Fix sphinx warnings

docs/conf.py

@@ -15,6 +15,11 @@
 
 extensions = ["sphinx.ext.autodoc", "sphinx.ext.napoleon", "sphinx.ext.viewcode"]
 
+autodoc_default_options = {
+    "private-members": None,
+    "exclude-members": "model_config,model_fields",
+}
+
 templates_path = ["_templates"]
 exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"]
 

src/intelligence_layer/core/complete.py

@@ -88,7 +88,7 @@ class InstructOutput(BaseModel):
     Attributes:
         response: The generated response to the instruction.
         prompt_with_metadata: To handle the instruction, a `PromptTemplate` is used.
-            The template defines two `PromptRange`s:
+            The template defines two `PromptRange`\ s:
             - "instruction": covering the instruction text as provided in the `InstructionInput`.
             - "input": covering the input text as provided in the `InstructionInput`.
             These can for example be used for downstream `TextHighlight` tasks.

src/intelligence_layer/core/logger.py

@@ -52,7 +52,7 @@
 
 @runtime_checkable
 class DebugLogger(Protocol):
-    """A protocol for instrumenting `Task`s with structured logging.
+    """A protocol for instrumenting `Task`\ s with structured logging.
 
     A logger needs to provide a way to collect an individual log, which should be serializable, and
     a way to generate nested loggers, so that sub-tasks can emit logs that are grouped together.
@@ -393,6 +393,11 @@ def _rich_render_(self) -> Tree:
         return tree
 
 
+# Required for sphinx, see also: https://docs.pydantic.dev/2.4/errors/usage_errors/#class-not-fully-defined
+InMemorySpan.model_rebuild()
+InMemoryDebugLogger.model_rebuild()
+
+
 class StartTask(BaseModel):
     """Represents the payload/entry of a log-line indicating that a `TaskSpan` was opened through `DebugLogger.task_span`.
 
@@ -498,7 +503,7 @@ class FileDebugLogger(DebugLogger):
         log_file_path: Denotes the file to log to.
 
     Attributes:
-        uuid: a uuid for the logger. If multiple `FileDebugLogger`s log to the same file
+        uuid: a uuid for the logger. If multiple `FileDebugLogger`\ s log to the same file
             the child-elements for a logger can be identified by referring to this id as parent.
     """
 

src/intelligence_layer/core/prompt_template.py

@@ -81,7 +81,7 @@ class PromptWithMetadata:
 
     Args:
       prompt: The actual `Prompt`.
-      ranges: A mapping of range name to a `Sequence` of corresponding `PromptRange`s.
+      ranges: A mapping of range name to a `Sequence` of corresponding `PromptRange`\ s.
     """
 
     prompt: Prompt

src/intelligence_layer/core/task.py

@@ -63,6 +63,7 @@ class Task(ABC, Generic[Input, Output]):
         Input: Interface to be passed to the task with all data needed to run the process.
             Ideally, these are specified in terms related to the use-case, rather than lower-level
             configuration options.
+
         Output: Interface of the output returned by the task.
     """
 
@@ -111,8 +112,8 @@ def run_concurrently(
                 this method call. This can be used to prevent queue-full or similar error of downstream APIs
                 when the global concurrency limit is too high for a certain task.
         Returns:
-            The `Output`s generated by calling `run` for each given `Input`. The order of `Output`s
-                corresponds to the order of the `Input`s.
+            The `Output`\ s generated by calling `run` for each given `Input`. The order of `Output`\ s
+                corresponds to the order of the `Input`\ s.
         """
 
         with debug_logger.span(f"Concurrent {type(self).__name__} tasks") as span:

src/intelligence_layer/core/text_highlight.py

@@ -75,9 +75,10 @@ class TextHighlight(Task[TextHighlightInput, TextHighlightOutput]):
         client: Aleph Alpha client instance for running model related API calls.
 
     Example:
+
     >>> client = Client(os.getenv("AA_TOKEN"))
     >>> text_highlight = TextHighlight(client=client)
-    >>> prompt_template_str = "{% promptrange r1 %}Question: What is 2 + 2?{% endpromptrange %}\nAnswer:"
+    >>> prompt_template_str = "{% promptrange r1 %\Question: What is 2 + 2?{% endpromptrange %}\\nAnswer:"
     >>> template = PromptTemplate(prompt_template_str)
     >>> prompt_with_metadata = template.to_prompt_with_metadata()
     >>> completion = " 4."