hotfix: Lazy import dreadnode to avoid cyclic issues for now

Author: monoxgas

docs/api/chat.mdx

@@ -1265,7 +1265,7 @@ def __init__(
     """How to handle cache_control entries on messages."""
     self.task_name: str = generator.to_identifier(short=True)
     """The name of the pipeline task, used for logging and debugging."""
-    self.scorers: list[dn.Scorer[Chat]] = []
+    self.scorers: list[Scorer[Chat]] = []
     """List of dreadnode scorers to evaluate the generated chat upon completion."""
 
     self.until_types: list[type[Model]] = []
@@ -2124,6 +2124,8 @@ async def run(
     Returns:
         The generated Chat.
     """
+    import dreadnode as dn
+
     if allow_failed:
         warnings.warn(
             "The 'allow_failed' argument is deprecated, use 'on_failed=\"include\"'.",
@@ -2270,6 +2272,8 @@ async def run_batch(
     Returns:
         A list of generatated Chats.
     """
+    import dreadnode as dn
+
     on_failed = on_failed or self.on_failed
     count, messages, params = self._fit_batch_args(many, params)
 
@@ -2410,6 +2414,8 @@ async def run_many(
     Returns:
         A list of generated Chats.
     """
+    import dreadnode as dn
+
     if count < 1:
         raise ValueError("Count must be greater than 0")
 
@@ -2536,6 +2542,8 @@ async def run_over(
     Returns:
         A list of generatated Chats.
     """
+    import dreadnode as dn
+
     on_failed = on_failed or self.on_failed
 
