Properly close flow logs

Author: Andrei Bratu

.fernignore

@@ -18,3 +18,7 @@ tests/
 ## CI
 
 .github/workflows/ci.yml
+
+## Config
+
+.gitignore

.gitignore

@@ -3,3 +3,5 @@ dist/
 __pycache__/
 poetry.toml
 .ruff_cache/
+.vscode
+.env

src/humanloop/client.py

@@ -175,14 +175,14 @@ def prompt(
         path: Optional[str] = None,
         **prompt_kernel: Unpack[DecoratorPromptKernelRequestParams],  # type: ignore
     ):
-        """Decorator for declaring a (Prompt)[https://humanloop.com/docs/explanation/prompts] in code.
+        """Decorator for declaring a [Prompt](https://humanloop.com/docs/explanation/prompts) in code.
 
         The decorator intercepts calls to LLM provider APIs and creates
         a new Prompt file based on the hyperparameters used in the call.
         If a hyperparameter is specified in the `@prompt` decorator, then
         they override any value intercepted from the LLM provider call.
 
-        If the (Prompt)[https://humanloop.com/docs/explanation/prompts] already exists
+        If the [Prompt](https://humanloop.com/docs/explanation/prompts) already exists
         on the specified path, a new version will be upserted when any of the above change.
 
         Here's an example of declaring a (Prompt)[https://humanloop.com/docs/explanation/prompts] in code:
@@ -200,7 +200,7 @@ def call_llm(messages):
             ).choices[0].message.content
         ```
 
-        This will create a (Prompt)[https://humanloop.com/docs/explanation/prompts] with the following attributes:
+        This will create a [Prompt](https://humanloop.com/docs/explanation/prompts] with the following attributes:
 
         ```python
         {
@@ -342,9 +342,9 @@ def flow(
     ):
         """Decorator for declaring a [Flow](https://humanloop.com/docs/explanation/flows) in code.
 
-        A [Flow](https://humanloop.com/docs/explanation/flows) decorator should be added
-        at the entrypoint of your LLM feature. Call other functions decorated with
-        Humanloop SDK decorators to create a Trace of Logs on Humanloop.
+        A [Flow](https://humanloop.com/docs/explanation/flows) wrapped callable should
+        be used as the entrypoint of your LLM feature. Call other functions wrapped with
+        Humanloop decorators to create a trace of Logs on Humanloop.
 
         Here's an example of declaring a [Flow](https://humanloop.com/docs/explanation/flows) in code:
         ```python

src/humanloop/decorators/flow.py

@@ -82,10 +82,6 @@ def wrapper(*args: Sequence[Any], **kwargs: Mapping[str, Any]) -> Any:
                     "output": output_stringified,
                     "error": error,
                 }
-                if inputs:
-                    flow_log["inputs"] = inputs
-                if output:
-                    flow_log["output"] = output
 
                 # Write the Flow Log to the Span on HL_LOG_OT_KEY
                 if flow_log:

src/humanloop/otel/exporter.py

@@ -1,5 +1,4 @@
 import contextvars
-import copy
 import json
 import logging
 import threading
@@ -70,6 +69,7 @@ def __init__(
         for thread in self._threads:
             thread.start()
             logger.debug("Exporter Thread %s started", thread.ident)
+        self._flow_logs_to_complete: list[str] = []
 
     def export(self, spans: trace.Sequence[ReadableSpan]) -> SpanExportResult:
         def is_evaluated_file(
@@ -133,6 +133,11 @@ def shutdown(self) -> None:
         for thread in self._threads:
             thread.join()
             logger.debug("Exporter Thread %s joined", thread.ident)
+        for log_id in self._flow_logs_to_complete:
+            self._client.flows.update_log(
+                log_id=log_id,
+                trace_status="complete",
+            )
 
     def force_flush(self, timeout_millis: int = 3000) -> bool:
         self._shutdown = True
@@ -340,6 +345,7 @@ def _export_flow(self, span: ReadableSpan) -> None:
                 **log_object,
                 trace_parent_id=trace_parent_id,
             )
+            self._flow_logs_to_complete.append(log_response.id)
             self._span_id_to_uploaded_log_id[span.get_span_context().span_id] = log_response.id
         except HumanloopApiError as e:
             logger.error(str(e))