.start_as_current_observation(
     name="movie-generation",
     model="gpt-4o",
-    prompt=prompt
+    prompt=prompt,
+    as_type="generation"
 ) as generation:
     # Your LLM call here
     generation.update(output="LLM response")

pages/docs/evaluation/evaluation-methods/custom-scores.mdx

@@ -54,7 +54,7 @@ langfuse.create_score(
 )
 
 # Method 2: Score current span/generation (within context)
-with langfuse.start_as_current_span(name="my-operation") as span:
+with langfuse.start_as_current_observation(name="my-operation") as span:
     # Score the current span
     span.score(
         name="correctness",
@@ -72,7 +72,7 @@ with langfuse.start_as_current_span(name="my-operation") as span:
 
 
 # Method 3: Score via the current context
-with langfuse.start_as_current_span(name="my-operation"):
+with langfuse.start_as_current_observation(name="my-operation"):
     # Score the current span
     langfuse.score_current_span(
         name="correctness",
@@ -108,7 +108,7 @@ langfuse.create_score(
 )
 
 # Method 2: Score current span/generation (within context)
-with langfuse.start_as_current_span(name="my-operation") as span:
+with langfuse.start_as_current_observation(name="my-operation") as span:
     # Score the current span
     span.score(
         name="accuracy",
@@ -125,7 +125,7 @@ with langfuse.start_as_current_span(name="my-operation") as span:
     )
 
 # Method 3: Score via the current context
-with langfuse.start_as_current_span(name="my-operation"):
+with langfuse.start_as_current_observation(name="my-operation"):
     # Score the current span
     langfuse.score_current_span(
         name="accuracy",
@@ -161,7 +161,7 @@ langfuse.create_score(
 )
 
 # Method 2: Score current span/generation (within context)
-with langfuse.start_as_current_span(name="my-operation") as span:
+with langfuse.start_as_current_observation(name="my-operation") as span:
     # Score the current span
     span.score(
         name="helpfulness",
@@ -177,7 +177,7 @@ with langfuse.start_as_current_span(name="my-operation") as span:
         data_type="BOOLEAN"
     )
 # Method 3: Score via the current context
-with langfuse.start_as_current_span(name="my-operation"):
+with langfuse.start_as_current_observation(name="my-operation"):
     # Score the current span
     langfuse.score_current_span(
         name="helpfulness",
@@ -325,7 +325,7 @@ langfuse.create_score(
 )
 
 # Method 2: Score within context
-with langfuse.start_as_current_span(name="my-operation") as span:
+with langfuse.start_as_current_observation(name="my-operation") as span:
     span.score(
         name="accuracy",
         value=0.9,
@@ -356,7 +356,7 @@ langfuse.create_score(
 )
 
 # Method 2: Score within context
-with langfuse.start_as_current_span(name="my-operation") as span:
+with langfuse.start_as_current_observation(name="my-operation") as span:
     span.score(
         name="correctness",
         value="correct",
@@ -387,7 +387,7 @@ langfuse.create_score(
 )
 
 # Method 2: Score within context
-with langfuse.start_as_current_span(name="my-operation") as span:
+with langfuse.start_as_current_observation(name="my-operation") as span:
     span.score(
         name="helpfulness",
         value=1,

pages/docs/observability/features/environments.mdx

@@ -50,7 +50,7 @@ os.environ["LANGFUSE_TRACING_ENVIRONMENT"] = "production"
 langfuse = get_client()
 
 # All operations will now be associated with the "production" environment
-with langfuse.start_as_current_span(name="my-operation") as span:
+with langfuse.start_as_current_observation(name="my-operation") as span:
     # Your code here
     pass
 

pages/docs/observability/features/log-levels.mdx

@@ -40,9 +40,9 @@ from langfuse import get_client
 langfuse = get_client()
 
 # Using context managers (recommended)
-with langfuse.start_as_current_span(name="my-operation") as span:
+with langfuse.start_as_current_observation(name="my-operation") as span:
     # Set level and status message on creation
-    with span.start_as_current_span(
+    with span.start_as_current_observation(
         name="potentially-risky-operation",
         level="WARNING",
         status_message="Operation may fail"
@@ -56,7 +56,7 @@ with langfuse.start_as_current_span(name="my-operation") as span:
         )
 