     _generators: list[Generator] = [
@@ -2608,7 +2616,7 @@ Adds one or more scorers to the pipeline to evaluate the generated chat upon com
 ```python
 def score(
     self,
-    *scorers: dn.Scorer[Chat] | ScorerCallable[Chat],
+    *scorers: "Scorer[Chat] | ScorerCallable[Chat]",
     filter: "ChatFilterMode | ChatFilterFunction" = "last",
 ) -> "ChatPipeline":
     """
@@ -2631,6 +2639,8 @@ def score(
     Returns:
         The updated pipeline.
     """
+    import dreadnode as dn
+
     self.scorers.extend(
         [
             dn.scorers.wrap_chat(

docs/api/completion.mdx

@@ -886,6 +886,8 @@ async def run(
     Returns:
         The generated Completion.
     """
+    import dreadnode as dn
+
     if on_failed is None:
         on_failed = "include" if allow_failed else self.on_failed
 
@@ -978,6 +980,8 @@ async def run_batch(
     Returns:
         A list of generatated Completions.
     """
+    import dreadnode as dn
+
     on_failed = on_failed or self.on_failed
     params = self._fit_params(len(many), params)
 
@@ -1061,6 +1065,8 @@ async def run_many(
     Returns:
         A list of generatated Completions.
     """
+    import dreadnode as dn
+
     on_failed = on_failed or self.on_failed
     states = self._initialize_states(count, params)
 
@@ -1144,6 +1150,8 @@ async def run_over(
     Returns:
         A list of generatated Completions.
     """
+    import dreadnode as dn
+
     on_failed = on_failed or self.on_failed
 
     _generators: list[Generator] = [

docs/api/prompt.mdx

@@ -264,6 +264,8 @@ def bind(
         await say_hello.bind("gpt-3.5-turbo")("the world")
         ~~~
     """
+    import dreadnode as dn
+
     pipeline = self._resolve_to_pipeline(other)
     if pipeline.on_failed == "skip":
         raise NotImplementedError(
@@ -369,6 +371,8 @@ def bind_many(
         await say_hello.bind_many("gpt-4.1")(5, "the world")
         ~~~
     """
+    import dreadnode as dn
+
     pipeline = self._resolve_to_pipeline(other)
     if pipeline.on_failed == "include" and not isinstance(self.output, ChatOutput):
         raise NotImplementedError(

docs/api/tools.mdx

@@ -142,6 +142,7 @@ async def handle_tool_call(  # noqa: PLR0912
         A tuple containing the message to send back to the generator and a
         boolean indicating whether tool calling should stop.
     """
+    import dreadnode as dn
 
     from rigging.message import ContentText, ContentTypes, Message
 

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "rigging"
-version = "3.2.0"
+version = "3.2.1"
 description = "LLM Interaction Framework"
 authors = ["Nick Landers <monoxgas@gmail.com>"]
 license = "MIT"

rigging/chat.py

@@ -18,8 +18,6 @@
 from typing import runtime_checkable
 from uuid import UUID, uuid4
 
-import dreadnode as dn
-from dreadnode.metric import ScorerCallable
 from pydantic import (
     BaseModel,
     ConfigDict,
@@ -60,6 +58,7 @@
 from rigging.util import flatten_list, get_qualified_name
 
 if t.TYPE_CHECKING:
+    from dreadnode.metric import Scorer, ScorerCallable
     from dreadnode.scorers.rigging import ChatFilterFunction, ChatFilterMode
     from elasticsearch import AsyncElasticsearch
 
@@ -761,6 +760,8 @@ def depth(self) -> int:
 
 
 def _wrap_watch_callback(callback: WatchChatCallback) -> WatchChatCallback:
+    import dreadnode as dn
+
     callback_name = get_qualified_name(callback)
     return dn.task(
         name=f"watch - {callback_name}",
@@ -804,7 +805,7 @@ def __init__(
         """How to handle cache_control entries on messages."""
         self.task_name: str = generator.to_identifier(short=True)
         """The name of the pipeline task, used for logging and debugging."""
-        self.scorers: list[dn.Scorer[Chat]] = []
+        self.scorers: list[Scorer[Chat]] = []
         """List of dreadnode scorers to evaluate the generated chat upon completion."""
 
         self.until_types: list[type[Model]] = []
@@ -1380,7 +1381,7 @@ async def get_weather(city: Annotated[str, "The city name to get weather for"])
 
     def score(
         self,
-        *scorers: dn.Scorer[Chat] | ScorerCallable[Chat],
+        *scorers: "Scorer[Chat] | ScorerCallable[Chat]",
         filter: "ChatFilterMode | ChatFilterFunction" = "last",
     ) -> "ChatPipeline":
         """
@@ -1403,6 +1404,8 @@ def score(
         Returns:
             The updated pipeline.
         """
+        import dreadnode as dn
+
         self.scorers.extend(
             [
                 dn.scorers.wrap_chat(
@@ -1512,6 +1515,8 @@ async def _process_tool_call(tool_call: ToolCall) -> bool:
         return next_pipeline.step()
 
     async def _then_parse(self, chat: Chat) -> PipelineStepContextManager | None:
+        import dreadnode as dn
+
         if chat.error:  # If we have an error, we should not attempt to parse.
             return None
 
@@ -1613,6 +1618,8 @@ async def complete() -> None:
                 state.chat = step.chats[-1] if step.chats else state.chat
 
     async def _score_chats(self, chats: list[Chat]) -> None:
+        import dreadnode as dn
+
         if not self.scorers:
             return
 
@@ -1644,6 +1651,8 @@ async def _step(  # noqa: PLR0915, PLR0912
         params: list[GenerateParams],
         on_failed: FailMode,
     ) -> PipelineStepGenerator:
+        import dreadnode as dn
+
         chats: ChatList = ChatList([])
 
         # Some pre-run work
@@ -2015,6 +2024,8 @@ async def run(
         Returns:
             The generated Chat.
         """
+        import dreadnode as dn
+
         if allow_failed:
