Naming changes and import bug fixes

app/pipeline/chat/__init__.py

@@ -1 +1 @@
-from simple_chat_pipeline import SimpleChatPipeline
+from pipeline.chat.simple_chat_pipeline import SimpleChatPipeline

app/pipeline/chat/chat_pipeline.py

@@ -1,20 +1,17 @@
-from abc import ABC, abstractmethod
+from abc import abstractmethod, ABCMeta
 
 from domain import IrisMessage
 from pipeline import Pipeline
 
 
-class ProgrammingExerciseTutorChatPipeline(Pipeline, ABC):
+class ChatPipeline(Pipeline, metaclass=ABCMeta):
     """
     Abstract class for the programming exercise tutor chat pipeline implementations.
     This class defines the signature of all implementations of this Iris feature.
     """
 
-    def __call__(self, query: IrisMessage, **kwargs) -> IrisMessage:
-        return self._run(query)
-
     @abstractmethod
-    def _run(self, query: IrisMessage) -> IrisMessage:
+    def __call__(self, query: IrisMessage, **kwargs) -> IrisMessage:
         """
         Runs the pipeline and returns the response message.
         """

app/pipeline/chat/simple_chat_pipeline.py

@@ -5,10 +5,10 @@
 
 from domain import IrisMessage, IrisMessageRole
 from llm.langchain import IrisLangchainChatModel
-from pipeline.chat.chat_pipeline import ProgrammingExerciseTutorChatPipeline
+from pipeline.chat.chat_pipeline import ChatPipeline
 
 
-class SimpleChatPipeline(ProgrammingExerciseTutorChatPipeline):
+class SimpleChatPipeline(ChatPipeline):
     """A simple chat pipeline that uses our custom langchain chat model for our own request handler"""
 
     llm: IrisLangchainChatModel
@@ -19,7 +19,7 @@ def __init__(self, llm: IrisLangchainChatModel):
         self.pipeline = {"query": itemgetter("query")} | llm | StrOutputParser()
         super().__init__(implementation_id="simple_chat_pipeline")
 
-    def _run(self, query: IrisMessage) -> IrisMessage:
+    def __call__(self, query: IrisMessage, **kwargs) -> IrisMessage:
         """
         Gets a response from the langchain chat model
         """

app/pipeline/chat/tutor_chat_pipeline.py

@@ -7,12 +7,12 @@
 
 from domain import IrisMessage, IrisMessageRole
 from llm.langchain import IrisLangchainChatModel
-from pipeline.chat.chat_pipeline import ProgrammingExerciseTutorChatPipeline
+from pipeline.chat.chat_pipeline import ChatPipeline
 
 logger = logging.getLogger(__name__)
 
 
-class TutorChatPipelineReferenceImpl(ProgrammingExerciseTutorChatPipeline):
+class TutorChatPipelineReferenceImpl(ChatPipeline):
     """Tutor chat pipeline that answers exercises related questions from students."""
 
     llm: IrisLangchainChatModel
@@ -38,7 +38,7 @@ def __init__(self, llm: IrisLangchainChatModel):
         # Create the pipeline
         self.pipeline = prompt | llm | StrOutputParser()
 
-    def _run(self, query: IrisMessage) -> IrisMessage:
+    def __call__(self, query: IrisMessage, **kwargs) -> IrisMessage:
         """
         Runs the pipeline
             :param query: The query

app/pipeline/shared/summary_pipeline.py

@@ -6,21 +6,21 @@
 from langchain_core.runnables import Runnable
 
 from llm.langchain import IrisLangchainChatModel
-from pipeline import AbstractPipeline
+from pipeline import Pipeline
 
 logger = logging.getLogger(__name__)
 
 
-class SummaryPipeline(AbstractPipeline):
+class SummaryPipeline(Pipeline):
     """A generic summary pipeline that can be used to summarize any text"""
 
     llm: IrisLangchainChatModel
     pipeline: Runnable
     prompt_str: str
     prompt: ChatPromptTemplate
 
-    def __init__(self, llm: IrisLangchainChatModel, name=None):
-        super().__init__(name=name)
+    def __init__(self, llm: IrisLangchainChatModel):
+        super().__init__(implementation_id="summary_pipeline")
         # Set the langchain chat model
         self.llm = llm
         # Load the prompt from a file