 # You can also update the currently active span without a direct reference
-with langfuse.start_as_current_span(name="another-operation"):
+with langfuse.start_as_current_observation(name="another-operation"):
     # ... some processing ...
     langfuse.update_current_span(
         level="DEBUG",
@@ -69,7 +69,8 @@ Levels can also be set when creating generations:
 ```python
 langfuse = get_client()
 
-with langfuse.start_as_current_generation(
+with langfuse.start_as_current_observation(
+    as_type="generation",
     name="llm-call",
     model="gpt-4o",
     level="DEFAULT"  # Default level

pages/docs/observability/features/masking.mdx

@@ -80,7 +80,7 @@ from langfuse import Langfuse
 
 langfuse = Langfuse(mask=masking_function)
 
-with langfuse.start_as_current_span(
+with langfuse.start_as_current_observation(
     name="sensitive-operation",
     input="SECRET_INPUT_DATA"
 ) as span:

pages/docs/observability/features/metadata.mdx

@@ -46,7 +46,7 @@ from langfuse import get_client
 langfuse = get_client()
 
 # Add metadata at trace level
-with langfuse.start_as_current_span(
+with langfuse.start_as_current_observation(
     name="process-request"
 ) as root_span:
     # Add metadata to the trace
@@ -56,7 +56,8 @@ with langfuse.start_as_current_span(
     root_span.update(metadata={"stage": "parsing"})
 
     # Create a child span with metadata
-    with root_span.start_as_current_generation(
+    with root_span.start_as_current_observation(
+        as_type="generation",
         name="generate-response",
         model="gpt-4o",
         metadata={"temperature": 0.7, "max_tokens": 1000}
@@ -69,7 +70,7 @@ You can add new keys to the metadata object by continuously updating the entity.
 We strongly discourage writing the same top-level key multiple times as this will produce an undefined behaviour.
 
 ```python
-with langfuse.start_as_current_span(name="operation") as span:
+with langfuse.start_as_current_observation(name="operation") as span:
     # First write
     span.update(metadata={"status": "started"})
 
@@ -240,7 +241,7 @@ prompt = ChatPromptTemplate.from_template("Tell me a joke about {topic}")
 chain = prompt | llm
 
 # Set trace attributes dynamically via enclosing span
-with langfuse.start_as_current_span(name="dynamic-langchain-trace") as span:
+with langfuse.start_as_current_observation(name="dynamic-langchain-trace") as span:
     span.update_trace(
         metadata={"foo": "bar", "baz": "qux"}
     )

pages/docs/observability/features/multi-modality.mdx

@@ -144,7 +144,7 @@ def process_document():
 
 langfuse = get_client()
 
-with langfuse.start_as_current_span(name="analyze-document") as span: # Include media in the span input, output, or metadata
+with langfuse.start_as_current_observation(name="analyze-document") as span: # Include media in the span input, output, or metadata
     span.update(
         input={"document": pdf_media},
         metadata={"file_size": len(pdf_bytes)}

pages/docs/observability/features/releases-and-versioning.mdx

@@ -63,7 +63,7 @@ def process_data():
 
 # With context managers
 langfuse = get_client()
-with langfuse.start_as_current_span(name="my-operation") as span:
+with langfuse.start_as_current_observation(name="my-operation") as span:
     span.update_trace(release="v2.1.24")
 ```
 
@@ -136,14 +136,15 @@ from langfuse import get_client
 langfuse = get_client()
 
 # Set version when creating a span
-with langfuse.start_as_current_span(
+with langfuse.start_as_current_observation(
     name="process-data",
     version="1.0"
 ) as span:
     # Processing...
 
     # Create a generation with version
-    with span.start_as_current_generation(
+    with span.start_as_current_observation(
+        as_type="generation",
         name="guess-countries",
         model="gpt-4o",
         version="1.0"

pages/docs/observability/features/sessions.mdx

@@ -43,14 +43,15 @@ from langfuse import get_client
 langfuse = get_client()
 
 # You can set the session_id when creating the root span
-with langfuse.start_as_current_span(
+with langfuse.start_as_current_observation(
     name="process-chat-message"
 ) as root_span:
     # Add session_id to the trace
     root_span.update_trace(session_id="chat-session-123")
 
     # All spans in this trace will belong to the same session
-    with root_span.start_as_current_generation(
+    with root_span.start_as_current_observation(
+        as_type="generation",
         name="generate-response",
         model="gpt-4o"
     ) as gen:
@@ -61,7 +62,7 @@ with langfuse.start_as_current_span(
 You can also update the session_id of the current trace without a direct reference to a span:
 