             warnings.warn(
                 "The 'allow_failed' argument is deprecated, use 'on_failed=\"include\"'.",
@@ -2123,6 +2134,8 @@ async def run_many(
         Returns:
             A list of generated Chats.
         """
+        import dreadnode as dn
+
         if count < 1:
             raise ValueError("Count must be greater than 0")
 
@@ -2286,6 +2299,8 @@ async def run_batch(
         Returns:
             A list of generatated Chats.
         """
+        import dreadnode as dn
+
         on_failed = on_failed or self.on_failed
         count, messages, params = self._fit_batch_args(many, params)
 
@@ -2370,6 +2385,8 @@ async def run_over(
         Returns:
             A list of generatated Chats.
         """
+        import dreadnode as dn
+
         on_failed = on_failed or self.on_failed
 
         _generators: list[Generator] = [

rigging/completion.py

@@ -11,7 +11,6 @@
 from typing import runtime_checkable
 from uuid import UUID, uuid4
 
-import dreadnode as dn
 from loguru import logger
 from pydantic import BaseModel, ConfigDict, Field, computed_field
 
@@ -22,6 +21,8 @@
 from rigging.util import get_qualified_name
 
 if t.TYPE_CHECKING:
+    from dreadnode import Span
+
     from rigging.chat import FailMode
     from rigging.model import Model, ModelT
 
@@ -571,6 +572,8 @@ def _until_parse_callback(self, text: str) -> bool:
         return False
 
     async def _watch_callback(self, completions: list[Completion]) -> None:
+        import dreadnode as dn
+
         def wrap_watch_callback(
             callback: WatchCompletionCallback,
         ) -> t.Callable[[list[Completion]], t.Awaitable[None]]:
@@ -623,6 +626,8 @@ async def _post_run(
         completions: list[Completion],
         on_failed: "FailMode",
     ) -> list[Completion]:
+        import dreadnode as dn
+
         if on_failed == "skip":
             completions = [c for c in completions if not c.failed]
 
@@ -723,7 +728,7 @@ def _initialize_states(
 
     async def _run(  # noqa: PLR0912
         self,
-        span: dn.Span,
+        span: "Span",
         states: list[RunState],
         on_failed: "FailMode",
         batch_mode: bool = False,  # noqa: FBT001, FBT002
@@ -822,6 +827,8 @@ async def run(
         Returns:
             The generated Completion.
         """
+        import dreadnode as dn
+
         if on_failed is None:
             on_failed = "include" if allow_failed else self.on_failed
 
@@ -871,6 +878,8 @@ async def run_many(
         Returns:
             A list of generatated Completions.
         """
+        import dreadnode as dn
+
         on_failed = on_failed or self.on_failed
         states = self._initialize_states(count, params)
 
@@ -913,6 +922,8 @@ async def run_batch(
         Returns:
             A list of generatated Completions.
         """
+        import dreadnode as dn
+
         on_failed = on_failed or self.on_failed
         params = self._fit_params(len(many), params)
 
@@ -960,6 +971,8 @@ async def run_over(
         Returns:
             A list of generatated Completions.
         """
+        import dreadnode as dn
+
         on_failed = on_failed or self.on_failed
 
         _generators: list[Generator] = [

rigging/generator/litellm_.py

@@ -4,7 +4,6 @@
 import re
 import typing as t
 
-import dreadnode as dn
 import litellm
 import litellm.types.utils
 from loguru import logger
@@ -161,6 +160,8 @@ def semaphore(self) -> asyncio.Semaphore:
         return self._semaphore
 
     async def supports_function_calling(self) -> bool | None:
+        import dreadnode as dn
+
         if self._supports_function_calling is not None:
             return self._supports_function_calling
 

rigging/prompt.py

@@ -9,7 +9,6 @@
 import typing as t
 from collections import OrderedDict
 
-import dreadnode as dn
 from jinja2 import Environment, StrictUndefined, meta
 from pydantic import ValidationError
 from typing_extensions import Concatenate, ParamSpec  # noqa: UP035
@@ -553,6 +552,8 @@ def _resolve_to_pipeline(self, other: ChatPipeline | Generator | Chat | str) ->
         raise ValueError(f"Invalid type for binding: {type(other)}")
 
     async def _then_parse(self, chat: Chat) -> PipelineStepContextManager | None:
+        import dreadnode as dn
+
         if self.output is None or isinstance(self.output, ChatOutput):
             return None
 
@@ -836,6 +837,8 @@ def say_hello(name: str) -> str:
             await say_hello.bind("gpt-3.5-turbo")("the world")
             ```
         """
+        import dreadnode as dn
+
         pipeline = self._resolve_to_pipeline(other)
         if pipeline.on_failed == "skip":
             raise NotImplementedError(
@@ -901,6 +904,8 @@ def say_hello(name: str) -> str:
             await say_hello.bind_many("gpt-4.1")(5, "the world")
             ```
         """
+        import dreadnode as dn
+
         pipeline = self._resolve_to_pipeline(other)
         if pipeline.on_failed == "include" and not isinstance(self.output, ChatOutput):
             raise NotImplementedError(

rigging/tools/base.py

@@ -10,7 +10,6 @@
 import warnings
 from functools import cached_property
 
-import dreadnode as dn
 import typing_extensions as te
 from pydantic import (
     BaseModel,
@@ -355,6 +354,7 @@ async def handle_tool_call(  # noqa: PLR0912
             A tuple containing the message to send back to the generator and a
             boolean indicating whether tool calling should stop.
         """
+        import dreadnode as dn
 
         from rigging.message import ContentText, ContentTypes, Message