 ```python
-with langfuse.start_as_current_span(name="another-operation"):
+with langfuse.start_as_current_observation(name="another-operation"):
     # Add to the current trace
     langfuse.update_current_trace(session_id="your-session-id")
 ```

pages/docs/observability/features/tags.mdx

@@ -34,22 +34,22 @@ from langfuse import get_client
 langfuse = get_client()
 
 # Add tags when creating the root span
-with langfuse.start_as_current_span(
+with langfuse.start_as_current_observation(
     name="my-operation"
 ) as root_span:
     # Add tags to the trace
     root_span.update_trace(tags=["tag-1", "tag-2"])
 
     # You can add more tags later from any span in the same trace
-    with root_span.start_as_current_generation(name="llm-call", model="gpt-4o") as gen:
+    with root_span.start_as_current_observation(as_type="generation", name="llm-call", model="gpt-4o") as gen:
         # Processing...
         gen.update_trace(tags=["llm-gen"])  # Adds another tag to the same trace
 ```
 
 You can also update the tags of the current trace without a direct reference to a span:
 
 ```python
-with langfuse.start_as_current_span(name="another-operation"):
+with langfuse.start_as_current_observation(name="another-operation"):
     # ... processing ...
     langfuse.update_current_trace(tags=["processing", "beta-feature"])
 ```

pages/docs/observability/features/token-and-cost-tracking.mdx

@@ -117,10 +117,11 @@ import anthropic
 langfuse = get_client()
 anthropic_client = anthropic.Anthropic()
 
-with langfuse.start_as_current_generation(
+with langfuse.start_as_current_observation(
     name="anthropic-completion",
     model="claude-3-opus-20240229",
-    input=[{"role": "user", "content": "Hello, Claude"}]
+    input=[{"role": "user", "content": "Hello, Claude"}],
+    as_type="generation"
 ) as generation:
     response = anthropic_client.messages.create(
         model="claude-3-opus-20240229",

pages/docs/observability/features/trace-ids-and-distributed-tracing.mdx

@@ -85,7 +85,7 @@ external_id = "request_12345"
 trace_id = langfuse.create_trace_id(seed=external_id)
 
 # Use this trace ID in a span
-with langfuse.start_as_current_span(
+with langfuse.start_as_current_observation(
     name="process-request",
     trace_context={"trace_id": trace_id}
 ) as span:
@@ -101,7 +101,7 @@ from langfuse import get_client
 langfuse = get_client()
 
 # Use a predefined trace ID with trace_context parameter
-with langfuse.start_as_current_span(
+with langfuse.start_as_current_observation(
     name="my-operation",
     trace_context={
         "trace_id": "abcdef1234567890abcdef1234567890",  # Must be 32 hex chars
@@ -119,7 +119,7 @@ from langfuse import get_client
 
 langfuse = get_client()
 
-with langfuse.start_as_current_span(name="outer-operation") as span:
+with langfuse.start_as_current_observation(name="outer-operation") as span:
     # Access the trace ID of the current span
     current_trace_id = langfuse.get_current_trace_id()
     current_span_id = langfuse.get_current_observation_id()

pages/docs/observability/features/url.mdx

@@ -39,7 +39,7 @@ from langfuse import get_client
 
 langfuse = get_client()
 
-with langfuse.start_as_current_span(name="process-request") as span:
+with langfuse.start_as_current_observation(name="process-request") as span:
     # Get the URL of this trace
     trace_url = langfuse.get_trace_url()
     print(f"View trace at: {trace_url}")
@@ -133,7 +133,7 @@ from langfuse import get_client
 
 langfuse = get_client()
 
-with langfuse.start_as_current_span(name="process-request") as span:
+with langfuse.start_as_current_observation(name="process-request") as span:
     # Make this trace public
     span.update_trace(public=True)
 

pages/docs/observability/features/users.mdx

@@ -41,16 +41,17 @@ from langfuse import get_client
 langfuse = get_client()
 
 # You can set the user_id when creating the root span via update_trace
-with langfuse.start_as_current_span(
+with langfuse.start_as_current_observation(
     name="process-user-request"
 ) as root_span:
     # Add user_id to the trace
     root_span.update_trace(user_id="user_12345")
 
     # All spans in this trace will be associated with this user
-    with root_span.start_as_current_generation(
+    with root_span.start_as_current_observation(
         name="generate-response",
-        model="gpt-4o"
+        model="gpt-4o",
+        as_type="generation"
     ) as gen:
         # ...generate response...
         pass
@@ -59,7 +60,7 @@ with langfuse.start_as_current_span(
 You can also update the user_id of the current trace without a direct reference to a span:
 
 ```python
-with langfuse.start_as_current_span(name="handle-user-interaction"):
+with langfuse.start_as_current_observation(name="handle-user-interaction"):
     # Add user_id to the current trace
     langfuse.update_current_trace(user_id="user_12345")
 ```